CN114518488A

CN114518488A - Distributed light storage charging and discharging system for high-precision internet-of-things intelligent electric meter based on electric energy parameter search measurement

Info

Publication number: CN114518488A
Application number: CN202210062360.9A
Authority: CN
Inventors: 黄和平; 顾章平; 吴斌; 冯学礼; 黄蕾; 黄林弟; 林洁; 郑艳霞; 叶青青
Original assignee: Zhejiang Chint Instrument and Meter Co Ltd
Current assignee: Zhejiang Chint Instrument and Meter Co Ltd
Priority date: 2022-01-19
Filing date: 2022-01-19
Publication date: 2022-05-20

Abstract

The invention discloses a distributed light storage and charge-discharge system for measuring a high-precision internet-of-things intelligent electric meter based on electric energy parameter searching, which comprises a first intelligent electric meter and a second intelligent electric meter, wherein the first intelligent electric meter and the second intelligent electric meter adopt electric energy parameter searching to measure the high-precision internet-of-things intelligent electric meter and are used for accurately measuring electric energy supplied to a load by an intelligent power grid and a distributed photovoltaic inversion power generation system; the electric energy parameter search measurement high-precision internet-of-things intelligent electric meter comprises an SVM search synthesizer, wherein the SVM search synthesizer is used for processing measured single-phase alternating current transient voltage and single-phase alternating current transient current respectively to obtain a Gaussian window function high-precision sine wave and the pulse number of the measured single-phase alternating current transient voltage and the measured single-phase alternating current, the output of the SVM search synthesizer enters a differential calibration unit to perform electric energy identification and signal calibration, the output voltage of the differential calibration unit enters a wavelet transformation module to identify harmonic waves and inter-harmonic waves to obtain voltage and current signals of the harmonic waves and the inter-harmonic waves, and a metering result is more accurate.

Description

Distributed light storage charging and discharging system for high-precision internet-of-things intelligent electric meter based on electric energy parameter search measurement

Technical Field

The invention belongs to the field of power transmission and distribution of an Internet of things smart power grid, and relates to a distributed light storage charging and discharging system for a high-precision Internet of things smart power meter based on electric energy parameter searching and measuring.

Background

Environmental, safe and reliable compliance enables traditional power generation cost optimization, sustainable development is not available, renewable energy, variability of distributed power generation cost and electric energy compliance enable the traditional power generation cost optimization, and renewable energy distributed energy is developed in spring. Renewable energy distributed energy gradually replaces most traditional energy, in the green smart grid era of the triple-play of internet of things, interconnection and smart grid formed by renewable energy and traditional power generation in a hybrid manner in the next 30 years, photovoltaic (wind power) distributed power generation is the most green energy with high cost performance of renewable energy, along with the increasingly dominant role of photovoltaic (wind power) distributed power generation in the smart grid, the smart grid depends on and is used for photovoltaic (wind power) distributed power generation to compensate the deficiency of traditional main power, thousands of photovoltaic (wind power) distributed power generation residual electricity is connected to the grid for electricity selling, and the prior art faces the following problems and cannot solve the following problems:

(1) due to the fact that environmental factors restrict inconsistency and indirectness of photovoltaic (wind power) distributed power generation, power cannot be supplied and sold stably, continuously and reliably; the battery light storage charging and discharging system is adopted immediately, and can only be used as short-time emergency electricity, the requirements of power generation, power sale and power utilization are scientifically predicted, the mixed power is enabled to realize uninterrupted power supply, reliable and stable power supply, the power generation, the power utilization and the power identity of a terminal user cannot be intelligently identified, the reliability and the accuracy of electric energy data are poor, and the defects can be overcome by no reliable device at present;

(2) a large amount of low-voltage low-cost photovoltaic (wind power) distributed power generation surplus electricity is networked, and an existing intelligent electric meter and an existing electric energy metering system provide integrated electricity selling supply information and data for an electric power company (assumed as an electricity selling department), and the integrated distributed data is provided. The existing exposed distributed energy communication network is unsafe, a power company cannot identify and divide data information and cannot control mass terminals under an internet of things, data without confidentiality is not available, and data which is easy to tamper under the drive of benefits and is on line with surplus power generated by distributed power generation (wind power) is distributed more easily. The electricity selling data received by the power company can not judge the correctness, accuracy and error of the data, and the scheduling and prediction of the electric energy caused by the data bring about the accident of power failure and power failure. Therefore, in practice, the electric power company cannot completely realize the business of surplus power on-line of photovoltaic (wind power) distributed power generation, and the continuous and large-area popularization and application of the photovoltaic (wind power) distributed power generation are also caused.

(3) The method has the advantages that new energy such as wind and light and novel loads in the existing Internet of things + smart grid are continuously connected, unstable energy brings more current high dynamic change to the grid, steady harmonic distortion brought by traditional nonlinear loads, complex characteristics of three-phase balance, harmonic, inter-harmonic and voltage and current drastic change of the grid due to a large amount of impact, accuracy of existing electric energy measurement is directly influenced, and electric energy measurement instruments designed based on a sine circuit power theory or a traditional non-sine circuit power theory cannot truly reflect electric energy absorbed from an electric power system. For example, an electric energy meter based on the sine circuit power theory cannot theoretically measure active and reactive electric energy of harmonic waves and inter-harmonic waves in impact load, so that a large error occurs in total active and reactive electric energy.

(4) The strategy for the renewable energy source intermittency is a short-time effective method, but cannot solve the problem of real-time and online measurement of the electric energy of the smart grid, and technical personnel and scholars of strategy renewable energy sources such as wind and light storage charging and discharging engineering study Fourier transform for harmonic and inter-harmonic parameter estimation, so that frequency spectrum leakage and grid erosion effects cannot be avoided, and the requirements on synchronous sampling and frequency resolution are high. The problems of large amount of samples, large calculation amount, unknown frequency and poor real-time property are caused by the adoption of the existing support vector machine and the neural network.

The smart power grid is used as a basic unit of the global energy Internet, the idea that the Internet, the Internet of things and the smart power grid are fused shows huge growth potential, zero carbon emission including new energy is constructed and merged into a novel power system, a smart meter capable of realizing real-time and on-line high-precision metering and identifying different loads and electric energy internet of things is researched and developed, the requirement that the renewable energy distributed light storage charging and discharging system is friendly to be connected into the smart power grid, the Internet of things and electric energy scheduling prediction is achieved is met, and huge economic benefits are achieved.

Disclosure of Invention

The embodiment of the invention aims to provide a distributed light storage and charging system for a high-precision internet-of-things intelligent electric meter based on electric energy parameter searching and measuring, which aims to solve the problems that the electric energy category and the electric identity of a terminal user in the distributed light storage and charging system of the existing intelligent power grid cannot be intelligently identified, electric energy transmission data is integrated metering data and cannot be divided into specific power generation and utilization individuals, the problems that the data of power sale, utilization and generation are easily distorted due to poor encryption of the existing electric power data, the problem that the residual electricity of the distributed light storage and charging and discharging system cannot be accurately and massively networked, the problem that a power company cannot control the terminal user and accurately predict and schedule the residual electricity to other areas of the intelligent power grid, and the problems that the existing intelligent electric meter cannot meter can not meter the active and reactive electric energy of harmonic waves and the inter-harmonic waves and cannot meter the active and reactive electric energy of different frequencies between the voltage and the current, the existing intelligent electric meter has large total active and reactive electric energy metering errors and cannot adapt to the problem of accurate and high-precision metering of electric energy on line and in time of an intelligent power grid.

The first technical scheme adopted by the embodiment of the invention is as follows: an SVM search synthesizer, comprising:

the orthogonal signal generator is used for carrying out orthogonal decomposition on the input single-phase alternating current transient voltage/current to obtain two mutually perpendicular voltage components/current components;

a first encoder for orthogonally encoding two mutually perpendicular voltage/current components;

the first measurement filter is used for filtering and parameter measurement of two orthogonal voltage components/current components after orthogonal coding to obtain the amplitude, phase and frequency of the two orthogonal voltage components/current components;

the compensation module is used for compensating the two mutually perpendicular voltage components/current components filtered by the first measurement filter by using the reference value with the same frequency;

the first transmitting filter is used for transmitting and filtering two voltage components/current components which are perpendicular to each other and output by the compensation module;

the amplitude phase detection judging module is used for judging whether the amplitudes and the phases of two mutually perpendicular voltage components/current components output by the filtering of the first transmitting filter meet the standard or not;

the integrator is used for integrating the two mutually perpendicular voltage components/current components output by the first transmitting filter as input when the amplitude phase detection judging module judges that the amplitudes and the phases of the two mutually perpendicular voltage components/current components output by the first transmitting filter are not in accordance with the standard, so that the phases and the amplitudes of the voltage/current obtained after integration are in accordance with the standard;

the analog-to-digital converter is used for performing analog-to-digital conversion on the output voltage/current of the integrator and dividing the digital signal obtained by conversion into an I path and a Q path for output; or respectively performing analog-to-digital conversion on two mutually perpendicular voltage components/current components which are output by the amplitude phase detection judging module and meet the standard, and defining two digital signals obtained by conversion as two paths of output of an I path and an Q path;

the digital signal processing module is used for performing signal processing on the I path and the Q path of the analog-digital converter and performing fourteen-stage interpolation fitting on the two paths of output to form a standard high-precision sine wave;

and the frequency amplitude phase searching module is used for searching the frequency, amplitude and phase of the standard high-precision sine wave output by the digital signal processing module based on a support vector machine and a TLS-ESPRIT algorithm inter-harmonic parameter estimation method to obtain the frequency, amplitude and phase of the standard high-precision sine wave.

Further, the compensation module comprises:

the first comparator is used for comparing one of the voltage components/current components filtered by the first measurement filter with a reference value cos2 pi ft with the same frequency of the voltage component/current component, and compensating the voltage component/current component output by the first measurement filter;

a second comparator for comparing the other voltage/current component outputted from the first measuring filter with a reference value-sin 2 pi ft having the same frequency as the other voltage/current component, and compensating the voltage/current component outputted from the first measuring filter;

the first synthesizer is used for synthesizing the outputs of the first comparator and the second comparator to obtain synthesized voltage/current;

a second encoder for encoding the output of the first synthesizer, i.e. the synthesized voltage/current;

the second orthogonal signal generator is used for carrying out orthogonal decomposition on the coded synthesized voltage/current to obtain two mutually perpendicular voltage components/current components corresponding to the output of the first orthogonal signal generator;

a third comparator for comparing one of the voltage/current components output from the second quadrature signal generator with a reference value cos2 pi ft having the same frequency as the one of the voltage/current components output from the second quadrature signal generator, and compensating the one of the voltage/current components output from the second quadrature signal generator;

and the fourth comparator is used for comparing the other voltage component/current component output by the second orthogonal signal generator with the reference value cos2 pi ft with the same frequency of the other voltage component/current component output by the second orthogonal signal generator and compensating the other voltage component/current component output by the second orthogonal signal generator.

Further, the digital signal processing module includes:

the phase oscillation register is used for carrying out phase correction on the I path and the Q path of output of the analog-to-digital converter ADC and registering;

the 01 register is used for carrying out 01 register on the digital signal of the phase oscillation register after phase correction;

the high-pass filter HPF is used for performing high-pass filtering on the I path and the Q path of the 01 register;

the low pass filter LPF is used for performing low pass filtering on the I path and the Q path of the output of the high pass filter HPF;

the I path register is used for registering the output of the LPF of the I path;

the Q-path register is used for registering the output of the low-pass filter LPF of the Q-path;

the I path mapping module is used for representing 0 in the digital signal consisting of 0 and 1 registered by the I path register by using a space and 1 by using a unit pulse to obtain an I path mapping waveform;

the Q-path mapping module is used for representing 0 in the signal consisting of 0 and 1 registered by the Q-path register by using a blank space and 1 by using a unit pulse to obtain a Q-path mapping waveform;

the 0 value filling module is used for carrying out 0 value filling on the I path mapping waveform and the Q path mapping waveform to obtain an I path 0 value filling waveform and a Q path 0 value filling waveform;

the second transmitting filter is used for transmitting and filtering the I path 0 value filling waveform and the Q path 0 value filling waveform;

the first sampling filter is used for performing fourteen-level interpolation on the I path 0 value filling waveform and the Q path 0 value filling waveform to obtain an I path interpolation fourteen-level discrete sine wave in a dense state and a Q path interpolation fourteen-level discrete sine wave;

the second measurement filter is used for measuring and filtering the input I path interpolation fourteen-level discrete sine waves and the Q path interpolation fourteen-level discrete sine waves;

and the second sampling filter is used for carrying out the fourteen-level interpolation fitting on the I-path interpolated fourteen-level discrete sine waves and the Q-path interpolated fourteen-level discrete sine waves output by the second measurement filter to form standard high-precision sine waves.

Further, the SVM search synthesizer further includes:

the encryption module is used for carrying out 14-level ladder encryption on the standard high-precision sinusoidal signals output by the second sampling filter;

and the SVM wave sending module is used for sending waves according to the frequency, the amplitude and the phase output by the frequency amplitude phase searching module to obtain a Gaussian window function high-precision sine wave and the pulse number thereof.

The second technical scheme adopted by the embodiment of the invention is as follows: the utility model provides an electric energy parameter search measures high accuracy thing and allies oneself with smart electric meter, includes:

the high-frequency crystal oscillator and the quartz crystal oscillator are used for providing a real-time clock for the system when different frequencies are required;

the four identification and metering circuits with the same structure are used for carrying out electric energy identification and electric energy metering after one pair of identification and metering circuits take electricity from phase lines A, B, C and neutral lines of a power grid;

wherein each identification metering circuit comprises:

the voltage sensor and the compensation circuit are used for accurately measuring the single-phase alternating current transient voltage of the three-phase power;

the current sensor is used for accurately measuring the single-phase alternating current transient current of the three-phase power;

the SVM search synthesizer is used for respectively processing the measured single-phase alternating current transient voltage and the measured single-phase alternating current transient current to obtain a Gaussian window function high-precision sine wave and the pulse number of the measured single-phase alternating current transient voltage and the measured single-phase alternating current transient current;

the specific difference calibration unit is used for correspondingly comparing single-phase alternating current transient voltage and single-phase alternating current transient current Gaussian window function high-precision sine waves with single-phase alternating current transient voltage and single-phase alternating current standard sine waves of various types of electric energy, taking the electric energy type corresponding to the minimum comparison error as the current measured electric energy type, realizing type identification of the measured electric energy, and calibrating the single-phase alternating current transient voltage and single-phase alternating current Gaussian window function high-precision sine waves according to the minimum comparison error to enable the single-phase alternating current transient voltage and single-phase alternating current high-precision sine waves to be closer to the identified current measured electric energy corresponding type standard sine waves;

the high-pass filter is used for performing high-pass filtering on the sine waves of the single-phase alternating current transient voltage and the single-phase alternating current transient current output by the comparison calibration unit;

the electric energy metering unit is used for metering electric energy by utilizing the output of the high-pass filter;

the CF pulse generating unit is used for judging whether the pulse number output by the SVM searching synthesizer, namely the flashing frequency of the CF end LED lamp of the electric energy metering unit is consistent with the pulse for monitoring electric energy metering;

the meter calibration parameter unit is communicated with the specific difference calibration unit, the electric energy metering unit and the CF pulse generation unit to obtain information and is used for calibrating the metering precision of the electric energy metering unit, the parameter of the meter difference calibration unit and the parameter of the CF pulse generation unit;

the power and effective value measuring unit is used for re-measuring the comparison calibration unit, the electric energy measuring unit and the electric energy before the CF pulse generating unit is calibrated;

and the data storage is used for storing the output data of the electric energy metering unit, the CF pulse generating unit and the power and effective value metering unit and is connected with a distributed IO interface of the microprocessor.

Further, the electric energy parameter search measurement high accuracy thing allies oneself with smart electric meter, still include:

the wavelet transformation module is used for performing wavelet transformation on the sinusoidal voltage signals output by the contrast calibration unit, identifying harmonic waves and inter-harmonic waves, and obtaining voltage signals and current signals of the harmonic waves and the inter-harmonic waves;

and the frequency sorting unit is used for carrying out frequency sorting on the voltage signals and the current signals of the harmonic waves and the inter-harmonic waves output by the wavelet transformation module and then calculating an average value to obtain the average values of the voltage signals and the current signals of the harmonic waves and the inter-harmonic waves, outputting the average values to a high-pass filter for high-pass filtering, inputting the average values to the electric energy metering module for electric energy metering of the harmonic waves and the inter-harmonic waves after filtering by the high-pass filter, and summing the electric energy metered by the electric energy metering module with the sinusoidal voltage signals and the current signals output by the specific difference calibration unit through the high-pass filter to obtain the total electric energy.

one output of the standby function measuring channel and the output of the temperature sensor are combined and output to a distributed IO interface of a microprocessor such as a DSP (digital signal processor) so as to control the temperature when the standby function measuring channel is used, and the normal operation of the high-precision internet of things intelligent electric meter for searching and measuring the electric energy parameters is not influenced by the starting of the standby function measuring channel; the other path of the standby function measuring channel is output to a comparator, the comparator is output to a modulator, the modulator is connected with the output of a phase-locked loop PLL, and the comparator and the modulator are used for modulating signals input by the standby function measuring channel;

and the phase-locked loop PLL is used for phase-locking a real-time clock provided by the high-frequency crystal oscillator or the quartz crystal oscillator, the output of the SVM search synthesizer in each identification metering circuit and the output of the modulator.

The third technical scheme adopted by the embodiment of the invention is as follows: a distributed light storage charging and discharging system based on an electric energy parameter search measurement high-precision internet-of-things intelligent electric meter comprises:

the distributed photovoltaic inversion power generation system is used for photovoltaic power generation;

the system comprises a BMS-battery management system, a first transformer and a second transformer, wherein the BMS-battery management system is used for intelligently managing and maintaining a battery pack, charging and discharging are carried out by utilizing the battery pack, the first transformer is connected with an intelligent power grid through the battery pack and an AC/DC PCS subsystem which are sequentially connected;

the light storage charging and discharging direct current cabinet is used for carrying out confluence and lightning protection treatment on direct current output of the distributed photovoltaic inversion power generation system and charging a battery pack of the BMS-battery management system under the control of the intelligent control manager;

an intelligent control manager for performing charge and discharge management control of a battery pack of the BMS-battery management system;

the metering lightning protection main distribution box is used for performing overvoltage and undervoltage protection, lightning protection and electric energy metering on the output of the distributed photovoltaic inverter power generation system, and the output end of the metering lightning protection main distribution box is connected with a three-phase four-wire commercial power;

the second intelligent electric meter is an electric energy parameter searching measurement high-precision internet-of-things intelligent electric meter, is arranged on the network side of an access point of the metering lightning protection total distribution box connected to the mains supply, and is used for accurately metering the electric energy supplied to the load by the intelligent power grid.

Further, measurement lightning protection total distribution box includes third circuit breaker, crosses undervoltage protection circuit, circuit ware, surge protection circuit, switch, binding post, a smart electric meter, wherein:

the first intelligent ammeter is an Internet of things intelligent ammeter for measuring high precision by adopting the electric energy parameter searching;

one end of the third circuit breaker is connected with the alternating current output end of the distributed photovoltaic inverter power generation system, and the other end of the third circuit breaker is connected with one end of the overvoltage and undervoltage protection circuit; the other end of the overvoltage and undervoltage protection circuit is connected in two paths, wherein one path is connected with one end of a circuit device, the other end of the circuit device is connected with a surge protection circuit, the other path is connected with one end of a disconnecting link switch, and the other end of the disconnecting link switch is connected with a first intelligent ammeter through a connecting terminal;

the first intelligent ammeter is connected with a three-phase four-wire mains supply through a three-phase composite switch, and the load side of the access point is connected with a three-phase load through a three-phase switch;

and the second intelligent ammeter is connected with the intelligent power grid through a second transformer.

Further, a distributed light storage system of filling of measurationing high accuracy thing allies oneself with smart electric meter based on electric energy parameter search still includes:

the anti-countercurrent controller is used for detecting the power grid so as to judge whether reverse current occurs when the distributed photovoltaic inverter power generation system generates power and carrying out system control to enable the reverse current to meet the requirement after the reverse current exceeds the requirement;

the intelligent control manager comprises:

the EMS monitoring management host protection system is used for monitoring and managing a plurality of BMS battery management systems;

the MPPT controller is used for carrying out maximum power tracking control;

the PWM controller is used for controlling the inversion or rectification of a current transformer in an AC/DC PCS subsystem connected with the battery pack in each BMS-battery management system;

every BMS-battery management system still is connected with temperature monitoring system, fire extinguishing system, wherein:

the temperature monitoring system is used for monitoring the temperature of the battery pack;

the fire fighting system is used for preventing the battery pack of the BMS-battery management system from being ignited and exploded;

the light stores up fills and fills direct current cabinet includes:

the confluence box is used for confluence of direct current output of the distributed photovoltaic inverter power generation system;

the first circuit breaker is used for carrying out on-off control on the output of the combiner box;

the lightning protection device is used for carrying out lightning protection control on the total current between the combiner box and the intelligent manager;

the ammeter and the voltmeter are used for detecting the voltage and the current of the total current between the combiner box and the intelligent manager;

and the second circuit breaker is used for carrying out on-off control on the total current between the light storage charging-discharging direct current cabinet and the intelligent manager.

The embodiment of the invention has the beneficial effects that:

1. on the interaction of an intelligent power grid, an electric power internet of things, electric power production, power transmission and distribution, terminal user electric power distribution, multi-carbon emission reduction metering and tracking transaction, a low-power-consumption digital electric power intelligent electric carbon sensing recognizer (SVM search synthesizer) is designed to form an electric energy parameter search measurement high-precision Internet of things intelligent electric meter. The electric energy parameter search measurement high-precision internet-of-things intelligent electric meter adopts an SVM search synthesizer to identify the electric energy category (the electric identity of power generation, power supply, power sale and power utilization) according to frequency, amplitude and phase, and effectively solves the problem that the electric energy category and the electric identity of a terminal user cannot be intelligently identified in the distributed optical storage charging and discharging system of the existing intelligent power grid.

2. The high-precision internet-of-things intelligent electric meter is measured by searching electric energy parameters between each electricity generation and utilization individual and the intelligent power grid, so that the independent statistics of electricity generation and utilization data of each electricity generation and utilization individual is realized, and the problems that electric energy transmission data are integrated metering data and specific individuals cannot be segmented are solved. After each electricity generation and utilization individual uses the electric energy parameter to search and measure the high-precision internet-of-things intelligent electric meter, the identity recognition of each electricity generation and utilization individual can be realized, the surplus electricity of a plurality of distributed light storage charging and discharging systems can be accurately and massively networked, the terminal user can be accurately controlled, the surplus electricity can be accurately predicted and scheduled to other areas of the intelligent electric network, and the problems that the surplus electricity of the distributed light storage charging and discharging systems cannot be accurately and massively networked, the terminal user cannot be controlled by an electric power company, and the surplus electricity cannot be accurately predicted and scheduled to other areas of the intelligent electric network at present are solved.

3. The SVM searching synthesizer is adopted to process actual power data, micro-electric synthesis and transmission are carried out, the actual power data cannot be accurately estimated by external force, so that the actual power data are not easy to tamper, and the problem that power selling, electricity using and generating data are easy to tamper due to poor encryption of the existing power data is solved; an SVM searching synthesizer is combined with wavelet transformation to realize active and reactive electric energy of harmonic waves and inter-harmonic waves, voltage and electric energy self-adaptation with different frequencies is carried out in a Gaussian function window, and then the electric energy parameter searching and measuring high-precision Internet of things intelligent electric meter can measure the active and reactive electric energy between the voltage and the current with different frequencies, so that the problems that the existing intelligent electric meter cannot measure the active and reactive electric energy of the harmonic waves and the inter-harmonic waves and cannot measure the active and reactive electric energy between the voltage and the current with different frequencies are solved; the method has the advantages that the high-precision sine wave of the Gaussian window function is generated by the aid of the SVM search synthesizer, high-precision electric energy metering is preliminarily achieved, active electric energy and reactive electric energy of harmonic waves and inter-harmonic waves are achieved by the aid of the SVM search synthesizer in combination with wavelet transformation, electric energy metering precision is further improved, the requirement of accurate and high-precision electric energy metering of the smart power grid in online timely mode is met, and the problems that the total active electric energy and reactive electric energy metering error is large and the smart power grid in online timely accurate and high-precision electric energy metering cannot be adapted are solved.

4. Through the IOT system station, the SVM search synthesizer carries out identity recognition and asset coding on the electric energy and multi-carbon of the concentrator, the electric energy parameter search measurement high-precision Internet of things intelligent electric meter, a load switch, electric equipment, wind power, solar power generation, biomass energy, hydroenergy, nuclear energy and thermal power generation, the system can realize the whole process of power supply and metering of electric energy and multi-carbon asset management from power generation, power transmission and distribution, end user power consumption, smart grids, electric Internet of things and international energy Internet, replaces a large amount of current sensors and metering devices in renewable energy sources, Internet of things and smart grids, improves the precision of electric energy metering, the wireless automatic switch of the electric equipment in the intelligent factory and the intelligent manufacturing can be realized through the cooperation of the 5G wireless network, so that an electric equipment controller, a PLC (programmable logic controller), a chip and a load switch in a power distribution system in the intelligent manufacturing are saved. The method realizes the online and timely matching of the power generation capacity and the demand of each user in the whole process of the power, provides real-time information and instant balance of supply and demand, and proposes, bills and economic cost of energy consumption information problems of manufacturers, distribution users and terminal users.

5. And any monitoring variable fault is updated on line, so that the utilization rate of energy is improved, and the energy-saving emission-reducing multi-carbon quantity price supply is improved. By analyzing the time data of the load, the future demand is predicted according to the consumer behavior, and the predicted energy management of the energy supply delivery is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a schematic structural diagram of a distributed light storage and charging system of a high-precision internet-of-things smart meter based on electric energy parameter search measurement according to an embodiment of the present invention.

Fig. 2 is a schematic structural diagram of an electric energy parameter search measurement high-precision internet-of-things smart meter according to an embodiment of the present invention.

Fig. 3 is a ladder encryption wave-making diagram of an SVM search synthesizer according to an embodiment of the present invention.

Fig. 4 is a simulation diagram of the characteristic frequency estimation value of the TLS-ESPRIT autocorrelation matrix of the high-precision algorithm for searching and measuring electric energy parameters in the embodiment of the present invention.

Fig. 5 is a simulation diagram of TLS-ESPRIT frequency search value of the high-precision algorithm for searching and measuring electric energy parameters according to the embodiment of the present invention.

Fig. 6 is a sinusoidal wave including harmonics and inter-harmonics identified by wavelet transform and a gaussian window function high-precision sinusoidal wave and a sinusoidal wave output by a frequency sorting unit according to an embodiment of the present invention, in which (a) is a voltage waveform diagram of the harmonics and inter-harmonics identified by wavelet transform, and (b) is a composite signal waveform diagram of a gaussian window function high-precision sinusoidal wave signal of single-phase ac transient voltage/current and a voltage/current signal of the harmonics and inter-harmonics.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1

The embodiment of the invention provides an SVM quadrature vector search frequency phase amplitude phase lock device, as shown in FIG. 3, comprising:

quadrature signal generator for applying a single-phase alternating current transient voltage (V) to an input_in) Current is orthogonally decomposed to obtain twoA mutually perpendicular voltage component (V)_αAnd V_β) Current component, single-phase AC transient voltage (V)_in) The current is correspondingly output by single-phase inversion units of the A phase, the B phase and the C phase of the three-phase alternating current;

a first encoder, which is a quadrature encoder, for two mutually perpendicular voltage components (V)_αAnd V_β) The current component is orthogonally coded;

a first measuring filter for quadrature-coded two mutually perpendicular voltage components (V)_αAnd V_β) The current component is filtered and the parameter is measured to obtain two voltage components (V) perpendicular to each other_αAnd V_β) Magnitude, phase and frequency of the current component;

the amplitude phase detection judging module is used for judging whether the amplitude and the phase of two mutually perpendicular voltage components/current components output by the filtering of the first transmitting filter meet the standard (a reference value can be used for carrying out waveform comparison, and whether the standard is compounded is judged through the coincidence rate);

the integrator is used for integrating the two mutually perpendicular voltage components/current components output by the first transmitting filter as input when the amplitude phase detection judging module judges that the amplitudes and the phases of the two mutually perpendicular voltage components/current components output by the first transmitting filter are not in accordance with the standard, so that the phases and the amplitudes of the voltage/current obtained after integration are in accordance with the standard (reference value);

the digital signal processing module is used for performing signal processing on the I path and the Q path of the analog-to-digital converter and performing fourteen-stage interpolation fitting on the two paths of output to form a standard high-precision sine wave;

Specifically, the compensation module includes:

a first comparator for comparing one of the voltage components (V) filtered by the first measurement filter_α) The voltage component (V) of the output filtered by the first measuring filter is compared with the current component and the reference value cos2 pi ft of the same frequency as the current component_α) Current component, avoiding the voltage component (V) filtered by the first measuring filter_α) The subsequent identification of defective current components;

a second comparator for comparing the other voltage component (V) filtered by the first measurement filter_β) The voltage component (V) filtered by the first measuring filter is compared with the current component and the reference value-sin 2 pi ft with the same frequency as the current component_β) Current component, avoiding the voltage component (V) filtered by the first measuring filter_β) The subsequent identification of defective current components;

a second orthogonal signal generator (not shown in the figure) for orthogonally decomposing the coded composite voltage/current to obtain two mutually perpendicular voltage/current components corresponding to the output of the first orthogonal signal generator;

the third comparator is used for comparing one voltage component/current component output by the second orthogonal signal generator with a reference value cos2 pi ft with the same frequency of the voltage component/current component output by the second orthogonal signal generator, and compensating one voltage component/current component output by the second orthogonal signal generator to avoid that one voltage component/current component output by the second orthogonal signal generator is defective to influence subsequent identification;

and the fourth comparator is used for comparing the other voltage component/current component output by the second orthogonal signal generator with the reference value cos2 pi ft of the same frequency of the other voltage component/current component output by the second orthogonal signal generator, and compensating the other voltage component/current component output by the second orthogonal signal generator so as to avoid that the other voltage component/current component output by the second orthogonal signal generator is defective and influences subsequent identification.

Specifically, the digital signal processing module includes:

the low-pass filter LPF is used for performing low-pass filtering on the I path and the Q path of the high-pass filter HPF;

the I-path mapping module is used for representing 0 in the digital signal consisting of 0 and 1 registered by the I-path register by using a blank space and 1 by using a unit pulse to obtain an I-path mapping waveform, and the I-path mapping waveform is shown in figure 3;

the Q-path mapping module is used for representing 0 in the signal consisting of 0 and 1 registered by the Q-path register by using a blank space and 1 by using a unit pulse to obtain a Q-path mapping waveform, and is shown in FIG. 3;

a 0 value padding module, configured to perform 0 value padding on the I-path mapping waveform and the Q-path mapping waveform to obtain an I-path 0 value padding waveform and a Q-path 0 value padding waveform, as shown in fig. 3;

the second transmitting filter is used for transmitting and filtering the I path of 0 value filling waveform and the Q path of 0 value filling waveform;

a first sampling filter (not shown in the figure) for performing fourteen-level interpolation on the I path 0 value filling waveform and the Q path 0 value filling waveform to obtain an I path interpolated fourteen-level discrete sine wave and a Q path interpolated fourteen-level discrete sine wave in a dense state;

a second sampling filter (not shown in the figure) for performing a fourteen-level interpolation fitting on the I-path interpolated fourteen-level discrete sine waves and the Q-path interpolated fourteen-level discrete sine waves output by the second measurement filter to form standard high-precision sine waves; the interference of bandwidth in the interpolated fourteen-level waveform is suppressed by means of measurement filtering and sampling filtering, the waveform precision is improved by multi-layer filtering of sampling filtering after the error of the interpolated waveform of the measurement filtering, and a standard sine wave with high precision is synthesized.

The SVM search synthesizer further comprises:

the encryption module is configured to perform 14-level ladder encryption on the standard high-precision sinusoidal signal output by the second sampling filter, and send the encrypted signal to the frequency amplitude phase search module, as shown in fig. 3, and specifically operate as follows:

the standard high-precision sine signal output by the second sampling filter and the first section of rising waves of 49.80-62.25 are encrypted by adopting a vector 011; 62.25-74.70, and vector 010 is used for encryption; 74.70-87.15, and is encrypted by vector 001; 87.15-99.60 fourth-segment ascending waves and descending waves, and encrypting by using vector 000; 87.15-74.7, and encrypting by using a vector 001; 74.70-62.25, and adopts vector 010 encryption; 62.25-49.8, the sixth section of the descending wave is encrypted by a vector 011; a seventh section of descending wave from 49.8 to 37.35 is encrypted by adopting a vector 100; the eighth section of the descending wave of 37.35 to 24.9 is encrypted by adopting a vector 101; the tenth section of the descending wave of 24.9-12.45 is encrypted by a vector 110; the eleventh section of the descending wave and the ascending wave of 12.45-0 are encrypted by adopting a vector 111; a twelfth segment of the rising wave at the bottom of 12.45-24.9 is encrypted by a vector 110; a thirteenth section of rising wave of 24.9-37.35 is encrypted by using a vector 101; the fourteenth rising wave of 37.35-49.8 is encrypted by using a vector 100.

The system comprises an SVM (space vector modulation) wave-sending module, a Gaussian window function high-precision sine wave and a pulse number thereof, wherein the SVM wave-sending module is used for sending waves according to the frequency, amplitude and phase output by the frequency amplitude phase search module to obtain the high-precision sine wave of the Gaussian window function and the pulse number thereof, each pulse sent by the SVM wave-sending module is a sine wave, and the SVM wave-sending module continuously sends waves to obtain the high-precision sine wave of the Gaussian window function.

Ac transient voltage V_inTo V_αTransfer function G of_d(s) is:

in the formula (1), ω ═ θ represents a single-phase ac transient voltage V_inThe resonant frequency of (d);

ac transient voltage V_inTo V_βTransfer function G of_β(s) is:

when k is 0-2, G_d(s) and G_q(s) is a resonant filter capable of extracting single-phase AC transient voltage V_inComponent of the resonance frequency ω, V_qAnd V_inWith the same magnitude, the phase angle has a 90 ° lag. When the frequency deviates from omega, | G_dI and | G_qThe response is reduced, the speed of the reduction is related to the gain k, therefore, when the fundamental component can pass through the orthogonal generator smoothly, the small gain k can bring better selectivity and restrain other frequency components, so that the TLS-ESPRIT frequency estimation method searches for omegaThe frequency f is obtained quickly and stably, enters a steady-state time period in a very short time, and

when s ═ j ω, G_d＝1，G_qWhen 1 is not substituted, then V_α＝V_in。

Example 2

The embodiment of the invention provides a high-precision internet-of-things intelligent electric meter for searching and measuring electric energy parameters, as shown in fig. 2, comprising:

high frequency crystal oscillators and quartz crystal oscillators, not limited to 4.096MHz, OSC type 32768HZ for example, are used to provide real time clocks to the system at different frequency requirements;

the phase-locked loop PLL is used for phase-locking the real-time clock provided by the high-frequency crystal oscillator or the quartz crystal oscillator, the output of the modulator and the SVM search synthesizer, the output of the phase-locked loop PLL is transmitted to the timing management, and the timing management is transmitted to the timing management and chip MCU;

four discernment metering circuit that the structure is the same for carry out electric energy discernment and electric energy measurement after getting from smart power grids's A phase line, B phase line, C phase line, central line one-to-one, in fig. 2, the discernment metering circuit of central line does not express, and every discernment metering circuit includes:

the SVM search synthesizer is used for respectively processing the measured single-phase alternating current transient voltage and the measured single-phase alternating current transient current to obtain a Gaussian window function high-precision sine wave of the single-phase alternating current transient voltage and the single-phase alternating current transient current;

a wavelet transform module for performing wavelet transform on the output of the contrast calibration unit to obtain voltage and current signals of harmonics and inter-harmonics, wherein the waveform diagram of the voltage/current signals of the harmonics and inter-harmonics is shown in fig. 6 (a), the waveform diagram of the gaussian window function high-precision sine wave signal of the single-phase alternating current transient voltage/current, and the waveform of the composite signal of the voltage/current signals of the harmonics and inter-harmonics is shown in fig. 6 (b);

the frequency sorting unit is used for carrying out frequency sorting on voltage signals and current signals of harmonic waves and inter-harmonic waves output by the wavelet transformation module and then calculating an average value to obtain the average values of the voltage signals and the current signals of the harmonic waves and the inter-harmonic waves, outputting the average values to a high-pass filter for high-pass filtering, inputting the average values to the electric energy metering module for electric energy metering of the harmonic waves and the inter-harmonic waves after filtering by the high-pass filter, and summing the electric energy metered by the sine voltage signals and the electric energy calculated by the electric energy metering module by the sine voltage signals and the current signals output by the specific difference calibration unit through the high-pass filter to obtain the total electric energy;

the high-pass filter is used for performing high-pass filtering on the sine waves of the single-phase alternating current transient voltage and the single-phase alternating current transient current output by the frequency sorting unit and the voltage signals and the current signals of the harmonic waves and the inter-harmonic waves output by the frequency sorting unit;

the electric energy metering unit is used for metering electric energy by utilizing the output of the high-pass filter, and the total electric energy metered is the sum of the electric energy of harmonic waves and inter-harmonic waves and the electric energy output by the specific difference calibration unit;

the CF pulse generating unit is used for monitoring whether the pulse for electric energy metering is consistent with the flickering frequency of the LED lamp at the CF end of the electric energy metering unit;

the meter calibration parameter unit is communicated with the specific difference calibration unit, the electric energy metering unit and the CF pulse generation unit to obtain information and is used for calibrating the metering precision of the electric energy metering unit, the meter difference calibration unit and the parameters of the CF pulse generation unit;

and the data storage is used for storing the output data of the electric energy metering unit, the CF pulse generating unit and the power and effective value metering unit and is connected with the distributed IO interfaces of the microprocessors such as the DSP.

The high-precision Internet of things intelligent electric meter for searching and measuring electric energy parameters further comprises a time sequence management unit, a timing management unit, a temperature sensor, a system control unit, an alarm display WDT, a clock chip RTC, a static random access memory SRAM, an output and input port GPIO/two-way two-wire system synchronous serial bus I²C. The device comprises an infrared modulation unit, a serial port communication UART (the serial port communication UART is connected with a wireless module) unit, a Liquid Crystal Display (LCD), a FLASH memory FLASH, a JTAG communication interface debugging unit, a reference voltage unit, a power management unit, a calendar clock unit, a high-energy battery, a voltage stabilizer, a power protection detection and power-on reset unit. The system control unit is used for carrying out system control on the electric meter and is realized by adopting a high-grade controller/microprocessor, and the reference voltage unit is used for generating reference voltage for wave sending of an SVM wave sending module of the SVM search synthesizer and three-phase reference voltage at a public point of the smart power grid.

The system comprises an SVM search synthesizer, a specific error calibration unit, a high-pass filter, a meter calibration parameter unit, a power and effective value measurement unit, an electric energy measurement chip, a CF pulse generation unit, a timing management unit, a power management unit, a calendar clock unit, a high-energy battery, a voltage stabilizer, a power protection detection unit and a power-on reset unit, wherein the CF pulse generation unit is realized by arranging LDE pulse display at the CF end of the electric energy measurement chip, the timing management unit, the power management unit, the calendar clock unit, the high-energy battery, the voltage stabilizer, the power protection detection unit and the power-on reset unit are realized by MCU chip software, the MCU chip and the electric energy measurement chip are connected into the distributed IO interfaces of the microprocessors of the DSP and the like and the system control unit, the microprocessor of the DSP and the like is connected into the distributed IO interfaces of the system control unit, the alarm display WDT, the output input GPIO/two-way two-wire system synchronous serial bus I²C. The infrared modulation unit, the serial port communication UART (the serial port communication UART is connected with the wireless module) unit, the liquid crystal display LCD, the FLASH memory FLASH, the JTAG communication interface debugging unit and the reference voltage unit are realized through the system control unit.

Calibration parameter unit and chip MCU, system control unit, alarm display WDT, clock chip RTC, static random access memory SRAM, general purpose output input port GPIO/bidirectional two-wire system synchronous serial bus I²C. An infrared modulation unit, a serial communication UART (the serial communication UART is connected with a wireless module) unit, a liquid crystal display LCD, a FLASH FLASH, a JTAG communication interface debugging unit, a reference voltage unit, a power management unit, a power protection detection and power-on reset unit, a temperature sensor and a data memory output information parameters to a chip MCU, a system control unit, an alarm display WDT, a clock chip RTC, a static random access memory SRAM, a general output input port GPIO/a two-way two-wire system synchronous serial bus I²C. The device comprises infrared modulation, a serial communication UART (the serial communication UART is connected with a wireless module), a liquid crystal display LCD, a FLASH memory FLASH, a JTAG communication interface debugging unit, a reference voltage unit, a power management unit, a power protection detection unit and a power-on reset unit.

The power management unit adopts a low-power-consumption power management unit, the power management unit is connected with the voltage stabilizer and the high-energy battery, the high-energy battery supplies power for the calendar clock, and the calendar clock supplies power for the MCU chip.

The SVM search synthesizer is connected with an SVM wave-generating module of the distributed light storage and charge-discharge system, a single-phase inversion unit of an A phase, a B phase and a C phase of an independent structure is driven to correspond to a plurality of groups of switches at high precision and quickly, photovoltaic electricity of the distributed light storage system is inverted and converted, besides, a sine wave of a Gaussian window function output by the SVM search synthesizer and with standard identification frequency is input into a wavelet transformation unit for wavelet transformation after ratio difference calibration and high-pass filtering, and then is sequentially input into a frequency sorting unit and an integrator for calculating integral current after wavelet transformation, the frequency sorting unit and the integrator are realized in an MCU through software, harmonic waves and inter-harmonic waves are obtained by utilizing the integral current to synthesize active electric energy measurement and reactive electric energy measurement, and forward power generation (selling) electric quantity and reverse power generation (buying) electric quantity measurement are completed.

A Gaussian function window with self-adaptive variable time-frequency is additionally arranged, an SVM search synthesizer is in butt joint with a wavelet transformation module, large-scale renewable energy sources and wind-solar energy storage are accessed into a smart grid (less than 10% of renewable energy sources and wind-solar energy storage are accessed into the smart grid, the advantages of the SVM search synthesizer are unchanged, if the advantages of the SVM search synthesizer are exceeded, the SVM search synthesizer are changed), so that the power harmonic waves and inter-harmonic waves of the smart grid are complex and changeable, particularly, the amplitude-frequency mutation distortion of the original SVM search synthesizer and the defect that the original Gaussian window function cannot be adjusted in a self-adaptive mode due to sudden changes and unstable signals of the power harmonic waves and the inter-harmonic waves in time domain and frequency domain are caused, and electric energy metering errors and fluctuation of an optical storage charging and discharging system are caused.

The wavelet transform process is as follows:

performing orthogonal wavelet decomposition on the voltage/current f (t) output by the SVM search synthesizer:

P_j-1f(t)＝P_jf(t)+D_jf(t)； (3)

wherein, P_jIs the j-th layer scale coefficient of f (t), P_j-1Is the (j-1) th layer scale factor of (f), (t), D_jIs the j-th layer wavelet coefficient of f (t),

and is

Is the j-th layer decomposition coefficient of f (t),

is the (j-1) th layer decomposition coefficient of (f), (t),

is the jth layer wavelet decomposition coefficient of f (t),

layer j-1 wavelet decomposition of f (t)The coefficient of solution is calculated,

as a function of scale, Ψ_j,k(t) is the wavelet basis function, h_0(n-2k)Low-pass filtering units, h, being wavelet packets_1(n-2k)A high pass filtering unit for wavelet packets;

wavelet packet decomposition and reconstruction:

wherein,

for the wavelet packet reconstruction coefficients,

and

is the wavelet packet decomposition coefficient, g_0(l-2k)Low-pass filtering unit for wavelet packet reconstruction, g_1(l-2k)A high-pass filtering unit for wavelet packet reconstruction, wherein l is a reconstructed harmonic sequence number;

during the sampling period, the voltage signal of the harmonic is:

where k is 0, and i is 0, which means only that the initial value of the summation calculation is 0;

during the sampling period, the current signal of the harmonic is:

wherein,

is a scaleA spatial function;

is a wavelet mother function;

to reconstruct the coefficients of the scale function in the voltage signal,

is the coefficient of the scale function in the reconstructed current signal;

transforming the wavelet packet transform coefficients in the reconstructed voltage signal;

wavelet packet transform coefficients in the reconstructed current signal.

With active computing

The expression for power P is:

the active electrical energy can then be expressed as:

when the SVM search synthesizer is in butt joint with a wavelet transform combination, an online time-frequency window which can change in time is provided, when a high-frequency signal appears, the time window of the Gaussian function sine wave can be automatically narrowed, when a low-frequency signal appears, the time window of the Gaussian function sine wave can be automatically widened, the characteristic that a local Gaussian function sine wave window is unchanged is changed, and the problem that the amplitude, the frequency and the phase of each subharmonic and interharmonic are difficult to accurately obtain in wavelet transform because the local Gaussian function sine wave window cannot reflect the sudden change of harmonic and interharmonic signals is solved. The time window of the Gaussian function sine wave can automatically adapt to changes brought by different conditions, maximum values of singularities of representation signals on different scales are reflected, sudden changes and time-varying tracking distortion of harmonic and inter-harmonic signals can be reflected, the step effect caused by data compression is eliminated through signal reconstruction, time domain signals in each sub-band are reconstructed through wavelet packet decomposition coefficients, rapid detection, measurement, analysis, resolution and tracking of power harmonic and inter-harmonic parameters in each frequency band are achieved, low-wave and high-wave filtering combination of wavelet packet reconstruction is achieved, the precision and details of original time-frequency standards of local signals of the Gaussian function sine wave window are reserved, and high-precision online timely electric energy is obtained according to an active electric energy calculation formula.

According to the SVM search synthesizer, wavelet transformation, frequency sequencing and integral current are butted, so that the measurement of harmonic waves and intermittent active and reactive electric energy, and the online resolution, analysis, detection, measurement and tracking of frequency, phase and amplitude can be easily obtained on line. By tracking the sequencing frequency, the frequency of different source side power generation and electric energy on the network side and the load side is automatically identified, and the electric identities of the source side power generation, the network side and the load identity of the load side are identified. The wireless network can be accessed, the electric energy, the bill, the carbon emission and the carbon comprehensive quantity of the wireless network meter and the online virtual intelligent electric meter can be obtained, and the high-precision electric energy metering can be realized.

One output of the standby function measuring channel and the output of the temperature sensor are combined and output to a distributed IO interface of a microprocessor such as a DSP (digital signal processor) so as to control the temperature when the standby function measuring channel is used, and the normal operation of the high-precision internet of things intelligent electric meter for searching and measuring the electric energy parameters is not influenced by the starting of the standby function measuring channel; and the comparator and the modulator are used for modulating the signal input by the standby function testing channel and inputting the modulated signal to the phase-locked loop PLL for phase locking.

In the embodiment of the high-precision internet-of-things intelligent electric meter for searching and measuring the electric energy parameters, the modulator is not limited to the second-order sigma-delta modulation, and multifunctional detection modulation not limited to system temperature detection and modulation not limited to system direct-current voltage detection are realized. The method is not limited to the adoption of four-order sigma-delta modulation, is not limited to the detection and modulation of the direct current of the system, and combines digital filtering and high-pass filtering to realize the measurement of the direct current forward power generation (selling) electric quantity and the reverse power generation (buying) electric quantity. The method is not limited to the adoption of third-order sigma-delta modulation, multifunctional detection modulation for system temperature detection, modulation for system alternating voltage detection and modulation for system alternating current detection, and the measurement of alternating current forward power generation (selling) electric quantity and reverse power generation (buying) electric quantity is realized by combining digital filtering and high-pass filtering; the three-order sigma-delta modulation is respectively accessed to the output A phase, the B phase, the C phase and the neutral line of an inverter of the distributed photovoltaic inverter power generation system, 67dB signal to noise ratio is provided by the 3kHz signal bandwidth, shunt type three-order sigma-delta current modulation is adopted, 72dB signal to noise ratio is provided by the 3kHz signal bandwidth, shunt type three-order sigma-delta voltage modulation is adopted, the distributed photovoltaic inverter power generation system supplies power to a load user and is defined as forward 1, the distributed photovoltaic inverter power generation system supplies power to a power grid and is defined as forward 2, the distributed photovoltaic inverter power generation system supplies power to a BMS-battery system (BMS battery pack) and is defined as forward 3, the BMS-battery system supplies power (not shown in the figure) to the load user and is defined as forward 4, the BMS-battery system discharges power to the power grid and is defined as forward 5, and the BMS-battery system supplies power to the distributed photovoltaic inverter power generation system and a control system (such as a temperature control system, a temperature control system, Fire extinguishing system) power supply is defined as forward 6, and the BMS-battery system supplies power to the distributed photovoltaic inversion power generation system and needs to be connected with a corresponding reverse connection system (not shown in figure 1); the power supply from the power grid to the distributed photovoltaic inversion power generation system (a corresponding reverse connection system needs to be connected, which is not shown in fig. 1) is defined as negative 1, the power supply from the power grid to a load user is defined as negative 2, and the power supply from the power grid to the BMS-battery system is defined as negative 3; the forward (reverse) voltage and current respectively provided by the voltage division type third-order sigma-delta voltage modulation and the voltage division type third-order sigma-delta voltage modulation are respectively provided to a multiplier of the electric energy metering unit for operation, and forward and reverse active electric energy, combined active electric energy, multi-quadrant reactive electric energy, combined reactive electric energy, apparent electric energy, split-phase electric energy and split-rate electric energy are calculated. The electric energy metering unit, buy and sell the electric quantity in real time, the real-time clock passes through MCU chip (measurement chip) control realization, the frequency of MCU chip output all is through microprocessor such as SPI interface connection to DSP, set up LCD around MCU and show, infrared communication, RS485 communication, the bluetooth communication, the carrier communication, the module communication, data storage, alarm output, the key input, magnetic field detection, real-time detection, low-power consumption power management, relay control and control module's function sets up the constitution.

Example 3

The embodiment of the invention provides an inter-harmonic parameter estimation method for a support vector machine and a TLS-ESPRIT algorithm, which is used for solving the phase, amplitude and frequency of single-phase alternating current and comprises the following specific processes:

the sampling real signal expression of the electric carbon of the power grid is as follows:

wherein x (n) is the real power grid sampling signal of the nth sampling point, p is the harmonic component of the real power grid sampling signal, EF_kIs the k-th carbon emission coefficient, alpha_kSampling the amplitude, omega, of the kth and inter-harmonic components of a real signal for a power grid_kThe angular frequency of the kth harmonic and inter-harmonic components of the real signal are sampled for the grid,

the phase of the k-th harmonic and inter-harmonic components of the real grid sampled signal is shown, and ω (n) is the noise component of the real grid sampled signal at the nth sampling point.

Solving the power grid frequency based on TLS-ESPRIT, and transforming the formula (9) into a sampling complex signal through Euler transformation, namely the formula (10):

wherein, alpha'_kIs the amplitude, ω ', of the kth harmonic and inter-harmonic components of the sampled complex signal'_kTo sample the angular frequencies of the kth harmonic and inter-harmonic components of the complex signal,

the phase of the kth harmonic and inter-harmonic components of the sampled complex signal.

Defining an L × 1(L > 2p) dimensional semaphore:

X(n)＝[x(n)，x(n+1)，…，x(n+L-1)]^T； (11)

equation (11) is described using equation (10) as:

in the formula,

A＝[α(ω′₁)，α(ω′₂)，…，α(ω′_2P)]，

W(n)＝[W(n)，W(n+1)，…，W(n+L-1)]^T；

in the formula (12), when k is more than or equal to 1 and less than or equal to p,

when p is less than or equal to k is less than or equal to 2p,

ω′_k＝-ω_k-p,

a_k-psampling the amplitude, omega, of the k-p harmonic and inter-harmonic components of a real signal for a power grid_k-pThe frequencies of the k-p th harmonic and inter-harmonic components of the real signal are sampled for the grid,

sampling the initial phase angles of the k-p harmonic and inter-harmonic components of the real signals for the power grid;

the first row S (n) and the last row are removed, and vectors S1 and S2 which are mutually staggered are obtained by a vertical decomposition method respectively:

is provided with

The frequency information of the signal is completely contained in the twiddle factor matrix

In (1).

The sampled data form a time series:

based on the constraint of minimum overall mean square error, the frequency parameters of the inter-harmonics are estimated, which is carried out as follows

(1) Constructing a HANKEL matrix by using the sampled data:

wherein M is the number of array elements, M > L > >2p, M + L-1 ═ N;

(2) singular value decomposition is performed on the matrix X:

wherein L is a left singular vector matrix, U^HIs a right singular vector matrix; sigma is a diagonal matrix of singular values arranged in descending order; l is_sLeft singular vector matrix, L, corresponding to the maximum singular value_nA left singular vector matrix corresponding to the minimum singular value;

is a right singular value vector matrix, sigma, corresponding to 2P maximum singular values_sIs that

To form a signal subspace;

is a right singular value vector matrix, sigma, corresponding to L-2p minimum singular values_nIs that

Is formed into a noise subspace.

(3) Remove

The first line and the last line of the vector are respectively obtained by a vertical decomposition method to form two mutually staggered vectors U₁And U₂Let U1 be Ψ U1, and use the least square idea to pair the matrix [ U ═ U1₁,U₂]Singular value decomposition is carried out:

(4) will be provided with

The matrix is decomposed into 4 square matrices of 2p × 2 p:

then there are:

(5) to psi_TLSDecomposing the characteristic value to obtain the characteristic value lambda_kCharacteristic value lambda_kI.e. a twiddle factor matrix

Thereby estimating the frequency parameters of the signal:

amplitude and phase search based on support vector machine:

transforming equation (9) yields:

in the formula,

the noise component omega (n) is the model error e of the nth signal sampling point_nThe amplitude of the signal is then alpha_kAnd phase

Can be composed of C_KAnd D_KObtaining:

let W be [ C ]₁，…C_p，D₁，…D_p]And selecting a quadratic epsilon insensitive loss function, introducing a Lagrange function into the optimization problem, and obtaining a standard iteration variable weight least square method format only related to W:

in the formula, L_WIs a minimum point of W, λ_n＝2α_n(e_n-ε)，

Lagrange multipliers can be obtained according to KKT conditions; by

Obtaining:

in the formula,

is a diagonal element of

The diagonal matrix of (a) is,

is a diagonal element of

A diagonal matrix of (a); x is a column vector of sampled data,

y_n＝[cosω₁n，…，cosω_pn，-sinω₁n，…，-sinω_pn]and epsilon is a column vector with elements of epsilon.

After obtaining W, the amplitude and phase of the signal can be determined from C_KAnd D_KThe result is obtained according to equation (21). The search for frequency, amplitude and phase in a large range is avoided, and the calculation amount of the support vector machine algorithm is reduced.

And (3) carrying out verification:

1. simulation of TLS-ESPRIT frequency search (in contrast to the estimation of the eigenfrequency of the conventional autocorrelation matrix)

The sampling frequency is 1000HZ, the sampling number is 1000 points, and c is 0.5; epsilon is 0.01; ω is white gaussian noise with SNR of 20 dB.

The autocorrelation matrix eigenfrequency estimates are given by figure 4 as 50.00048 respectively; 8546954, respectively; 150.0358, FIG. 5 shows TLS-ESPRIT frequency search values: 50.0000, respectively; 85.0001, comparing FIG. 4 with FIG. 5: in the low signal-to-noise ratio case, the accuracy of the TLS-ESPRIT frequency search inter-harmonic frequencies is higher than the autocorrelation matrix eigenfrequency estimates, and the TLS-ESPRIT frequency search reduces correlation calculations.

TABLE 1 TLS-ESPRIT frequency search value simulation signal parameter estimation results

Item	frequency/Hz	amplitude/V	Phase Angle/(°)
				1	45.00049	2.50000	19.9852
2	50.0987	99.66599	30.00498
				3	115.0001	1.991598	39.9479
4	149.9999	3.98909	60.09809
				5	175.00001	1.49598	44.9759

From the estimation result of the TLS-ESPRIT frequency search value simulation signal parameters in the table 1, the TLS-ESPRIT frequency search can accurately search and estimate the signal parameters of the smart grid containing multiple harmonics and inter-harmonic components, of which the fundamental frequency deviates, under the condition of low signal-to-noise ratio.

2. Simulation of phase amplitude search for support vector machine (in contrast to least squares LS estimation)

TABLE 2 LS vs. SVM search algorithm estimation results comparison

As can be seen from the comparison in Table 2, under the condition of high signal-to-noise ratio, the support vector machine algorithm and the least square method LS have good estimation performance of amplitude and phase parameters; however, under the condition of low signal to noise ratio, the support vector machine algorithm has better estimation performance and better stability.

The embodiment of the invention combines the advantages of TLS-ESPRIT search frequency, phase amplitude estimation of a support vector machine and wavelet transformation, and solves the problems that the calculation amount is large and the precision is not high by singly adopting an algorithm, the renewable energy sources comprise the sudden change and distortion of harmonic waves and inter-harmonic waves caused by the large-scale access of wind-solar energy storage to a smart grid, the analysis time consumption of a chip is long, and the requirement of the smart grid networking standard cannot be met. Especially under low signal-to-noise ratio, the precision is higher than that of the existing methodGo out 2 grades to 10^-5～10^-3Magnitude. TLS-ESPRIT accurately divides the signal space of the smart grid, shields the influence of noise on frequency, and has higher calculation precision than the algorithm in the prior art through TLS-ESPRIT and the phase amplitude plus wavelet transformation of the support vector machine.

Example 4

As shown in fig. 1, a distributed light storage charging and discharging system for a smart grid and an internet of things based on an electric energy parameter search measurement high-precision internet of things smart meter, includes:

the system comprises a BMS-battery management system, a first transformer (10kv/0.4kv power transformer) and a second transformer, wherein the BMS-battery management system is used for intelligently managing and maintaining a battery pack, is connected with the smart grid through the battery pack and an AC/DC PCS subsystem which are sequentially connected, and is used for charging and discharging by utilizing the battery pack and realizing frequency modulation, voltage regulation, emergency power support and peak regulation of the smart grid;

the light storage charging and discharging direct current cabinet is used for carrying out confluence and lightning protection treatment on direct current output of the distributed photovoltaic inversion power generation system and then charging a battery pack of the BMS-battery management system under the control of the intelligent control manager;

as shown in fig. 1, the light storage charging and discharging dc cabinet includes:

Distributed light storage charging and discharging system based on electric energy parameter search measurement high-precision internet-of-things intelligent electric meter further comprises:

intelligent control manager, intelligent control manager includes:

the EMS monitoring management host protection system is used for monitoring and managing the BMS battery management systems;

the MPPT controller is used for carrying out maximum power tracking control, detecting the power generation voltage of the solar panel in real time, and tracking the maximum voltage and current value to enable the system to output at the maximum power;

and the PWM controller is used for controlling the inversion or rectification of a current transformer in the AC/DC PCS subsystem connected with the battery pack in each BMS-battery management system.

Each BMS-battery management system is also connected with a temperature monitoring system and a fire fighting system, the temperature monitoring system is used for monitoring the temperature of the battery pack, and the fire fighting system is used for preventing the battery pack from being ignited and exploded;

the metering lightning protection total distribution box is connected with the distributed light storage and discharge system, is used for performing overvoltage and undervoltage protection, lightning protection and metering on electric energy output by the distributed photovoltaic inversion power generation system and supplying power to a load, and comprises a third circuit breaker, an overvoltage/undervoltage protection circuit, a circuit device, a surge protection circuit, a disconnecting switch, a wiring terminal and a first intelligent electric meter, particularly, the first intelligent electric meter adopts the electric energy parameter search measurement high-precision physical connection intelligent electric meter, one end of the third circuit breaker is connected with the alternating current output end of the distributed photovoltaic inversion power generation system, the other end of the third circuit breaker is connected with one end of the overvoltage/undervoltage protection circuit, the other end of the overvoltage/undervoltage protection circuit is connected in two ways, one way is connected with one end of the circuit device, and the other end of the circuit device is connected with the surge protection circuit, wherein another way is connected with switch one end, and the switch other end is connected first smart electric meter through connecting terminal, and first smart electric meter inserts three-phase four-wire commercial power transmission line through three-phase combination switch, and the access point net side sets up second smart electric meter, and second smart electric meter also adopts electric energy parameter search measurement high accuracy thing allies oneself with smart electric meter, and access point load side is through three-phase switch connection three-phase load.

Further, the other end of the second intelligent electric meter is connected with the intelligent power grid through a second transformer (10kv/0.4kv power transformer).

Further, based on electric energy parameter search volume high accuracy thing allies oneself with smart electric meter's distributed light storage system of filling still includes:

the anti-reflux controller is used for detecting a power grid to judge whether a reverse current occurs in the system when the distributed photovoltaic inverter power generation system generates power, and the system is controlled to enable the reverse current to meet requirements after the reverse current exceeds the requirements, and is specific:

when the distributed photovoltaic inversion power generation system generates power, if the occurrence of reverse current is detected, judging the electric quantity of a battery pack in the BMS battery management system, if the electric quantity of the battery pack in the BMS battery management system is not full, controlling the distributed photovoltaic inversion power generation system to charge the battery pack in the BMS battery management system, then judging whether reverse current still exists, if the reverse current continues to exist, controlling to reduce the output current of an inverter until the reverse current meets the requirement; and if the battery pack in the BMS battery management system is full of electric quantity, controlling to directly reduce the output current of the distributed photovoltaic inverter power generation system until the inverse current meets the requirement.

When the smart grid generates power to the distributed photovoltaic inverter power generation system, the smart grid needs to be connected with the distributed photovoltaic inverter power generation system through a corresponding reverse connection system, and specifically, a 3S/2R conversion module is firstly adopted to convert three-phase power at a public point of the smart grid into a direct-current component V under a synchronous rotating coordinate system_d、V_qAnd then, a phase-locked loop PLL is adopted for phase locking, the frequency, the phase and the amplitude of the three-phase power at the public point of the smart grid are output, and an SVM (space vector modulation) wave-transmitting module is adopted for wave-transmitting control of the converter for rectification by utilizing the frequency output by the phase-locked loop PLL.

When adopting phase-locked loop PLL to carry out the lock phase, phase-locked loop PLL is inside including loop filter, PI controller and the integrator that connects gradually, and phase-locked loop PLL's input connects the multiplier, and the input is the three-phase electricity of smart power grids public point department all the way of multiplier, and another way input is phase-locked loop PLL's output, and two inputs are got after multiplier multiplication:

wherein the former item

For the low-frequency component of the input and output phase difference of the phase-locked loop PLL, the latter term

The high frequency component which can be filtered by the loop filter; omega is the frequency of the output signal of the phase locked loop PLL,

for the output stator flux signal, omega, of a phase-locked loop PLL_gBeing the frequency of the input signal of the phase locked loop PLL,

excitation signal, V, being the input signal of a phase-locked loop PLL_mIs the reference voltage in the multiplier;

input phase locked loop PLL, loop filter (LPF) for phase locked loop PLL to filter out high frequency components

Output signal V_f：

Then the signal V_fAs a direct current component V_dInputting the frequency to a PI controller, and generating an estimated frequency omega (theta) after PI regulationAfter integration, the output signal of the PLL is formed, the output phase is locked with the input phase, the difference between the input signal and the output signal is 90 degrees, the input signal is a cosine function, the output signal is a sine function, the phase angle of the output signal is added with a constant value, and the requirement of any phase angle can be met.

Involving V in a synchronously rotating coordinate system_d、V_qTwo direct current components, θ ═ θ is required to lock the phase of the input signal_g，ω＝ω_g，

At steady state, V_dThe output of the PI controller is an estimated frequency which is integrated to obtain an estimated phase, and the amplitude of the estimated voltage is equal to 0

When the phase is locked, E ═ V_qAnd at the moment, the frequency, the amplitude and the phase angle can be obtained from the synchronous rotating coordinate phase-locked loop, and then wave sending is carried out by utilizing the estimated frequency, the estimated phase and the estimated voltage amplitude E.

The estimated frequency serves as a phase error detection during the 3S/2R conversion, since V_dThe loop filter is a simple unit gain, the PI controller and the integrator can generate frequency and phase, and static errors are eliminated by tracking the phase and the frequency, so that the fast and accurate tracking performance is obtained under the condition of high bandwidth.

In order to verify the effectiveness of a distributed optical storage charging and discharging system of a high-precision internet-of-things intelligent ammeter based on electric energy parameter search measurement, a photovoltaic electric energy matching electric energy parameter search measurement high-precision internet-of-things intelligent ammeter is simplified and designed according to a graph 1, the 1 electric energy parameter search measurement high-precision internet-of-things intelligent ammeter is connected to two prototype machines connected in parallel with 500KW converters for verification, the maximum power tracking efficiency (MPPT) of the KW with a 500KW topological structure is more than or equal to 99.9%, a space vector modulation algorithm (SVM/SVPWM) is adopted, DSP control is adopted, a DSP control chip controls MTTP and PMW for TMS320F28075-Q, an electric energy multidirectional metering selection metering chip ADE7913, an MCU selection chip UPD78F1166 is adopted, under the control of hardware and software, photovoltaic electric energy matching grid-connected metering is realized for the distributed optical storage charging and discharging system based on electric energy parameter search measurement high-precision internet-of things intelligent ammeter, and forward and backward active electric energy matching grid-connected metering is realized, and forward and backward active electric energy matching grid-connected metering are realized, and forward and reverse direction active electric energy matching metering is realized, and reverse direction active electric energy matching grid-connected by the distributed optical storage charging and discharging system is realized by the distributed photovoltaic electric energy matching electric meter, and discharging system is realized by the distributed intelligent ammeter based on the distributed electric energy matching grid-connected with the design method based on the advantages of which is realized by the design and forward and discharging system based on the control of high-connected with the control of high-based on electric energy parameter search measurement high-connected with the high-connected electric energy parameter search measurement of electric energy searching and forward and reverse measurement of electric energy searching and reverse measurement of which are realized by the design and forward and reverse connection of which are realized by the high-connected with the design and reverse connection of electric energy parameter search measurement high-connected electric energy searching and reverse connection of which are realized by the high-connected with the high-connected electric energy parameter search measurement of which are realized by adopting the space vector selection chip UPD and reverse connection of which are realized by the space vector selection chip UPD topological structure of the space vector selection chip UPD and reverse and forward and reverse direction of which are realized by the space vector selection chip UPD and reverse direction of which are realized by adopting the space vector selection chip UPD which are realized by adopting the space vector selection chip UPD and reverse direction of which are realized by the space vector selection chip UPD and forward and reverse direction of which are realized by adopting the space vector connected with the space vector connected, The electric energy meter has the advantages that the electric energy meter has the functions of passive forward and reverse, combined active electric energy, multi-quadrant reactive electric energy, combined reactive electric energy, apparent electric energy, split-phase electric energy and split-rate electric energy metering, the characteristic words of the combined mode can be set, and the electric energy meter has a remote charge control function (charge control intelligent electric energy meter configuration). The electric energy meter has a historical electric energy storage function of 12 settlement periods, the stored historical electric energy comprises forward and reverse active electric energy, combined active electric energy, multi-quadrant reactive electric energy, combined reactive function, total and fractional rate electric energy data and split-phase electric energy data of forward and reverse apparent electric energy, current error detection of a live wire and a ground wire (zero line) is adopted, the function of electricity larceny prevention is achieved, and meanwhile light load efficiency, accuracy, economy and reliability are improved.

The electric energy parameter searching and measuring high-precision internet-of-things intelligent electric meter shown in fig. 2 has the technical parameter requirements that: rated voltage 3 × 220/380; reference frequency (Hz) 50; current amount: 3 × 1.5 (6); function grade: active 1 grade and passive 2 grade; pulse constant: active (imp/kwh, 6400) and inactive imp/kwh, 6400.

The real-time data of the high-precision internet-of-things intelligent electric meter searched and measured based on the electric energy parameters in the distributed light storage charging and discharging system of the high-precision internet-of-things intelligent electric meter searched and measured based on the electric energy parameters are detected fully automatically through the electric energy meter of a standard laboratory detection platform, the comparison object is a power source, and the result is shown in tables 3-6.

Table 3 electric energy parameter search measurement high precision real-time positive error of intelligent electricity meter for internet of things in embodiments of the present invention

Table 4 electric energy parameter search measurement high precision real time error of active power reversal of intelligent electricity meter for internet of things in accordance with embodiments of the present invention

Table 5 electric energy parameter search measurement high-precision real-time error of reactive power direction of internet of things smart meter according to embodiment of the present invention

Table 6 high-precision electric energy parameter search measurement reactive reverse real-time error of internet-of-things intelligent electric meter according to embodiment of the present invention

The electric energy parameter searching and measuring high-precision internet-of-things intelligent electric meter has the advantages that the active forward error meets the design level 1 standard, the active reverse error meets the design level 1 standard, the reactive forward error meets the design level 2 standard, and the reactive reverse error meets the design level 2 standard, so that the distributed light storage charging and discharging system for measuring the high-precision internet-of-things intelligent electric meter based on the electric energy parameter searching is effectively designed, and the photovoltaic power generation and metering standards are met.

The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims

1. An SVM search synthesizer, comprising:

2. The SVM search synthesizer of claim 1, wherein said compensation module comprises:

3. The SVM search synthesizer of claim 1, wherein said digital signal processing module comprises:

the I path mapping module is used for representing 0 in the digital signal consisting of 0 and 1 registered by the I path register by using a blank space and 1 by using a unit pulse to obtain an I path mapping waveform;

4. The SVM search synthesizer of claim 1, further comprising:

5. The utility model provides an electric energy parameter search measures high accuracy thing and allies oneself with smart electric meter which characterized in that includes:

wherein each identification metering circuit comprises:

6. The electric energy parameter search measurement high-precision internet-of-things intelligent electric meter according to claim 5, further comprising:

and the frequency sequencing unit is used for carrying out frequency sequencing on the voltage signals and the current signals of the harmonic waves and the inter-harmonic waves output by the wavelet transformation module and then averaging to obtain the average values of the voltage signals and the current signals of the harmonic waves and the inter-harmonic waves, outputting the average values to the high-pass filter for high-pass filtering, inputting the average values to the electric energy metering module for electric energy metering of the harmonic waves and the inter-harmonic waves after filtering of the high-pass filter, and summing the electric energy calculated by the sinusoidal voltage signals and the current signals output by the specific difference calibration unit in the electric energy metering module through the high-pass filter to obtain the total metered electric energy.

7. The electric energy parameter search measurement high-precision internet-of-things intelligent electric meter according to claim 5, further comprising:

8. The utility model provides a high accuracy thing allies oneself with smart electric meter's distributed light storage system of filling that measurations based on electric energy parameter search, its characterized in that includes:

the light storage charging and discharging direct current cabinet is used for converging direct current output of the distributed photovoltaic inversion power generation system, performing lightning protection treatment and charging a battery pack of the BMS-battery management system under the control of the intelligent control manager;

the second intelligent ammeter is used for searching and measuring the high-precision internet-of-things intelligent ammeter according to the electric energy parameters of any one of claims 5 to 7, is arranged on the network side of an access point of a metering lightning protection main distribution box connected to commercial power, and is used for accurately metering the electric energy supplied to a load by an intelligent power grid.

9. The distributed light storage and discharge system for measuring high-precision internet of things smart electric meters based on electric energy parameter search of claim 8, wherein the metering lightning protection total distribution box comprises a third circuit breaker, an over/under voltage protection circuit, a circuit device, a surge protection circuit, a disconnecting link switch, a wiring terminal and a first smart electric meter, wherein:

the first intelligent ammeter is an Internet of things intelligent ammeter for measuring high precision by adopting the electric energy parameter search method according to any one of claims 5 to 7;

the first intelligent electric meter is connected with a three-phase four-wire commercial power through a three-phase composite switch, and the load side of the access point is connected with a three-phase load through a three-phase switch;

10. The distributed light storage and charging and discharging system for searching and measuring the high-precision internet-of-things intelligent electric meter based on the electric energy parameters is characterized by further comprising:

the intelligent control manager comprises:

the MPPT controller is used for carrying out maximum power tracking control;

the light stores up fills and fills direct current cabinet includes:

and the second circuit breaker is used for carrying out on-off control on the total current between the light storage charging and discharging direct current cabinet and the intelligent manager.