CN117852979B - New energy consumption evaluation method, device, equipment and medium - Google Patents
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Abstract
The invention belongs to the technical field of new energy consumption, and particularly relates to a new energy consumption evaluation method, a new energy consumption evaluation device, new energy consumption evaluation equipment and a new energy consumption evaluation medium. The method comprises the following steps: acquiring new energy data and load point data in a preset area; calculating the absorption priority of the output of each new energy according to the new energy data and the load point data; carrying out normalization processing on the new energy data and the load point data to generate a new energy power characteristic curve and a load point power characteristic curve; according to the new energy power characteristic curve and the load point power characteristic curve, calculating the correlation coefficient of each new energy and the load point power characteristic curve in sequence according to the absorption priority of each new energy output; and evaluating the new energy consumption according to the correlation coefficient of the output of each new energy, and displaying the power consumption of the new energy. According to the method, the new energy consumption priority is determined by calculating the distance between the center of gravity and the new energy, so that the complex process of calculating the impedance of the electric equivalent of the grid rack is avoided, the calculation process of evaluating the consumption capacity is simplified, and a new thought is provided for selecting the new energy consumption priority.
Description
Technical Field
The invention belongs to the technical field of new energy consumption, and particularly relates to a new energy consumption evaluation method, a new energy consumption evaluation device, new energy consumption evaluation equipment and a new energy consumption evaluation medium.
Background
The new energy consumption evaluation current stage mainly adopts a typical daily analysis method, a random production simulation analysis method and a time sequence curve fitting analysis method, and can evaluate and analyze the new energy consumption capability in a typical mode and a limit mode, but is limited by weather, load and grid structure random change, so that the new energy consumption capability evaluation result is conservative, key data such as power consumption load, conventional power supply output, new energy output, regional section power and the like related to new energy consumption are required to be extracted from a grid model and massive operation data, the calculated amount of the existing new energy consumption capability evaluation method is large, and the evaluation result is inaccurate.
Disclosure of Invention
The invention aims to provide a new energy consumption evaluation method, device, equipment and medium, which are used for solving the technical problems of low calculation speed and low precision caused by large data quantity required in the existing new energy consumption evaluation.
In order to achieve the above purpose, the invention adopts the following technical scheme:
in a first aspect, a new energy consumption evaluation method includes the steps of:
acquiring new energy data and load point data in a preset area;
calculating the absorption priority of the output of each new energy according to the new energy data and the load point data;
carrying out normalization processing on the new energy data and the load point data to generate a new energy power characteristic curve and a load point power characteristic curve;
According to the new energy power characteristic curve and the load point power characteristic curve, calculating the correlation coefficient of each new energy and the load point power characteristic curve in sequence according to the absorption priority of each new energy output;
And evaluating the new energy consumption according to the correlation coefficient of the output of each new energy, and displaying the power consumption of the new energy.
The invention further improves that: the new energy data includes: new energy output curve data, new energy position information and new energy rated capacity;
The load point data includes: load point power data, load point position information, and load point variable capacity.
The invention further improves that: the step of calculating the absorption priority of the output of each new energy according to the new energy data and the load point data specifically comprises the following steps:
calculating a load point distribution weight coefficient in the space according to the load point data;
Calculating barycentric coordinates according to the load point data;
And calculating the absorption priority of each new energy according to the load point data, the gravity center coordinates and the new energy data.
The invention further improves that: the step of calculating the barycentric coordinates according to the load point data specifically comprises the following steps:
obtaining longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates of each load point, and setting a gravity center v;
calculating the distance from each load point to the center of gravity by using haversine formula;
Correcting the distance from each load point to the center of gravity according to the load point distribution weight coefficient in the space to obtain a corrected distance;
and obtaining the barycenter coordinates according to the corrected distance.
The invention further improves that: the step of calculating the absorption priority of each new energy according to the load point data, the barycentric coordinates and the new energy data specifically comprises the following steps:
acquiring longitude and latitude coordinates of each new energy according to the new energy data, and acquiring longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates, barycentric coordinates and longitude and latitude coordinates of each load point of each new energy source;
calculating the distance from each new energy source to the center of gravity according to the longitude and latitude coordinates, the center of gravity coordinates and the longitude and latitude coordinates of each load point of each new energy source after radian conversion;
and sorting the distances from the new energy sources to the gravity centers according to the sizes, wherein the smaller the distance from the new energy sources to the gravity centers is, the higher the absorption priority is.
The invention further improves that: the correlation coefficient is r (F j,Fi);
Wherein r (F j,Fi) represents the correlation coefficient of the new energy power characteristic curve j and the load point power characteristic curve i; cov (F j,Fi) represents the covariance of the new energy power characteristic curve j and the load point power characteristic curve i, var|f i | represents the variance of the load point power characteristic curve i, and var|f j | represents the variance of the new energy power characteristic curve j.
The invention further improves that: the step of evaluating the new energy consumption according to the correlation coefficient of the output of each new energy and displaying the power consumption of the new energy specifically comprises the following steps:
Each load point sequentially dissipates new energy according to the sequence of the absolute value of the photographic relation number from high to low;
when the power of the new energy to be absorbed is larger than or equal to the power of the load point, the power of the new energy to be absorbed is equal to the power consumption of the load;
when the power of the new energy to be absorbed is smaller than the power of the load point;
Wherein W j , is the new energy generating capacity when the new energy power to be consumed is smaller than the load point power, P i-1 is the load point t-1 moment power, and P jt is the new energy t moment power generation power;
when the absolute value of the correlation coefficient is smaller than a preset value, acquiring the conventional power supply and the adjustable power of the outgoing section in a preset area;
Wherein W j ,, is the new energy power generation amount when the absolute value of the correlation coefficient is smaller than a preset value, P j is the new energy output power at the time t-1, and P abj is the conventional power supply and the adjustable power of the outgoing section;
New energy may consume electricity=w j ,+Wj ,,.
In a second aspect, the present invention provides a new energy consumption evaluation device, comprising:
And a data acquisition module: the method comprises the steps of acquiring new energy data and load point data in a preset area;
priority calculation module: the method comprises the steps of calculating the absorption priority of the output of each new energy according to the new energy data and the load point data;
And a curve generation module: the method comprises the steps of carrying out normalization processing on new energy data and load point data to generate a new energy power characteristic curve and a load point power characteristic curve;
And a correlation coefficient calculation module: the method comprises the steps of sequentially calculating correlation coefficients of each new energy and a load point power characteristic curve according to the new energy power characteristic curve and the load point power characteristic curve and the absorption priority of each new energy output;
And an output module: the method is used for evaluating the new energy consumption according to the correlation coefficient of the output of each new energy and displaying the power consumption of the new energy.
In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements a new energy consumption evaluation method as described above when executing the computer program.
In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements a new energy consumption evaluation method as described above.
Compared with the prior art, the invention at least comprises the following beneficial effects:
According to the method, the new energy consumption priority is determined by calculating the distance between the center of gravity and the new energy, so that the complex process of calculating the impedance of the electric equivalent of the grid rack is avoided, the calculation process of evaluating the consumption capacity is simplified, and a new thought is provided for selecting the new energy consumption priority.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a new energy consumption evaluation method of the present invention;
Fig. 2 is a block diagram showing a structure of a new energy consumption evaluation device according to the present invention.
Detailed Description
The invention will be described in detail below with reference to the drawings in connection with embodiments. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
The following detailed description is exemplary and is intended to provide further details of the invention. Unless defined otherwise, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the invention.
Example 1
A new energy consumption evaluation method, as shown in figure 1, comprises the following steps:
s1, acquiring new energy data and load point data in a preset area;
Specifically, the new energy data includes: new energy output curve data, new energy position information, new energy rated capacity and the like;
the load point data includes: load point power data, load point position information, load point variable capacity and the like;
s2, calculating the absorption priority of the output of each new energy according to the new energy data and the load point data;
Specifically, the method comprises the following steps:
s21, calculating a load point distribution weight coefficient in a space according to the load point data;
Specifically, a load point distribution weight coefficient w i in space;
wi=pmax/Savg；
Wherein p max is the maximum load moment power of the load point, and S avg is the average value of the variable capacitance of the load point;
p max is obtained through load point power data, and S avg is calculated through load point variable capacitance;
s22, calculating barycenter coordinates according to the load point data;
Specifically, in S22, the following steps are included:
s221, obtaining longitude and latitude coordinates (lngi, lnti) of each load point according to the position information of the load point in the load point data;
s222, performing radian conversion on longitude and latitude coordinates of each load point, and setting a gravity center v, wherein the longitude and latitude coordinates of the gravity center v are (lng 0, lnt 0);
s223, calculating the distance from each load point to the center of gravity by utilizing a haversine formula;
s224, correcting the distance from each load point to the center of gravity according to the load point distribution weight coefficient in the space to obtain a corrected distance;
Wherein D is a correction distance, D is a distance from a load point to the center of gravity, and w i is a load point distribution weight coefficient in space;
s225, obtaining a barycenter coordinate according to the corrected distance;
when the distance D from the load point to the center of gravity of the load point distribution weight is considered to be the minimum value, the coordinates (lng 0, lnt 0) are the center of gravity Is defined by the coordinates of (a).
S23, calculating the absorption priority of each new energy according to the load point data, the gravity center coordinates and the new energy data;
s231, acquiring longitude and latitude coordinates of each new energy according to the new energy data, and acquiring longitude and latitude coordinates of each load point according to the load point data;
S232, performing radian conversion on longitude and latitude coordinates, barycentric coordinates and longitude and latitude coordinates of each load point of each new energy source;
The longitude and latitude coordinates of the new energy v j after radian conversion are (rlngm, rlatm), the longitude and latitude coordinates of the load point after radian conversion are (rlngn, rlatn), and the longitude and latitude coordinates of the center of gravity after radian conversion are (rlng, rlat 0);
S233, calculating the distance from each new energy source to the center of gravity according to the longitude and latitude coordinates, the center of gravity coordinates and the longitude and latitude coordinates of each load point of each new energy source after radian conversion;
Wherein d , represents the distance from the new energy source to the center of gravity; a , represents the difference between the center of gravity and the latitude of the new energy, namely a ,=rlat0-rlatm;b, represents the difference between the center of gravity and the longitude of the new energy, namely b , = rlng0-rlngm, r represents the radius of the earth, and r= 6371.137km;
S234, sorting the distances from the new energy sources to the gravity centers according to the size, wherein the smaller the distance from the new energy sources to the gravity centers is, the higher the absorption priority is;
S3, carrying out normalization processing on the new energy data and the load point data to generate a new energy power characteristic curve and a load point power characteristic curve;
Specifically, in S3, the new energy power characteristic curve is obtained by performing normalization processing with the new energy rated capacity as a reference capacity;
carrying out normalization processing by taking the load point transformation capacity as a reference capacity so as to obtain a load point power characteristic curve;
Specifically, the new energy power characteristic curve:
Fj=Pj/Sj；
Fi=Pi/Si；
Wherein F j is a new energy power characteristic curve, P j is 96-point power of the new energy, and S j is rated capacity of the new energy; f i is a load point power characteristic curve, P i is load point 96 point power, and S i is load point rated capacity;
s4, according to the new energy power characteristic curve and the load point power characteristic curve, calculating correlation coefficients of the new energy and the load point power characteristic curve in sequence according to the absorption priority of the output of each new energy;
Wherein r (F j,Fi) represents the correlation coefficient of the new energy power characteristic curve j and the load point power characteristic curve i; cov (F j,Fi) represents the covariance of the new energy power characteristic curve j and the load point power characteristic curve i, var|f i | represents the variance of the load point power characteristic curve i, and var|f j | represents the variance of the new energy power characteristic curve j;
Specifically, r (F j,Fi) epsilon [ -1,1], when r (F j,Fi) is close to 1 or-1, the correlation is stronger; the correlation is lower when r (F j,Fi) approaches 0;
Therefore, the intensity of the correlation can be judged by the absolute value of r (F j,Fi), and the larger the absolute value of the correlation coefficient is, the stronger the correlation is;
And S5, evaluating the new energy consumption according to the correlation coefficient of the output of each new energy, and displaying the power consumption of the new energy.
Specifically, the method comprises the following steps:
each load point sequentially dissipates new energy according to the sequence of the absolute value of the photographing relation number from high to low, and when the power of the new energy to be dissipated is more than or equal to that of the load point, the power of the new energy to be dissipated is equal to the power consumption of the load;
Wherein W j is new energy-dissipatable electric quantity (new energy generating quantity) when the new energy power to be consumed is greater than or equal to the load point power, W i is load point electric quantity, and P i is load point power at time t;
when the power of the new energy to be absorbed is smaller than the power of the load point;
Wherein W j , is the new energy generating capacity when the new energy power to be consumed is smaller than the load point power, P i-1 is the load point t-1 moment power, and P jt is the new energy t moment power generation power;
when the absolute value of the correlation coefficient is smaller than a preset value, acquiring the conventional power supply and the adjustable power of the outgoing section in a preset area, and calculating the new energy source power consumption according to the conventional power supply and the adjustable power of the outgoing section;
specifically, the preset value is 0.5;
Wherein W j ,, is the new energy power generation amount when the absolute value of the correlation coefficient is smaller than a preset value, P j is the new energy output power at the time t-1, and P abj is the conventional power supply and the adjustable power of the outgoing section;
the new energy power generation amount is the sum of the new energy power generation amount when the absolute value of the new energy power consumption is smaller than a preset value and the new energy power to be consumed is smaller than the load point power;
wherein W abs is new energy which can consume electric quantity.
Aiming at the condition of low correlation between new energy and a load point power curve, when the absolute value of a correlation coefficient is smaller than a preset value, the conventional power supply and the area outgoing section adjusting capability are considered, and the electric quantity in the adjusting capability range is taken into consideration in the new energy absorbing capability. And accumulating the electric quantity of the new energy source consumed by the load points and the adjustable electric quantity of the conventional power source and the area outgoing section to obtain the capacity of the new energy source consumed by the area.
Example 2
As shown in fig. 2, the new energy consumption evaluation device includes:
And a data acquisition module: the method comprises the steps of acquiring new energy data and load point data in a preset area;
Specifically, the new energy data includes: new energy output curve data, new energy position information, new energy rated capacity and the like;
the load point data includes: load point power data, load point position information, load point variable capacity and the like;
priority calculation module: the method comprises the steps of calculating the absorption priority of the output of each new energy according to the new energy data and the load point data;
Specifically, the method comprises the following steps:
calculating a load point distribution weight coefficient in the space according to the load point data;
Specifically, a load point distribution weight coefficient w i in space;
wi=pmax/Savg；
Wherein p max is the maximum load moment power of the load point, and S avg is the average value of the variable capacitance of the load point;
p max is obtained through load point power data, and S avg is calculated through load point variable capacitance;
Calculating barycentric coordinates according to the load point data;
Specifically, the step of calculating the barycentric coordinates from the load point data includes:
Obtaining longitude and latitude coordinates (lngi, lnti) of each load point according to the position information of the load point in the load point data;
performing radian conversion on longitude and latitude coordinates of each load point, and setting a gravity center v, wherein the longitude and latitude coordinates of the gravity center v are (lng 0, lnt 0);
calculating the distance from each load point to the center of gravity by using haversine formula;
Correcting the distance from each load point to the center of gravity according to the load point distribution weight coefficient in the space to obtain a corrected distance;
Wherein D is a correction distance, D is a distance from a load point to the center of gravity, and w i is a load point distribution weight coefficient in space;
obtaining a barycenter coordinate according to the corrected distance;
when the distance D from the load point to the center of gravity of the load point distribution weight is considered to be the minimum value, the coordinates (lng 0, lnt 0) are the center of gravity Is defined by the coordinates of (a).
Calculating the absorption priority of each new energy according to the load point data, the gravity center coordinates and the new energy data;
acquiring longitude and latitude coordinates of each new energy according to the new energy data, and acquiring longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates, barycentric coordinates and longitude and latitude coordinates of each load point of each new energy source;
The longitude and latitude coordinates of the new energy v j after radian conversion are (rlngm, rlatm), the longitude and latitude coordinates of the load point after radian conversion are (rlngn, rlatn), and the longitude and latitude coordinates of the center of gravity after radian conversion are (rlng, rlat 0);
calculating the distance from each new energy source to the center of gravity according to the longitude and latitude coordinates, the center of gravity coordinates and the longitude and latitude coordinates of each load point of each new energy source after radian conversion;
Wherein d , represents the distance from the new energy source to the center of gravity; a , represents the difference between the center of gravity and the latitude of the new energy, namely a ,=rlat0-rlatm;b, represents the difference between the center of gravity and the longitude of the new energy, namely b , = rlng0-rlngm, r represents the radius of the earth, and r= 6371.137km;
Sequencing the distances from the new energy sources to the gravity centers according to the size, wherein the smaller the distance from the new energy sources to the gravity centers is, the higher the absorption priority is;
And a curve generation module: the method comprises the steps of carrying out normalization processing on new energy data and load point data to generate a new energy power characteristic curve and a load point power characteristic curve;
Specifically, the new energy power characteristic curve:
Fj=Pj/Sj；
Fi=Pi/Si；
Wherein F j is a new energy power characteristic curve, P j is 96-point power of the new energy, and S j is rated capacity of the new energy; f i is a load point power characteristic curve, P i is load point 96 point power, and S i is load point rated capacity;
And a correlation coefficient calculation module: the method comprises the steps of sequentially calculating correlation coefficients of each new energy and a load point power characteristic curve according to the new energy power characteristic curve and the load point power characteristic curve and the absorption priority of each new energy output;
Wherein r (F j,Fi) represents the correlation coefficient of the new energy power characteristic curve j and the load point power characteristic curve i; cov (F j,Fi) represents the covariance of the new energy power characteristic curve j and the load point power characteristic curve i, var|f i | represents the variance of the load point power characteristic curve i, and var|f j | represents the variance of the new energy power characteristic curve j;
Specifically, r (F j,Fi) epsilon [ -1,1], when r (F j,Fi) is close to 1 or-1, the correlation is stronger; the correlation is lower when r (F j,Fi) approaches 0;
Therefore, the intensity of the correlation can be judged by the absolute value of r (F j,Fi), and the larger the absolute value of the correlation coefficient is, the stronger the correlation is;
And an output module: the method is used for evaluating the new energy consumption according to the correlation coefficient of the output of each new energy and displaying the power consumption of the new energy.
Specifically, the method comprises the following steps:
Each load point sequentially dissipates new energy according to the sequence of the absolute value of the photographing relation number from high to low, and the power consumption of the new energy is equal to that of the load;
Wherein W j is new energy-dissipatable electric quantity (new energy generating quantity) when the new energy power to be consumed is greater than or equal to the load point power, W i is load point electric quantity, and P i is load point power at time t;
when the power of the new energy to be absorbed is smaller than the power of the load point;
Wherein W j , is the new energy generating capacity when the new energy power to be consumed is smaller than the load point power, P i-1 is the load point t-1 moment power, and P jt is the new energy t moment power generation power;
when the absolute value of the correlation coefficient is smaller than a preset value, acquiring the conventional power supply and the adjustable power of the outgoing section in a preset area, and calculating the new energy source power consumption according to the conventional power supply and the adjustable power of the outgoing section;
Wherein W j ,, is the new energy power generation amount when the absolute value of the correlation coefficient is smaller than a preset value, P j is the new energy output power at the time t-1, and P abj is the conventional power supply and the adjustable power of the outgoing section;
the new energy power generation amount is the sum of the new energy power generation amount when the absolute value of the new energy power consumption is smaller than a preset value and the new energy power to be consumed is smaller than the load point power;
specifically, the preset value is 0.5;
wherein W abs is new energy which can consume electric quantity.
Example 3
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing a new energy consumption evaluation method as described in embodiment 1 when executing the computer program.
Example 4
A computer-readable storage medium storing a computer program which, when executed by a processor, implements a new energy consumption evaluation method described in embodiment 1.
It will be appreciated by those skilled in the art that the present invention can be carried out in other embodiments without departing from the spirit or essential characteristics thereof. Accordingly, the above disclosed embodiments are illustrative in all respects, and not exclusive. All changes that come within the scope of the invention or equivalents thereto are intended to be embraced therein.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (7)
1. The new energy consumption evaluation method is characterized by comprising the following steps of:
acquiring new energy data and load point data in a preset area;
calculating the absorption priority of the output of each new energy according to the new energy data and the load point data;
carrying out normalization processing on the new energy data and the load point data to generate a new energy power characteristic curve and a load point power characteristic curve;
According to the new energy power characteristic curve and the load point power characteristic curve, calculating the correlation coefficient of each new energy and the load point power characteristic curve in sequence according to the absorption priority of each new energy output;
evaluating the new energy consumption according to the correlation coefficient of the output of each new energy, and displaying the power consumption of the new energy;
The step of calculating the absorption priority of the output of each new energy according to the new energy data and the load point data specifically comprises the following steps:
calculating a load point distribution weight coefficient in the space according to the load point data;
Calculating barycentric coordinates according to the load point data;
calculating the absorption priority of each new energy according to the load point data, the gravity center coordinates and the new energy data;
The step of calculating the barycentric coordinates according to the load point data specifically comprises the following steps:
obtaining longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates of each load point, and setting a gravity center v;
calculating the distance from each load point to the center of gravity by using haversine formula;
Correcting the distance from each load point to the center of gravity according to the load point distribution weight coefficient in the space to obtain a corrected distance;
obtaining a barycenter coordinate according to the corrected distance;
The step of calculating the absorption priority of each new energy according to the load point data, the barycentric coordinates and the new energy data specifically comprises the following steps:
acquiring longitude and latitude coordinates of each new energy according to the new energy data, and acquiring longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates, barycentric coordinates and longitude and latitude coordinates of each load point of each new energy source;
calculating the distance from each new energy source to the center of gravity according to the longitude and latitude coordinates, the center of gravity coordinates and the longitude and latitude coordinates of each load point of each new energy source after radian conversion;
and sorting the distances from the new energy sources to the gravity centers according to the sizes, wherein the smaller the distance from the new energy sources to the gravity centers is, the higher the absorption priority is.
2. The new energy consumption evaluation method according to claim 1, wherein the new energy data comprises: new energy output curve data, new energy position information and new energy rated capacity;
The load point data includes: load point power data, load point position information, and load point variable capacity.
3. The new energy consumption evaluation method according to claim 1, wherein the correlation coefficient is r (F j,Fi);
Wherein r (F j,Fi) represents the correlation coefficient of the new energy power characteristic curve j and the load point power characteristic curve i; cov (F j,Fi) represents the covariance of the new energy power characteristic curve j and the load point power characteristic curve i, var|f i | represents the variance of the load point power characteristic curve i, and var|f j | represents the variance of the new energy power characteristic curve j.
4. The method for evaluating new energy consumption according to claim 1, wherein the step of evaluating new energy consumption according to the correlation coefficient of each new energy output and displaying the power consumption of the new energy comprises the following steps:
Each load point sequentially dissipates new energy according to the sequence of the absolute value of the photographic relation number from high to low;
when the power of the new energy to be absorbed is larger than or equal to the power of the load point, the power of the new energy to be absorbed is equal to the power consumption of the load;
when the power of the new energy to be absorbed is smaller than the power of the load point;
Wherein W j , is the new energy generating capacity when the new energy power to be consumed is smaller than the load point power, P i-1 is the load point t-1 moment power, and P jt is the new energy t moment power generation power;
when the absolute value of the correlation coefficient is smaller than a preset value, acquiring the conventional power supply and the adjustable power of the outgoing section in a preset area;
Wherein W j ,, is the new energy power generation amount when the absolute value of the correlation coefficient is smaller than a preset value, P j is the new energy output power at the time t-1, and P abj is the conventional power supply and the adjustable power of the outgoing section;
New energy may consume electricity=w j ,+Wj ,,.
5. The new energy consumption evaluation device is characterized by comprising:
And a data acquisition module: the method comprises the steps of acquiring new energy data and load point data in a preset area;
priority calculation module: the method comprises the steps of calculating the absorption priority of the output of each new energy according to the new energy data and the load point data;
And a curve generation module: the method comprises the steps of carrying out normalization processing on new energy data and load point data to generate a new energy power characteristic curve and a load point power characteristic curve;
And a correlation coefficient calculation module: the method comprises the steps of sequentially calculating correlation coefficients of each new energy and a load point power characteristic curve according to the new energy power characteristic curve and the load point power characteristic curve and the absorption priority of each new energy output;
and an output module: the method is used for evaluating the new energy consumption according to the correlation coefficient of the output of each new energy and displaying the power consumption of the new energy;
The step of calculating the absorption priority of the output of each new energy according to the new energy data and the load point data specifically comprises the following steps:
calculating a load point distribution weight coefficient in the space according to the load point data;
Calculating barycentric coordinates according to the load point data;
calculating the absorption priority of each new energy according to the load point data, the gravity center coordinates and the new energy data;
The step of calculating the barycentric coordinates according to the load point data specifically comprises the following steps:
obtaining longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates of each load point, and setting a gravity center v;
calculating the distance from each load point to the center of gravity by using haversine formula;
Correcting the distance from each load point to the center of gravity according to the load point distribution weight coefficient in the space to obtain a corrected distance;
obtaining a barycenter coordinate according to the corrected distance;
The step of calculating the absorption priority of each new energy according to the load point data, the barycentric coordinates and the new energy data specifically comprises the following steps:
acquiring longitude and latitude coordinates of each new energy according to the new energy data, and acquiring longitude and latitude coordinates of each load point according to the load point data;
Performing radian conversion on longitude and latitude coordinates, barycentric coordinates and longitude and latitude coordinates of each load point of each new energy source;
calculating the distance from each new energy source to the center of gravity according to the longitude and latitude coordinates, the center of gravity coordinates and the longitude and latitude coordinates of each load point of each new energy source after radian conversion;
and sorting the distances from the new energy sources to the gravity centers according to the sizes, wherein the smaller the distance from the new energy sources to the gravity centers is, the higher the absorption priority is.
6. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements a new energy consumption evaluation method according to any one of claims 1-4 when executing the computer program.
7. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements a new energy consumption evaluation method according to any one of claims 1 to 4.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08111935A (en) * | 1994-10-11 | 1996-04-30 | Toshiba Corp | Regional load forecasting system in power system |
| WO2010082536A1 (en) * | 2009-01-13 | 2010-07-22 | 株式会社日立製作所 | Power demand-supply management server and power demand-supply management system |
| CN113315171A (en) * | 2021-05-18 | 2021-08-27 | 南方电网能源发展研究院有限责任公司 | New energy consumption capacity evaluation method and device, computer equipment and storage medium |
| CN114358485A (en) * | 2021-11-30 | 2022-04-15 | 国网山东省电力公司日照供电公司 | Source-load matching evaluation method, system, medium and electronic equipment |
| CN115081902A (en) * | 2022-06-30 | 2022-09-20 | 国网北京市电力公司 | Comprehensive planning method, device, equipment and medium based on source network load-storage cooperation |
| CN115564293A (en) * | 2022-10-27 | 2023-01-03 | 国网安徽省电力有限公司经济技术研究院 | Source-load collaborative optimization planning method, device and equipment based on absorption matching degree |
| CN115833261A (en) * | 2022-12-19 | 2023-03-21 | 国家电网有限公司 | Analysis method of new energy consumption space, related device and computer storage medium |
| CN115833144A (en) * | 2022-12-02 | 2023-03-21 | 国网辽宁省电力有限公司葫芦岛供电公司 | Multi-flexible resource aggregation matching method based on reduction of wind energy waste rate |
| CN116454967A (en) * | 2023-04-10 | 2023-07-18 | 国网冀北电力有限公司电力科学研究院 | New energy consumption capability assessment method and device for power grid |
| CN116632932A (en) * | 2023-03-08 | 2023-08-22 | 国网辽宁省电力有限公司电力科学研究院 | Regional power grid dispatching control strategy |
| CN117293906A (en) * | 2023-10-10 | 2023-12-26 | 国网浙江省电力有限公司宁波供电公司 | Distributed photovoltaic bearing capacity rapid evaluation method and system for power distribution network based on gravity center theory |
-
2024
- 2024-03-08 CN CN202410263358.7A patent/CN117852979B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08111935A (en) * | 1994-10-11 | 1996-04-30 | Toshiba Corp | Regional load forecasting system in power system |
| WO2010082536A1 (en) * | 2009-01-13 | 2010-07-22 | 株式会社日立製作所 | Power demand-supply management server and power demand-supply management system |
| CN113315171A (en) * | 2021-05-18 | 2021-08-27 | 南方电网能源发展研究院有限责任公司 | New energy consumption capacity evaluation method and device, computer equipment and storage medium |
| CN114358485A (en) * | 2021-11-30 | 2022-04-15 | 国网山东省电力公司日照供电公司 | Source-load matching evaluation method, system, medium and electronic equipment |
| CN115081902A (en) * | 2022-06-30 | 2022-09-20 | 国网北京市电力公司 | Comprehensive planning method, device, equipment and medium based on source network load-storage cooperation |
| CN115564293A (en) * | 2022-10-27 | 2023-01-03 | 国网安徽省电力有限公司经济技术研究院 | Source-load collaborative optimization planning method, device and equipment based on absorption matching degree |
| CN115833144A (en) * | 2022-12-02 | 2023-03-21 | 国网辽宁省电力有限公司葫芦岛供电公司 | Multi-flexible resource aggregation matching method based on reduction of wind energy waste rate |
| CN115833261A (en) * | 2022-12-19 | 2023-03-21 | 国家电网有限公司 | Analysis method of new energy consumption space, related device and computer storage medium |
| CN116632932A (en) * | 2023-03-08 | 2023-08-22 | 国网辽宁省电力有限公司电力科学研究院 | Regional power grid dispatching control strategy |
| CN116454967A (en) * | 2023-04-10 | 2023-07-18 | 国网冀北电力有限公司电力科学研究院 | New energy consumption capability assessment method and device for power grid |
| CN117293906A (en) * | 2023-10-10 | 2023-12-26 | 国网浙江省电力有限公司宁波供电公司 | Distributed photovoltaic bearing capacity rapid evaluation method and system for power distribution network based on gravity center theory |
Non-Patent Citations (1)
| Title |
|---|
| 谢呈阳等.《产业转移与区域创新发展》.南京：东南大学出版社,2020,第88-89页. * |
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