CN112686454A - Energy efficiency optimization system and method of client side energy utilization control system - Google Patents
Energy efficiency optimization system and method of client side energy utilization control system Download PDFInfo
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Abstract
The invention discloses an energy efficiency optimization system of a client side energy consumption control system, which comprises a data acquisition module, an operation process analysis module, an energy efficiency evaluation module and an optimization scheme arrangement module; the data acquisition module acquires data of the control system and provides data support for the operation process analysis module, the energy efficiency evaluation module and the optimization scheme arrangement module; the operation process analysis module obtains energy efficiency factors of the control system; the energy efficiency evaluation module obtains an energy efficiency optimization operation result of the control system according to the energy efficiency evaluation model; and the optimization scheme arranging module is used for obtaining the optimization scheme of the control system according to the energy efficiency optimization operation result of the control system. The invention also discloses an energy efficiency optimization method of the client side energy consumption control system. The invention obtains the overall energy consumption condition, the reflection efficiency conversion, the energy-saving potential, the saving environment protection and the reliability in the operation process of the client side energy consumption control system, and obtains the optimal control scheme according to the evaluation result to effectively reduce the energy consumption cost of the client.
Description
Technical Field
The present invention relates to an optimization system and method, and in particular, to an energy efficiency optimization system and method for a client-side energy consumption control system.
Background
Energy shortage has become a bottleneck problem of economic development of countries in the world in the 21 st century, and besides the rapid development of new energy, reduction of energy consumption and improvement of energy utilization efficiency are main approaches to solving energy problems. While the contradiction of energy constraint is obvious, the energy utilization efficiency of China is far from the advanced level of the world, and the traditional economic development growth mode of high investment, high consumption, high emission and low efficiency is reached to the end, so that the development of energy conservation and emission reduction work of China is imperative.
In order to promote green, low-carbon and sustainable development of energy, China actively promotes the energy consumption revolution, deeply develops comprehensive energy service, inhibits unreasonable energy consumption and improves the energy utilization efficiency. However, at present, the comprehensive energy efficiency level of the client side is low, the energy consumption cost is high, and the comprehensive energy service needs to be further developed and promoted urgently. In addition, the problems of insufficient energy utilization, high energy consumption and the like of the energy utilization control system at the client side are obvious, improvement is urgently needed, but the lack of an effective related factor system in the assessment process is one of the main problems faced by the work of the energy utilization control system at present. At present, research on many factors of the control system is limited to specific devices, processes or energy types, and a scientific, comprehensive and uniform factor system and an evaluation model are not formed. Thereby causing a problem of low energy efficiency of the energy consumption control system on the client side
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to solve the defects in the prior art, provides an energy efficiency optimization system of a client side energy consumption control system, and solves the problem of low energy efficiency of the client side energy consumption control system.
The technical scheme is as follows: the energy efficiency optimization system of the client side energy consumption control system comprises a data acquisition module, an operation process analysis module, an energy efficiency evaluation module and an optimization scheme arrangement module; the data acquisition module acquires data of the client-side energy utilization control system and provides data support for the operation process analysis module, the energy efficiency evaluation module and the optimization scheme arrangement module; the operation process analysis module obtains energy efficiency factors of the client side energy utilization control system; the energy efficiency evaluation module obtains an energy efficiency optimization operation result of the client side energy consumption control system according to the energy efficiency evaluation model; and the optimization scheme arranging module obtains the optimization scheme of the client side energy utilization control system according to the energy efficiency optimization operation result.
The operation process analysis module comprises an energy supply and utilization system conversion efficiency unit, an economy and finance unit, an economization and emission reduction unit and an energy supply reliability analysis unit; the energy supply and utilization system conversion efficiency unit obtains the energy supply and utilization system conversion efficiency, the energy supply and utilization conversion efficiency, the transmission efficiency and the energy utilization efficiency; the economic and financial unit obtains the purchasing energy cost of the control system to save expenditure, income, cost and potential value; the saving and emission reduction unit obtains unit building area pollutant emission reduction amount, per-capita pollutant emission reduction amount, unit output value pollutant emission reduction amount and standard coal saving amount; the energy supply reliability analysis unit obtains the importance of the equipment, the energy supply reliability of clean energy, the energy storage and supply reliability and the energy conversion reliability;
the operation process analysis module outputs a primary energy efficiency factor U and a secondary energy efficiency factor Ui, i is more than or equal to 1 and less than or equal to 4,
U＝{U1,U2,U3,U4the conversion efficiency of a power supply and energy utilization system, economy and finance, conservation and emission reduction and power supply reliability are reduced,
U1＝{u11,u12,u13,u14the conversion efficiency of an energy supply system, the conversion efficiency of energy supply, the transmission efficiency and the energy utilization efficiency are determined,
U2＝{u21,u22,u23,u24energy cost savings, revenue, cost, potential value },
U3＝{u31,u32,u33,u34the unit building area pollutant discharge reduction, per-capita pollutant discharge reduction, unit production value pollutant discharge reduction and standard coal saving quantity saving
U4＝{u41,u42,u43,u44And (4) the reliability of equipment importance, clean energy supply, energy storage and supply and energy conversion.
The energy supply conversion efficiency comprises a echelon utilization heat ratio, a echelon utilization cold ratio, a clean energy to total power consumption ratio, a high energy efficiency ratio equipment heat production ratio, a high energy efficiency ratio equipment cold production ratio, a heat production unit energy performance, a cold production unit energy performance, an energy storage and energy supply ratio, an electric heat complementation rate, a gas-electricity complementation rate, a gas-heat complementation rate and an electric complementation rate; the transmission efficiency comprises a comprehensive line loss rate and a comprehensive management loss rate; the energy utilization efficiency comprises an excessive heating rate and an excessive cooling rate;
the energy purchasing cost saving expenditure comprises energy saving cost, energy storage peak shifting valley filling cost and available waste heat/residual cold/residual pressure benefit; the income comprises demand response income, renewable energy income and energy outsourcing income; the cost comprises investment cost, operation and maintenance cost and energy outsourcing cost; the potential value comprises renewable energy waste value, residual gas excavation benefit, residual heat excavation benefit, residual cold excavation benefit and residual pressure excavation benefit.
The energy efficiency evaluation module comprises an energy efficiency evaluation model, wherein the energy efficiency evaluation model f is W multiplied by B multiplied by ST，
Wherein, S is an evaluation set score vector (90, 80,70,60, 50),
W＝[W1,W2,W3,W4]is a primary energy efficiency factor weight vector,
wherein, Bi＝wi·RiIs an ith primary energy efficiency factor evaluation model, i is more than or equal to 1 and less than or equal to 4,
wherein, wi＝[wi1,wi2,wi3,wi4]I is more than or equal to 1 and less than or equal to 4;
wherein, wijI is more than or equal to 1 and less than or equal to 4, and j is more than or equal to 1 and less than or equal to 4.
And the optimization scheme arranging module is used for obtaining an optimization strategy of a user with high energy consumption and low efficiency by using an energy efficiency measure library according to an energy efficiency optimization operation result output by the energy efficiency evaluation module, and controlling the operation of the client side energy utilization control system.
The energy efficiency optimization method of the client side energy consumption control system comprises the following steps:
(1) collecting data of an energy control system used by a client side;
(2) acquiring a primary energy efficiency factor and a secondary energy efficiency factor of a client side energy consumption control system in the operation process;
(3) obtaining an energy efficiency optimization operation result according to an energy efficiency evaluation model of the client side energy utilization control system;
(4) and controlling the operation of the client side energy utilization control system according to the energy efficiency optimization operation result.
The primary energy efficiency factor in the step (2)
U＝{U1,U2,U3,U4The energy supply system has the advantages of conversion efficiency, economy, finance, saving, emission reduction and energy supply reliability
The secondary energy efficiency factor Ui, i is more than or equal to 1 and less than or equal to 4, wherein,
U1＝{u11,u12,u13,u14the energy supply system conversion efficiency, the energy supply conversion efficiency, the transmission efficiency and the energy utilization efficiency are determined
U2＝{u21,u22,u23,u24Energy cost savings, revenue, cost, potential value }
U3＝{u31,u32,u33,u34The unit building area pollutant discharge reduction rate, per-capita pollutant discharge reduction rate, unit production value pollutant discharge reduction rate and standard coal saving rate are obtained
U4＝{u41,u42,u43,u44And (4) the reliability of equipment importance, clean energy supply, energy storage and supply and energy conversion.
The step (3) comprises the following steps:
(31) obtaining the energy efficiency factor according to a first-level energy efficiency factor U and a second-level energy efficiency factor Ui by adopting an analytic hierarchy process
First-order energy efficiency factor weight vector W ═ W1,W2,W3,W4]，
Two-level energy efficiency factor weight matrix
Wherein, wi＝[wi1,wi2,wi3,wi4]Is the ith secondary energy efficiency factor weight vector, wijI is more than or equal to 1 and less than or equal to 4, and j is more than or equal to 1 and less than or equal to 4.
(32) A comprehensive target evaluation decision matrix B is obtained,
wherein, Bi＝wi·Ri，
A secondary energy efficiency factor evaluation matrix;
(33) the energy efficiency optimization operation result of the energy consumption control system at the client side is obtained,
f＝W×B×ST
where, S ═ 90,80,70,60,50], is an evaluation set score vector.
And (4) when the energy efficiency optimization operation result of the energy consumption control system at the client side is lower than a threshold value, obtaining an optimization strategy of a user with high energy consumption and low efficiency by using an energy efficiency measure library, and controlling the energy consumption control system at the client side to operate.
Has the advantages that: compared with the prior art, the method has the obvious advantages that the overall energy consumption condition in the operation process of the client side energy consumption control system is comprehensively obtained, and the problems of efficiency conversion, energy-saving potential, environmental protection and reliability are reflected; and according to the evaluation result, an optimal control scheme is made in a targeted manner, so that the energy cost of the client is effectively reduced.
Drawings
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a block diagram of an energy efficiency factor system for an energy management system according to the present invention;
FIG. 3 is a flow chart of the optimization method of the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in fig. 1, the system of the invention includes a data acquisition module, an operation process analysis module, an energy efficiency evaluation module and an optimization scheme arrangement module; the data acquisition module acquires data of the client-side energy utilization control system and provides data support for the operation process analysis module, the energy efficiency evaluation module and the optimization scheme arrangement module; the operation process analysis module obtains energy efficiency factors of the client side energy utilization control system; the energy efficiency evaluation module obtains an energy efficiency optimization operation result of the client side energy consumption control system according to the energy efficiency evaluation model; and the optimization scheme arranging module obtains the optimization scheme of the client side energy utilization control system according to the energy efficiency optimization operation result.
As can be seen from fig. 2, the energy efficiency factors analyzed in the operation process of the client-side energy consumption control system include 4 primary energy efficiency factors of energy supply system conversion efficiency, cost, conservation, emission reduction, and energy supply reliability. Wherein, energy supply and use energy system conversion efficiency factor includes energy supply system conversion efficiency, energy supply conversion efficiency, transmission efficiency, with 4 second grade efficiency factors of energy efficiency, economy and financial factor are including purchasing the energy cost and saving expenditure, the income, the cost, 4 second grade efficiency factors of latent value, it includes that unit building area pollutant reduces the discharge capacity to practice thrift and reduce discharging the factor, per capita value pollutant reduces the discharge capacity, practice thrift four second grade efficiency factors of standard coal volume, energy supply reliability factor includes the equipment importance degree, clean energy supply reliability, energy storage energy supply reliability, 4 second grade efficiency factors of energy conversion reliability.
Each secondary energy efficiency factor is obtained by the following formula according to the collected data:
(1) energy supply and utilization system conversion efficiency factor
a. The conversion efficiency of the energy supply system is obtained according to the formula (1):
in the formula: eta is the conversion efficiency (%) of the energy supply system; qe,loadOutputting the electric quantity (kW.h) for the distribution line in the statistical period; qh,outOutputting heat (MJ) for a system heat transfer station in a statistical period; qc,outOutputting cold quantity (MJ) for a system cold sending station in a statistical period; beta is a heat (cold) energy conversion coefficient (constant: 0.2778 kW. h/MJ); qe,gridThe electric quantity (kW.h) is transmitted for the inside and the outside of the statistical period; qh,gridHeat (MJ) is delivered for the inside and outside of the statistical period; beta is acoalFor burning coalBit heating value (MJ/kg); b iscoalSupplying total coal consumption (kg) for the inside of the system in a statistical period; beta is agasIs the low heating value (MJ/m) of natural gas3)；BgasSupplying total natural gas quantity (m) for the system in the statistical period3)。
b. The energy supply conversion efficiency considers the echelon utilization heat ratio, the echelon utilization cold ratio, the proportion of clean energy to total power consumption, the high energy efficiency ratio equipment heat production ratio, the high energy efficiency ratio equipment cold production ratio, the heat production unit energy performance, the cold production unit energy performance, the energy storage energy supply ratio, the electric heat complementary rate, the gas-electricity complementary rate, the gas-heat complementary rate and the electric complementary rate, and is obtained according to the formula (2):
in the formula: p is a radical ofhtGradient utilization rate (%) of heat energy, QhtHeat (MJ), Q) for direct echelon utilizationhrWaste heat (MJ), Q, to be recycledh,outTotal output heat (MJ); p is a radical ofctFraction (%) of cold used in echelon, QctCold (MJ), Q) directly used in echeloncrWaste cold (MJ), Q, being recycledc,outTotal output heat (MJ); p is a radical ofrThe proportion (%) of the clean energy to the total power consumption, and QereClean energy generated (kW.h) including photovoltaic, wind power generation, etc., Qe,gridThe power generation capacity (kW.h) of the traditional energy source; p is a radical ofhhHigh energy efficiency ratio equipment heat production ratio (%), Qe,h,inHigh energy efficiency ratio device produced heat (MJ), ηh,COPEnergy efficiency ratio, Q, of heat-producing equipmenth,outAll equipment produced heat (MJ); p is a radical ofchHigh energy efficiency ratio equipment cold production ratio (%), Qe,c,inThe equipment with high energy efficiency ratio produces cold (MJ), etac,COPEnergy efficiency ratio, Q, of cold producing equipmenth,outAll equipment produces cold (MJ); etahPerformance (%) of heat-generating unit, ηh,COPEnergy efficiency ratio, η, of heat-producing equipmenth,SCOPThe rated working condition energy efficiency ratio of the heat production equipment; etacRefrigerating unit performance (%), etac,COPEnergy efficiency ratio, η, of cold producing equipmentc,SCOPThe rated working condition energy efficiency ratio of the refrigeration equipment;psenergy storage and supply ratio, Qe,dischaEnergy storage capacity (kW. h), Q of energy storage systemh,dischaStored heat (MJ), Q of energy storage systemsc,dischaCold accumulation (MJ), Q of energy storage systeme,loadPower consumption, Q, of the energy storage systemh,inHeat input into the system heat transfer station (MJ), Qc,inInputting the cold quantity (MJ) of the system cold-conveying station; etaphElectric heat complementation rate (%), Qp2hHeating value by electricity (MJ), QthTotal heat demand (MJ); etagePneumatic-electric complementation rate (%), Qg2pGas power generation (kW. h), QtpTotal electricity demand (kW · h); etaghGas-heat complementation rate (%), Qg2hUsing gas calorific value (MJ), QthTotal heat demand (MJ); etapgElectrical complementation rate (%), Bp2gProduction of gas by electricity (m3), Bt,gasTotal gas demand (m 3).
c. The transmission efficiency is obtained according to the formula (3) in consideration of the comprehensive line loss rate and the comprehensive pipe loss rate:
in the formula: etaLLComprehensive line loss rate (%), Qe,sulpPower supply (kW. h), Qe,useUser power usage (kW · h); etaPLComprehensive pipe loss rate (%), Qh,suplHeating (cooling) quantity (MJ), Qh,useHeat (cold) load (MJ) for the user.
d. The energy use efficiency includes an excess heating (cooling) rate, obtained according to equation (4):
in the formula: alpha is alphaexExcess heat (cold) rate factor; qbExcess heating (cold) factor (MJ); qrTheoretical heat (cold) consumption factor (MJ).
(2) Cost situation factor
a. Energy purchasing cost saving and expenditure considering energy saving cost, energy storage peak shifting and valley filling cost and available waste heat/residual cold/residual pressure benefits are obtained according to the formula (5):
in the formula: fECEnergy saving benefit (Yuan), CEC,befEnergy cost before optimization, CEC,aftOptimized energy consumption cost (Yuan); fESS,shfEnergy storage peak shift valley fill gain (Yuan), QePeak shifting valley filling total electric quantity (kW. h), Δ cpvPeak to valley valence difference (yuan);
the benefit of the surplus energy i can be exploited,
the amount of available residual energy i, ciThe price of the remaining energy i can be utilized.
b. And the income is obtained according to the formula (6) by considering participation demand response income, renewable energy income and energy outsourcing income:
in the formula: fDRThe demand response revenue (dollar),
counting the total amount of the load i participating in the response (kW.h) in the period,
unit price (yuan/kW.h), n of load i participating in demand responseDRCounting the number (number) of loads participating in demand response in a system in a period; fRERenewable energy yield (Yuan), QREEnergy generated by renewable energy plants (kW · h),
price per unit energy (yuan/kW · h); fE,offEnergy sales yield (Yuan), IE,offIncome from energy sales, CE,offCost of energy sold (Yuan), M tax and additional (Yuan).
c. The cost is obtained according to the formula (7) by considering investment cost, operation and maintenance cost and energy outsourcing cost:
in the formula: cinvThe investment acquisition cost (Yuan),
the energy cost (dollar) of the conventional device i,
installation acquisition cost (dollar) of the conventional device i,
installation acquisition cost (yuan) of renewable energy device j,
the installation acquisition cost (dollar) of the energy storage device k,
installation acquisition cost (N) of other devices lnorNumber of conventional devices in the system, nRENumber (n) of renewable energy devices in the systemESSNumber (n) of energy storage devices in the systemotrNumber(s) of other devices in the system; coprSystem operation and maintenance cost (Yuan), PiThe capacity of the plant i (kW · h),
the unit capacity of the device i fixes the cost (dollar),
the average run time (hours) of the device i,
variable cost per unit capacity (n) for device ioprThe number of devices (in) that need to be maintained in the system; cE,buyCost of energy outsourcing (Yuan), Ce,buyCost of electricity purchase outside system, Cf,buyThe system conventionally supplies the equipment consuming fuel costs (dollars).
d. The potential value considers the renewable energy abandoned energy value, the residual gas excavation benefit, the residual heat excavation benefit, the residual cold excavation benefit and the residual pressure excavation benefit, and is obtained according to the formula (8):
in the formula: cQ.RGThe energy-saving value of the renewable energy source,
user's electricity price (yuan/kW.h), VQ,RGThe total power (kW.h) of wind and light abandoning of a user; cQ.gCan excavate residual gas benefit, betag2pConversion coefficient of gas-electric energy (kW.h/kg or kW.h/m)3) (if the residual gas is liquid hydrogen, then betag2p39.52(kW · h/kg), and β if the residual gas is hydrogen gasg2p＝3.5533(kW·h/m3) (ii) a If the residual gas is natural gas, then betag2p＝8.95～10.82(kW·h/kg))，VQ,gThe user can excavate the total amount of residual gas (kg or m)3)；CQ.hCan exploit the waste heat efficiency, betah2pHeat-electric energy conversion coefficient (kW. h/MJ), betah2p＝0.28(kW·h/MJ)，VQ,hThe total amount of waste heat (MJ) can be mined by the user; cQ.cCan excavate waste heat benefit, VQ,cThe user can mine the total amount of remaining cold energy (MJ); cQ.paCan excavate the residual pressure benefit, VQ,pa2pDifferential pressure power generation (kW. h).
(3) Saving and emission reduction factor
a. The unit building area pollutant reduction amount is obtained according to the formula (9):
in the formula: i is a pollutant type, mainly sulfur dioxide, nitrogen oxide, smoke dust and carbon dioxide;
the unit building area of the ith pollutant is reduced by the discharge capacity (kg/m)2)；ViReducing the discharge (kg) of the i pollutant; sBIs the area of a building (m)2)。
b. Per capita pollutant emission reduction
The per-person pollutant reduction amount is obtained according to the formula (10):
in the formula:
per-capita emission reduction of the ith pollutant; n is the number of people (human).
c. Unit output value pollutant discharge reducing amount
The unit output pollutant reduction amount is calculated according to the formula (11):
in the formula:
reduced displacement per unit yield (kg/ten thousand GDP) for the i-th pollutant; g is the pollutant discharge amount.
d. Saving standard coal quantity
The standard coal amount corresponding to the saved electric quantity in the system is obtained according to the formula (12):
in the formula: b issaveStandard coal quantity (ton) for saving; beta is acoalThe equivalent electrical method conversion coefficient of the coal (309 g/kWh); qsave jSaving a power component (kWh) for the user.
(4) Reliability factor of energy supply
a. The equipment importance is calculated according to equation (13):
in the formula: i isiThe importance of the equipment; e.g. of the typeiThe self-steady-state effectiveness of the device i; viThe degree of influence of failure of the device i.
b. The reliability of the clean energy supply is calculated according to the formula (14):
in the formula: rCEThe system clean energy supply reliability (%); n isCEThe number of clean energy devices in the system (stations);
capacity of clean energy facility i (kW · h);
failure rate (%) of the clean energy apparatus i;
the maintenance probability of the clean energy device i.
c. The energy storage and supply reliability is divided into energy charging reliability and energy discharging reliability, and is obtained according to the formula (15):
in the formula: rESS,chaThe system energy storage and charging reliability (%);RESS,disthe reliability (%) of energy storage and release of the system; n isESSThe number of energy storage devices in the system (stations);
counting the chargeable capacity (kW.h) of the energy storage device i at the beginning of the period;
counting the dischargeable capacity (kW & h) of the energy storage device i at the beginning of the period;
failure rate (%) of the energy storage device i;
the maintenance probability (%) of the energy storage device i.
d. Within the statistical period, the energy conversion reliability is obtained as in equation (16):
in the formula: rTSystem energy conversion reliability (%); n isTThe number of energy conversion devices in the system (stations);
rated output energy (kW · h) of the energy conversion device i;
failure rate (%) of the energy conversion device i;
and (4) the maintenance probability of the energy conversion equipment i.
The operation process analysis module outputs a primary energy efficiency factor U and a secondary energy efficiency factor Ui, wherein i is more than or equal to 1 and less than or equal to 4:
(17)
U＝{U1,U2,U3,U4the energy supply and utilization system has conversion efficiency, cost, saving and emission reduction indexes and energy supply reliability
U1＝{u11,u12,u13,u14(18) energy conversion efficiency, transmission efficiency, energy consumption efficiency } of the energy supply system
U2＝{u21,u22,u23,u24(19) cost savings in energy purchase, revenue, cost, potential value }
U3＝{u31,u32,u33,u34(1) } { (pollutant reduction capacity per unit building area, pollutant reduction capacity per capita, (20) pollutant reduction capacity per unit production value, and standard coal saving }
U4＝{u41,u42,u43,u44The reliability of energy storage and energy supply (21), and the reliability of energy conversion (c) }
And the energy efficiency evaluation module obtains an energy efficiency optimization operation result of the control system according to the energy efficiency evaluation model.
And determining the weight of each energy efficiency factor by adopting an analytic hierarchy process.
First-order energy efficiency factor weight vector W ═ W1,W2,W3,W4] (22)
Two-level energy efficiency factor weight matrix
Wherein, wi＝[wi1,wi2,wi3,wi4]A second-level energy efficiency factor weight vector is obtained; w is aijAnd the corresponding weight of the jth secondary energy efficiency factor of the ith primary energy efficiency factor of the system is given.
Obtaining a secondary energy efficiency factor evaluation matrix R by using an expert scoring methodiAnd establishing a comprehensive target evaluation decision matrix B. Aiming at the energy efficiency optimization operation condition of the energy consumption control system at the client side, one secondary energy efficiency factor corresponds to each secondary energy efficiency factor and is calculated by an expertAnd (3) obtaining evaluation grades by a division method, namely: v ═ V1,v2,v3,v4,v5}，v1Is excellent, v2Is good, v3Is general, v4Is poor, v5Is very poor. The evaluation grades of 4 secondary energy efficiency factors corresponding to each primary energy efficiency factor are combined to form a secondary energy efficiency factor evaluation matrix Ri，1≤i≤4。
BiI is more than or equal to 1 and less than or equal to 4 of the ith primary energy efficiency factor evaluation model
Bi＝wi·Ri (25)
Comprehensive target evaluation decision matrix
The evaluation result of the energy efficiency optimization operation of the energy consumption control system on the client side can be obtained by the formula (24) to the formula (26).
f＝W×R×ST (27)
Where, S ═ 90,80,70,60,50], is an evaluation set score vector.
And the optimization scheme arranging module is used for obtaining an optimization strategy of a user with high energy consumption and low efficiency by using the energy efficiency measure library according to the energy efficiency optimization operation result output by the energy efficiency evaluation module, and controlling the operation of the client side energy utilization control system.
As can be seen from fig. 3, the energy efficiency optimization method for the client-side energy consumption control system according to the present invention includes the following steps:
(1) collecting data of an energy control system used by a client side;
(2) acquiring a primary energy efficiency factor and a secondary energy efficiency factor of a client side energy consumption control system in the operation process;
(3) obtaining an energy efficiency optimization operation result according to an energy efficiency evaluation model of the client side energy utilization control system;
(4) and controlling the operation of the client side energy utilization control system according to the energy efficiency optimization operation result.
And (3) obtaining 4 primary energy efficiency factors and 16 secondary energy efficiency factors of the energy supply and utilization system, such as conversion efficiency, economy and finance, conservation and emission reduction, and energy supply reliability.
For the conversion efficiency of the energy supply and utilization system, the utilization efficiency of the energy utilization system to energy is reflected, and the improvement of the energy conversion efficiency is an important target of the energy utilization control system. The energy supply system conversion efficiency, the energy supply conversion efficiency, the transmission efficiency and the energy utilization efficiency are four secondary energy efficiency factors under the energy supply and utilization factor, and the secondary energy efficiency factors can accurately reflect the conversion efficiency of the energy supply and utilization system. Economy and finance are necessary conditions for ensuring long-term stable operation of the energy-consumption control system, and reflect the level and degree of cost saving in resource investment and use processes and the reasonability of resource use. The economic and financial secondary energy efficiency factors are cost, benefit, cost and potential value savings. These factors can fully reflect the economic benefits of the energy control system. Energy conservation and emission reduction, namely energy conservation, energy consumption reduction and pollutant emission reduction, are important means for solving the problem of environment, and the energy conservation and emission reduction of the energy consumption control system at the client side can effectively reduce the pollution to the environment. The secondary energy efficiency factors are unit building area pollutant emission reduction, per-capita pollutant emission reduction, unit output value pollutant emission reduction and standard coal saving amount, and the energy saving characteristic of the energy consumption control system is comprehensively reflected. And finally, considering the energy supply reliability controlled by the energy consumption, which is a necessary condition for ensuring the safe and stable operation of the energy consumption control system, wherein the lower secondary energy efficiency factors are equipment importance, clean energy supply reliability, energy storage and supply reliability and energy conversion reliability. These factors reflect the reliability of the overall energy supply of the energy control system.
And (3) quantizing the 16 secondary energy efficiency factors according to the formulas (1) to (16), and then obtaining an expert scoring table according to a quantization result.
In the step (3), the method comprises the following steps:
(31) and determining the weight of each energy efficiency factor by adopting an analytic hierarchy process, and establishing a weight coefficient matrix.
First-order energy efficiency factor weight vector W ═ W1,W2,W3,W4]， (22)
Two-level energy efficiency factor weight matrix
Wherein, wi＝[wi1,wi2,wi3,wi4]A second-level energy efficiency factor weight vector is obtained; w is aijAnd weighting the jth secondary energy efficiency factor of the ith primary energy efficiency factor of the system.
(32) Obtaining a comprehensive target evaluation decision matrix B according to the weight vector of each secondary energy efficiency factor,
wherein, Bi＝wi·Ri (24)
(33) obtaining the energy efficiency optimization operation evaluation result of the energy consumption control system at the client side,
f＝W×B×ST (26)
wherein: and S is a score vector corresponding to the evaluation set [90,80,70,60,50 ].
In the step (4), the method comprises the following steps:
(41) setting a score threshold value for starting an optimization program, obtaining the reasons of high energy consumption and low efficiency of an access user when an evaluation result is lower than the threshold value, and obtaining an optimization energy utilization strategy according to an energy efficiency evaluation model and an energy efficiency measure library;
(42) and the energy efficiency optimization system issues an optimization energy utilization strategy to control the operation of the client side energy utilization control system.
In this embodiment, an expert experience scoring table of each energy efficiency factor is obtained according to the quantization result, as shown in table 1.
TABLE 1 grading table for each energy efficiency factor expert
And (3) according to the evaluation scores of the factors in the expert scoring table in the table 1, obtaining a weight matrix of the energy efficiency factors, as shown in the table 2.
TABLE 2 expert rating table
The comprehensive objective evaluation decision matrix is obtained from Table 2 and equations (23) to (25)
The comprehensive evaluation results were obtained from Table 2 and equation (26),
f＝W×R×S＝[0.331，0.195，0.273，0.130，0.071]×S＝75.85
finally, inquiring the capability rating table 3 to obtain a general energy efficiency optimization evaluation result.
TABLE 3 capability scoring sheet
And if the evaluation result is not satisfactory, giving an optimization strategy by the energy efficiency optimization system layer according to the highest optimization target energy efficiency, the lowest cost, the lowest pollutant discharge amount and the high energy supply reliability, and issuing a regulation and control instruction to the control system terminal layer for response.
And the terminal layer receives a scheduling instruction of the energy utilization control system and autonomously performs coordinated operation control according to the real-time operation information and state of the bottom layer equipment. The multi-terminal combined action is realized by setting the temperature strategy of the air conditioner at each time interval, and when the power utilization peak period or the environmental temperature meets a preset value, some terminal equipment is automatically closed, so that the requirement of terminal energy conservation is met. The system energy supply reliability is improved through multi-energy flow regulation and control means such as regional flexible load, combined cooling heating and power, electricity energy storage and the like.
Claims (9)
1. An energy efficiency optimization system of a client-side energy consumption control system, characterized in that: the system comprises a data acquisition module, an operation process analysis module, an energy efficiency evaluation module and an optimization scheme arrangement module; the data acquisition module acquires data of the client-side energy utilization control system and provides data support for the operation process analysis module, the energy efficiency evaluation module and the optimization scheme arrangement module; the operation process analysis module obtains energy efficiency factors of the client side energy utilization control system; the energy efficiency evaluation module obtains an energy efficiency optimization operation result of the client side energy consumption control system according to the energy efficiency evaluation model; and the optimization scheme arranging module obtains the optimization scheme of the client side energy utilization control system according to the energy efficiency optimization operation result.
2. The energy efficiency optimization system of the client-side energy consumption control system according to claim 1, characterized in that: the operation process analysis module comprises an energy supply and utilization system conversion efficiency unit, an economy and finance unit, an economization and emission reduction unit and an energy supply reliability analysis unit; the energy supply and utilization system conversion efficiency unit obtains the energy supply and utilization system conversion efficiency, the energy supply and utilization conversion efficiency, the transmission efficiency and the energy utilization efficiency; the economic and financial unit obtains the purchasing energy cost of the control system to save expenditure, income, cost and potential value; the saving and emission reduction unit obtains unit building area pollutant emission reduction amount, per-capita pollutant emission reduction amount, unit output value pollutant emission reduction amount and standard coal saving amount; the energy supply reliability analysis unit obtains the importance of the equipment, the energy supply reliability of clean energy, the energy storage and supply reliability and the energy conversion reliability;
the operation process analysis module outputs a primary energy efficiency factor U and a secondary energy efficiency factor Ui, i is more than or equal to 1 and less than or equal to 4,
U＝{U1,U2,U3,U4the conversion efficiency of a power supply and energy utilization system, economy and finance, conservation and emission reduction and power supply reliability are reduced,
U1＝{u11,u12,u13,u14the conversion efficiency of an energy supply system, the conversion efficiency of energy supply, the transmission efficiency and the energy utilization efficiency are determined,
U2＝{u21,u22,u23,u24energy cost savings, revenue, cost, potential value },
3. the energy efficiency optimization system of the client-side energy consumption control system according to claim 2, characterized in that: the energy supply conversion efficiency comprises a echelon utilization heat ratio, a echelon utilization cold ratio, a clean energy to total power consumption ratio, a high energy efficiency ratio equipment heat production ratio, a high energy efficiency ratio equipment cold production ratio, a heat production unit energy performance, a cold production unit energy performance, an energy storage and energy supply ratio, an electric heat complementation rate, a gas-electricity complementation rate, a gas-heat complementation rate and an electric complementation rate; the transmission efficiency comprises a comprehensive line loss rate and a comprehensive management loss rate; the energy utilization efficiency comprises an excessive heating rate and an excessive cooling rate;
the energy purchasing cost saving expenditure comprises energy saving cost, energy storage peak shifting valley filling cost and available waste heat/residual cold/residual pressure benefit; the income comprises demand response income, renewable energy income and energy outsourcing income; the cost comprises investment cost, operation and maintenance cost and energy outsourcing cost; the potential value comprises renewable energy waste value, residual gas excavation benefit, residual heat excavation benefit, residual cold excavation benefit and residual pressure excavation benefit.
4. The energy efficiency optimization system of the client-side energy consumption control system according to claim 1, characterized in that: the energy efficiency evaluation module comprises an energy efficiency evaluation model, wherein the energy efficiency evaluation model f is W multiplied by B multiplied by ST，
Wherein, S is an evaluation set score vector (90, 80,70,60, 50),
W＝[W1,W2,W3,W4]is a primary energy efficiency factor weight vector,
wherein, Bi＝wi·RiIs an ith primary energy efficiency factor evaluation model, i is more than or equal to 1 and less than or equal to 4,
wherein, wi＝[wi1,wi2,wi3,wi4]I is more than or equal to 1 and less than or equal to 4;
wherein, wijI is more than or equal to 1 and less than or equal to 4, and j is more than or equal to 1 and less than or equal to 4.
5. The energy efficiency optimization system of the client-side energy consumption control system according to claim 1, characterized in that: and the optimization scheme arranging module is used for obtaining an optimization strategy of a user with high energy consumption and low efficiency by using an energy efficiency measure library according to an energy efficiency optimization operation result output by the energy efficiency evaluation module, and controlling the operation of the client side energy utilization control system.
6. A method for optimizing energy efficiency of a client side energy consumption control system is characterized by comprising the following steps: the method comprises the following steps:
(1) collecting data of an energy control system used by a client side;
(2) acquiring a primary energy efficiency factor and a secondary energy efficiency factor of a client side energy consumption control system in the operation process;
(3) obtaining an energy efficiency optimization operation result according to an energy efficiency evaluation model of the client side energy utilization control system;
(4) and controlling the operation of the client side energy utilization control system according to the energy efficiency optimization operation result.
7. The energy efficiency optimization method of the client-side energy consumption control system according to claim 6, characterized in that: the primary energy efficiency factor in the step (2)
U＝{U1,U2,U3,U4The energy supply system has the advantages of conversion efficiency, economy, finance, saving, emission reduction and energy supply reliability
The secondary energy efficiency factor Ui, i is more than or equal to 1 and less than or equal to 4, wherein,
U1＝{u11,u12,u13,u14the energy supply system conversion efficiency, the energy supply conversion efficiency, the transmission efficiency and the energy utilization efficiency are determined
U2＝{u21,u22,u23,u24Energy cost savings, revenue, cost, potential value }
U3＝{u31,u32,u33,u34The unit building area pollutant discharge reduction rate, per-capita pollutant discharge reduction rate, unit production value pollutant discharge reduction rate and standard coal saving rate are obtained
8. The energy efficiency optimization method of the client-side energy consumption control system according to claim 6, characterized in that: the step (3) comprises the following steps:
(31) obtaining the energy efficiency factor according to a first-level energy efficiency factor U and a second-level energy efficiency factor Ui by adopting an analytic hierarchy process
First-order energy efficiency factor weight vector W ═ W1,W2,W3,W4]，
Two-level energy efficiency factor weight matrix
Wherein, wi＝[wi1,wi2,wi3,wi4]Is the ith secondary energy efficiency factor weight vector, wijI is more than or equal to 1 and less than or equal to 4, and j is more than or equal to 1 and less than or equal to 4.
(32) A comprehensive target evaluation decision matrix B is obtained,
wherein, Bi＝wi·Ri，
A secondary energy efficiency factor evaluation matrix;
(33) the energy efficiency optimization operation result of the energy consumption control system at the client side is obtained,
f＝W×B×ST
where, S ═ 90,80,70,60,50], is an evaluation set score vector.
9. The energy efficiency optimization method of the client-side energy consumption control system according to claim 6, characterized in that: and (4) when the energy efficiency optimization operation result of the energy consumption control system at the client side is lower than a threshold value, obtaining an optimization strategy of a user with high energy consumption and low efficiency by using an energy efficiency measure library, and controlling the energy consumption control system at the client side to operate.
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