CN113240330A - Multi-dimensional value evaluation method and scheduling strategy for demand side virtual power plant - Google Patents
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Abstract
The invention discloses a multidimensional value evaluation method and a scheduling strategy for a demand side virtual power plant, belongs to the technical field of electric power, and provides a value evaluation system for comprehensive benefit evaluation of virtual power plant projects from 4 dimensions such as power saving benefit, investment benefit, economic benefit, environmental benefit and the like by analyzing the construction and operation cost and benefit source of the virtual power plant, points out the meanings and calculation methods of corresponding indexes, and simultaneously, establishes an entropy method-fuzzy comprehensive evaluation model to compare and analyze the good and bad degrees of the indexes, thereby providing technical support for the design of a virtual power plant market mechanism and a business model. And a demand side virtual power plant scheduling strategy is designed based on the constructed multidimensional value evaluation system, so that the virtual power plant participates in demand response in the whole operation control period to obtain the maximum comprehensive benefit.
Description
Technical Field
The invention discloses a multidimensional value evaluation method and a scheduling strategy for a demand side virtual power plant, and belongs to the technical field of power.
Background
In recent years, social power load increases rapidly, peak-to-valley difference continues to increase, and in addition, a large amount of new energy power generation is accessed, and the proportion of external power is increased continuously, so that the power load characteristic is deteriorated, and the contradiction that the peak regulation of a system is difficult is highlighted. And because the user side has demand response resources such as a distributed power supply, energy storage and air conditioning load, the situations of insufficient system reserve capacity, difficult peak regulation and the like can be relieved by participating in demand response or auxiliary service and the like when the system reserve capacity is insufficient, and the problem of social power shortage is solved. The development of virtual power plants as an effective means for exploring demand resources is a concrete implementation of national policies. In the research projects and achievements of the existing virtual power plants, the current operation income of the virtual power plants is found to come from subsidies of governments and power companies, a proper market mechanism is lacked, a reasonable and mature business model is not formed, and the user enthusiasm cannot be effectively mobilized.
Therefore, cost and overall income of each part in construction and operation of the virtual power plant under a certain scale need to be researched, a virtual power plant multidimensional value evaluation system is constructed, and benefit evaluation of virtual power plant projects can be scientifically and reasonably carried out, so that a multidimensional value evaluation method and a scheduling strategy of a demand side virtual power plant are provided.
Disclosure of Invention
The invention aims to provide a virtual power plant multidimensional value evaluation method aiming at the defects of the background technology, the proposed method analyzes the cost and benefit sources of the construction and operation of the virtual power plant, provides a value evaluation system for comprehensive benefit evaluation of virtual power plant projects from 4 dimensions such as power saving benefit, investment benefit, economic benefit, environmental benefit and the like, points out the meanings and calculation methods of corresponding indexes, and simultaneously, establishes an entropy method-fuzzy comprehensive evaluation model to compare and analyze the good and bad degrees of the indexes, thereby providing technical support for the design of virtual power plant market mechanisms and business models. And designing a demand side virtual power plant scheduling strategy based on the constructed multi-dimensional value evaluation system.
The purpose of the invention can be realized by the following technical scheme: a multidimensional value assessment method and a scheduling strategy for a demand side virtual power plant comprise the following steps:
1) constructing a multi-dimensional value evaluation index system of the virtual power plant;
2) constructing a virtual power plant entropy method-fuzzy comprehensive evaluation model, and comprehensively evaluating the advantages and disadvantages of the indexes in the step 1);
3) based on the scheduling strategy of the multidimensional value evaluation method in the steps 1) and 2).
As a further scheme of the invention, the multidimensional value evaluation indexes of the virtual power plant in the step 1) comprise power saving benefits, investment benefits, economic benefits and environmental benefits;
(1) the electricity-saving benefit is as follows: calculating the comprehensive electricity-saving quantity of all the demand side resources according to an electricity consumption quota comparison method;
(2) investment benefits are as follows: the direct expression of the development benefit of the energy efficiency power plant project is realized, the indexes are benefit indexes, namely, the higher the index value is, the better the investment benefit is;
the investment benefit is evaluated through two parameters of an investment benefit coefficient and a project increment rate, and the investment benefit coefficient represents the ratio of the annual profit sum to the project investment sum; the project increment rate is used for measuring the continuous profitability of the project and reflects the residual value of the investment cost subtracted from the investment income brought by the virtual power plant project on the development demand side;
(3) the economic benefit is evaluated through the profit-cost ratio, namely the ratio of the current value of the energy-saving net cash flow obtained in the economic operation period to the operation cost in the process of developing the virtual power plant project on the demand side;
(4) the environmental benefit is comprehensively evaluated through an environmental protection effect coefficient and the dye emission reduction, wherein the environmental protection effect coefficient is the ratio of the pollution reduction amount of the energy-saving equipment at the power demand side to the power consumption of the whole society; pollutant emission reduction is the emission reduction of various pollutants after the virtual power plant project participates in carbon transaction.
As a further scheme of the invention, the step 2) of virtual power plant entropy method-fuzzy comprehensive evaluation model construction is carried out according to the following steps:
(1) normalization processing of evaluation index
Considering that the numerical values of various evaluation indexes have self physical meanings and normal ranges, in order to carry out comprehensive comparative analysis, normalization processing is required, and an analysis method of relative deterioration degree is adopted, namely, the numerical values are converted into specific numerical values between intervals [0,1] according to the quality of the index state reflected by the numerical values of the indexes, wherein 0 represents the worst, and 1 represents the best;
(2) determining the weight ratio of each index
The weight reflects the relative importance of each index to the comprehensive performance, and the weight A is determined by adopting an entropy value weighting method1,a2,a3,…aN]TAssuming that there are n samples and m indexes, the normalized index value is yij(i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to m), the specific gravity of each index is
Entropy of index j is
The weight of the index j is
(3) Establishing membership function
Constructing a fuzzy evaluation matrix R, wherein R ═ (R)ij)m×nIs a fuzzy relationship on nxv, which can be expressed as:
wherein r isij＝μR(Ii,vj) Indicating index IiAt decision vjThe degree of likelihood (membership), (X, V, R) constitutes the evaluation space;
(4) obtaining a fuzzy evaluation set
And calculating the membership degree of the evaluated object to each grade fuzzy subset by calculating a fuzzy evaluation set B as A.R, and selecting the evaluation grade corresponding to the maximum numerical value according to the maximum membership degree principle to obtain the final evaluation result.
As a further aspect of the present invention, the method for analyzing the relative deterioration degree includes the following calculation means:
for the larger and more excellent indexes, the standardization processing method comprises the following steps:
in the formula: i isxThe larger the index, the better the type; n is the set of all indexes in the evaluation system
For smaller and more optimal indexes, the standardization processing method comprises the following steps:
in the formula: i isyThe smaller the better the classThe index of type.
As a further scheme of the present invention, the step 3) of the scheduling policy based on the multidimensional value evaluation method is performed according to the following steps:
the optimal scheduling strategy of the virtual power plant at the demand side is that the overall benefit F obtained by participation of the whole operation control period in demand response is the largest, and if the control period comprises NT stages, the optimal decision under all scenes in the scheduling period is based on a multi-stage random optimization model and can be expressed as follows:
wherein, FsaveThe power saving effect is achieved; fecoThe income is derived from the income of selling electricity to the market and supplying power to the internal load, and the cost is derived from the calling cost of demand response resources, the cost of outsourcing electricity, default punishment and the like; finvThe investment benefit is achieved; fenvirIs an environmental benefit; cj(P) is an operation cost function of the virtual power plant participating in demand response; p is an operation decision set of VPP control quantity, including the regulation quantity of a load, an energy storage and a power supply; ce、CBC、CM、Cz、Ch、CxoRespectively the unit income coefficients of various benefit indexes; t isconstraintAnd the constraint condition set comprises power balance constraint, adjustable resource output upper and lower limit constraint and the like. K is an uncertain operation scene in the VPP demand response process, K is a set of operation scenes, and each benefit index is subjected to normalization and weighting processing
The invention has the beneficial effects that: a value evaluation system of comprehensive benefit evaluation of a virtual power plant project is given out from 4 dimensions such as power saving benefit, investment benefit, economic benefit, environmental benefit and the like, meanings and calculation methods of corresponding indexes are pointed out, meanwhile, an entropy method-fuzzy comprehensive evaluation model is constructed to compare and analyze the quality degree of each index, and technical support is provided for the design of a virtual power plant market mechanism and a business model;
and a demand side virtual power plant scheduling strategy is designed based on the constructed multidimensional value evaluation system, so that a scheduling scheme is optimized conveniently.
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the following embodiments of the present invention, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A multidimensional value evaluation method and a scheduling strategy for a demand side virtual power plant specifically comprise the following steps,
the method comprises the following steps: constructing a multi-dimensional value evaluation system of a virtual power plant,
(1) power saving effect
In the formula,. DELTA.WEThe comprehensive electricity-saving quantity of all the demand side resources calculated according to the electricity consumption quota comparison method is represented; wBPRepresenting the energy consumption of all the demand side resources in the base period; wSPRepresenting the energy consumption of all demand side resources in the statistical period; eBPRepresenting the total energy consumption of the single demand side resource in the base period; eSPRepresenting the total energy consumption of the single demand side resource in the statistical period; l isi BPIndicating the yield of a product at the basal period; l isi SPIndicating the yield of a certain product in a statistical period; n is the number of product types; m isiIs an energy conversion coefficient.
(2) Benefit of investment
The investment benefit is direct expression of the development benefit of the energy efficiency power plant project, the indexes are benefit indexes, and the larger the index value is, the better the investment benefit is.
a) Coefficient of investment benefit
In the formula IinvestmentRepresenting the investment benefit coefficient; l isprofitsRepresents the annual profit gross; l isinvestmentRepresenting the total plan investment.
b) Item increment rate
The project increment rate is used for measuring the continuous profitability of the project and reflects the residual value of the investment profit minus the investment cost brought by the virtual power plant project on the development demand side.
In the formula IzThe added value rate of the project is expressed to measure the continuous profitability of the project; zaddIndicating the current value of the added value of the item; zsumAnd (4) representing the current value of the total product of the project.
(3) Economic benefits
In the formula, BC represents a profit-cost ratio, which refers to a ratio of a present value of an energy-saving net cash flow obtained in an economic operation period to an operation cost in the process of developing a virtual power plant project on a demand side; cbenefitRepresenting the total profit in the construction and operation of the virtual power plant, CcostRepresenting the total cost of the virtual plant in its construction and operation.
(4) Environmental benefits
a) Coefficient of environmental protection effect
In the formula IenvirRepresenting an environmental protection effect coefficient; Δ WDRIndicating that the energy-saving equipment on the power demand side reduces the pollution amount; and E represents the power consumption of the whole society.
b) Pollutant discharge reducing amount
After the virtual power plant project participates in carbon transaction, the emission reduction amount of various pollutants is as follows:
in the formula,. DELTA.WxoReduction of CO after participation in carbon trading in virtual power plant projects2、SO2、NOxThe discharge amount of main pollutants XO such as dust and the like is reduced; lambda [ alpha ]XORepresents the XO emission reduction coefficient; alpha is alphaXORepresenting the X content of the fire coal; beta is aXORepresenting the conversion coefficient, gamma, of X-XOxThe X release rate is shown.
Step two: and (3) constructing a virtual power plant entropy method-fuzzy comprehensive evaluation model.
And (3) evaluating the quality of each index in a comprehensive evaluation value evaluation system by constructing an entropy method-fuzzy comprehensive evaluation model.
(1) Normalization of evaluation index
Considering that the numerical values of various evaluation indexes have self physical meanings and normal ranges, normalization processing is required to perform comprehensive comparative analysis. And (3) adopting an analysis method of relative degradation degree, namely converting the numerical value into a specific numerical value between intervals [0,1] according to the quality of the index state reflected by the numerical value of each index, wherein 0 represents the worst, and 1 represents the best. The virtual power plant value evaluation system established by the invention mainly relates to the following two degradation degree calculation methods.
a) For the larger and more excellent indexes, the standardization processing method comprises the following steps:
in the formula: i isxThe larger the index, the better the type; n is the set of all indexes in the evaluation system
b) For smaller and more optimal indexes, the standardization processing method comprises the following steps:
in the formula: i isyThe smaller the better the type of index
(2) Determining weights
The weight reflects the relative importance of each index to the comprehensive performance, and the invention adopts an entropy value weighting method to determine the weight A ═ a1,a2,a3,…aN]T. Assuming that n samples and m indexes are provided, the normalized index value is yij(i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to m), the specific gravity of each index is
Entropy of index j is
The weight of the index j is
(3) Establishing membership function
Constructing a fuzzy evaluation matrix R, wherein R ═ (R)ij)m×nIs a fuzzy relationship on nxv, which can be expressed as:
wherein r isij＝μR(Ii,vj) Indicating index IiAt decision vjThe degree of likelihood (membership), (X, V, R) constitutes the evaluation space.
(4) Obtaining a fuzzy evaluation set
And calculating the membership degree of the evaluated object to each grade fuzzy subset by calculating a fuzzy evaluation set B as A.R, and selecting the evaluation grade corresponding to the maximum numerical value according to the maximum membership degree principle to obtain the final evaluation result.
Step three: and scheduling strategies based on the multidimensional value evaluation method.
The optimal scheduling strategy of the virtual power plant at the demand side is the maximum comprehensive benefit F obtained by participation in demand response in the whole operation control period. If the control period includes NT stages, the optimization decision for all scenarios in the scheduling period based on the multi-stage stochastic optimization model can be expressed as:
wherein, FsaveThe power saving effect is achieved; fecoThe income is derived from the income of selling electricity to the market and supplying power to the internal load, and the cost is derived from the calling cost of demand response resources, the cost of outsourcing electricity, default punishment and the like; finvThe investment benefit is achieved; fenvirIs an environmental benefit; cj(P) is an operation cost function of the virtual power plant participating in demand response; p is an operation decision set of VPP control quantity, including the regulation quantity of a load, an energy storage and a power supply; ce、CBC、CM、Cz、Ch、CxoRespectively the unit income coefficients of various benefit indexes; t isconstraintAnd the constraint condition set comprises power balance constraint, adjustable resource output upper and lower limit constraint and the like. K is an uncertain operation scene in the VPP demand response process, and K is a set of operation scenes.
Note that: each benefit indicator has been normalized and weighted.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (5)
1. A multidimensional value assessment method and a scheduling strategy for a demand side virtual power plant are characterized in that: the method comprises the following steps:
1) constructing a multi-dimensional value evaluation index system of the virtual power plant;
2) constructing a virtual power plant entropy method-fuzzy comprehensive evaluation model, and comprehensively evaluating the advantages and disadvantages of the indexes in the step 1);
3) based on the scheduling strategy of the multidimensional value evaluation method in the steps 1) and 2).
2. The method and the scheduling strategy for evaluating the multidimensional value of the demand side virtual power plant according to claim 1, wherein the multidimensional value evaluation indexes of the virtual power plant in the step 1) comprise power saving benefits, investment benefits, economic benefits and environmental benefits;
(1) the electricity-saving benefit is as follows: calculating the comprehensive electricity-saving quantity of all the demand side resources according to an electricity consumption quota comparison method;
(2) investment benefits are as follows: the direct expression of the development benefit of the energy efficiency power plant project is realized, the indexes are benefit indexes, namely, the higher the index value is, the better the investment benefit is;
the investment benefit is evaluated through two parameters of an investment benefit coefficient and a project increment rate, and the investment benefit coefficient represents the ratio of the annual profit sum to the project investment sum; the project increment rate is used for measuring the continuous profitability of the project and reflects the residual value of the investment cost subtracted from the investment income brought by the virtual power plant project on the development demand side;
(3) the economic benefit is evaluated through the profit-cost ratio, namely the ratio of the current value of the energy-saving net cash flow obtained in the economic operation period to the operation cost in the process of developing the virtual power plant project on the demand side;
(4) the environmental benefit is comprehensively evaluated through an environmental protection effect coefficient and the dye emission reduction, wherein the environmental protection effect coefficient is the ratio of the pollution reduction amount of the energy-saving equipment at the power demand side to the power consumption of the whole society; pollutant emission reduction is the emission reduction of various pollutants after the virtual power plant project participates in carbon transaction.
3. The method for evaluating the multidimensional value of the demand side virtual power plant and the scheduling strategy according to claim 2, wherein the step 2) of building the entropy value method-fuzzy comprehensive evaluation model of the virtual power plant is carried out according to the following steps:
(1) normalization processing of evaluation index
Considering that the numerical values of various evaluation indexes have self physical meanings and normal ranges, in order to carry out comprehensive comparative analysis, normalization processing is required, and an analysis method of relative deterioration degree is adopted, namely, the numerical values are converted into specific numerical values between intervals [0,1] according to the quality of the index state reflected by the numerical values of the indexes, wherein 0 represents the worst, and 1 represents the best;
(2) determining the weight ratio of each index
The weight reflects the relative importance of each index to the comprehensive performance, and the weight A is determined by adopting an entropy value weighting method1,a2,a3,…aN]TAssuming that there are n samples and m indexes, the normalized index value is yij(i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to m), the specific gravity of each index is
Entropy of index j is
The weight of the index j is
(3) Establishing membership function
Constructing a fuzzy evaluation matrix R, wherein R ═ (R)ij)m×nIs a fuzzy relationship on nxv, which can be expressed as:
wherein r isij＝μR(Ii,vj) Indicating index IiAt decision vjThe degree of likelihood (membership), (X, V, R) constitutes the evaluation space;
(4) obtaining a fuzzy evaluation set
And calculating the membership degree of the evaluated object to each grade fuzzy subset by calculating a fuzzy evaluation set B as A.R, and selecting the evaluation grade corresponding to the maximum numerical value according to the maximum membership degree principle to obtain the final evaluation result.
4. The method for assessing the multidimensional value of the demand side virtual power plant and the scheduling strategy according to claim 3, wherein the method for analyzing the relative degradation degree comprises the following calculation methods:
for the larger and more excellent indexes, the standardization processing method comprises the following steps:
in the formula: i isxThe larger the index, the better the type; n is the set of all indexes in the evaluation system
For smaller and more optimal indexes, the standardization processing method comprises the following steps:
in the formula: i isyThe smaller the better the type of indicator.
5. The demand side virtual power plant multidimensional value assessment method and the scheduling strategy according to claim 4, wherein the step 3) of the scheduling strategy based on the multidimensional value assessment method is performed according to the following steps:
the optimal scheduling strategy of the virtual power plant at the demand side is that the overall benefit F obtained by participation of the whole operation control period in demand response is the largest, and if the control period comprises NT stages, the optimal decision under all scenes in the scheduling period is based on a multi-stage random optimization model and can be expressed as follows:
wherein, FsaveThe power saving effect is achieved; fecoThe income is derived from the income of selling electricity to the market and supplying power to the internal load, and the cost is derived from the calling cost of demand response resources, the cost of outsourcing electricity, default punishment and the like; finvThe investment benefit is achieved; fenvirIs an environmental benefit; cj(P) is an operation cost function of the virtual power plant participating in demand response; p is an operation decision set of VPP control quantity, including the regulation quantity of a load, an energy storage and a power supply; ce、CBC、CM、Cz、Ch、CxoRespectively the unit income coefficients of various benefit indexes; t isconstraintAnd the constraint condition set comprises power balance constraint, adjustable resource output upper and lower limit constraint and the like. K is an uncertain operation scene in the VPP demand response process, K is a set of operation scenes, and each benefit index is subjected to normalization and weighting processing.
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| CN113705989A (en) * | 2021-08-17 | 2021-11-26 | 上海交通大学 | Virtual power plant user response detection method based on data drive and deviation criterion |
| CN113837448A (en) * | 2021-08-30 | 2021-12-24 | 国网河南省电力公司经济技术研究院 | Operation optimization method for virtual power plant participating in rural energy internet construction |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107292520A (en) * | 2017-06-26 | 2017-10-24 | 华北电力大学 | A kind of Wu electricity villages utilization of new energy resources Benefit Evaluation Method |
| CN107358332A (en) * | 2017-05-18 | 2017-11-17 | 国网浙江省电力公司 | A kind of dispatching of power netwoks runs lean evaluation method |
| CN107609779A (en) * | 2017-09-21 | 2018-01-19 | 国网上海市电力公司 | A kind of comprehensive benefit assessment method of distributed energy management system |
| CN112234617A (en) * | 2020-10-15 | 2021-01-15 | 国网上海市电力公司 | Virtual power plant multi-objective optimization scheduling method considering output external characteristics |
| CN112598538A (en) * | 2020-12-25 | 2021-04-02 | 北京科东电力控制系统有限责任公司 | Internal benefit allocation method for virtual power plant to participate in medium-and-long-term power transaction |
-
2021
- 2021-06-03 CN CN202110620225.7A patent/CN113240330A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107358332A (en) * | 2017-05-18 | 2017-11-17 | 国网浙江省电力公司 | A kind of dispatching of power netwoks runs lean evaluation method |
| CN107292520A (en) * | 2017-06-26 | 2017-10-24 | 华北电力大学 | A kind of Wu electricity villages utilization of new energy resources Benefit Evaluation Method |
| CN107609779A (en) * | 2017-09-21 | 2018-01-19 | 国网上海市电力公司 | A kind of comprehensive benefit assessment method of distributed energy management system |
| CN112234617A (en) * | 2020-10-15 | 2021-01-15 | 国网上海市电力公司 | Virtual power plant multi-objective optimization scheduling method considering output external characteristics |
| CN112598538A (en) * | 2020-12-25 | 2021-04-02 | 北京科东电力控制系统有限责任公司 | Internal benefit allocation method for virtual power plant to participate in medium-and-long-term power transaction |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113705989A (en) * | 2021-08-17 | 2021-11-26 | 上海交通大学 | Virtual power plant user response detection method based on data drive and deviation criterion |
| CN113705989B (en) * | 2021-08-17 | 2023-12-08 | 上海交通大学 | Virtual power plant user response detection method based on data driving and deviation criteria |
| CN113837448A (en) * | 2021-08-30 | 2021-12-24 | 国网河南省电力公司经济技术研究院 | Operation optimization method for virtual power plant participating in rural energy internet construction |
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