CN117196680A - Method and device for distributing benefits of internal main body of virtual power plant participating in market transaction - Google Patents
Method and device for distributing benefits of internal main body of virtual power plant participating in market transaction Download PDFInfo
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Abstract
The invention discloses an internal main body benefit distribution method and device for virtual power plants to participate in market trading, comprising the following steps of 1, constructing a day-ahead and real-time power market trading model, wherein in the model, if the VPP real-time power generation exceeds the market bidding electric quantity in the day-ahead, the redundant power generation is stabilized by positive unbalanced electricity price, and the positive unbalanced electricity price is lower than or equal to the market clearing price in the day-ahead; if the VPP real-time power generation is lower than the market bidding power before the day. According to the benefit distribution method provided by the invention, the initial benefit distribution value of the VPP is obtained by constructing a daily and real-time power market transaction model, then the initial benefit distribution value is corrected based on factors such as cost, contribution rate and risk of the main body, the corrected benefit distribution value is obtained, and finally the satisfaction degree model is combined, so that the optimal satisfaction degree is selected as the final benefit distribution result.
Description
Technical Field
The invention relates to an internal main body benefit distribution method for virtual power plants participating in market transaction, and belongs to the field of electric field management.
Background
With the continuous development of the electric power market and the increasing complexity of the electric power system, how to fairly and reasonably distribute benefits of each participating subject becomes an important research topic. Particularly in a new power trading mode of a Virtual Power Plant (VPP), the problem of internal benefit distribution is more complex due to the multiple energy units involved, such as wind power, photovoltaic, etc.
Virtual power plants are used as an organization form integrating various distributed energy resources, and various energy units such as wind power, photovoltaics and the like are related to the virtual power plants. The performance and contribution of these units in the electricity market are different, so how to distribute the benefits fairly and reasonably becomes a key issue.
Disclosure of Invention
The invention mainly aims to provide an internal main body benefit distribution method for virtual power plants to participate in market transactions, which can distribute benefits to multiple main bodies from multiple angles, and ensure that the distribution of benefits to the multiple main bodies can be satisfied as much as possible.
The aim of the invention can be achieved by adopting the following technical scheme:
In a first aspect, the present invention provides a method for distributing internal body benefits of a virtual power plant in a market transaction, comprising:
step 1, constructing a daily-life real-time electric power market transaction model;
step 2, acquiring an initial benefit distribution value of the VPP based on a day-ahead real-time electricity price model;
step 3, respectively carrying out cost correction, contribution rate correction and risk correction on the VPP initial benefit distribution value to obtain a benefit distribution result based on cost, a benefit distribution result based on contribution rate and a benefit distribution result based on risk;
step 4, determining the cost, the cooperation contribution rate and the weight of the risk, and calculating the comprehensive benefits of all participants based on the determined cost, the cooperation contribution rate and the weight of the risk by combining the benefit distribution result based on the cost, the benefit distribution result based on the contribution rate and the benefit distribution result based on the risk; calculating an improved Shapley value and an improved Banzhaf value according to the comprehensive benefits of all participants;
step 5, calculating to obtain a distribution result based on the Shapley value and a distribution result based on the Banzhaf value based on the improved Shapley value and the improved Banzhaf value; and respectively calculating the satisfaction degree of each benefit distribution result based on the satisfaction degree model according to the distribution result based on the Shapley value and the distribution result based on the Banzhaf value, and selecting the benefit distribution result with the highest satisfaction degree.
Further, in step 1, constructing a day-ahead, real-time power market transaction model, including:
in the daily and real-time electric power market transaction model, if the VPP real-time generated energy exceeds the bidding electric quantity of the daily market, the redundant generated energy is stabilized by positive unbalanced electricity price, and the positive unbalanced electricity price is lower than or equal to the daily market clearing price;
if the VPP real-time power generation amount is lower than the bidding power of the market in the past, the power generation red character of the VPP real-time power generation amount is stabilized by a negative unbalanced power price which is greater than or equal to the clear power price of the market in the past;
the day-ahead real-time electricity price model is as follows:
wherein: lambda (lambda) rmb (t)、λ rms (t) real-time market negative unbalanced power price and positive unbalanced power price at time t respectively; lambda (lambda) bm (t) the current price of the current market before the day at the moment t;penalty coefficients for real-time market imbalance electricity prices.
Further, performing cost correction on the VPP initial benefit allocation value includes:
the cost-based benefit allocation result is calculated by the following formula:
wherein: c is daily hair of each energy unitThe overall net cost of the electricity is that,the net cost of daily power generation of the photovoltaic unit is +.>The daily electricity generation net cost of the wind turbine generator is realized;
wherein: n is the participation quantity of each energy unit in the virtual power plant; v is the total income of the virtual power plant, V' i The results are assigned to the subject i cost-based benefits.
Further, performing contribution rate correction on the VPP initial benefit allocation value includes:
the benefit allocation result based on the contribution rate is calculated by the following formula:
wherein: d is the total load demand, D i The load amounts respectively contributed by the ith unit, D w Load amount contributing to wind turbine generator system D p Load amount contributing to the photovoltaic unit.
Further, performing output risk correction on the VPP initial benefit distribution value includes:
calculating benefit distribution results based on the output risk by the following formula:
wherein: r is the actual risk, V ', V' i And (5) distributing results for benefits of the ith unit based on the output risk.
Further, in step 4, determining weights of cost, collaboration contribution rate and risk includes:
in step 4, determining weights of cost, collaboration contribution rate and risk, including:
the weight vector W of cost, co-contribution rate and risk is denoted (W 1 ,w 2 ,w 3 ) The method comprises the steps of carrying out a first treatment on the surface of the The weights of the cost, the cooperation contribution rate and the risk are determined to be 1/3, and the weight vector W= [1/3,1/3]The importance of the cost, the contribution rate and the risk is equal.
Or obtaining the weights of the cost, the cooperation contribution rate and the risk through fuzzy comprehensive evaluation, wherein the method comprises the following steps of:
step 4.1: determining an evaluation factor: cost, collaboration contribution rate, and risk, respectively;
Step 4.2: setting an initial weight: setting an initial weight vector, W= [1/3,1/3 ], which means that the importance of cost, contribution rate and risk are equal;
step 4.3: constructing a fuzzy relation matrix: constructing a fuzzy relation matrix based on the benefit distribution result of each evaluation factor, wherein the matrix describes the performances of each participant under different evaluation factors;
through constructing the fuzzy relation matrix, the performance of each participant under different evaluation factors (cost, cooperation contribution rate and risk) can be quantitatively described, so that basic data is provided for subsequent fuzzy comprehensive evaluation, and benefit distribution is fairer, more reasonable and transparent;
step 4.4: and (3) performing fuzzy comprehensive evaluation: using the weight vector and the fuzzy relation matrix, (multiplying) to calculate a comprehensive evaluation result, wherein the result can help to know the relative importance of each evaluation factor;
the fuzzy comprehensive evaluation provides a comprehensive and quantitative evaluation result, and the result integrates the influence of all the evaluation factors, so that the relative importance of each evaluation factor on benefit distribution can be more clearly known, thereby providing a basis for weight adjustment;
Step 4.5: and (5) adjusting weights: according to the comprehensive evaluation result, the weight is further adjusted to better reflect the importance of each evaluation factor;
step (a)4.6: iterative calculation: repeating the above steps until the weight is stable to obtain (w 1 ,w 2 ,w 3 )。
Step 4.3: construction of fuzzy relation matrix
Step 4.3.1: determining an evaluation object and an evaluation factor: the evaluation objects are all participants in the virtual power plant; the evaluation factors are cost, cooperation contribution rate and risk;
step 4.3.2: collecting data: for each evaluation object, collecting data under each evaluation factor, wherein the data can be quantitative or qualitative;
step 4.3.3: blurring data: the collected data is converted into a fuzzy set, for example, three grades of high, medium and low are used for evaluation, and then the three grades can be converted into the fuzzy set;
step 4.3.4: constructing a fuzzy relation matrix: based on the blurred data, a blurred relation matrix is constructed, the rows of the matrix represent evaluation objects, and the columns represent evaluation factors;
in step 4.3, data providing a quantitative or qualitative description of the performance of the evaluation object (here, each participant in the virtual power plant) under each evaluation factor, provide a basis for the subsequent construction of the fuzzy and fuzzy relation matrices:
Step 4.3.2: collecting data:
cost: each participant (or group) has a net cost of its daily power generation, and this data can be obtained from equations 1 and 2, for example,is the daily electricity generation net cost of the photovoltaic unit, < >>Is the daily electricity generation net cost of the wind turbine generator.
Cooperative contribution rate: this means the contribution of each unit to the total load demand, D from equation 3 i Is the load contributed by the ith unit.
Risk: the risk is described by formula 4, wherein R represents the actual risk;
step 4.3.3: blurring data: for the collected data, it needs to be converted into a fuzzy set, for example, if the cost of a certain unit is relatively low, it is blurred to "low"; if its cooperative contribution rate is moderate, it can be blurred to "medium"; if the risk is high, it can be blurred to be "high"
Step 4.3.4: constructing a fuzzy relation matrix: constructing a fuzzy relation matrix based on the fuzzy data, wherein each row of the matrix represents an evaluation object (unit), each column represents an evaluation factor, and each element in the matrix represents a fuzzy evaluation result of the evaluation object under the evaluation factor;
the data collection is used for acquiring the concrete performance of each evaluation object under each evaluation factor, and the data provides necessary input for the subsequent fuzzy comprehensive evaluation.
Step 4.4: performing fuzzy comprehensive evaluation
Step 4.4.1: determining a weight vector: this is a row vector representing the weight of each evaluation factor;
step 4.4.2: calculating a fuzzy comprehensive evaluation result: matrix multiplication is carried out by using the weight vector and the fuzzy relation matrix to obtain a fuzzy comprehensive evaluation result, wherein the result is a fuzzy set and describes the comprehensive evaluation of each evaluation object;
step 4.5: adjusting weights
Step 4.5.1: and (5) analyzing a fuzzy comprehensive evaluation result: analyzing the relative importance of each evaluation factor according to the fuzzy comprehensive evaluation result;
step 4.5.2: and (5) adjusting weights: if the importance of a certain evaluation factor is underestimated or overestimated, its weight can be adjusted accordingly.
Further, in step 4, based on the determined cost, the cooperative contribution rate and the weight of the risk, in combination with the cost-based benefit distribution result, the contribution rate-based benefit distribution result and the risk-based benefit distribution result, the comprehensive benefits of all the participants are calculated, including:
for each participant i, comprehensive benefit E i The calculation can be made by the following formula:
\[E i ＝w 1 ×V′ i +w 2 ×V″ i +w 3 ×V″′ i \]
wherein,
V' i is the cost-based benefit allocation result of participant i;
V″ i is the benefit distribution result of the participant i based on the contribution rate;
V″′ i Is the benefit distribution result of the participant i based on the risks;
comprehensive benefit value E i Reflects the overall benefit of participant i after three factors of cost, collaboration contribution rate and risk are considered, weight (w 1 ,w 2 ,w 3 ) Determining the relative importance of each factor in the comprehensive benefit;
the above steps are repeated to calculate their overall benefit for all participants.
Further, in step 4, an improved Shapley value and an improved Banzhaf value are calculated according to the comprehensive benefit of all participants, including:
the improved calculation formulas of the Shapley value and the Banzhaf value are as follows:
improved Shapley:
in this formula:
(φ' i (v) A modified Shapley value representing participant i;
s is any subset of the participant set N except for participant \ (i\), which represents different combinations of units in the virtual power plant;
(v '(S & { i })) and (v' (S)) represent the combined benefit of the set combination with and without the inclusion of participant \ (i\), respectively;
improved Banzhaf value:
in this formula:
(β' i (v) A modified Banzhaf value representing participant \ (i\);
(S\) is any subset of the set of participants\N\except for participant\i\which represents different combinations of units in the virtual power plant;
(v' (S.
Further, in step 5, based on the improved Shapley value and the improved Banzhaf value, a allocation result based on the Shapley value and a allocation result based on the Banzhaf value are calculated, which includes:
based on modified Shapley values: allocating the benefit or the resource for each participant by using the improved Shapley value based on the benefit or the resource allocation of each participant in proportion to the improved Shapley value, and forming an allocation result based on the Shapley value;
based on the modified Banzhaf value: the improved Banzhaf value is used to allocate the benefit or resource for each participant based on the benefit or resource allocation of each participant in proportion to the improved Banzhaf value, forming an allocation result based on the Banzhaf value.
Further, in step 5, according to the allocation result based on the shape value and the allocation result based on the Banzhaf value, based on the satisfaction model, calculating the satisfaction degree of each benefit allocation result, and selecting the benefit allocation result with the highest satisfaction degree, including the following steps:
calculating satisfaction: for each participant, its satisfaction with the Shapley value-based and Banzhaf value-based allocation results was calculated using the following satisfaction model;
The satisfaction model is shown as the following formula:
wherein: m is M i Satisfaction of revenue distribution for principal i, r ”io "is the primary benefit distribution result of main body i, r in The result is allocated to the benefit of the subject i.
Selecting an optimal solution: all participants were compared for satisfaction with both allocation schemes, and the scheme with the highest overall satisfaction was selected as the final allocation scheme.
In a second aspect, the present invention provides an internal body benefit distribution device for a virtual power plant to participate in a market transaction, the device comprising:
model construction module: the method is used for constructing a daily-life and real-time electric power market transaction model;
the initial benefit distribution module: the method comprises the steps of obtaining a VPP initial benefit distribution value based on a day-ahead real-time electricity price model;
the secondary benefit distribution module: the method comprises the steps of carrying out cost correction, contribution rate correction and risk correction on the VPP initial benefit distribution value respectively to obtain a benefit distribution result based on cost, a benefit distribution result based on contribution rate and a benefit distribution result based on risk;
the improvement module: the comprehensive benefits of all participants are calculated by determining the weights of the cost, the cooperation contribution rate and the risk and combining the benefit distribution result based on the cost, the benefit distribution result based on the contribution rate and the benefit distribution result based on the risk based on the weights of the determined cost, the cooperation contribution rate and the risk; calculating an improved Shapley value and an improved Banzhaf value according to the comprehensive benefits of all participants;
Satisfaction selecting module: the method is used for calculating a distribution result based on the Shapley value and a distribution result based on the Banzhaf value based on the improved Shapley value and the improved Banzhaf value; and respectively calculating the satisfaction degree of each benefit distribution result based on the satisfaction degree model according to the distribution result based on the Shapley value and the distribution result based on the Banzhaf value, and selecting the benefit distribution result with the highest satisfaction degree.
In a third aspect, the present invention provides an internal body benefit distribution device for a virtual power plant to participate in market transactions, comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of the first aspect.
Compared with the prior art, the invention has the beneficial effects that:
according to the benefit distribution method provided by the invention, the initial benefit distribution value of the VPP is obtained by constructing a daily and real-time power market transaction model, then the initial benefit distribution value is corrected based on factors such as cost, contribution rate and risk of the main body, the corrected benefit distribution value is obtained, and finally the satisfaction degree model is combined, so that the optimal satisfaction degree is selected as the final benefit distribution result.
Drawings
FIG. 1 is a schematic diagram of an electric power market transaction model according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
Embodiment one:
as shown in FIG. 1, the method for distributing the benefits of the internal main body of the virtual power plant participating in the market transaction provided by the embodiment comprises the following steps of
Step 1, constructing a daily and real-time electric power market transaction model, wherein in the transaction model, VPP (virtual power plant) is used as a price receiver to complete daily wind-light output prediction, and bid electric quantity of 24 hours of the next day is declared to an electric power market based on the wind-light output prediction;
because of the existence of wind and light output prediction deviation, when the wind and light output deviation cannot be eliminated due to the charging and discharging of an energy storage system in the VPP and the response of flexible load demands, the VPP needs to eliminate the output deviation in real-time market transaction;
if the VPP real-time generated energy exceeds the bidding electric quantity of the market in the day-ahead, the redundant generated energy is stabilized by the positive unbalanced electric price, and the positive unbalanced electric price is lower than or equal to the market clearing price in the day-ahead;
if the VPP real-time power generation amount is lower than the bidding power of the market in the past, the power generation red character of the VPP real-time power generation amount is stabilized by a negative unbalanced power price which is greater than or equal to the clear power price of the market in the past;
The day-ahead real-time electricity price model is as follows:
wherein: lambda (lambda) rmb (t)、λ rms (t) real-time market negative unbalanced power price and positive unbalanced power price at time t respectively; lambda (lambda) bm (t) the current price of the current market before the day at the moment t;punishment coefficients for real-time market unbalanced electricity prices;
step 2, acquiring an initial benefit distribution value of the Virtual Power Plant (VPP), namely an unmodified benefit distribution proportion, based on a day-ahead real-time electricity price model;
step 3, obtaining a virtual power plant secondary benefit distribution value based on a cost correction method, a contribution rate correction method and a risk correction method, wherein the actual risk of each participating main body (each unit) is determined by a subjective and objective weight design valve combined by a hierarchical analysis method and an entropy weight method, and the cost and the contribution rate can be directly or indirectly obtained, so that the risk of each unit is only determined, and the cost, the contribution rate and the risk are combined to obtain a VPP secondary benefit distribution value, namely the corrected benefit distribution proportion is obtained;
in this embodiment, the cost-based correction method is implemented by the following formula:
wherein: c is the total net cost of daily power generation of each energy unit,the net cost of daily power generation of the photovoltaic unit is +.>The daily electricity generation net cost of the wind turbine generator is realized;
wherein: n is the participation quantity of each energy unit in the virtual power plant; v is the total income of the virtual power plant, V' i Assigning results for cost-based benefits;
the correction method based on the contribution rate comprises the following steps:
wherein: d is the total load demand, D i Respectively the load amounts contributed by different units, D w Load amount contributing to wind turbine generator system D p The amount of load contributed to the photovoltaic unit; the correction method based on the output risk comprises the following steps:
wherein: r is the actual risk, V ', V' i Assigning results to benefits based on the output risk; a satisfaction model, as shown in the following formula:
wherein: m is M i For principal i to be satisfied with the distribution of benefits, r ”io "is the primary benefit distribution result of main body i, r in The result is allocated to the benefit of the subject i.
In the embodiment, the cost, contribution rate, risk and other factors are corrected to the VPP initial benefit distribution value, and the benefit distribution method is improved from multiple angles, so that the optimal virtual power plant benefit distribution result can be effectively obtained.
Step 4, determining the cost, the cooperation contribution rate and the weight of the risk, and calculating the comprehensive benefits of all participants based on the determined cost, the cooperation contribution rate and the weight of the risk by combining the benefit distribution result based on the cost, the benefit distribution result based on the contribution rate and the benefit distribution result based on the risk; calculating an improved Shapley value and an improved Banzhaf value according to the comprehensive benefits of all participants;
The calculation process may be the following steps:
the fuzzy comprehensive evaluation method comprises the following steps: the objective of this approach is to integrate multiple evaluation factors (here, cost, co-operative contribution and risk) to obtain an overall evaluation result. The specific calculation process generally comprises the following steps:
determining an evaluation factor and an evaluation grade: here, the evaluation factors are cost, cooperation contribution rate, and risk, and the evaluation level may be set according to actual conditions, for example, "low", "medium", "high", and the like.
Establishing a fuzzy evaluation matrix: for each evaluation factor, constructing a fuzzy evaluation matrix according to the membership degree of each evaluation level, wherein the calculation of the membership degree can be performed according to the actual data and the principle of fuzzy logic;
determining weights: the weight represents the importance of each evaluation factor in the overall evaluation, wherein the weight is the weight occupied by the cost, the cooperation contribution rate and the risk, and the weight determination can be carried out according to methods such as expert scoring, historical data analysis and the like;
and (3) performing fuzzy comprehensive evaluation: performing fuzzy comprehensive evaluation according to the fuzzy evaluation matrix and the weight to obtain an overall evaluation result;
the specific method for determining the weights of the cost, the cooperation contribution rate and the risk comprises the following steps:
In step 4, determining weights of cost, collaboration contribution rate and risk, including:
the weight vector W of cost, co-contribution rate and risk is denoted (W 1 ,w 2 ,w 3 ) The method comprises the steps of carrying out a first treatment on the surface of the The weights of the cost, the cooperation contribution rate and the risk are determined to be 1/3, and the weight vector W= [1/3,1/3]The importance of the cost, the contribution rate and the risk is equal.
Or obtaining the weights of the cost, the cooperation contribution rate and the risk through fuzzy comprehensive evaluation, wherein the method comprises the following steps of:
step 4.1: determining an evaluation factor: cost, collaboration contribution rate, and risk, respectively;
step 4.2: setting an initial weight: setting an initial weight vector, W= [1/3,1/3 ], which means that the importance of cost, contribution rate and risk are equal;
step 4.3: constructing a fuzzy relation matrix: constructing a fuzzy relation matrix based on the benefit distribution result of each evaluation factor, wherein the matrix describes the performances of each participant under different evaluation factors;
through constructing the fuzzy relation matrix, the performance of each participant under different evaluation factors (cost, cooperation contribution rate and risk) can be quantitatively described, so that basic data is provided for subsequent fuzzy comprehensive evaluation, and benefit distribution is fairer, more reasonable and transparent;
Step 4.4: and (3) performing fuzzy comprehensive evaluation: using the weight vector and the fuzzy relation matrix, (multiplying) to calculate a comprehensive evaluation result, wherein the result can help to know the relative importance of each evaluation factor;
the fuzzy comprehensive evaluation provides a comprehensive and quantitative evaluation result, and the result integrates the influence of all the evaluation factors, so that the relative importance of each evaluation factor on benefit distribution can be more clearly known, thereby providing a basis for weight adjustment;
step 4.5: and (5) adjusting weights: according to the comprehensive evaluation result, the weight is further adjusted to better reflect the importance of each evaluation factor;
step 4.6: iterative calculation: repeating the above steps until the weight is stable to obtain (w 1 ,w 2 ,w 3 )。
Step 4.3: construction of fuzzy relation matrix
Step 4.3.1: determining an evaluation object and an evaluation factor: the evaluation objects are all participants in the virtual power plant; the evaluation factors are cost, cooperation contribution rate and risk;
step 4.3.2: collecting data: for each evaluation object, collecting data under each evaluation factor, wherein the data can be quantitative or qualitative;
step 4.3.3: blurring data: the collected data is converted into a fuzzy set, for example, three grades of high, medium and low are used for evaluation, and then the three grades can be converted into the fuzzy set;
Step 4.3.4: constructing a fuzzy relation matrix: based on the blurred data, a blurred relation matrix is constructed, the rows of the matrix represent evaluation objects, and the columns represent evaluation factors;
in step 4.3, data providing a quantitative or qualitative description of the performance of the evaluation object (here, each participant in the virtual power plant) under each evaluation factor, provide a basis for the subsequent construction of the fuzzy and fuzzy relation matrices:
step 4.3.2: collecting data:
cost: each participant (or group) has a net cost of its daily power generation, and this data can be obtained from equations 1 and 2, for example,is the daily electricity generation net cost of the photovoltaic unit, < >>Is the daily electricity generation net cost of the wind turbine generator.
Contribution rate of cooperation: this means the contribution of each unit to the total load demand, D from equation 3 i Is the load contributed by the ith unit.
Risk: the risk is described by formula 4, wherein R represents the actual risk;
step 4.3.3: blurring data: for the collected data, it needs to be converted into a fuzzy set, for example, if the cost of a certain unit is relatively low, it is blurred to "low"; if its cooperative contribution rate is moderate, it can be blurred to "medium"; if the risk is high, it can be blurred to be "high"
Step 4.3.4: constructing a fuzzy relation matrix: constructing a fuzzy relation matrix based on the fuzzy data, wherein each row of the matrix represents an evaluation object (unit), each column represents an evaluation factor, and each element in the matrix represents a fuzzy evaluation result of the evaluation object under the evaluation factor;
the data collection is used for acquiring the concrete performance of each evaluation object under each evaluation factor, and the data provides necessary input for the subsequent fuzzy comprehensive evaluation.
Step 4.4: performing fuzzy comprehensive evaluation
Step 4.4.1: determining a weight vector: this is a row vector representing the weight of each evaluation factor;
step 4.4.2: calculating a fuzzy comprehensive evaluation result: matrix multiplication is carried out by using the weight vector and the fuzzy relation matrix to obtain a fuzzy comprehensive evaluation result, wherein the result is a fuzzy set and describes the comprehensive evaluation of each evaluation object;
step 4.5: adjusting weights
Step 4.5.1: and (5) analyzing a fuzzy comprehensive evaluation result: analyzing the relative importance of each evaluation factor according to the fuzzy comprehensive evaluation result;
step 4.5.2: and (5) adjusting weights: if the importance of a certain evaluation factor is underestimated or overestimated, its weight can be adjusted accordingly.
The Shapley value and the Banzhaf value are two important benefit distribution methods in the cooperative game theory, and the Shapley value and the Banzhaf value are required to be improved according to the fuzzy comprehensive evaluation result: specifically, the comprehensive evaluation index is regarded as the comprehensive benefit of each participant, and then the comprehensive benefit is used for replacing the original benefit or benefit when the Shapley value and the Banzhaf value are calculated, so that the improved Shapley value and the Banzhaf value can better reflect the cost, the cooperation contribution rate and the risk of each participant.
Shapley and Banzhaf are benefit distribution methods based on cooperative game theory, and their calculation usually only considers the contribution of participants, but not other factors such as cost and risk. The fuzzy comprehensive evaluation results take the factors into consideration, so that the Shapley value and the Banzhaf value can be improved according to the fuzzy comprehensive evaluation results, and the actual situation can be reflected better.
Both Shapley and Banzhaf are benefit distribution methods based on cooperative game theory, whose calculation usually only takes into account the contribution of the participants, and not other factors such as cost and risk. In the invention, three factors of cost, cooperation contribution rate and risk are combined through a fuzzy comprehensive evaluation method to obtain an overall evaluation result, and the result is regarded as the comprehensive benefit of each participant.
Specifically, in step 4, the cost, the cooperative contribution rate and the weight occupied by the risk are obtained by combining, so as to obtain the final improved Shapley value and the improved Banzhaf value, and the method comprises the following steps:
both Shapley and Banzhaf are benefit distribution methods based on cooperative game theory, whose calculation usually only takes into account the contribution of the participants, and not other factors such as cost and risk. In the invention, three factors of cost, cooperation contribution rate and risk are combined through a fuzzy comprehensive evaluation method to obtain an overall evaluation result, and the result is regarded as the benefit of each participant.
The improved calculation formulas of the Shapley value and the Banzhaf value are as follows:
1. improved Shapley:
in this formula:
ο(φ′ i (v) A modified Shapley value representing participant i.
Where S is any subset of the set of participants N other than participant \ (i\), which subsets represent different combinations of units in the virtual power plant.
The 'benefit' of the unit combination containing and not containing the participator \ (i\) is calculated by a fuzzy comprehensive evaluation method, and three factors of cost, cooperation contribution rate and risk are comprehensively considered.
2. Improved Banzhaf value:
in this formula:
ο(β′ i (v) A modified Banzhaf value representing participant \ (i\).
Where \ (s\) is any subset of the set of participants\ (n\) other than participant\ (i\), which subsets represent different combinations of units in the virtual power plant.
The 'benefit' of the unit combination containing and not containing the participator \ (i\) is calculated by a fuzzy comprehensive evaluation method, and three factors of cost, cooperation contribution rate and risk are comprehensively considered.
In this way, the improved Shapley and Banzhaf values better reflect the cost, collaboration contribution and risk of each participant.
Based on modified Shapley values: the benefit or resource allocation of each participant is proportional to its modified Shapley value, e.g., if participant a's modified Shapley value is 0.6 and the total benefit is 100, a will obtain a benefit of 60;
based on the modified Banzhaf value: the benefit or resource allocation of each participant is proportional to its modified Banzhaf value, e.g., if participant a's modified Banzhaf value is 0.7 and the total benefit is 100, a will achieve a benefit of 70;
the selection is made for both allocation results using step 5.
Obtaining a cost-based benefit distribution result, a contribution-based benefit distribution result and a risk-based benefit distribution result based on the improved Shapley value and the improved Banzhaf value, comprising the steps of:
the method is based on a fuzzy comprehensive evaluation method, and the cost, the cooperation contribution rate and the weight occupied by risks are obtained, so that the final improved Shapley value and the improved Banzhaf value are obtained.
The improved benefit distribution results were found based on the final improved Shapley value and the improved Banzhaf value.
Step 5, calculating to obtain a distribution result based on the Shapley value and a distribution result based on the Banzhaf value based on the improved Shapley value and the improved Banzhaf value; and respectively calculating the satisfaction degree of each benefit distribution result based on the satisfaction degree model according to the distribution result based on the Shapley value and the distribution result based on the Banzhaf value, and selecting the benefit distribution result with the highest satisfaction degree.
The specific operation steps are as follows:
1. calculating an allocation result based on the Shapley value: allocating revenue or resources to each participant using the modified Shapley value;
2. calculating a distribution result based on the Banzhaf value: allocating revenue or resources to each participant using the modified Banzhaf value;
3. calculating satisfaction: for each participant, calculating the satisfaction of each participant with the allocation results based on the Shapley value and the Banzhaf value by using the satisfaction model;
4. Selecting an optimal solution: comparing satisfaction degrees of all participants on the two allocation schemes, and selecting the scheme with the highest overall satisfaction degree as the final allocation scheme;
this approach ensures that the allocation scheme is not only fair, but also meets the expectations of most or all participants, thereby improving the acceptability of the allocation scheme.
In summary, in this embodiment, in the benefit distribution method provided in this embodiment, an initial benefit distribution value of the VPP is obtained by constructing a day-ahead and real-time power market transaction model, then the initial benefit distribution value is corrected based on factors such as cost, contribution rate and risk of the main body, a corrected benefit distribution value is obtained, and finally, a satisfaction model is combined, so that the satisfaction degree is selected to be the final benefit distribution result.
Embodiment two:
the embodiment provides an internal body benefit distribution device for a virtual power plant to participate in market trade, the device comprises:
model construction module: the method is used for constructing a daily-life and real-time electric power market transaction model;
The initial benefit distribution module: the method comprises the steps of obtaining a VPP initial benefit distribution value based on a day-ahead real-time electricity price model;
the secondary benefit distribution module: the method comprises the steps of carrying out cost correction, contribution rate correction and risk correction on the VPP initial benefit distribution value respectively to obtain a benefit distribution result based on cost, a benefit distribution result based on contribution rate and a benefit distribution result based on risk;
the improvement module: the comprehensive benefits of all participants are calculated by determining the weights of the cost, the cooperation contribution rate and the risk and combining the benefit distribution result based on the cost, the benefit distribution result based on the contribution rate and the benefit distribution result based on the risk based on the weights of the determined cost, the cooperation contribution rate and the risk; calculating an improved Shapley value and an improved Banzhaf value according to the comprehensive benefits of all participants;
satisfaction selecting module: the method is used for calculating a distribution result based on the Shapley value and a distribution result based on the Banzhaf value based on the improved Shapley value and the improved Banzhaf value; and respectively calculating the satisfaction degree of each benefit distribution result based on the satisfaction degree model according to the distribution result based on the Shapley value and the distribution result based on the Banzhaf value, and selecting the benefit distribution result with the highest satisfaction degree.
The apparatus of this embodiment may be used to implement the method described in embodiment one.
Embodiment III:
the embodiment of the application also provides an internal main body benefit distribution device for the virtual power plant to participate in market transaction, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method of embodiment one.
Embodiment four:
the embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the steps of the method of the embodiment one.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application 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 application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. 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.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. An internal main benefit distribution method for a virtual power plant to participate in market transaction is characterized by comprising the following steps: the method comprises the following steps:
step 1, constructing a daily-life real-time electric power market transaction model;
step 2, acquiring an initial benefit distribution value of the VPP based on a day-ahead real-time electricity price model;
step 3, respectively carrying out cost correction, contribution rate correction and risk correction on the VPP initial benefit distribution value to obtain a benefit distribution result based on cost, a benefit distribution result based on contribution rate and a benefit distribution result based on risk;
step 4, determining the cost, the cooperation contribution rate and the weight of the risk, and calculating the comprehensive benefits of all participants based on the determined cost, the cooperation contribution rate and the weight of the risk by combining the benefit distribution result based on the cost, the benefit distribution result based on the contribution rate and the benefit distribution result based on the risk; calculating an improved Shapley value and an improved Banzhaf value according to the comprehensive benefits of all participants;
step 5, calculating to obtain a distribution result based on the Shapley value and a distribution result based on the Banzhaf value based on the improved Shapley value and the improved Banzhaf value; and respectively calculating the satisfaction degree of each benefit distribution result based on the satisfaction degree model according to the distribution result based on the Shapley value and the distribution result based on the Banzhaf value, and selecting the benefit distribution result with the highest satisfaction degree.
2. The method for distributing internal body benefits of a virtual power plant in a market transaction according to claim 1, wherein: in step 1, a day-ahead, real-time power market transaction model is constructed, comprising:
in the daily and real-time electric power market transaction model, if the VPP real-time generated energy exceeds the bidding electric quantity of the daily market, the redundant generated energy is stabilized by positive unbalanced electricity price, and the positive unbalanced electricity price is lower than or equal to the daily market clearing price;
if the VPP real-time power generation amount is lower than the bidding power of the market in the past, the power generation red character of the VPP real-time power generation amount is stabilized by a negative unbalanced power price which is greater than or equal to the clear power price of the market in the past;
the day-ahead real-time electricity price model is as follows:
wherein: lambda (lambda) rmb (t)、λ rms (t) real-time market negative unbalanced power price and positive unbalanced power price at time t respectively; lambda (lambda) bm (t) the current price of the current market before the day at the moment t;penalty coefficients for real-time market imbalance electricity prices.
3. The method for distributing internal body benefits of a virtual power plant in a market transaction according to claim 1, wherein: and carrying out cost correction on the VPP initial benefit distribution value, wherein the cost correction comprises the following steps:
the cost-based benefit allocation result is calculated by the following formula:
wherein: c is the total net cost of daily power generation of each energy unit, The net cost of daily power generation of the photovoltaic unit is +.>The daily electricity generation net cost of the wind turbine generator is realized;
wherein: n is the participation quantity of each energy unit in the virtual power plant; v is the total income of the virtual power plant, V' i Assigning a cost-based benefit to principal i;
and/or, performing contribution rate correction on the VPP initial benefit allocation value, including:
the benefit allocation result based on the contribution rate is calculated by the following formula:
wherein: d is the total load demand, D i The load amounts respectively contributed by the ith unit, D w Load amount contributing to wind turbine generator system D p The amount of load contributed to the photovoltaic unit;
and/or, performing output risk correction on the VPP initial benefit allocation value, including:
calculating benefit distribution results based on the output risk by the following formula:
wherein: r is the actual risk, V ', V' i And (5) distributing results for benefits of the ith unit based on the output risk.
4. The method for distributing internal body benefits of a virtual power plant in a market transaction according to claim 1, wherein: in step 4, determining weights of cost, collaboration contribution rate and risk, including:
the weight vector W of cost, co-contribution rate and risk is denoted (W 1 ,w 2 ,w 3 ) The method comprises the steps of carrying out a first treatment on the surface of the The weights of the cost, the cooperation contribution rate and the risk are determined to be 1/3, and the weight vector W= [1/3,1/3 ]The importance of the cost, the contribution rate and the risk is equal.
5. The method for distributing internal body benefits of a virtual power plant engaged in a market transaction according to claim 4, wherein: in step 4, based on the determined cost, the cooperative contribution rate and the weight of the risk, and in combination with the cost-based benefit distribution result, the contribution rate-based benefit distribution result and the risk-based benefit distribution result, the comprehensive benefits of all the participants are calculated, including:
for each participant i, comprehensive benefit E i The calculation can be made by the following formula:
\[E i ＝w 1 ×V′ i +w 2 ×V i +w 3 ×V″′ i \]
wherein,
V' i is the cost-based benefit allocation result of participant i;
V″ i is the benefit distribution result of the participant i based on the contribution rate;
V″′ i is the benefit distribution result of participant i based on risks；
Comprehensive benefit value E i Reflects the overall benefit of participant i after three factors of cost, collaboration contribution rate and risk are considered, weight (w 1 ,w 2 ,w 3 ) Determining the relative importance of each factor in the comprehensive benefit;
the above steps are repeated to calculate their overall benefit for all participants.
6. The method for distributing internal body benefits of a virtual power plant in a market transaction according to claim 1, wherein: in step 4, an improved Shapley value and an improved Banzhaf value are calculated according to the comprehensive benefits of all participants, including:
The improved calculation formulas of the Shapley value and the Banzhaf value are as follows:
improved Shapley:
in this formula:
(φ′ i (v) A modified Shapley value representing participant i;
s is any subset of the participant set N except for participant \ (i\), which represents different combinations of units in the virtual power plant;
(v '(S & { i })) and (v' (S)) represent the combined benefit of the set combination with and without the inclusion of participant \ (i\), respectively;
improved Banzhaf value:
in this formula:
(β' i (v) A modified Banzhaf value representing participant \ (i\);
(S\) is any subset of the set of participants\N\except for participant\i\which represents different combinations of units in the virtual power plant;
(v' (S.
7. The method for distributing internal body benefits of a virtual power plant in a market transaction according to claim 1, wherein: in step 5, based on the improved Shapley value and the improved Banzhaf value, a allocation result based on the Shapley value and a allocation result based on the Banzhaf value are calculated, including:
based on modified Shapley values: allocating the benefit or the resource for each participant by using the improved Shapley value based on the benefit or the resource allocation of each participant in proportion to the improved Shapley value, and forming an allocation result based on the Shapley value;
Based on the modified Banzhaf value: allocating the benefit or the resource for each participant by using the improved Banzhaf value based on the benefit or the resource allocation of each participant in direct proportion to the improved Banzhaf value, and forming an allocation result based on the Banzhaf value;
in step 5, according to the allocation result based on the Shapley value and the allocation result based on the Banzhaf value, calculating the satisfaction degree of each benefit allocation result based on the satisfaction degree model, and selecting the benefit allocation result with the highest satisfaction degree, wherein the method comprises the following steps:
calculating satisfaction: for each participant, its satisfaction with the Shapley value-based and Banzhaf value-based allocation results was calculated using the following satisfaction model;
the satisfaction model is shown as the following formula:
wherein: m is M i Satisfaction of revenue distribution for principal i, r ”io "is the primary benefit distribution result of the main body i, the primary benefit distribution result of the main body i is the initial benefit distribution value of the VPP, r in The result is allocated for the benefit of the subject i;
selecting an optimal solution: all participants were compared for satisfaction with both allocation schemes, and the scheme with the highest overall satisfaction was selected as the final allocation scheme.
8. An internal body benefit distribution device for a virtual power plant to participate in a market transaction, the device comprising:
Model construction module: the method is used for constructing a daily-life and real-time electric power market transaction model;
the initial benefit distribution module: the method comprises the steps of obtaining a VPP initial benefit distribution value based on a day-ahead real-time electricity price model;
the secondary benefit distribution module: the method comprises the steps of carrying out cost correction, contribution rate correction and risk correction on the VPP initial benefit distribution value respectively to obtain a benefit distribution result based on cost, a benefit distribution result based on contribution rate and a benefit distribution result based on risk;
the improvement module: the comprehensive benefits of all participants are calculated by determining the weights of the cost, the cooperation contribution rate and the risk and combining the benefit distribution result based on the cost, the benefit distribution result based on the contribution rate and the benefit distribution result based on the risk based on the weights of the determined cost, the cooperation contribution rate and the risk; calculating an improved Shapley value and an improved Banzhaf value according to the comprehensive benefits of all participants;
satisfaction selecting module: the method is used for calculating a distribution result based on the Shapley value and a distribution result based on the Banzhaf value based on the improved Shapley value and the improved Banzhaf value; and respectively calculating the satisfaction degree of each benefit distribution result based on the satisfaction degree model according to the distribution result based on the Shapley value and the distribution result based on the Banzhaf value, and selecting the benefit distribution result with the highest satisfaction degree.
9. An internal main body benefit distribution device for a virtual power plant to participate in market trade is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor being operative according to the instructions to perform the steps of the method according to any one of claims 1 to 7.
10. Computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
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