CN111784451A - Distributed electric power multilateral transaction method and system based on multiple time scales - Google Patents

Distributed electric power multilateral transaction method and system based on multiple time scales Download PDF

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CN111784451A
CN111784451A CN202010606206.4A CN202010606206A CN111784451A CN 111784451 A CN111784451 A CN 111784451A CN 202010606206 A CN202010606206 A CN 202010606206A CN 111784451 A CN111784451 A CN 111784451A
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于韶源
杨胜春
耿建
李亚平
范洁
赵彤
王珂
刘建涛
周竞
郭晓蕊
朱克东
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China Electric Power Research Institute Co Ltd CEPRI
State Grid Jiangsu Electric Power Co Ltd
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China Electric Power Research Institute Co Ltd CEPRI
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Abstract

The invention discloses a distributed electric multilateral transaction method and a system based on multiple time scales, which comprises the following steps: collecting the power selling amount and quotation range data of the power selling user in multiple time periods, and the power purchasing amount and quotation range data of the power purchasing user in multiple time periods; inputting the acquired data into a pre-established multilateral transaction model considering multi-time scale user game, and solving the electricity price and the electric quantity of the distributed electric power transaction users to achieve transaction; the multilateral transaction model considering the multi-time scale user game comprises objective functions and constraint conditions of electricity selling users and electricity purchasing users determined according to different time scales. According to the invention, from the overall situation, the user can select a plurality of transaction objects according to different quotations at different time scales, and meanwhile, the user performs dynamic game evolution within the price range given by the two parties, so that the benefit optimization of all the users is realized, and the relative balance of the distributed power generation market is finally achieved.

Description

Distributed electric power multilateral transaction method and system based on multiple time scales
Technical Field
The invention belongs to the technical field of power markets, and particularly relates to a distributed power multilateral trading method based on multiple time scales.
Background
The basic elements of a game include participants, strategies and payments, wherein the participants refer to decision-making subjects, and if N persons participate in the game, the set of participants is represented by N ═ {1, 2.., N }; si＝{S1,S2,...SnDenotes the set of policies for all participants i (i ∈ N), s ═ s1,s2,...snRepresents the policy set of all participants; the payout is used to quantify the profit of the participant in the game, u ═ u { (u {)1,u2,...unRepresents the payment set of all participants. A typical game may be denoted G ═ N; s1,S2,...Sn；u1,u2,...un}. The game theory mainly comprises three kinds: cooperative gaming, non-cooperative gaming, and evolutionary gaming. In the cooperative game, the participant can form a union, and the participants can cooperate to play the game, but in the non-cooperative game, the strategies of the participant are individual behaviors. In the concept of evolutionary gaming, participants are not entirely rational. Participants have limited knowledge and do not have full knowledge of the rules and structure of the game. The limited rationality has a great influence on the decision and behavior of the participants. Participants gain policy through some information delivery mechanism by making an irrational choice. In the evolutionary game theory, a behavior subject is assumed to adopt a certain set behavior in a programmed way, and simulates a successful behavior and strategy, so that the successful behavior and strategy are continuously corrected and improved in the evolutionary process, and the more satisfactory benefit of the participating subject is obtained.
In the distributed transaction, the objective functions of the electricity purchasing users and the electricity selling users are contradictory, the lower the electricity purchasing price the electricity purchasing users want, the better the electricity selling price the electricity selling users want, and the user information is mastered limitedly, so the transaction process achieved by the two parties is really an evolved non-cooperative game process, the benefit balance of the two parties is difficult to achieve, and the stable operation of a power supply system is influenced.
Disclosure of Invention
The invention provides a multi-time scale-based distributed electric power multilateral trading method, which is used for matching distributed users to achieve trading, maximizing multi-party benefits, finally achieving the relative balance of a distributed power generation market and ensuring the stable operation of a power supply system.
In order to achieve the purpose, the invention adopts the following technical scheme:
a distributed electric multilateral trading method based on multiple time scales comprises the following steps,
collecting the power selling amount and quotation range data of the power selling user in multiple time periods, and the power purchasing amount and quotation range data of the power purchasing user in multiple time periods;
inputting the collected electric quantity sold and quoted range data of the electricity selling users in multiple time periods and the electric quantity purchased and quoted range data of the electricity purchasing users in multiple time periods into a pre-established multilateral transaction model considering the multi-time scale user game, and solving the electricity price and the electric quantity of the distributed electricity transaction users to achieve the transaction;
the multilateral transaction model considering the multi-time scale user game comprises objective functions and constraint conditions of electricity selling users and electricity purchasing users determined according to different time scales.
Further, the multilateral transaction model considering the multi-time scale user game comprises the following steps:
benefit function u (E) of electricity purchasing user iDi) Comprises the following steps:
Figure BDA0002561115620000021
wherein the time is divided into a plurality of time scales, denoted T, at one hour intervalsDi＝[t1,t2,...,tn]，ti∈TDi；EDiThe electricity demand of a power purchase user i is met; n isgThe users are a set of electricity selling users;
Figure BDA0002561115620000022
the proportion of the electric quantity obtained from different electricity selling users j to the total electric quantity requirement is calculated for each time scale;
Figure BDA0002561115620000023
is that the electricity purchasing user i is at tiThe time scale is compared with the bidding price of the electricity selling user j during the transaction;
the objective function of the electricity purchasing user is as follows:
Figure BDA0002561115620000024
the constraint conditions are as follows:
Figure BDA0002561115620000025
wherein p isbmax、pbminRespectively representing the upper limit and the lower limit of the electricity purchasing price set by the electricity purchasing user;
benefit function u (E) of electricity selling user jEj) Comprises the following steps:
Figure BDA0002561115620000026
wherein E isEjThe redundant electric quantity of the electricity selling user is; divided in one hour intervals, denoted TEj＝[t1,t2,...,tn]，tj∈TEj；ncThe method comprises the steps of (1) selecting a set of electricity purchasing users;
Figure BDA0002561115620000031
is that the electricity selling user j is at tjThe time scale and the competitive bidding price of the electricity purchasing user j during the transaction;
Figure BDA0002561115620000032
the electricity sold to the electricity purchasing user i for each time scale accounts for the proportion of the total sold electricity,
Figure BDA0002561115620000033
the objective function of the electricity selling user is as follows:
Figure BDA0002561115620000034
the constraint condition is
Figure BDA0002561115620000035
Wherein p issmax、psminRespectively showing the upper limit and the lower limit of the electricity selling price set by the electricity selling user.
Further, the multilateral transaction model considering the multi-time scale user game further comprises the following constraints:
(1) the transaction amount of each time period is equal to the smaller one of the electricity purchasing amount and the electricity selling amount, which is expressed by the formula (10),
Figure BDA0002561115620000036
(2) the transaction amount of each user does not exceed the requirement per time period, and is expressed as an equation (11) and an equation (12),
Figure BDA0002561115620000037
Figure BDA0002561115620000038
further, the step of solving the electricity price and the electricity quantity of the transaction completed by the distributed power transaction user specifically comprises the following steps:
firstly, converting multilateral transaction models and constraint conditions considering multi-time scale user gaming into standard forms of formulas (1) and (2):
Figure BDA0002561115620000039
Figure BDA0002561115620000041
f (X) represents an objective function set of all power selling users and power purchasing users, and phi (X) represents a set of constraint conditions;
in the transaction, the objective functions of the electricity selling user and the electricity purchasing user to be optimized are the objective functions min (u (E) respectively set for the electricity purchasing user and the electricity selling user to obtain high benefitDi) Max (u (E))Ej) Constraint conditions including price constraint and transaction amount constraint, standard forms of the formula (1) and the formula (2) are rewritten as shown in the formula (5) and the formula (6),
Figure BDA0002561115620000042
Figure BDA0002561115620000043
wherein the content of the first and second substances,
Figure BDA0002561115620000044
indicating that the purchase price is within the acceptance range of the electricity purchasing user, pbmin≤pbti,j≤pbmax，
Figure BDA0002561115620000045
The purchase price of the electricity is required to be within the acceptance range of the electricity selling users,
Figure BDA0002561115620000048
representing a constraint on the amount of the transaction during the course of the transaction.
Further, a set of target-idealized desired targets f corresponding to the objective function is set prior to solvingi *Each target corresponding to a weight coefficient of wiI ═ 1,2, …, k; setting a relaxation factor gamma, and f for distributed transactioni *Expected electricity sales revenue u for each trading user*(EEj) Or electricity purchase overhead u*(EDi) Weight coefficient w for each trading useriIs composed of
Figure BDA0002561115620000047
When the solution is carried out by the multi-objective coordination approach solving algorithm, the maximum value of the difference between the objective function and the function to be optimized is minimized and is expressed as an expression (13),
Figure BDA0002561115620000051
converting the multi-subject target problem to formula (14):
Figure BDA0002561115620000052
and solving the electricity price and the electricity quantity of the transaction of the distributed electricity transaction user.
Further, after solving the electricity price and the electricity quantity of the distributed electricity trading user to reach the trade, the method further comprises the following steps: and outputting a power rate and electric quantity result table of the transaction of the distributed electric power transaction user.
A multi-timescale-based distributed electric power multilateral trading system comprising a memory having stored therein a computer program operable on the processor, a processor which, when executed, implements the method steps of one multi-timescale-based distributed electric power multilateral trading method.
A multi-timescale-based distributed power multilateral trading system, comprising:
the data acquisition module is used for acquiring the electric quantity sold and the quotation range data of the electricity selling user in multiple time periods, and the electric quantity purchased and the quotation range data of the electricity purchasing user in multiple time periods;
the data processing module is used for inputting the collected electric quantity selling and quotation range data of the electric power selling users in multiple time periods and the collected electric quantity purchasing and quotation range data of the electric power purchasing users in multiple time periods into a pre-established multilateral transaction model considering the multi-time scale user game, and solving the electricity price and the electric quantity of the distributed electric power transaction users for achieving the transaction;
the multilateral transaction model considering the multi-time scale user game comprises objective functions and constraint conditions of electricity selling users and electricity purchasing users determined according to different time scales.
Further, after solving the electricity price and the electric quantity of the distributed electric power trading user for achieving the trading, the data processing module outputs an electricity price and electric quantity result table of the distributed electric power trading user for achieving the trading.
The invention has the beneficial effects that:
according to the multi-time scale-based distributed electric power multilateral transaction method, the main characteristics of distributed electric power transaction users are considered, the time characteristic of the transaction is considered, the multi-time scale-considered game method is established, and the multi-time scale-considered game method is more suitable for the application scene of matching transactions of the distributed users; in the distributed transaction, the electricity selling user and the electricity purchasing user both expect the maximum income, and certain benefit conflict exists.
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The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a diagram of a conventional bilateral transaction mechanism.
Fig. 2 is a schematic diagram of a multilateral transaction mechanism of a multi-time scale user game based on the multi-time scale distributed electric power multilateral transaction method of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The following detailed description is exemplary in nature and is intended to provide further details of the invention. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.
Example 1
A multi-time scale based distributed electric power multilateral trading method, see fig. 2, includes the following steps,
firstly, establishing a multilateral transaction model considering multi-time scale user game;
in the distributed power generation transaction mechanism, the user deals with the electric quantity, and the distributed power generation equipment is greatly influenced by time factors, so that the distributed power generation equipment has a time attribute, and the user can give different offers in different time periods; also, consider that a user's offer may not easily give an accurate value, but an acceptable price range.
The method comprises the following steps that a user issues transaction information in a plurality of time periods, the transaction information comprises electric quantity to be traded and quotation ranges, starting from the whole situation, the total income of all the time periods of each user is the maximum of an objective function, the user selects a plurality of transaction objects in different time scales according to different quotations, and meanwhile, the user performs dynamic game evolution in the price range given by two parties, so that the transaction electric price and the transaction electric quantity in each time period are finally agreed, the benefit optimization of all the users is realized, and the relative balance of a distributed power generation market is finally achieved;
secondly, acquiring the data of the electric quantity sold and the quotation range of the electricity selling user in multiple time periods, and the data of the electric quantity purchased and the quotation range of the electricity purchasing user in multiple time periods;
the production and consumption users have independent power generation equipment and have strong autonomy, self-profit and uncertainty in participating in market trading. Whether the user needs to buy the electricity or the user needs to sell the electricity, the price quoted in the transaction is influenced by various factors.
For users with electricity selling demands, firstly, analyzing and predicting own electricity utilization behaviors, electricity quantity to be sold and expected profit values according to the electricity generation cost of own photovoltaic equipment, comparing the transaction conditions of the previous transaction period or the same period of the previous day by combining the real-time electricity price of a large power grid, including the quotation behaviors of other electricity selling users and achieving the transaction electricity quantity, predicting the shortage electricity quantity quotation behaviors of the next period, and meanwhile, providing an optimal quotation range capable of achieving the transaction while ensuring own benefits based on the problems of market demand elasticity, user activity, self credit degree and own market influence;
for users with electricity purchasing requirements, a bidding range for minimizing the electricity consumption cost of the users is given by combining market demand elasticity, user liveness, self credibility and self market influence on the basis of real-time electricity price of a large power grid, historical quotation of electricity selling users, historical trading electricity price in the previous period or the same period in the previous day and expected electric quantity achievement of trading;
in the distributed transaction, a game mechanism is established, so that both parties can achieve the transaction while guaranteeing the income;
thirdly, inputting the data collected in the second step into the first step model, and solving the electricity price and the electric quantity of the distributed electric power trading users to reach the trading by adopting a multi-target coordination approach solving algorithm, comprising the following processes,
(1) considering that the user refers to the electricity price of the large power grid when making a quoted price, if the transaction can be achieved, higher profit must be obtained than the mode of 'remaining electricity surfing the internet' or purchasing electricity from the large power grid, and the transaction volume of one party must be completely achieved in each time period for all electricity purchasing users and all electricity selling users who participate in the transaction;
firstly, converting multilateral transaction models and constraint conditions considering multi-time scale user gaming into standard forms of formula (1) and formula (2),
Figure BDA0002561115620000081
Figure BDA0002561115620000082
(2) solving the form, F (X) represents the objective function set of all subjects, and phi (X) represents the set of constraint conditions;
F(x)＝[f1(X),f2(X),...,fk(X)](3)
Figure BDA0002561115620000083
the objective functions set by the two trading parties are contradictory, the lower the electricity purchasing price the better the electricity purchasing user wants to purchase the electricity, the higher the electricity selling price the better the electricity selling user wants to sell, so that the negotiation process of the two trading parties is actually the process that the two parties play games according to the benefit function of the two parties and the trading information given by the other party, and finally the games obtain the trading results meeting the benefit requirements of the various subjects. Therefore, the process can be regarded as a process of solving a final optimal non-inferior solution according to the contradictory objective functions of the two trading parties, and a multi-subject objective coordination approach solving algorithm is used for solving the final optimal non-inferior solution.
(3) The model to be solved is set for the electricity purchasing user and the electricity selling user respectively to obtain high benefit in the tradeSet objective function min (u (E)Di) Max (u (E))Ej) Constraint conditions comprise price constraint and transaction amount constraint, a main body objective function model to be solved and the constraint conditions are equation (5) and equation (6),
Figure BDA0002561115620000091
Figure BDA0002561115620000092
wherein the content of the first and second substances,
Figure BDA0002561115620000093
indicating that the purchase price is within the range of acceptance of the electricity purchasing user, i.e. pbmin≤pbti,j≤pbmax，
Figure BDA0002561115620000094
The electricity purchase price needs to be within the acceptance range of electricity selling users, that is
Figure BDA0002561115620000097
Representing a constraint on the amount of the transaction during the course of the transaction.
Example 2
Referring to fig. 2, the multi-time-scale-based distributed electric power multi-edge transaction method in embodiment 1 may further specifically be that, in the first step, a multi-edge transaction model considering a multi-time-scale user game is established, and the model is set as:
the users participating in the transaction are divided into electricity purchasing users according to electricity purchasing and selling (i ∈η)c) And electricity selling users (j ∈η)g). Setting the electricity utilization time of the users participating in the transaction as ti1～ti2Time to sell electricity is tj1～tj2；
Setting the electric quantity demand of the electricity purchasing user i as EDiIn kw.h, the electricity consumption time is tibegin～tiendTime is divided into a plurality of time scales, denoted T, at one hour intervalsDi＝[t1,t2,...,tn]，ti∈TDi. Here, for convenience, t is consideredibegin～tiendThe electricity purchasing quantity of the user can be divided into an integral number of time periods, the electricity purchasing quantity required by the user can be obtained from a plurality of electricity selling users in a plurality of time scales, and the proportion of the electricity quantity obtained from different electricity selling users j in each time scale to the total electricity quantity requirement is set to be αti,jIs provided with
Figure BDA0002561115620000096
The benefit function of the electricity purchasing user i is the formula (7),
Figure BDA0002561115620000101
wherein
Figure BDA0002561115620000102
Is that the electricity purchasing user i is at tiThe time scale is compared with the bidding price of the electricity selling user j during the transaction;
the electricity purchasing user aims to minimize the electricity purchasing cost, and thus can be expressed as equation (8),
Figure BDA0002561115620000103
the constraint condition is
Figure BDA0002561115620000104
Wherein p isbmax、pbminRespectively representing the upper limit and the lower limit of the acceptable electricity purchasing price set by the electricity purchasing user.
It is also preferable that, in the second step, when the multilateral transaction mechanism of the multi-time scale user game is set, the surplus electric quantity of the electricity selling user is set as EEjIn kw h, the time for selling electricity is tjbegin～tjendAlso divided at one hour intervals, denoted TEj＝[t1,t2,...,tn]，tj∈TEj. Here, for convenience, t is consideredjbegin～tjendCan be divided into an integral number ofA time period. The sold electric quantity can be sold to the electricity purchasing users in a plurality of time scales, and the proportion of the electric quantity sold to the electricity purchasing users i in each time scale to the total sold electric quantity is set as
Figure BDA0002561115620000105
It is obvious that
Figure BDA0002561115620000106
The benefit function of electricity selling user j is
Figure BDA0002561115620000107
Wherein
Figure BDA0002561115620000108
Is that the electricity selling user j is at tjThe time scale is related to the competitive bidding price of the electricity purchasing user j in the transaction.
The goal of the electricity selling user is to sell electricity with the greatest revenue, and therefore can be expressed as equation (9),
Figure BDA0002561115620000109
the constraint condition is
Figure BDA00025611156200001010
Wherein p issmax、psminRespectively representing the upper limit and the lower limit of the acceptable electricity selling price set by the electricity selling user.
More specifically, in the first step, when the multilateral transaction model considering the multi-time scale user game is established, the game process among the users participating in the distributed power generation market transaction is as follows:
firstly, one party selects a trading object and initiates a trade;
the user receiving the transaction request gives feedback according to the received transaction information including transaction electric quantity and electricity price and by combining the quotation range and the expected value given by the user;
the user receiving the feedback adjusts according to the feedback information or directly completes the transaction; the user can negotiate the game with a plurality of users for a plurality of times on the electric quantity, the electricity price and other targets;
and finally, one or more trading objects are determined, and the trading electric quantity and the price of each trading object are determined, so that market balance is achieved to a certain degree.
In the first step, when the multilateral transaction model considering the multi-time scale user game is established, the constraint conditions are as follows:
(1) the transaction amount of each time period is equal to the smaller one of the electricity purchasing amount and the electricity selling amount, which is expressed by the formula (10),
Figure BDA0002561115620000111
(2) the transaction amount of each user does not exceed the requirement per time period, and is expressed as an equation (11) and an equation (12),
Figure BDA0002561115620000112
Figure BDA0002561115620000113
specifically, in the third step, when the multi-target coordination approach solving algorithm is performed, before solving, a group of target value idealized expected targets f corresponding to the target function is seti *(i 1, 2.. k), each target corresponds to a weight coefficient wi(i 1, 2.. k), and a relaxation factor γ is set, and for distributed transactions, f isi *I.e. expected electricity sales revenue u for each trading user*(EEj) Or electricity purchase overhead u*(EDi) Weight coefficient w for each trading useriThe setting of (A) may be the same, or some rules may be designed to determine, where the weights are set to be consistent, and the weight of each objective function is
Figure BDA0002561115620000114
In the third step, when the multi-objective coordination approach solving algorithm is performed, the game multi-subject coordination approach method is to minimize the maximum value of the difference between the objective function and the function to be optimized, and is expressed as formula (13),
Figure BDA0002561115620000115
the multi-subject problem is transformed into equation (14),
Figure BDA0002561115620000121
the price and quantity of electricity achieved by both parties are solved.
The distributed electric power multilateral trading method based on the multiple time scales is started from the overall situation, the total income of all time periods of each user is the maximum of an objective function, the user can select a plurality of trading objects according to different quotations in different time scales, and meanwhile, the user carries out dynamic game evolution in the price range given by two parties, and finally the trading electricity price and the trading electric quantity in each time period are consistent, so that the benefit optimization of all the users is realized, and the relative balance of a distributed power generation market is finally achieved; the game model is solved by adopting a multi-target coordination approach algorithm.
In yet another embodiment of the present invention, there is also provided a multi-timescale-based distributed electric power multilateral trading system, including a memory, a processor, a computer program stored in the memory and executable on the processor, the processor implementing the method steps of one of the above-mentioned multi-timescale-based distributed electric power multilateral trading methods when executing the computer program.
In another embodiment of the present invention, there is also provided a multi-time scale-based distributed electric multilateral trading system, including:
the data acquisition module is used for acquiring the electric quantity sold and the quotation range data of the electricity selling user in multiple time periods, and the electric quantity purchased and the quotation range data of the electricity purchasing user in multiple time periods;
a data processing module for processing the data of the mobile phone,
inputting the collected electric quantity sold and quoted range data of the electricity selling users in multiple time periods and the electric quantity purchased and quoted range data of the electricity purchasing users in multiple time periods into a pre-established multilateral transaction model considering the multi-time scale user game, and solving the electricity price and the electric quantity of the distributed electricity transaction users to achieve the transaction;
the multilateral transaction model considering the multi-time scale user game comprises objective functions and constraint conditions of electricity selling users and electricity purchasing users determined according to different time scales.
As will be appreciated by one skilled in the art, 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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (10)

1. A distributed electric multilateral trading method based on multiple time scales is characterized by comprising the following steps,
collecting the power selling amount and quotation range data of the power selling user in multiple time periods, and the power purchasing amount and quotation range data of the power purchasing user in multiple time periods;
inputting the collected electric quantity sold and quoted range data of the electricity selling users in multiple time periods and the electric quantity purchased and quoted range data of the electricity purchasing users in multiple time periods into a pre-established multilateral transaction model considering the multi-time scale user game, and solving the electricity price and the electric quantity of the distributed electricity transaction users to achieve the transaction;
the multilateral transaction model considering the multi-time scale user game comprises objective functions and constraint conditions of electricity selling users and electricity purchasing users determined according to different time scales.
2. The multi-timescale-based distributed power multilateral transaction method of claim 1, wherein considering a multilateral transaction model for a multi-timescale user game comprises:
benefit function u (E) of electricity purchasing user iDi) Comprises the following steps:
Figure FDA0002561115610000011
wherein the time is divided into a plurality of time scales, denoted T, at one hour intervalsDi＝[t1,t2,...,tn]，ti∈TDi；EDiThe electricity demand of a power purchase user i is met; n isgThe users are a set of electricity selling users;
Figure FDA0002561115610000012
the proportion of the electric quantity obtained from different electricity selling users j to the total electric quantity requirement is calculated for each time scale;
Figure FDA0002561115610000013
is that the electricity purchasing user i is at tiThe time scale is compared with the bidding price of the electricity selling user j during the transaction;
the objective function of the electricity purchasing user is as follows:
Figure FDA0002561115610000014
the constraint conditions are as follows:
Figure FDA0002561115610000015
wherein p isbmax、pbminRespectively representing the upper limit and the lower limit of the electricity purchasing price set by the electricity purchasing user;
benefit function u (E) of electricity selling user jEj) Comprises the following steps:
Figure FDA0002561115610000016
wherein E isEjThe redundant electric quantity of the electricity selling user is; divided in one hour intervals, denoted TEj＝[t1,t2,...,tn]，tj∈TEj；ncThe method comprises the steps of (1) selecting a set of electricity purchasing users;
Figure FDA0002561115610000021
is that the electricity selling user j is at tjThe time scale and the competitive bidding price of the electricity purchasing user j during the transaction;
Figure FDA0002561115610000022
the electricity sold to the electricity purchasing user i for each time scale accounts for the proportion of the total sold electricity,
Figure FDA0002561115610000023
the objective function of the electricity selling user is as follows:
Figure FDA0002561115610000024
the constraint condition is
Figure FDA0002561115610000025
Wherein p issmax、psminRespectively showing the upper limit and the lower limit of the electricity selling price set by the electricity selling user.
3. The multi-timescale-based distributed power multilateral transaction method of claim 2, wherein the multilateral transaction model that considers multi-timescale user gaming further includes the following constraints:
(1) the transaction amount of each time period is equal to the smaller one of the electricity purchasing amount and the electricity selling amount, which is expressed by the formula (10),
Figure FDA0002561115610000026
(2) the transaction amount of each user does not exceed the requirement per time period, and is expressed as an equation (11) and an equation (12),
Figure FDA0002561115610000027
Figure FDA0002561115610000028
4. the multi-time scale-based distributed electric power multilateral transaction method according to claim 3, wherein the step of solving the electricity price and the amount of electricity for the distributed electric power transaction user to reach the transaction specifically comprises:
firstly, converting multilateral transaction models and constraint conditions considering multi-time scale user gaming into standard forms of formulas (1) and (2):
Figure FDA0002561115610000031
Figure FDA0002561115610000032
f (X) represents an objective function set of all power selling users and power purchasing users, and phi (X) represents a set of constraint conditions;
in the transaction, the objective functions of the electricity selling user and the electricity purchasing user to be optimized are the objective functions min (u (E) respectively set for the electricity purchasing user and the electricity selling user to obtain high benefitDi) Max (u (E))Ej) Constraint conditions including price constraint and transaction amount constraint, standard forms of the formula (1) and the formula (2) are rewritten as shown in the formula (5) and the formula (6),
Figure FDA0002561115610000033
Figure FDA0002561115610000034
wherein the content of the first and second substances,
Figure FDA0002561115610000035
indicating that the electricity purchasing price needs to be within the acceptance range of the electricity purchasing user,
Figure FDA0002561115610000036
Figure FDA0002561115610000037
the purchase price of the electricity is required to be within the acceptance range of the electricity selling users,
Figure FDA0002561115610000038
Figure FDA0002561115610000039
representing a constraint on the amount of the transaction during the course of the transaction.
5. The multi-timescale-based distributed power multilateral trading method of claim 4, wherein prior to solving, a set of target-idealized desired targets f corresponding to the objective function is seti *Each target corresponding to a weight coefficient of wiI ═ 1,2, …, k; setting a relaxation factor gamma, and f for distributed transactioni *Expected electricity sales revenue u for each trading user*(EEj) Or electricity purchase overhead u*(EDi) Weight coefficient w for each trading useriIs composed of
Figure FDA0002561115610000041
When the solution is carried out by the multi-objective coordination approach solving algorithm, the maximum value of the difference between the objective function and the function to be optimized is minimized and is expressed as an expression (13),
Figure FDA0002561115610000042
converting the multi-subject target problem to formula (14):
Figure FDA0002561115610000043
and solving the electricity price and the electricity quantity of the transaction of the distributed electricity transaction user.
6. The multi-timescale-based distributed power multilateral transaction method of claim 1, wherein after solving for the electricity price and amount at which the distributed power transaction user completes the transaction, further comprising:
and outputting a power rate and electric quantity result table of the transaction of the distributed electric power transaction user.
7. The multi-timescale-based distributed power multilateral transaction method of claim 1, wherein after solving for the electricity price and amount at which the distributed power transaction user completes the transaction, further comprising:
and guiding the distributed power trading users to trade according to the electricity price and the electricity quantity.
8. A multi-timescale-based distributed electric power multilateral transaction system, comprising a memory, a processor, a computer program stored in the memory and executable on the processor, when executing the computer program, implementing the method steps of a multi-timescale-based distributed electric power multilateral transaction method according to any one of claims 1 to 7.
9. A multi-timescale-based distributed electric multilateral transaction system, comprising:
the data acquisition module is used for acquiring the electric quantity sold and the quotation range data of the electricity selling user in multiple time periods, and the electric quantity purchased and the quotation range data of the electricity purchasing user in multiple time periods;
the data processing module is used for inputting the collected electric quantity selling and quotation range data of the electric power selling users in multiple time periods and the collected electric quantity purchasing and quotation range data of the electric power purchasing users in multiple time periods into a pre-established multilateral transaction model considering the multi-time scale user game, and solving the electricity price and the electric quantity of the distributed electric power transaction users for achieving the transaction;
the multilateral transaction model considering the multi-time scale user game comprises objective functions and constraint conditions of electricity selling users and electricity purchasing users determined according to different time scales.
10. The multi-time scale-based distributed electric power multilateral transaction system of claim 9, wherein the data processing module outputs a result table of the electricity price and the electric quantity of the transaction completed by the distributed electric power transaction user after solving the electricity price and the electric quantity of the transaction completed by the distributed electric power transaction user.
CN202010606206.4A 2020-06-29 2020-06-29 Distributed electric power multilateral transaction method and system based on multiple time scales Pending CN111784451A (en)

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Cited By (3)

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Publication number Priority date Publication date Assignee Title
CN113095909A (en) * 2021-04-23 2021-07-09 广东电网有限责任公司电力调度控制中心 Electric power market listing transaction method and device
CN113240311A (en) * 2021-05-27 2021-08-10 湖南大学 Multi-main-body distributed power supply electric energy transaction planning method considering power supply reliability
CN113887800A (en) * 2021-09-29 2022-01-04 西安峰频能源科技有限公司 Monthly or ten-day time period transaction auxiliary decision making method and system

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113095909A (en) * 2021-04-23 2021-07-09 广东电网有限责任公司电力调度控制中心 Electric power market listing transaction method and device
CN113095909B (en) * 2021-04-23 2023-05-26 广东电网有限责任公司电力调度控制中心 Electric power market listing transaction method and device
CN113240311A (en) * 2021-05-27 2021-08-10 湖南大学 Multi-main-body distributed power supply electric energy transaction planning method considering power supply reliability
CN113240311B (en) * 2021-05-27 2024-03-01 湖南大学 Multi-main-body distributed power supply electric energy transaction planning method considering power supply reliability
CN113887800A (en) * 2021-09-29 2022-01-04 西安峰频能源科技有限公司 Monthly or ten-day time period transaction auxiliary decision making method and system

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