A day-ahead real-time distributed energy trading method considering source-load uncertainty

Abstract

The present invention discloses a method for day-ahead real-time distributed electric energy trading taking into account the uncertainty of source and load, and relates to the field of terminal power market on the distribution network side. The present invention introduces blockchain technology, and proposes a trading method combining blockchain with a distributed trading model for the day-ahead and real-time two-stages, which can well solve the privacy and trust problems of both parties in the community energy Internet cluster electric energy trading. Then, an adjustable robust optimization method is adopted to formulate a day-ahead real-time distributed electric energy trading strategy for the community energy Internet cluster taking into account the uncertainty of renewable energy output and the network security constraints of the distribution network, which can effectively improve the overall economy, reduce unnecessary electric energy interaction with the distribution network, and improve the absorption capacity of renewable energy.

Description

Technical Field

[0001] The present invention relates to the field of terminal power market on the distribution network side, and more specifically, to a day-ahead real-time distributed power trading method taking into account source-load uncertainty. Background Art

[0002] As the scale of community energy Internet gradually expands, the proportion of renewable energy in community energy Internet is also increasing. The access of community energy Internet cluster system to distribution network will also have an adverse effect on the normal operation of distribution network. Therefore, in order to reduce the operating cost of community energy Internet cluster system, reduce the operating pressure of distribution network, promote the local consumption of renewable energy and improve the reliability of user electricity use, the research on distributed trading of community energy Internet cluster is of great significance.

[0003] Electric energy trading methods are mainly divided into centralized trading mode and distributed trading mode. In the traditional centralized trading mode, the central agency manages the user's account information and historical transaction records in general, and the transaction security is poor. Once the central agency is attacked, the data in the database will be difficult to recover. In addition, users participating in the transaction cannot know the transaction information of other users, so the establishment of a mutual trust market will be affected, and the traditional centralized trading model will be difficult to meet the needs of real-time traceability in the current big data era. The existence of the central agency requires the employment of a large number of manpower, which leads to increased operating costs and reduced operating efficiency, and unreasonable trading strategies will have an adverse impact on the effective use of renewable energy. Different from the traditional centralized trading model, the distributed trading model has the characteristics of transparent information, high decision-making efficiency, low operating costs, and simple trading rules, which meets the deep needs of the community energy Internet cluster system for the trading platform. However, the distributed trading model lacks supervision in the decision-making process, and there are many problems in data tampering, historical traceability, and subject trust. With the rapid development of energy Internet and the deepening of power market system reform, the community energy Internet cluster power trading that integrates production and sales has put forward higher technical requirements for promoting the local consumption of renewable energy and improving the safety and stability of distribution network operation. The current community energy Internet cluster power trading technology still has shortcomings. The shortcomings are as follows: First, community energy Internet power trading has the characteristics of small transaction volume, frequent transaction times, and massive information data. There are problems such as high maintenance cost, reduced transaction efficiency, and increased security risks. Secondly, power trading is different from ordinary commodity trading. Power trading must meet certain physical laws. Current research does not fully consider the network security constraints in the power trading process. Finally, in distributed power trading, due to the lack of supervision by central institutions and the uncertainty of renewable energy output, it may lead to more serious defaults due to individuals pursuing their own interests. Summary of the invention

[0004] The technical problem solved by the present invention is the deficiency of the existing community energy Internet cluster electricity trading. The purpose of the present invention is to provide a day-ahead real-time distributed electricity trading method taking into account the uncertainty of source and load. The present invention introduces blockchain technology and proposes a trading method combining blockchain and distributed trading model for the day-ahead and real-time stages, which can well solve the privacy and trust issues of both parties in the community energy Internet cluster electricity trading. Then, an adjustable robust optimization method is adopted to formulate a day-ahead real-time distributed electricity trading strategy for the community energy Internet cluster taking into account the uncertainty of renewable energy output and the network security constraints of the distribution network, which can effectively improve the overall economy, reduce unnecessary electricity interaction with the distribution network, and improve the absorption capacity of renewable energy.

[0005] The above technical objectives of the present invention are achieved through the following technical solutions:

[0006] A method for day-ahead real-time distributed electric energy trading taking into account source-load uncertainty comprises the following steps:

[0007] A two-stage robust bidding model is used to determine the bidding strategy of the community energy Internet. A non-cooperative game model of the bidding strategy is constructed with the minimum operating cost as the goal. A community energy Internet cluster game scheduling transaction model is constructed based on the robust bidding model and the non-cooperative game model.

[0008] Formulate a trading strategy according to the game scheduling trading model, update the trading strategy, obtain the day-ahead trading strategy, perform network security constraint verification on the day-ahead trading strategy to obtain the optimal day-ahead trading strategy, and perform transaction settlement on the day-ahead trading strategy based on the smart contract of the smart meter;

[0009] Based on the continuous double auction bidding mechanism, the electric energy transaction process between buyers and sellers is obtained, and the electric energy transaction process is adjusted by adaptive aggressive value bidding strategy to obtain the optimal bid;

[0010] Based on the smart contract in the smart meter, the deviation of electricity volume in the real-time stage of electricity transaction is corrected to obtain the final settlement and transfer of electricity transaction.

[0011] The present invention takes into account the lack of supervision in the decision-making process of existing power trading methods, which will cause problems in data tampering and historical tracing, thereby affecting the trust of trading participants. Therefore, the present invention introduces blockchain technology and proposes a trading method combining blockchain and distributed trading model for the two stages of day-ahead and real-time, which can well solve the privacy and trust issues of both parties in the power trading of community energy Internet clusters, and then adopts an adjustable robust optimization method to formulate a community energy Internet cluster day-ahead-real-time distributed power trading strategy that takes into account the uncertainty of renewable energy output and the network security constraints of the distribution network, which can effectively improve the overall economy, reduce unnecessary power interaction with the distribution network, and improve the absorption capacity of renewable energy.

[0012] Furthermore, the specific steps of constructing the community energy Internet cluster game scheduling transaction model are as follows:

[0013] The first stage of the robust bidding model constructs bidding constraints to obtain the day-ahead market bidding strategy for the community energy internet;

[0014] The second stage of the robust bidding model builds a max-min optimization model to optimize the day-ahead market bidding strategy and formulate a bidding strategy that can cope with the uncertainty of renewable energy output;

[0015] Constructing a non-cooperative game model according to the bidding strategy and the minimum operating cost, and obtaining the optimal bidding strategy according to the non-cooperative game model;

[0016] According to the optimal bidding strategy, the strategy set of the community energy Internet cluster system is obtained, and the game scheduling transaction model is constructed with the decision-making plan and the strategy set. According to the game scheduling transaction model, the optimal bidding plan is obtained.

[0017] Furthermore, the specific steps of the non-cooperative game model to obtain the optimal bidding strategy are as follows:

[0018] Step S11, before the transaction, each community energy internet realizes the openness and transparency of transaction information on the blockchain platform;

[0019] Step S12, each community energy internet formulates a corresponding bidding strategy based on the historical bidding strategies of other networks;

[0020] Step S13, broadcasting the latest bidding strategy through smart meters, and the rest of the community energy internets re-formulate the optimal bidding strategy;

[0021] Step S14, return to step S12, and repeat the iteration until the optimal Nash equilibrium solution is reached, that is, the optimal bidding strategy is obtained.

[0022] Furthermore, the specific steps for transaction settlement of the day-ahead trading strategy are as follows:

[0023] Step S21, obtaining the first round of trading strategy according to the game scheduling trading model;

[0024] Step S22, updating the first round of trading strategy to obtain the day-ahead trading strategy, and generating a new sub-blockchain according to the day-ahead trading strategy as an input parameter for the second round of trading strategy;

[0025] Step S23, determining whether the day-ahead transaction strategy is the optimal bidding strategy, if so, terminating the iteration, otherwise, returning to step S21 and executing again;

[0026] Step S24, after executing the day-ahead trading strategy obtained in the third stage, perform network security constraint verification, and perform security verification according to the day-ahead trading strategy of each community energy Internet; if passed, the final day-ahead trading strategy is obtained; if not passed, constraints are added to the sub-problem for the lines that do not meet the security constraints, and step S21 is re-executed;

[0027] Step S25, all day-ahead transaction strategies in the community energy Internet cluster system are written into the main blockchain, and then the smart meters within each community energy Internet perform transaction settlement according to the day-ahead transaction strategies.

[0028] Furthermore, the constraints for safety constraint checking are: Among them, Φ li is the element in the lth row and ith column of the PTDF matrix, ΔP i is the power change of node i, is the indicator coefficient of the node type, is the real part, P i is the power value of node i, V i is the node voltage of node i, is the conjugate value of the node voltage at node i, is the branch transmission capacity margin, is the node voltage offset margin.

[0029] Furthermore, the specific steps of the process of obtaining the electric energy transaction matching between the buyer and the seller based on the continuous double auction mechanism are as follows:

[0030] Step S31: The community energy internet formulates the initial bid for the continuous two-way auction mechanism based on its own renewable energy output and load power consumption. When the community energy internet is the electricity seller, its initial bid is When the community energy internet is the electricity buyer, its initial bid is Among them, α t,res represents the power generation of the community energy Internet in time period t, α t,loadrepresents the load power consumption of the community energy Internet in time period t, λ0(t) represents the purchase price of the distribution network in time period t, and λ grid (t) represents the price at which the community energy Internet purchases electricity from the distribution grid in period t, and β represents the user preference factor;

[0031] Step S32: after receiving valid quotations from both the buyer and seller, the sellers will be reordered in ascending order of quotations, and the buyers will be reordered in descending order of quotations;

[0032] Step S33, compare the lowest bid among the electricity sellers within time period t with the highest bid among the electricity buyers. If the two can meet, a round of transaction is completed, otherwise the two parties will enter the next round of transaction until the buyer's best bid is lower than the seller's best bid.

[0033] Furthermore, when the seller's electricity price is higher than the buyer's electricity price, both parties need to adjust their quotations to improve the success rate and efficiency of transaction matching. The calculation formula of the adaptive aggressiveness value is: Among them, γ represents the willingness factor of community energy Internet to participate in transactions, and ω represents the market price fluctuation influencing factor.

[0034] Furthermore, the specific steps for obtaining the final settlement and transfer of electric energy transactions are as follows:

[0035] Step S41, each community energy internet participating in the electric energy transaction formulates its electric energy transaction plan for the current period according to the deviation data of the prediction result of its smart meter for the current period, and encrypts it in the form of a randomly generated string, and uses the hash algorithm in the blockchain technology to seal the encrypted transaction plan and publish it to the smart contract to prepare for transaction matching;

[0036] Step S42: Each entity participating in the electric energy transaction needs to disclose its real quotation and encrypted string to other entities in a timely manner within a certain period of time. The smart contract will automatically perform a hash algorithm to determine whether the result obtained after the unsealing is the same as the real quotation. If they are not the same, the quotation will be judged as an invalid quotation. If they are the same, the quotation will be regarded as a valid quotation, and the transaction parties will enter the next stage of smart contract execution. Finally, if the real quotations of all entities have been completely decrypted and disclosed, this stage will be terminated and the next stage of smart contract execution will be entered.

[0037] Step S43, collecting the power trading plans formulated by all entities according to the continuous double auction mechanism, sorting the bids of buyers and sellers, and matching the transactions according to the best bids of buyers and sellers;

[0038] Step S44, using the power transmission distribution factor and the voltage sensitivity factor to perform dynamic security verification on the matched transaction, and obtain the successfully matched electric energy transaction result;

[0039] Step S45: When the community energy internet successfully sells or buys all the electricity required for the transaction or reaches the preset transaction round limit, all matching results that are deemed valid are confirmed as the final transaction results. The smart meter transmits electricity according to the valid transaction results and promptly feeds back the transaction information to the smart contract. The smart contract settles and transfers the transaction according to the feedback transaction information.

[0040] Furthermore, if the dynamic security check passes, the transaction is matched successfully. If the check fails, the matchmaking is resolved and the process returns to the continuous two-way auction stage to obtain a new electricity transaction process.

[0041] Furthermore, due to network security constraints and the imbalance in the amount of electricity bought and sold, some community energy Internets may be unable to purchase the required electricity or may still have surplus electricity to be sold. The entities that still need to purchase electricity will be supplemented by standby units, and the surplus electricity will be purchased by the distribution network at the on-grid electricity price.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. The present invention takes into account the deviation in formulating the day-ahead trading strategy caused by the uncertainty of actual renewable energy output, introduces adjustable robust theory and non-cooperative game method, proposes a community energy Internet robust game scheduling model, and solves the optimal day-ahead trading strategy that can improve the overall economy of the community energy Internet cluster system and effectively deal with the uncertainty of renewable energy.

[0044] 2. In response to the current problems that the two parties to the transaction cannot adjust their quotations in time according to market fluctuations and the transaction market mechanism is not flexible enough, the present invention proposes an improved continuous two-way auction transaction mechanism, which can effectively protect the vested interests of both parties to the transaction, improve the success rate and efficiency of transaction matching, dynamically adjust prices according to market conditions, and has better adaptability to community energy Internet cluster power transactions.

[0045] 3. The present invention aims at the problems of high security risks, high data maintenance and storage costs, and low transparency of the traditional centralized power trading model, and the characteristics of small transaction volume and frequent transaction times of community energy Internet cluster power trading, and proposes a distributed power trading model supported by blockchain as the underlying technology. By utilizing the decentralization of blockchain technology, the openness and transparency of data, the non-tamperability and the automatic execution of smart contracts, the openness, transparency and intelligence of community energy Internet cluster power trading are realized, the cost of purchasing and selling electricity is reduced, the frequency of power interaction between community energy Internet and distribution network is reduced, and the local consumption of renewable energy is promoted, so that the configuration of renewable energy output on the distribution network side is optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0047] Figure 1 A flow chart of a method provided by an embodiment of the present invention;

[0048] Figure 2 An energy trading game model for a community energy internet cluster system provided by an embodiment of the present invention;

[0049] Figure 3 A flow chart of solving the energy trading game model provided by an embodiment of the present invention;

[0050] Figure 4 Provide a distributed transaction architecture for a community energy internet cluster system for embodiments of the present invention;

[0051] Figure 5 A continuous double auction mechanism matching process provided by an embodiment of the present invention;

[0052] Figure 6 A real-time electric energy trading process based on smart contracts is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0054] It should be noted that when a component is referred to as being "fixed to" or "disposed on" another component, it can be directly on the other component or indirectly on the other component. When a component is referred to as being "connected to" another component, it can be directly or indirectly connected to the other component.

[0055] It should be understood that the orientation or position relationship indicated by terms such as "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0056] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0057] Example

[0058] The technical problems solved by the embodiments of the present invention include the following four points:

[0059] 1. When the community energy Internet cluster system conducts electricity trading, each community energy Internet will play different roles (producer and consumer), the trading method will be more flexible, and the market competition will be more intense. There will be complex interest interactions between community energy Internets. How to reduce the amount of electricity traded with the distribution network, promote the consumption of renewable energy, and reduce the operating costs of community energy Internet by formulating the optimal day-ahead scheduling trading strategy is one of the technical problems that the proposal of this invention intends to solve.

[0060] 2. The distributed transaction model lacks supervision in the decision-making process, and there are many problems in data tampering, historical tracing and subject trust. Therefore, how to further strengthen the management ability of transaction information on the basis of ensuring transaction performance is one of the technical problems that the proposal of this invention intends to solve.

[0061] 3. Renewable energy generation has the natural properties of randomness and intermittency, and there are certain errors in the output and load forecasts of the community energy Internet. In order to promote the local consumption of renewable energy and reduce the interaction between the community energy Internet and the distribution network, how to correct the power deviation in the real-time stage is one of the technical problems that the proposal of this invention intends to solve.

[0062] 4. In the real-time phase of power trading in the community energy Internet cluster, each individual needs to respond quickly to its power trading request to complete the correction of the deviation before the next period. How to improve the response speed of power trading in the real-time phase and improve the efficiency and success rate of power trading matching under the condition of meeting network security constraints is one of the technical problems that the proposal of this invention intends to solve.

[0063] Based on this, this embodiment provides a day-ahead real-time distributed energy trading method taking into account source-load uncertainty, such as Figure 1 As shown, the method comprises the following steps:

[0064] Step S1, using a two-stage robust bidding model to determine the bidding strategy of the community energy Internet, constructing a non-cooperative game model of the bidding strategy with the minimum operating cost as the goal, and constructing a community energy Internet cluster game scheduling transaction model based on the robust bidding model and the non-cooperative game model;

[0065] Step S2, formulate a trading strategy according to the game scheduling trading model, update the trading strategy, obtain the day-ahead trading strategy, perform network security constraint verification on the day-ahead trading strategy to obtain the optimal day-ahead trading strategy, and perform transaction settlement on the day-ahead trading strategy based on the smart contract of the smart meter;

[0066] Step S3, obtaining the electric energy transaction process between the buyer and the seller based on the continuous double auction quotation mechanism, and adjusting the electric energy transaction process by adaptively adjusting the aggressive value quotation strategy to obtain the optimal quotation;

[0067] Step S4, based on the smart contract in the smart meter, the deviation of the electric energy transaction in the real-time stage is corrected to obtain the final settlement and transfer of the electric energy transaction.

[0068] The present invention is to solve the four technical problems mentioned:

[0069] In step S1, in order to solve the technical problem 1, a day-ahead game scheduling and trading model for the community energy Internet cluster system based on adjustable robust theory and non-cooperative game framework is proposed.

[0070] Step S2 is to solve the technical problem 2 and propose a community energy Internet distributed transaction method based on smart contracts.

[0071] Step S3 is to solve the technical problem 3 and propose a community energy Internet cluster electricity trading strategy based on a continuous two-way auction mechanism.

[0072] Step S4 is to solve the technical problem 4, and propose a real-time distributed power trading method based on smart contract to correct the prediction deviation. The following embodiments are used to specifically illustrate how the above four steps solve the corresponding technical problems.

[0073] Preferably, the specific steps of constructing the community energy Internet cluster game scheduling transaction model are as follows:

[0074] The first stage of the robust bidding model constructs bidding constraints to obtain the day-ahead market bidding strategy for the community energy internet;

[0075] The second stage of the robust bidding model builds a max-min optimization model to optimize the day-ahead market bidding strategy and formulate a bidding strategy that can cope with the uncertainty of renewable energy output;

[0076] Construct a non-cooperative game model based on the bidding strategy and minimum operating cost, and obtain the optimal bidding strategy based on the non-cooperative game model;

[0077] According to the optimal bidding strategy, the strategy set of the community energy Internet cluster system is obtained, and the game scheduling transaction model is constructed with the decision-making plan and the strategy set. According to the game scheduling transaction model, the optimal bidding plan is obtained.

[0078] Specifically, there are such electricity trading rules in the electricity trading process, as follows: the maximum and minimum bidding electricity prices obtained by the sales network game should be lower than the electricity purchase price from the distribution network and higher than the electricity sale price to the distribution network; in order to minimize the operating cost, the purchasing network trades with the sales network in order from low to high transaction prices until the electricity purchase demand is met; the remaining or insufficient electricity after the internal transaction of the community energy Internet cluster system is supplemented by the distribution network.

[0079] According to the constraints and objective function of the two-stage adjustable robust bidding model, the day-ahead market bidding strategy is determined and optimized. The steps are as follows:

[0080] Taking minimizing the operation cost of community energy Internet as the optimization goal, a day-ahead market bidding strategy {σ it ,κ it}And optimize the decision-making plan. The determination of variables in this stage does not take into account the influence of uncertain parameters.

[0081] x=(σ t ,κ t ,P MT (t),U MT (t),P GB (t),U GB (t),P EB (t),U EB (t),

[0082]

[0083] The first stage is as follows: since the final transaction volume and electricity price of the community energy Internet in the trading market will be affected by the bidding prices and volumes of other networks, and the power-purchasing community energy Internet purchases electricity in order of price until its own load demand is met, the bidding prices of the remaining networks can be expressed as The corresponding bidding power is expressed as Therefore, the bidding constraints of community energy Internet in the trading market can be expressed as follows.

[0084]

[0085] In the formula, S is the total amount of electricity purchased by the energy internet in each community in the region at time t; nt is an auxiliary variable introduced, which is a binary variable. 1t +S 2t +…+S nt ≤1 makes the bidding electricity price and electricity value of the community energy Internet at time t corresponding and unique.

[0086] The power balance constraint is

[0087]

[0088] The interactive power constraint of the community energy internet is

[0089]

[0090] Where: The maximum power of the community energy Internet interacting with other networks; and They are respectively the electricity purchasing and selling status of the community energy Internet at time t.

[0091] The second stage is as follows: after solving the decision variables in the first stage, a max-min optimization model is constructed. The outer max solves the worst renewable energy output scenario, and the inner min optimizes the control plan of the decision variables under the worst renewable energy output scenario, and formulates the optimal strategy to cope with the uncertainty of renewable energy output.

[0092]

[0093] Since it is impossible to know the actual output of renewable energy on the dispatch day, the control quantity in this stage is the simulated control quantity under the worst renewable energy output scenario and is not used as an actual dispatch plan.

[0094] The power balance constraint is:

[0095]

[0096] The output control constraint of renewable energy units is

[0097]

[0098] Where: is an uncertain variable.

[0099] Preferably, the specific steps of the non-cooperative game model to obtain the optimal bidding strategy are as follows:

[0100] Step S11, before the transaction, each community energy internet realizes the openness and transparency of transaction information on the blockchain platform;

[0101] Step S12, each community energy internet formulates a corresponding bidding strategy based on the historical bidding strategies of other networks;

[0102] Step S13, broadcasting the latest bidding strategy through smart meters, and the rest of the community energy internets re-formulate the optimal bidding strategy;

[0103] Step S14, return to step S12, and repeat the iteration until the optimal Nash equilibrium solution is reached, that is, the optimal bidding strategy is obtained.

[0104] Specifically, the bidding strategy is decided with the minimum operating cost of the community energy Internet as the goal, and a non-cooperative game model of the community energy Internet cluster system is established to resolve the conflicts of interest between different entities:

[0105] Z=(G1,G2,…,G n ; F1, F2, …, F n ),

[0106] Where: G i (i=1,2,…,n) is the bidding strategy of the i-th community energy internet; F i (i=1,2,…,n) is the operating cost of the i-th community energy Internet.

[0107] The game players are community energy internets with surplus electricity; the game strategy is the bidding strategy G of each community energy internet with surplus electricity, including the bidding electricity price σ t and bidding power κ t The game goal is to minimize the total operating cost F, including the operating cost of the controllable units, the cost of power purchase and sale on the distribution network, and the bidding income. The optimal Nash equilibrium solution of the non-cooperative game model of power trading in the community energy Internet cluster system Should meet in It represents the optimal Nash equilibrium solution of the other community energy Internets except community energy Internet i.

[0108] like Figure 2 As shown, Figure 2 The energy trading game model of the community energy Internet cluster system is constructed based on the non-cooperative game model and the robust bidding model in the above embodiment to build a community energy Internet cluster game scheduling trading model, and solve the game scheduling trading model to obtain the optimal bidding plan. The specific steps are as follows:

[0109] In the non-cooperative game model of the community energy Internet cluster system, each community energy Internet participates in the game as an individual and needs to consider the bidding information of competitors and make decisions. When each community energy Internet reaches the individual relatively optimal decision under the decision scheme given by other networks, the game reaches equilibrium. The model solution process is as follows: Figure 3 shown.

[0110] Assume Q = (q1, q2, ..., q i ) is the strategy set of the community energy Internet cluster system, then Q * The necessary and sufficient condition for the game equilibrium solution is: for each decision plan q of each game participant i , both have:

[0111] W i (Q * ||q i )≤W i (Q * ),

[0112] Where: Q * ||q i The strategy for community energy internet i is changed, and the strategies for other community energy internets remain unchanged.

[0113] Assume that the bidding solution set of the game participants in the community energy Internet cluster system after the nth round of game is Q n =(q n,1 ,q n,2 ,…,q n,i ), then the bidding plan after the n+1th round of game is Q n+1 =(q n+1,1 ,q n+1,2 ,…,q n+1,i ),

[0114]

[0115] Where: q n,i and q n+1,i are the decision results of the nth and n+1th rounds of game respectively; under the premise that the bidding strategies of other community energy internet remain unchanged, The optimal bidding solution is obtained by solving the two-stage adjustable game bidding model for the community energy Internet.

[0116] Preferably, the specific steps for performing transaction settlement on the day-ahead transaction strategy are as follows:

[0117] Step S21, obtaining the first round of trading strategy according to the game scheduling trading model;

[0118] Step S22, updating the first round of trading strategy to obtain the day-ahead trading strategy, and generating a new sub-blockchain according to the day-ahead trading strategy as an input parameter for the second round of trading strategy;

[0119] Step S23, determining whether the day-ahead transaction strategy is the optimal bidding strategy, if so, terminating the iteration, otherwise, returning to step S21 and executing again;

[0120] Step S24, after executing the day-ahead trading strategy obtained in the third stage, perform network security constraint verification, and perform security verification according to the day-ahead trading strategy of each community energy Internet; if passed, the final day-ahead trading strategy is obtained; if not passed, constraints are added to the sub-problem for the lines that do not meet the security constraints, and step S21 is re-executed;

[0121] Step S25, all day-ahead transaction strategies in the community energy Internet cluster system are written into the main blockchain, and then the smart meters within each community energy Internet perform transaction settlement according to the day-ahead transaction strategies.

[0122] Specifically, Figure 4 As shown, Figure 4 For the distributed trading architecture of the community energy Internet cluster system, in the distributed computing stage, the day-ahead game scheduling trading model of the community energy Internet cluster system based on the adjustable robust theory and non-cooperative game framework is constructed, and the trading strategy is formulated to realize the direct trading of electricity. The transaction step is 1 hour, and the execution of all day-ahead smart contracts should be completed before 0:00 on the same day.

[0123] First, the community energy internet obtains the previous day's day-ahead trading strategy from the main blockchain as the initial input data for this round of distributed computing. Secondly, combined with the forecast value of renewable energy output in the region, the first round of game quotation strategy is solved based on the established adjustable robust game trading model. Finally, the power sales and electricity prices in the day-ahead trading plan of the community energy internet are sent to the cluster system through encrypted broadcast. Since only the power sales and electricity prices are broadcast, the risk of internal privacy information such as the model of the community energy internet equipment and electricity consumption characteristics can be effectively reduced.

[0124] In the trading strategy update phase, the community energy internet updates the trading strategies for all periods of the first round by referring to the day-ahead trading strategies formulated by other community energy internets. Next, the updated day-ahead trading strategies are integrated to generate new sub-blockchains, which are then used as input parameters for solving the second round of trading strategies.

[0125] In the equilibrium solution judgment stage, it is determined whether the day-ahead trading strategy obtained in the previous stage is the required Nash equilibrium solution. If so, the iteration is terminated; otherwise, it returns to the distribution operation stage and executes again.

[0126] In the packaging and settlement phase, after passing the security check, all day-ahead trading strategies in the community energy internet cluster system will be written into the main blockchain, and then the smart meters inside each community energy internet will prepare for charging and discharging power according to the day-ahead trading strategy smart contract. Finally, the smart contract will conduct transaction settlement based on the information fed back.

[0127] Preferably, the constraint conditions for safety constraint checking are Among them, Φ li is the element in the lth row and ith column of the PTDF matrix, ΔP i is the power change of node i, is the indicator coefficient of the node type, is the real part, P i is the power value of node i, V i is the node voltage of node i, is the conjugate value of the node voltage at node i, is the branch transmission capacity margin, is the node voltage offset margin.

[0128] Specifically, It is the indicator coefficient of the node type. If it is a power purchasing node, it takes -1, and if it is a power selling node, it takes 1.

[0129] Preferably, the specific steps of obtaining the electric energy transaction matching process between the buyer and the seller based on the continuous double auction mechanism are as follows:

[0130] Step S31: The community energy internet formulates the initial bid for the continuous two-way auction mechanism based on its own renewable energy output and load power consumption. When the community energy internet is the electricity seller, its initial bid is When the community energy internet is the electricity buyer, its initial bid is Among them, α t,res represents the power generation of the community energy Internet in time period t, α t,load represents the load power consumption of the community energy Internet in time period t, λ0(t) represents the purchase price of the distribution network in time period t, and λ grid (t) represents the price at which the community energy Internet purchases electricity from the distribution grid in period t, and β represents the user preference factor;

[0131] Step S32: after receiving valid quotations from both the buyer and seller, the sellers will be reordered in ascending order of quotations, and the buyers will be reordered in descending order of quotations;

[0132] Step S33, compare the lowest bid among the electricity sellers within time period t with the highest bid among the electricity buyers. If the two can meet, a round of transaction is completed, otherwise the two parties will enter the next round of transaction until the buyer's best bid is lower than the seller's best bid.

[0133] Specifically, in the real-time stage of community energy Internet cluster electricity trading, when some community energy Internets still have surplus electricity due to their own output and load forecast deviations, they act as sellers. Conversely, when there is a shortage of electricity, they act as buyers. In the electricity market, individuals often exist in a many-to-many form. The two parties to the transaction can submit their demand for electricity and related quotations at any time during the designated trading period. Once the prices of both parties can match, the electricity transaction is completed immediately. Under this electricity market structure, the continuous two-way auction mechanism can quickly and effectively complete the matching transaction between buyers and sellers while ensuring that the bidding between buyers and sellers is relatively fair, thereby ensuring the interests of all participating individuals. The electricity transaction matching process between buyers and sellers in the community energy Internet under the continuous two-way auction mechanism is as follows: Figure 5 shown.

[0134] In the initial quotation stage, the community energy internet formulates the initial quotation of the continuous two-way auction mechanism based on its own renewable energy output and load power consumption. After the initial quotation is completed, it enters the quotation sorting stage for both parties of the transaction. The sellers will be re-sorted in the order of increasing quotations, and the buyers will be re-sorted in the order of decreasing quotations. Finally, it enters the transaction matching stage to compare and analyze the lowest quotation of the sellers and the highest quotation of the buyers during the period. If the two can meet, the transaction will be matched between the buyer and the seller. The actual transaction price is the average of the two prices. At this time, a round of transactions is completed. Otherwise, the two parties will enter the next round of transactions until the buyer's best quotation is lower than the seller's best quotation.

[0135] Preferably, when the seller's electricity price is higher than the buyer's electricity price, both parties need to adjust their quotations to improve the success rate and efficiency of transaction matching. The calculation formula of the adaptive aggressiveness value is: Among them, γ represents the willingness factor of community energy Internet to participate in transactions, and ω represents the market price fluctuation influencing factor.

[0136] Specifically, in the price adjustment stage, all buyers and sellers entering the next round of transactions need to add or subtract a value based on the previous round of quotations so that the prices of both parties gradually converge. Therefore, the use of an adaptive aggressive value adjustment strategy can accurately reflect the intensity of the willingness of each entity to participate in market transaction competition, adjust prices more flexibly, and speed up the efficiency of successful transaction matching.

[0137] For the adaptive aggressive value bidding strategy, r∈[-1,1], the closer its value is to 1, the stronger the willingness of the community energy Internet to participate in transactions, and the higher the success rate of transaction matching; on the contrary, the closer r is to -1, the more negative the willingness of the community energy Internet to participate in transactions, and the success rate of matching decreases, but higher benefits can be obtained after successful matching. ω is the market price fluctuation influencing factor, which can accurately feedback the changes in market information to the community energy Internet, and can be calculated using the historical transaction electricity prices stored on the blockchain. The calculation formula is as follows,

[0138]

[0139] Where: δ is the normalized value of the standard deviation of the transaction price in the previous n rounds; ρ∈(0,1) is the adaptive learning speed; λ l is the transaction price in the first round; λ' is the equilibrium price of the first n rounds of transactions, and the calculation formula is shown in the formula; ω'(δ) can find the optimal ω(n+1) through market price change information, and its calculation formula is as follows,

[0140]

[0141] Where: max and ω min ,δ max and δ min are the upper and lower limits of ω and δ respectively.

[0142]

[0143] Where: ε l is the weight of the first transaction, which can be solved according to the order relationship analysis method.

[0144] Preferably, if Figure 6 As shown, Figure 6 The five stages of the real-time power transaction process based on smart contracts, the specific steps to obtain the final power transaction settlement and transfer are as follows:

[0145] Step S41, each community energy internet participating in the electric energy transaction formulates its electric energy transaction plan for the current period according to the deviation data of the prediction result of its smart meter for the current period, and encrypts it in the form of a randomly generated string, and uses the hash algorithm in the blockchain technology to seal the encrypted transaction plan and publish it to the smart contract to prepare for transaction matching;

[0146] Step S42: Each entity participating in the electric energy transaction needs to disclose its real quotation and encrypted string to other entities in a timely manner within a certain period of time. The smart contract will automatically perform a hash algorithm to determine whether the result obtained after the unsealing is the same as the real quotation. If they are not the same, the quotation will be judged as an invalid quotation. If they are the same, the quotation will be regarded as a valid quotation, and the transaction parties will enter the next stage of smart contract execution. Finally, if the real quotations of all entities have been completely decrypted and disclosed, this stage will be terminated and the next stage of smart contract execution will be entered.

[0147] Step S43, collecting the power trading plans formulated by all entities according to the continuous double auction mechanism, sorting the bids of buyers and sellers, and matching the transactions according to the best bids of buyers and sellers;

[0148] Step S44, using the power transmission distribution factor and the voltage sensitivity factor to perform dynamic security verification on the matched transaction, and obtain the successfully matched electric energy transaction result;

[0149] Step S45: When the community energy internet successfully sells or buys all the electricity required for the transaction or reaches the preset transaction round limit, all matching results that are deemed valid are confirmed as the final transaction results. The smart meter transmits electricity according to the valid transaction results and promptly feeds back the transaction information to the smart contract. The smart contract settles and transfers the transaction according to the feedback transaction information.

[0150] In the dynamic constraint verification stage, since power transactions must meet certain physical laws, network security constraints need to be used to perform security verification on matched transactions. The power transfer distribution factor (PTDF) is often used as an indicator to describe branch congestion, while the voltage sensitivity factor (VSC) can effectively reflect the impact of power interaction on node voltage, so PTDF and VSC are used to perform dynamic security verification on the generated transaction results.

[0151] Preferably, if the dynamic security check passes, the transaction is matched successfully; if the check fails, the matchmaking is resolved and the process returns to the continuous two-way auction stage to obtain a new electricity transaction process.

[0152] PTDF is usually calculated using the node admittance matrix:

[0153]

[0154] Where: Φ l is the PTDF matrix of branch l; is the node susceptance diagonal matrix of branch l; A is the node association matrix;

[0155]

[0156] To obtain VSC, the calculation formula of voltage sensitivity factor is as follows:

[0157]

[0158] Where: Y is the node admittance matrix; P k is the injected power of the node; N and S are the PQ node and the balance node respectively.

[0159] According to the transaction results obtained in the continuous double auction stage, the transaction matrix ΔP of each node is obtained.

[0160] The PTDF and VSC matrices are used to perform dynamic safety checks on the line flow and node voltage respectively. If the check passes, the transaction is successfully matched; if the check fails, the matchmaking is cancelled, ΔP is obtained, and the transaction returns to the third step. The expression of dynamic safety check is shown in the formula:

[0161]

[0162] Where: Φ li is the element in the lth row and ith column of the PTDF matrix; is the indicator coefficient of the node type, that is, when the node purchases electricity, it takes -1, otherwise it takes 1; is the branch transmission capacity margin, is the node voltage offset margin.

[0163] Preferably, according to network security constraints and the imbalance of buying and selling electricity, if some community energy Internet cannot purchase the required electricity or there is still surplus electricity to be sold, the entities that still need to purchase electricity will be supplemented by standby units, and the surplus electricity will be purchased by the distribution network according to the on-grid electricity price.

[0164] Specifically, the main profit distribution calculation of the electricity purchase price is shown in the formula.

[0165]

[0166] Where: B total The cost of purchasing electricity for the community energy internet; C B The amount paid to the seller; C DSO The network fee is borne by both the buyer and the seller. BU The income from supplementing the power of the standby unit, S total Profits from selling electricity for the community energy internet; C grid The income from selling electricity to the distribution network. To prevent the transaction from being terminated, the number of matching rounds needs to be limited, and its value is related to the number of participating entities.

[0167] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for real-time distributed power trading taking into account source-load uncertainty, characterized in that: The method comprises the following steps: A two-stage robust bidding model is used to determine the bidding strategy of the community energy Internet. A non-cooperative game model of the bidding strategy is constructed with the minimum operating cost as the goal. A community energy Internet cluster game scheduling and trading model is constructed based on the robust bidding model and the non-cooperative game model. Among them, the specific steps of constructing the community energy Internet cluster game scheduling and trading model are as follows: the first stage of the robust bidding model constructs bidding constraints to obtain the day-ahead market bidding strategy of the community energy Internet; the second stage of the robust bidding model constructs a max-min optimization model to optimize the day-ahead market bidding strategy, and formulates a bidding strategy that can cope with the uncertainty of renewable energy output; a non-cooperative game model is constructed based on the bidding strategy and the minimum operating cost, and according to the non-cooperative game model The optimal bidding strategy is obtained by using the model; the strategy set of the community energy Internet cluster system is obtained according to the optimal bidding strategy, a game scheduling transaction model is constructed with the decision-making plan and the strategy set, and the optimal bidding plan is obtained according to the game scheduling transaction model; wherein, the specific steps for obtaining the optimal bidding strategy are as follows: step S11, before the transaction, each community energy Internet realizes the openness and transparency of transaction information on the blockchain platform; step S12, each community energy Internet formulates a corresponding bidding strategy according to the historical bidding strategies of other networks; step S13, the latest bidding strategy is broadcasted through the smart meter, and the other community energy Internets re-formulate the optimal bidding strategy; step S14, return to step S12, repeat the iteration until the optimal Nash equilibrium solution is reached, that is, the optimal bidding strategy is obtained; Formulate a trading strategy according to the game scheduling trading model, update the trading strategy to obtain the day-ahead trading strategy, perform security constraint check on the day-ahead trading strategy to obtain the optimal day-ahead trading strategy, and perform transaction settlement on the optimal day-ahead trading strategy based on the smart contract of the smart meter; wherein the specific steps of performing transaction settlement on the optimal day-ahead trading strategy are as follows: step S21, obtain the first round of trading strategy according to the game scheduling trading model; step S22, update the first round of trading strategy to obtain the day-ahead trading strategy, and generate a new sub-blockchain according to the day-ahead trading strategy as the input parameter of the second round of trading strategy; step S23, determine the day-ahead trading strategy Is the strategy the optimal bidding strategy? If so, the iteration is terminated. Otherwise, it is necessary to return to step S21 and re-execute; step S24, after executing the day-ahead trading strategy obtained in step S23, perform network security constraint verification, and perform security constraint verification according to the day-ahead trading strategy of each community energy Internet; if passed, the optimal day-ahead trading strategy is obtained. If not, constraints are added to the sub-problem for the lines that do not meet the security constraint verification, and step S21 is re-executed; step S25, all day-ahead trading strategies in the community energy Internet cluster system are written into the main blockchain, and then the smart meters in each community energy Internet perform transaction settlement according to the optimal day-ahead trading strategy; Based on the continuous double-sided auction quotation mechanism, the electric energy transaction process between the buyer and the seller under the optimal day-ahead transaction strategy is obtained, and the electric energy transaction process is adjusted by the adaptive aggressive value quotation strategy to obtain the optimal quotation; wherein, the specific steps of obtaining the electric energy transaction process between the buyer and the seller based on the continuous double-sided auction mechanism are as follows: Step S31, the community energy Internet formulates the initial quotation of the continuous double-sided auction mechanism according to its own renewable energy output and load power consumption. When the community energy Internet is the electricity seller, its initial quotation is When the community energy internet is the electricity buyer, its initial bid is Among them, α t,res represents the power generation of the community energy Internet in time period t, α t,load represents the load power consumption of the community energy Internet in time period t, λ0(t) represents the purchase price of the distribution network in time period t, and λ grid (t) represents the price at which the community energy internet purchases electricity from the distribution network during time period t, and β represents the user preference factor; Step S32, after receiving valid quotations from both the buyer and the seller, the sellers will be reordered in ascending order, and the buyers will be reordered in descending order; Step S33, the lowest quotation among the sellers during time period t will be compared with the highest quotation of the buyers. If the two can be satisfied, a round of transactions will be completed, otherwise the two parties will enter the next round of transactions until the buyer's best quotation is lower than the seller's best quotation; wherein the seller's best quotation refers to the lowest quotation, and the buyer's best quotation refers to the highest quotation; Based on the smart contract in the smart meter, the deviation of the electricity transaction process is corrected to obtain the final settlement and transfer of the electricity transaction; wherein, the specific steps to obtain the final settlement and transfer of the electricity transaction are as follows: Step S41, each community energy Internet participating in the electricity transaction formulates its electricity transaction plan within the current period according to the deviation data of the prediction results of its smart meter within a period of time, and encrypts it in the form of a randomly generated string, and uses the Hash algorithm in the blockchain technology to seal the encrypted transaction plan and publish it to the smart contract to prepare for transaction matching and matching; Step S42, each subject participating in the electricity transaction needs to disclose its true quotation and encrypted string to other subjects in a timely manner within a certain period of time, and the smart contract will automatically perform the Hash algorithm operation to determine whether the result obtained after unsealing is the same as the real quotation. If not, the quotation will be judged as an invalid quotation; if the same, the quotation will be regarded as invalid. The price is a valid quotation, and the transaction parties enter the next stage of smart contract execution. Finally, if the true quotations of all entities have been completely decrypted and disclosed, this stage is terminated and the next stage of smart contract execution is entered; step S43, according to the continuous two-way auction mechanism, the power trading plans formulated by all entities are collected, the quotations of buyers and sellers are sorted, and the transactions are matched according to the best quotations of buyers and sellers; step S44, the power transmission distribution factor and the voltage sensitivity factor are used to perform dynamic security verification on the matched transactions to obtain the successfully matched power transaction results; step S45, when the community energy Internet successfully sells or buys all the electricity required for the transaction or reaches the preset transaction round limit, all the matching results that are recognized as valid are confirmed as the final transaction results, and the smart meter transmits electricity according to the final transaction result, and promptly feedbacks the transaction information to the smart contract, and the smart contract settles and transfers the transaction according to the feedback transaction information.

2. A method for day-ahead real-time distributed electric energy trading taking into account source-load uncertainty according to claim 1, characterized in that: The constraints for safety constraint checking are: Among them, Φ li is the element in the lth row and ith column of the PTDF matrix, ΔP i is the power change of node i, is the indicator coefficient of the node type, is the real part, P i is the power value of node i, V i is the node voltage of node i, is the conjugate value of the node voltage at node i, is the branch transmission capacity margin, is the node voltage offset margin.

3. A method for day-ahead real-time distributed electric energy trading taking into account source-load uncertainty according to claim 1, characterized in that: When the seller's electricity price is higher than the buyer's electricity price, both parties need to adjust their quotations to improve the success rate and efficiency of transaction matching. The calculation formula of the adaptive aggressiveness value is: Among them, γ represents the willingness factor of community energy Internet to participate in transactions, and ω represents the market price fluctuation influencing factor.

4. A method for day-ahead real-time distributed electric energy trading taking into account source-load uncertainty according to claim 1, characterized in that: If the dynamic security check passes, the transaction is matched successfully. If the check fails, the matchmaking is cancelled and the process returns to the continuous two-way auction stage to obtain a new electricity transaction process.

5. A method for day-ahead real-time distributed electric energy trading taking into account source-load uncertainty according to claim 1, characterized in that: Due to network security constraints and the imbalance in electricity sales, some community energy Internets are unable to purchase the required electricity or still have surplus electricity to be sold. The entities that still need to purchase electricity will be supplemented by standby units, and the surplus electricity will be purchased by the distribution network at the on-grid electricity price.

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