A microgrid peer-to-peer power trading method and system based on blockchain

Abstract

The present application provides a microgrid point-to-point electricity trading method and system based on blockchain, the method comprising: each type of participating subject joins the blockchain network as a node and registers their corresponding identity information; each type of participating subject at least includes a power generator and a user; the power generator and the user conduct a master-slave game based on a pre-built master-slave game model to obtain the master-slave game result; the user power consumption and the power generator electricity price corresponding to the master-slave game result are stored and broadcast to the power generator and the user; the power generator publishes the electricity price according to the result of the master-slave game, and at the same time, the user publishes the power required by himself according to the result of the master-slave game to conduct electricity trading. The present application combines power trading with blockchain to realize point-to-point transactions between power generators and users, without the help of a central agency to establish a trust relationship between different participants, multi-node data storage enables each participating subject to realize data sharing, and uses smart contracts to automatically execute transactions to improve transaction efficiency.

Description

Technical Field

[0001] The present application relates to the field of power trading technology, and in particular to a microgrid point-to-point power trading method and system based on blockchain. Background Art

[0002] The transactions between the various participants in the electricity market have become very complicated. Each of them aims to maximize its own interests and compete with each other. There are correlations and conflicts between their interests. Among them, the power generation side takes electricity price as the main strategy, and the user takes electricity volume as the main strategy, mainly leaving the electricity price to the market. In addition, the transaction process involves a large number of users and multiple power generators. After all the participants are connected to the transaction center, they trade with each other.

[0003] However, traditional power trading centers are managed by central institutions. There are certain limitations in trading prices and trading volumes. Trading information is in the hands of a third party, and data loss and leakage may occur, which to a certain extent affects the formulation and implementation of bidding and electricity strategies of participating entities. At the same time, due to the unequal and opaque information exchange, trust issues arise between the two parties to the transaction. The data of various power generators and users are not interconnected, and the growing scale leads to data island problems.

[0004] Therefore, there is an urgent need to provide a microgrid peer-to-peer electricity trading method that is a key technology for resolving conflicts of interest, promoting mutual trust, breaking data silos, and achieving weak centralization. Summary of the invention

[0005] In view of this, the present application provides a microgrid peer-to-peer electricity trading method and system based on blockchain to solve the above-mentioned technical problems in electricity trading in the prior art.

[0006] A microgrid peer-to-peer electricity trading method based on blockchain, comprising:

[0007] Each type of participant joins the blockchain network as a node and registers their corresponding identity information; each type of participant includes at least power generators and users;

[0008] The power generator and the user perform a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result;

[0009] The user power consumption and the power price of the power generator corresponding to the master-slave game result are stored and broadcasted to the power generator and the user;

[0010] The power generator publishes the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by itself according to the result of the master-slave game to conduct electricity trading and form an electricity trading order.

[0011] Furthermore, before the power generator and the user perform a master-slave game based on a pre-built master-slave game model, the method further includes:

[0012] The energy regulator among the various types of participating entities calls the smart contract init function to open the power trading market so that the various types of participating entities can conduct power trading;

[0013] After the power trading order is formed, the following steps are also included:

[0014] Packaging and broadcasting the electricity trading order to the consensus nodes, and storing it after the consensus nodes reach a consensus;

[0015] Calculate the trust between the power generator and the user, take corresponding measures based on the comparison result between the trust and the trust threshold, and store the result as a voucher for the next round of transactions;

[0016] The smart contract bill function is automatically triggered to settle the transaction bill. At the same time, the trust range is taken into consideration to settle the participating entities that need to be fined.

[0017] Furthermore, the power generator and the user conduct a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result, including:

[0018] Obtaining the optimal segmented power consumption of the user based on the user's benefit function;

[0019] Feedback the optimal segmented electricity consumption of the user to the power generator, so that the power generator adopts the NSGA-Ⅱ multi-objective optimization algorithm to re-formulate the electricity price and send it to the user according to the energy consumption strategy of the user and the profit function of the power generator;

[0020] The power consumption is recalculated based on the user's profit function according to the new electricity price and fed back to the power generator until the number of iterations is reached or an equilibrium solution is obtained; wherein the equilibrium solution is used to indicate that the user and the power generator achieve maximum profit on the basis of satisfying their respective constraints.

[0021] Furthermore, the user's profit function is expressed as:

[0022] The user's constraints are:

[0023]

[0024] in, represents the expected revenue of user i in time i; represents the utility function of user i at time t, and represents the preference coefficient of user i for power consumption in time t, represents the amount of electricity purchased by user i from traditional energy generators within time t, represents the amount of electricity purchased by user i from renewable energy power generators within time t, where the power generators include the traditional energy power generators and the renewable energy power generators; represents the cost function of user i in time t, represents the electricity price set by the traditional energy power generator within time t, represents the electricity price set by the renewable energy power generator within time t; It indicates the network access fee charged by the power supplier to user i; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the traditional energy generator; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the renewable energy power generator; n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users. The users include the residential users, the commercial users and the industrial users.

[0025] Furthermore, the power generator includes a traditional energy power generator and a renewable energy power generator. Accordingly, the revenue function of the power generator includes: the revenue function of the traditional energy power generator and the revenue function of the renewable energy power generator, wherein:

[0026] The expression of the profit function of the traditional energy power generator is:

[0027]

[0028] The constraints of the traditional energy generators are:

[0029] in, represents the expected revenue of traditional energy generators in time t; represents the electricity sales revenue of traditional energy generators in time t, n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users, wherein the users include the residential users, the commercial users, and the industrial users; represents the amount of electricity purchased by user i from traditional energy generators, represents the electricity price set by traditional energy generators in time t, P represents the power generation of traditional energy generators in time t, t represents the fixed price of the external large grid; represents the power generation cost of traditional energy generators, a, b, and c represent the power generation cost coefficients; represents the environmental governance incentive income of traditional energy power generators, p0 represents the incentive unit price of energy pollutant emissions per unit mass, Indicates the emission reduction, μ k represents the emission factor of the kth type of pollutant, represents the energy consumption of traditional energy generators in time t, represents the energy consumption of the power grid in time t; It means that the power supplier charges the traditional energy power generators a transmission fee; They represent the lower and upper limits of the electricity price of traditional energy generators in time t respectively;

[0030] The expression of the revenue function of the renewable energy power generator is:

[0031]

[0032] The constraints of the renewable energy generator are:

[0033] in, represents the expected revenue of renewable energy generators in time t; represents the electricity sales revenue of renewable energy generators in time t, Indicates user i Electricity purchased from renewable energy generators; represents the electricity price set by renewable energy generators in time t, It represents the power generation of renewable energy generators in time t; represents the electricity generation cost of renewable energy generators, represents the renewable energy subsidy income, ω represents the renewable energy subsidy factor, represents the on-grid electricity price of renewable energy in time t, It represents the on-grid electricity price of a traditional energy source in time t; It means that power suppliers charge renewable energy generators for access fees; They represent the lower and upper limits of the electricity price for renewable energy generators within time t.

[0034] A microgrid peer-to-peer power trading system based on blockchain, comprising:

[0035] A registration unit, used for various types of participating entities to join the blockchain network as nodes and register their corresponding identity information; the various types of participating entities at least include power generators and users;

[0036] A game unit, used for the power generator and the user to perform a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result;

[0037] A first storage and broadcasting unit, used for storing the user power consumption and the power price of the power generator corresponding to the master-slave game result, and broadcasting them to the power generator and the user;

[0038] The trading unit is used for the power generator to publish the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by himself according to the result of the master-slave game, so as to conduct electricity trading and form an electricity trading order.

[0039] Furthermore, it also includes:

[0040] An opening unit is used for energy regulators among the various types of participating entities to call the smart contract init function to open the power trading market so that the various types of participating entities can conduct power trading;

[0041] A second storage and broadcasting unit, used for packaging and broadcasting the power trading order to the consensus nodes, and storing the order after the consensus nodes reach a consensus;

[0042] A calculation storage unit, used to calculate the trust between the power generator and the user, take corresponding measures based on the comparison result between the trust and the trust threshold, and store the result as a voucher for the next round of transactions;

[0043] The clearing unit is used to automatically trigger the smart contract bill function to clear transaction bills. It also takes into account the trust level and clears the participants who need to be fined.

[0044] Furthermore, the gaming unit includes:

[0045] A user benefit calculation unit, used to obtain the user's optimal segmented power consumption based on the user's benefit function;

[0046] The power generator profit calculation unit is used to feed back the optimal segmented power consumption of the user to the power generator, so that the power generator adopts the NSGA-Ⅱ multi-objective optimization algorithm to re-formulate the power price and send it to the user according to the energy consumption strategy of the user and the profit function of the power generator;

[0047] The user benefit calculation unit is also used to recalculate the electricity consumption based on the user's benefit function according to the new electricity price, and feed it back to the power generator until the number of iterations is reached or an equilibrium solution is obtained; wherein the equilibrium solution is used to indicate that the user and the power generator achieve maximum benefits on the basis of satisfying their respective constraints.

[0048] Furthermore, the user's profit function is expressed as:

[0049] The user's constraints are:

[0050]

[0051] in, represents the expected revenue of user i in time i; represents the utility function of user i at time t, and represents the preference coefficient of user i for power consumption in time t, represents the amount of electricity purchased by user i from traditional energy generators within time t, represents the amount of electricity purchased by user i from renewable energy power generators within time t, where the power generators include the traditional energy power generators and the renewable energy power generators; represents the cost function of user i in time t, represents the electricity price set by the traditional energy power generator within time t, represents the electricity price set by the renewable energy power generator within time t; It indicates the network access fee charged by the power supplier to user i; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the traditional energy generator; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the renewable energy power generator; n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users. The users include the residential users, the commercial users and the industrial users.

[0052] Furthermore, the power generator includes a traditional energy power generator and a renewable energy power generator. Accordingly, the revenue function of the power generator includes: the revenue function of the traditional energy power generator and the revenue function of the renewable energy power generator, wherein:

[0053] The expression of the profit function of the traditional energy power generator is:

[0054]

[0055] The constraints of the traditional energy generators are:

[0056] in, represents the expected revenue of traditional energy generators in time t; represents the electricity sales revenue of traditional energy generators in time t, n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users, wherein the users include the residential users, the commercial users, and the industrial users; represents the amount of electricity purchased by user i from traditional energy generators, represents the electricity price set by traditional energy generators in time t, P represents the power generation of traditional energy generators in time t, t represents the fixed price of the external large grid; represents the power generation cost of traditional energy generators, a, b, and c represent the power generation cost coefficients; represents the environmental governance incentive income of traditional energy power generators, p0 represents the incentive unit price of energy pollutant emissions per unit mass, Indicates the emission reduction, μ k represents the emission factor of the kth type of pollutant, represents the energy consumption of traditional energy generators in time t, represents the energy consumption of the power grid in time t; It means that the power supplier charges the traditional energy power generators a transmission fee; They represent the lower and upper limits of the electricity price of traditional energy generators in time t respectively;

[0057] The expression of the revenue function of the renewable energy power generator is:

[0058]

[0059] The constraints of the renewable energy generator are:

[0060] in, represents the expected revenue of renewable energy generators in time t; represents the electricity sales revenue of renewable energy generators in time t, Indicates user i Electricity purchased from renewable energy generators; represents the electricity price set by renewable energy generators in time t, It represents the power generation of renewable energy generators in time t; represents the electricity generation cost of renewable energy generators, represents the renewable energy subsidy income, ω represents the renewable energy subsidy factor, represents the on-grid electricity price of renewable energy in time t, It represents the on-grid electricity price of a traditional energy source in time t; It means that power suppliers charge renewable energy generators for access fees; They represent the lower and upper limits of the electricity price for renewable energy generators within time t.

[0061] The present application provides a microgrid point-to-point electricity trading method and system based on blockchain, the method comprising: each type of participating subject joins the blockchain network as a node and registers their corresponding identity information; each type of participating subject at least includes a power generator and a user; the power generator and the user conduct a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result; the user power consumption and the power generator electricity price corresponding to the master-slave game result are stored and broadcast to the power generator and the user; the power generator publishes the electricity price according to the result of the master-slave game, and at the same time, the user publishes the power required by itself according to the result of the master-slave game to conduct power trading and form a power trading order. The present application combines power trading with blockchain to realize point-to-point trading between power generators and users, and can generate a trust relationship between different participants without the help of a central agency. Multi-node data storage enables each participating subject to realize data sharing, and the use of smart contracts to automatically execute transactions improves the efficiency of transactions. The transparency of electricity price setting and user electricity consumption in the electricity trading process is an important reference for improving the efficiency of electricity trading and an important factor in maintaining the stable operation of the power system. The master-slave game model constructed between power generators and users takes into account multiple influencing factors, which provides support for the formulation of electricity prices. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0063] Figure 1 A master-slave game model provided for this application;

[0064] Figure 2A flowchart of a microgrid peer-to-peer electricity trading method based on blockchain provided for this application;

[0065] Figure 3 A flowchart of another microgrid peer-to-peer electricity trading method based on blockchain provided for this application;

[0066] Figure 4 A schematic diagram of the structure of a microgrid peer-to-peer power trading system based on blockchain provided in an embodiment of the present application;

[0067] Figure 5 A schematic diagram of the structure of another blockchain-based microgrid peer-to-peer electricity trading system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] At present, the conflicts of interest among the various participants in power trading have led to inconsistent and opaque electricity price standards, making the various participants passive in the energy trading process and unable to make these data an effective resource for the power trading center; different operators of the power trading center, including energy regulators, governments, banks, power generators, users and other participants, continuously generate a large amount of transaction data and the identity data of the participants themselves during the transaction process, forming a large number of "information islands". Limited energy management personnel face these huge amounts of fragmented big data, with extremely low work efficiency and difficulty in discovering real hidden dangers; a large number of manual operations in the power trading center not only waste manpower and material resources, but also have low transaction efficiency; moreover, the existence of third-party institutions in the power trading center requires transactions between power generators and power users to go through third-party institutions, resulting in the inability to conduct point-to-point transactions, and there are also problems such as high costs and data privacy leaks.

[0070] In order to solve the above problems in the prior art, the present invention proposes a master-slave game model and peer-to-peer power trading method based on blockchain. The participants involved are mainly traditional energy power generators, renewable energy power generators, various users and energy regulators. Each type of participant is added to the blockchain as a node. Among them, each participant aims to maximize its own interests. The master-slave game model constructed between traditional energy power generators, renewable energy power generators and users is as follows Figure 1 shown.

[0071] The master game includes traditional energy generators and renewable energy generators. Both make decisions at the same time without knowing each other's electricity pricing strategy, and the other party's electricity pricing strategy will affect their own electricity pricing strategy. Similarly, in the slave game, residential users and industrial and commercial users make decisions at the same time without knowing each other's electricity strategy, and the other party's electricity strategy will also affect their own electricity strategy.

[0072] 1) Power producer model

[0073] In peer-to-peer transactions, the main trading partners of power generators are electricity users, which are divided into residential users with less electricity consumption and industrial and commercial users with more electricity consumption. In addition, according to the different power generation methods, power generators are divided into renewable energy power generators and traditional energy power generators. In this paper, renewable energy power generation is mainly considered as solar power generation and wind power generation.

[0074] A. Cost Function

[0075] This paper considers that the electricity consumption of users on the same day and the next day is generally not much different, so the electricity consumption of all users on the same day is used to predict the electricity consumption of users on the next day. Traditional energy power generators and renewable energy power generators formulate power generation plans according to a certain ratio, and the excess electricity is sold to the external large power grid at a fixed price. Among them, the power generation cost of renewable energy power generators is set to 0, that is, The power generation cost of traditional energy generators is formulated as a quadratic function, using It is expressed as shown in formula (1).

[0076]

[0077] In the formula, It represents the power generation of traditional energy power generators in time t; a, b, c represent the power generation cost coefficients.

[0078] B. Income Function

[0079] The main power supply objects of power generators are residential users, commercial users and industrial users. The electricity sales income of traditional energy power generators in time t is and the electricity sales revenue of renewable energy generators in time t As shown in formula (2).

[0080]

[0081] In the formula, represents the amount of electricity purchased by user i from traditional energy generators; represents the electricity price set by traditional energy generators in time t; represents the amount of electricity purchased by user i from renewable energy generators; P represents the electricity price set by renewable energy generators within time t; t Represents the fixed price of the external large grid.

[0082] C. Revenue Function

[0083] The revenue of power generators is divided into five parts: electricity sales revenue, power generation costs, environmental governance incentive income, renewable energy subsidies and grid access fees.

[0084] Traditional energy generation emits certain pollutants, so an incentive method is used to encourage traditional energy generators to reduce pollutant emissions. It is expressed as shown in formula (3). The emission reduction of traditional energy power generators is defined as the amount of pollutant emissions reduced compared with the benchmark power generator under the condition of obtaining the same power supply. Taking the power supply of the grid as the benchmark, the emission reduction is expressed as To express.

[0085]

[0086] In the formula, μ k represents the emission factor of the kth type of pollutant; It represents the energy consumption of traditional energy power generators in time t, which needs to be converted into standard coal mass; It represents the energy consumption of the power grid within time t, which needs to be converted into the mass of standard coal; p0 represents the incentive unit price of pollutant emissions per unit mass of standard coal.

[0087] Since renewable energy generation does not cause environmental pollution, a renewable energy subsidy mechanism is set up, and the renewable energy subsidy income is used It is expressed as shown in formula (4).

[0088]

[0089] Where ω represents the renewable energy subsidy factor; represents the on-grid electricity price of renewable energy in time t; It represents the on-grid electricity price of a traditional energy source within time t. Here, the on-grid electricity price of coal-fired power is selected.

[0090] The expected profit function of traditional energy generators and renewable energy generators in time t is shown in formula (5).

[0091]

[0092] In the formula, It means that the power supplier charges the traditional energy power generators a transmission fee; It means that the power supplier charges the renewable energy power generator the transmission fee; the specific analysis can be seen in the power supplier model below.

[0093] D. Constraints

[0094]

[0095] In the formula, They represent the upper and lower limits of electricity prices of traditional energy power generators in time t respectively; They represent the upper and lower limits of the electricity price of renewable energy generators within time t.

[0096] 2) User Model

[0097] Assume that the microgrid area consists of n1 residential users, n2 commercial users and n3 industrial users. Set N1 = {1, 2, ..., n1} represents residential users, set N2 = {1, 2, ..., n2} represents commercial users, and set N3 = {1, 2, ..., n3} represents industrial users, where each user is represented by i, i∈N1 or i∈N2 or i∈N3. As consumers and demand side of energy, users set electricity consumption with the goal of maximizing their own benefits while meeting their own needs.

[0098] A. Cost Function

[0099] The user's cost is mainly the purchase of electricity, including the purchase of electricity from power generators and external large power grids. The cost function of user i in time t is shown in formula (7).

[0100]

[0101] B. Utility Function

[0102] Each user generates different utilities based on the amount of electricity consumed and the satisfaction obtained. The utility function is defined as a measure of the user's satisfaction with electricity consumption. Using a logarithmic function to measure the utility generated by the user after consuming electricity, the utility function of user i in time t is shown in formula (8).

[0103]

[0104] In the formula, α i , β i and γ i Represents the preference coefficient of user i for power consumption within time t.

[0105] C. Revenue Function

[0106] The user's benefit is the utility minus the expenditure, so the expected benefit function of user i in time i is shown in formula (9).

[0107]

[0108] In the formula, It represents the network access fee charged by the power supplier to user i. The specific analysis is in the following power supplier model.

[0109] D. Constraints

[0110]

[0111] In the formula, They represent the upper and lower limits of the electricity that user i can purchase from traditional energy generators; They represent the upper and lower limits of the electricity that user i can purchase from renewable energy generators.

[0112] 3) Power supplier model

[0113] As a third party between power generators and users, power suppliers mainly collect transmission fees in point-to-point transactions between power generators and users, and do not participate in specific transactions. In addition, how to adjust the transmission fee price to maximize the power supplier's profit is not the focus of this paper, so power suppliers do not participate in the game process.

[0114] A. Income Function

[0115] The income function of the power supplier is expressed as the transmission fee. The transmission fee in this application is borne by the power generator and the user. Then the transmission fee income of the power supplier in time t is expressed as F t It is represented as shown in formula (11).

[0116]

[0117] In the formula, They represent the transmission fees collected from traditional energy generators, renewable energy generators and user i respectively; They represent the transmission fee factors charged to traditional energy generators, renewable energy generators and user i, respectively, and Indicates the grid access electricity price charged to users.

[0118] B. Constraints

[0119]

[0120] In the formula, They respectively represent the upper and lower limits of the on-grid electricity price charged by the power supplier to users within time t.

[0121] 4) Model solution

[0122] The game theory is used to analyze the necessary elements of the non-cooperative game model between microgrid generators and users.

[0123] Participants: Users, traditional energy generators and renewable energy generators in the microgrid all have individual rationality.

[0124] Strategy: User i can adjust his own electricity consumption at different time periods Traditional energy generators and renewable energy generators can adjust electricity prices at different times

[0125] Payment: The profit function is shown in equations (5) and (9). The goal is to maximize the profit by changing its own strategy.

[0126] The optimal strategies of traditional energy generators and renewable energy generators satisfy:

[0127]

[0128] Similarly, the optimal strategy for user i satisfies:

[0129]

[0130] From the definition of Nash equilibrium, we know that when all participants achieve maximum benefits, the game reaches a stable state, and the strategies of all decision-makers at this time constitute the Nash equilibrium solution of the model. They are the collection of traditional energy generators, renewable energy generators and user strategies, among which, The electricity price strategies for traditional energy power generators at different times. The electricity price strategy for renewable energy generators at different times. is the power strategy of user i in different time periods, then The necessary and sufficient condition for Nash equilibrium is that no matter whether it is a power generator or a user, when the optimal strategies of other participants remain unchanged, the variable strategy is adjusted to make the payment of the participant optimal, then the participant reaches the optimal strategy.

[0131] In this master-slave game, the environmental governance incentive income, renewable energy subsidies, grid access fees and other mechanisms are comprehensively considered to more accurately measure the interests of the participating entities, laying a solid foundation for the game. Based on this, the NSGA-Ⅱ algorithm is used to solve the equilibrium solution for both parties in the game. The NSGA-Ⅱ algorithm is one of the classic genetic algorithms for solving multi-objective optimization problems.

[0132] Specifically, the present application provides a microgrid peer-to-peer power trading method based on blockchain, such as Figure 2 As shown, including:

[0133] Step S101: Each type of participant joins the blockchain network as a node and registers their corresponding identity information;

[0134] Each type of participant includes at least power generators and users. Each participant, including power generators, users, energy regulators, etc., joins the blockchain network as a node, and then each node registers its identity according to its own needs. For example, when a user purchases electricity, he registers as a buyer.

[0135] Step S102: The power generator and the user conduct a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result;

[0136] Step S103: storing the user power consumption and power price of the power generator corresponding to the master-slave game result, and broadcasting them to the power generator and the user;

[0137] Step S104: The power generator publishes the electricity price according to the result of the master-slave game. At the same time, the user publishes the amount of electricity required by himself according to the result of the master-slave game to conduct electricity trading and form an electricity trading order.

[0138] This embodiment combines power trading with blockchain to realize peer-to-peer transactions between power generators and users. Multi-node data storage enables data sharing among all participating entities, and uses smart contracts to automatically execute transactions to improve transaction efficiency. The transparency of electricity price formulation and user energy consumption during power trading is an important reference for improving power trading efficiency and an important factor in maintaining the stable operation of the power system. The master-slave game model between power generators and users is constructed, which takes into account a variety of influencing factors and provides support for the formulation of electricity prices.

[0139] In addition, this application also provides another blockchain microgrid peer-to-peer electricity trading method, such as Figure 3 As shown, including:

[0140] Step S201: Each type of participant joins the blockchain network as a node and registers their corresponding identity information;

[0141] Various types of participants include generators, users and energy regulators;

[0142] Step S202: The energy regulator calls the smart contract init function to open the power trading market so that various types of participants can conduct power trading;

[0143] Step S203: the power generator and the user conduct a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result;

[0144] Specifically, the process includes:

[0145] A. Obtain the user's optimal segmented electricity consumption based on the user's benefit function;

[0146] The user's profit function is expressed as: It is differentiable, so the first-order partial derivative is solved, as shown in formula (15). At the same time, setting the partial derivative equal to 0, the optimal segmented power consumption of user i can be obtained, as shown in formula (16).

[0147]

[0148] B. Feedback the user's optimal segmented electricity consumption to the power generator, so that the power generator can use the NSGA-Ⅱ multi-objective optimization algorithm to re-formulate the electricity price and send it to the user according to the user's energy consumption strategy and the power generator's profit function;

[0149] The revenue function of the power generator can be referred to in formula (5), which will not be elaborated here.

[0150] C. Recalculate the electricity consumption based on the user's profit function according to the new electricity price and feed it back to the power generator until the number of iterations is reached or an equilibrium solution is obtained; the equilibrium solution is used to indicate that the user and the power generator can maximize their profits on the basis of satisfying their respective constraints.

[0151] Step S204: storing the user power consumption and the power price of the power generator corresponding to the master-slave game result, and broadcasting them to the power generator and the user;

[0152] Step S205: the power generator publishes the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by himself according to the result of the master-slave game to conduct electricity trading and form an electricity trading order;

[0153] Step S206: Packaging the power trading order and broadcasting it to the consensus nodes, and storing it after the consensus nodes reach a consensus;

[0154] Step S207: Calculate the trust between the power generator and the user, take corresponding measures based on the comparison result between the trust and the trust threshold, and store the result as a voucher for the next round of transactions;

[0155] Trust is a measure proposed to measure whether there are any violations in the transaction process of the participants, such as temporary reduction of power consumption by user nodes, temporary increase of electricity prices by power generators, and failure to provide promised power generation. At present, traditional trading centers do not take any measures or only use measures such as fines to reduce the violations of the participants. However, such measures do not have any impact on the next transaction of the participants and cannot effectively prevent the violations of the participants. Therefore, this application proposes a method of using trust to effectively prevent the violations of the participants.

[0156] Assume that user i reports the planned electricity consumption to the trading center as The actual electricity consumption of the end user is Then calculate Among them, only the behavior of user nodes reducing power consumption is considered, and the behavior of user nodes increasing power consumption is not considered. Similarly, the planned power generation reported by power generator j to the trading center is The actual power generation amount of the power generator is Then calculate Among them, only the behavior of the generator node reducing power generation is considered, and the behavior of the generator node increasing power generation is not considered, satisfying At the same time, power generator j reports the planned electricity price to the trading center as The actual electricity price of the power generator is Then calculate Among them, only the behavior of power generation node increasing electricity price is considered, and the behavior of power generation node reducing electricity price is not considered. Therefore, the trust calculation method between user i and generator j is shown in formula (17).

[0157]

[0158] In the formula, 0≤ τ≤1, indicating the coefficient factor.

[0159] After waiting for a round of transactions to end, the energy regulator calculates the trustworthiness of the participating entities and updates it in real time, using it as a valid credential for participating in the next round of transactions, and then determines whether punitive measures need to be taken against the participating entities.

[0160] Set user thresholds ε1 and ε2, where the ε1 threshold is the reference value for limiting the next transaction, and the ε2 threshold is the reference value for submitting a fine to the energy regulator for the next transaction. If the trust of user i is less than the threshold ε1, that is, TR i <ε1, the transaction will be restricted and the trust of the next round of transactions will be affected to a certain extent; if the trust of user i is between the threshold ε1 and ε2, that is, ε1<TR i <ε2, a penalty operation is performed according to formula (18), and the trust of the next round of transactions is affected to a certain extent; if the trust of user i is greater than the threshold ε2, that is, TR i >ε2, no penalty measures will be taken before entering the next round of transactions, and the trust in the next round of transactions will be affected to a certain extent. However, in the above three cases, the trust after each round of transactions will only affect the trust in the next round of transactions, which is updated according to formula (19).

[0161]

[0162] In the formula, Indicates the unit penalty electricity price.

[0163]

[0164] Where λ1 and λ2 represent coefficient factors.

[0165] Step S208: Automatically trigger the smart contract bill function to settle the transaction bill, and at the same time consider the trust range to settle the participating entities that need to be fined.

[0166] After the liquidation is completed, the energy regulator calls the close function of the smart contract to close the electricity trading market and end this round of transactions.

[0167] The smart contract functions involved in this peer-to-peer transaction are as follows:

[0168] (1) init / close function. This contract is managed by the energy regulator. Each round of trading requires the energy regulator to open the trading market so that all participating entities can trade electricity. The energy regulator uses time as a reference and waits for the end of this round of trading to close the trading market.

[0169] (2) register function. This function provides identity registration function for each participant. After the participant joins the blockchain as a node, it should register the buyer's identity or the seller's identity within the transaction period in order to conduct subsequent transactions. Before the next round of transactions begins, the identity needs to be re-registered.

[0170] (3) Game function. This function is the above-mentioned game process. The generator and the user play a master-slave game, and the optimal result is stored in the smart contract store function.

[0171] (4) Store function. This function mainly stores the optimal result of the game, that is, the planned electricity price and planned electricity consumption of each participant; it also stores information such as transaction orders.

[0172] (5) Sellers / buyers function. Each participant publishes the transaction price and electricity consumption through this function and broadcasts it to each node.

[0173] (6) Query function. This function establishes an open and transparent query system based on the above stored information. Participants can call this smart contract function to query transaction information and other related information.

[0174] (7) Order function. This function matches the transaction based on the game results with the electricity price and quantity published by the participating entities. After the transaction intention is reached, a transaction order is formed, which includes information such as the transaction parties, transaction quantity, transaction time, and transaction price.

[0175] (8) Bill function. After the transaction is concluded between the participating entities, this function is automatically executed for settlement. The process uses tokens for settlement.

[0176] The blockchain-based microgrid point-to-point power trading method provided in this embodiment realizes point-to-point transactions between power generators and users by combining power trading with blockchain, and can generate a trust relationship between different participants without the help of a central agency. Multi-node data storage enables each participant to share data, and uses smart contracts to automatically execute transactions to improve transaction efficiency. The transparency of electricity price formulation and user power consumption during power trading is an important reference for improving power trading efficiency and an important factor in maintaining the stable operation of the power system. The master-slave game model between power generators and users is constructed, which takes into account a variety of influencing factors and provides support for the formulation of electricity prices. At the same time, by using blockchain to establish a trust mechanism, punitive measures can be taken against participants who do not comply with regulations to reduce violations in the next round of transactions.

[0177] In order to implement the method in the above embodiment, the present application provides a microgrid peer-to-peer power trading system based on blockchain, such as Figure 4 As shown, it includes: a registration unit 301, a gaming unit 302, a first storage and broadcasting unit 303 and a transaction unit 304, wherein:

[0178] The registration unit 301 is used for various types of participating entities to join the blockchain network as nodes and register their corresponding identity information; various types of participating entities at least include power generators and users;

[0179] A game unit 302 is used for the power generator and the user to perform a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result;

[0180] The first storage and broadcasting unit 303 is used to store the user power consumption and the power price of the power generator corresponding to the master-slave game result, and broadcast it to the power generator and the user;

[0181] The trading unit 304 is used for the power generator to publish the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by himself according to the result of the master-slave game to conduct electricity trading and form an electricity trading order.

[0182] This embodiment combines power trading with blockchain to realize peer-to-peer transactions between power generators and users. Multi-node data storage enables data sharing among all participating entities, and uses smart contracts to automatically execute transactions to improve transaction efficiency. The transparency of electricity price formulation and user energy consumption during power trading is an important reference for improving power trading efficiency and an important factor in maintaining the stable operation of the power system. The master-slave game model between power generators and users is constructed, which takes into account a variety of influencing factors and provides support for the formulation of electricity prices.

[0183] This application also provides another microgrid peer-to-peer power trading system based on blockchain, such as Figure 5As shown, it includes: a registration unit 401, an opening unit 402, a gaming unit 403, a first storage and broadcasting unit 404, a transaction unit 405, a second storage and broadcasting unit 406, a calculation and storage unit 407 and a clearing unit 408, wherein:

[0184] The registration unit 401 is used for various types of participating entities to join the blockchain network as nodes and register their corresponding identity information; various types of participating entities at least include power generators and users;

[0185] The opening unit 402 is used for energy regulators among various types of participating entities to call the smart contract init function to open the power trading market so that various types of participating entities can conduct power trading;

[0186] The game unit 403 is used for the power generator and the user to perform a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result;

[0187] The game unit includes: a user benefit calculation unit and a power generator benefit calculation unit, wherein:

[0188] A user benefit calculation unit, used to obtain the user's optimal segmented power consumption based on the user's benefit function;

[0189] The user's profit function is expressed as:

[0190] The user's constraints are:

[0191] Please refer to the above introduction for details, which will not be repeated here.

[0192] The generator revenue calculation unit is used to feed back the user's optimal segmented electricity consumption to the generator, so that the generator can use the NSGA-Ⅱ multi-objective optimization algorithm to re-formulate the electricity price and send it to the user according to the user's energy consumption strategy and the generator's revenue function;

[0193] The expected profit function of traditional energy generators and renewable energy generators in time t is:

[0194]

[0195] The constraints are:

[0196] Please refer to the above introduction for details, which will not be repeated here.

[0197] The user benefit calculation unit is also used to recalculate the electricity consumption based on the user's benefit function according to the new electricity price, and feed it back to the power generator until the number of iterations is reached or an equilibrium solution is obtained; among which, the equilibrium solution is used to indicate that the user and the power generator can maximize their benefits on the basis of satisfying their respective constraints.

[0198] The first storage and broadcasting unit 404 is used to store the user power consumption and the power price of the power generator corresponding to the master-slave game result, and broadcast it to the power generator and the user;

[0199] The trading unit 405 is used for the power generator to publish the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by himself according to the result of the master-slave game to conduct electricity trading and form an electricity trading order;

[0200] The second storage and broadcasting unit 406 is used to package and broadcast the power trading order to the consensus nodes, and store it after the consensus nodes reach a consensus;

[0201] The calculation storage unit 407 is used to calculate the trust between the power generator and the user, take corresponding measures based on the comparison result between the trust and the trust threshold, and store the result as a voucher for the next round of transactions;

[0202] The clearing unit 408 is used to automatically trigger the smart contract bill function to clear the transaction bill, and at the same time consider the trust range to clear the participating entities that need to be fined.

[0203] For an introduction to the system, please refer to the introduction to the above method embodiment, which will not be repeated in this application.

[0204] The blockchain-based microgrid point-to-point power trading system provided in this embodiment realizes point-to-point transactions between power generators and users by combining power transactions with blockchain, and can generate a trust relationship between different participants without the help of a central agency. Multi-node data storage enables each participant to share data, and uses smart contracts to automatically execute transactions to improve transaction efficiency. The transparency of electricity price formulation and user power consumption during power trading is an important reference for improving power trading efficiency and an important factor in maintaining the stable operation of the power system. The master-slave game model between power generators and users is constructed, which takes into account a variety of influencing factors and provides support for the formulation of electricity prices. At the same time, by using blockchain to establish a trust mechanism, punitive measures can be taken against participants who do not comply with regulations to reduce violations in the next round of transactions.

[0205] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0206] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0207] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A microgrid peer-to-peer power trading method based on blockchain, characterized in that: include: Each type of participant joins the blockchain network as a node and registers their corresponding identity information; each type of participant includes at least power generators and users; The power generator and the user perform a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result, including: Obtaining the optimal segmented power consumption of the user based on the user's benefit function; Feedback the optimal segmented electricity consumption of the user to the power generator, so that the power generator adopts the NSGA-Ⅱ multi-objective optimization algorithm to re-formulate the electricity price and send it to the user according to the energy consumption strategy of the user and the profit function of the power generator; Recalculate the power consumption based on the user's profit function according to the new power price, and feed it back to the power generator until the number of iterations is reached or an equilibrium solution is obtained; wherein the equilibrium solution is used to indicate that the user and the power generator can maximize their profits on the basis of satisfying their respective constraints; The expression of the user's profit function is: The user's constraints are: in, represents the expected revenue of user i in time t; represents the utility function of user i at time t, and represents the preference coefficient of user i for power consumption in time t, represents the amount of electricity purchased by user i from traditional energy generators within time t, represents the amount of electricity purchased by user i from renewable energy power generators within time t, where the power generators include the traditional energy power generators and the renewable energy power generators; represents the cost function of user i in time t, represents the electricity price set by the traditional energy power generator within time t, represents the electricity price set by the renewable energy power generator within time t; It indicates the network access fee charged by the power supplier to user i; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the traditional energy generator; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the renewable energy power generator; n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users. The users include the residential users, the commercial users, and the industrial users; The user power consumption and the power price of the power generator corresponding to the master-slave game result are stored and broadcasted to the power generator and the user; The power generator publishes the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by the user according to the result of the master-slave game to conduct electricity trading and form an electricity trading order; The power generators include traditional energy power generators and renewable energy power generators. Accordingly, the revenue function of the power generators includes: the revenue function of the traditional energy power generators and the revenue function of the renewable energy power generators, wherein: The expression of the profit function of the traditional energy power generator is: The constraints of the traditional energy generators are: in, represents the expected revenue of traditional energy generators in time t; represents the electricity sales revenue of traditional energy generators in time t, n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users, wherein the users include the residential users, the commercial users, and the industrial users; represents the amount of electricity purchased by user i from traditional energy generators within time t, represents the electricity price set by traditional energy generators in time t, P represents the power generation of traditional energy generators in time t, t represents the fixed price of the external large grid; represents the power generation cost of traditional energy generators, a, b, and c represent the power generation cost coefficients; represents the environmental governance incentive income of traditional energy power generators, p0 represents the incentive unit price of energy pollutant emissions per unit mass, Indicates the emission reduction, μ k represents the emission factor of the kth type of pollutant, represents the energy consumption of traditional energy generators in time t, represents the energy consumption of the power grid in time t; It means that the power supplier charges the traditional energy power generators a transmission fee; They represent the lower and upper limits of the electricity price of traditional energy generators in time t respectively; The expression of the revenue function of the renewable energy power generator is: The constraints of the renewable energy generator are: in, represents the expected revenue of renewable energy generators in time t; represents the electricity sales revenue of renewable energy generators in time t, Indicates user i Electricity purchased from renewable energy generators; represents the electricity price set by renewable energy generators in time t, It represents the power generation of renewable energy generators in time t; represents the electricity generation cost of renewable energy generators, represents the renewable energy subsidy income, ω represents the renewable energy subsidy factor, represents the on-grid electricity price of renewable energy in time t, It represents the on-grid electricity price of a traditional energy source in time t; It means that power suppliers charge renewable energy generators for access fees; They represent the lower and upper limits of the electricity price for renewable energy generators within time t.

2. The method according to claim 1, characterized in that: Before the power generator and the user play a master-slave game based on a pre-built master-slave game model, the method further includes: The energy regulator among the various types of participating entities calls the smart contract init function to open the power trading market so that the various types of participating entities can conduct power trading; After the power trading order is formed, the following steps are also included: Packaging and broadcasting the electricity trading order to the consensus nodes, and storing it after the consensus nodes reach a consensus; Calculate the trust between the power generator and the user, take corresponding measures based on the comparison result between the trust and the trust threshold, and store the result as a voucher for the next round of transactions; The smart contract bill function is automatically triggered to settle the transaction bill. At the same time, the trust range is taken into consideration to settle the participating entities that need to be fined.

3. A microgrid peer-to-peer power trading system based on blockchain, characterized in that: include: A registration unit, used for various types of participating entities to join the blockchain network as nodes and register their corresponding identity information; the various types of participating entities at least include power generators and users; A game unit is used for the power generator and the user to play a master-slave game based on a pre-built master-slave game model to obtain a master-slave game result, and the game unit includes: A user benefit calculation unit, used to obtain the user's optimal segmented power consumption based on the user's benefit function; The power generator profit calculation unit is used to feed back the optimal segmented power consumption of the user to the power generator, so that the power generator adopts the NSGA-Ⅱ multi-objective optimization algorithm to re-formulate the power price and send it to the user according to the energy consumption strategy of the user and the profit function of the power generator; The user benefit calculation unit is further used to recalculate the power consumption based on the user's benefit function according to the new electricity price, and feed it back to the power generator until the number of iterations is reached or an equilibrium solution is obtained; wherein the equilibrium solution is used to indicate that the user and the power generator achieve maximum benefits on the basis of satisfying their respective constraints; The expression of the user's profit function is: The user's constraints are: in, represents the expected revenue of user i in time t; represents the utility function of user i at time t, and represents the preference coefficient of user i for power consumption in time t, represents the amount of electricity purchased by user i from traditional energy generators within time t, W represents the amount of electricity purchased by user i from renewable energy power generators within time t, where the power generators include the traditional energy power generators and the renewable energy power generators; i t represents the cost function of user i in time t, represents the electricity price set by the traditional energy power generator within time t, represents the electricity price set by the renewable energy power generator within time t; It indicates the network access fee charged by the power supplier to user i; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the traditional energy generator; They respectively represent the lower limit and upper limit of the amount of electricity that user i can purchase from the renewable energy power generator; n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users. The users include the residential users, the commercial users, and the industrial users; The power generators include traditional energy power generators and renewable energy power generators. Accordingly, the revenue function of the power generators includes: the revenue function of the traditional energy power generators and the revenue function of the renewable energy power generators, wherein: The expression of the profit function of the traditional energy power generator is: The constraints of the traditional energy generators are: in, represents the expected revenue of traditional energy generators in time t; represents the electricity sales revenue of traditional energy generators in time t, n1 represents the number of residential users, n2 represents the number of commercial users, and n3 represents the number of industrial users, wherein the users include the residential users, the commercial users, and the industrial users; represents the amount of electricity purchased by user i from traditional energy generators within time t, represents the electricity price set by traditional energy generators in time t, P represents the power generation of traditional energy generators in time t, t represents the fixed price of the external large grid; represents the power generation cost of traditional energy generators, a, b, and c represent the power generation cost coefficients; represents the environmental governance incentive income of traditional energy power generators, p0 represents the incentive unit price of energy pollutant emissions per unit mass, Indicates the emission reduction, μ k represents the emission factor of the kth type of pollutant, represents the energy consumption of traditional energy generators in time t, represents the energy consumption of the power grid in time t; It means that the power supplier charges the traditional energy power generators a transmission fee; They represent the lower and upper limits of the electricity price of traditional energy generators in time t respectively; The expression of the revenue function of the renewable energy power generator is: The constraints of the renewable energy generator are: in, represents the expected revenue of renewable energy generators in time t; represents the electricity sales revenue of renewable energy generators in time t, Indicates user i Electricity purchased from renewable energy generators; represents the electricity price set by renewable energy generators in time t, It represents the power generation of renewable energy generators in time t; represents the electricity generation cost of renewable energy generators, represents the renewable energy subsidy income, ω represents the renewable energy subsidy factor, represents the on-grid electricity price of renewable energy in time t, It represents the on-grid electricity price of a traditional energy source in time t; It means that power suppliers charge renewable energy generators for access fees; They represent the lower and upper limits of the electricity price of renewable energy generators in time t respectively; A first storage and broadcasting unit, used for storing the user power consumption and the power price of the power generator corresponding to the master-slave game result, and broadcasting them to the power generator and the user; The trading unit is used for the power generator to publish the electricity price according to the result of the master-slave game, and at the same time, the user publishes the amount of electricity required by himself according to the result of the master-slave game, so as to conduct electricity trading and form an electricity trading order.

4. The system according to claim 3, characterized in that Also includes: An opening unit is used for energy regulators among the various types of participating entities to call the smart contract init function to open the power trading market so that the various types of participating entities can conduct power trading; A second storage and broadcasting unit, used for packaging and broadcasting the power trading order to the consensus nodes, and storing the order after the consensus nodes reach a consensus; A calculation storage unit, used to calculate the trust between the power generator and the user, take corresponding measures based on the comparison result between the trust and the trust threshold, and store the result as a voucher for the next round of transactions; The clearing unit is used to automatically trigger the smart contract bill function to clear transaction bills. At the same time, it takes into account the trust range and clears the participating entities that need to be fined.

Images