Electric vehicle frequency modulation transaction optimization method and system under multi-chain structure

Abstract

The invention discloses an electric vehicle frequency modulation transaction optimization method and system under a multi-chain structure. The method comprises the following steps: constructing an electric vehicle frequency modulation transaction model based on the multi-chain structure according to operation characteristics of an electric vehicle in an electricity market; based on the electric vehicle frequency modulation transaction model, obtaining a block chain-based electric vehicle frequency modulation transaction data evidence storage model and a chain forming mechanism; and designing an electric vehicle frequency modulation transaction contract for the intelligent contract part through an electric vehicle frequency modulation transaction data storage model and a chaining mechanism, and solving a target function to complete optimization of the electric vehicle frequency modulation transaction under a multi-chain structure. According to the method, data transparency and non-tampering of the electric vehicles participating in the frequency modulation service in the electricity market are ensured, and efficient recording and management of the whole process from declaration, execution to evaluation are realized by defining a detailed frequency modulation transaction data evidence storage process.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic optimization of power systems, and particularly to an optimization method and system for electric vehicle frequency modulation trading under a multi-chain structure. Background Technique

[0002] In the electric vehicle charging and frequency modulation ancillary service markets, aggregators, as the intermediate link coordinating the interaction between electric vehicles and the power grid, have to a certain extent solved the communication problem between vehicles, charging piles and the grid. However, aggregators aggregate a large number of charging piles and electric vehicle resources, and have greater information advantages than users. At the same time, as a profit entity, aggregators pay more attention to their own benefits when participating in the market. There are significant information barriers for users to participate in the market. At this time, aggregators are likely to take advantage of this information asymmetry to obtain higher benefits. Related research has explored from the perspective of electricity prices, considering dynamic prices and arranging charging times and deadlines to reduce the peak demand of charging stations. Some research uses game theory based on Nash equilibrium, considering the interaction between electricity prices and electric vehicle demand, and develops a day-ahead charging scheduling model; some research optimizes the strategies of electric vehicle aggregators by considering the uncertainty related to electricity prices; some research introduces a P2P energy trading system, in which the coordination of energy trading between electric vehicles is executed by aggregators. In addition, each electric vehicle also adopts an optimal charging scheduling strategy one day in advance to adjust its remaining or insufficient energy.

[0003] Existing research has made certain explorations on the application of blockchain technology in electric vehicles participating in the power market. Some research proposes a pricing mechanism that uses plug-in hybrid electric vehicles to balance local power demand. The pricing and traded electricity volume between plug-in electric vehicles are determined by an iterative double auction scheme to maximize social welfare. A consortium blockchain is established on local energy aggregators to audit, verify and protect transaction records without relying on a trusted third party. However, the iterative double auction mechanism is still executed by a third party outside the blockchain. Similarly, some research proposes a blockchain-based decentralized electric vehicle charging coordination scheme, which consists of two main steps: (1) First, fairly allocate charging power quotas among charging stations, and (2) Use a double auction mechanism for charging stations to exchange their allocated quotas with each other. This system is implemented through smart contracts. In addition, in order to effectively implement the auction mechanism on the blockchain, some research focuses on ensuring bid confidentiality and protecting auctions in a decentralized environment. To achieve the confidentiality effect, zero-knowledge proof protocols and trusted execution environment technologies are adopted.

[0004] At present, existing research has not solved the problems of privacy security and information transparency between aggregators and users. Aggregators still participate in the interaction between the power grid dispatching center and electric vehicle users as the central coordinating agency. The problems of privacy security and interest conflicts between aggregators and users have a greater impact on user enthusiasm. There is a lack of diverse vehicle-grid interaction channels, and the implementation details of smart contracts and how to settle prices during the trading period are not detailed enough. Summary of the Invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides an optimization method and system for electric vehicle frequency regulation trading under a multi-chain structure, which solves the problems of information asymmetry, privacy security, and interest conflicts between aggregators and users in the prior art, and the problem that the implementation details of smart contracts and the trading settlement mechanism are not yet perfect.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides an optimization method for electric vehicle frequency regulation trading under a multi-chain structure, including: constructing an electric vehicle frequency regulation trading model based on a multi-chain structure according to the operating characteristics of electric vehicles in the power market; based on the electric vehicle frequency regulation trading model, obtaining an electric vehicle frequency regulation trading data deposit model and a chain formation mechanism based on the blockchain; through the electric vehicle frequency regulation trading data deposit model and the chain formation mechanism, designing an electric vehicle frequency regulation trading contract for the smart contract part, and completing the optimization of the electric vehicle frequency regulation trading under the multi-chain structure by solving the objective function.

[0009] As a preferred solution of the optimization method for electric vehicle frequency regulation trading under the multi-chain structure of the present invention, wherein: the design of the electric vehicle frequency regulation trading contract for the smart contract part includes:

[0010] The battery loss generated when the electric vehicle feeds back electric energy to the power grid will cause potential costs. The electric vehicle obtains incentive income from the aggregators participating in frequency regulation. Then the total cost of the electric vehicle's charging / discharging behavior is expressed as:

[0011]

[0012] where represents the charging cost, represents the battery loss cost, represents the discharging profit, represents the reward fee paid by the aggregator; the charging cost is related to the charging price and charging power, and the battery loss The cost of charging, discharging and unit capacity loss w loss (i V ) is related to the discharge profit The incentive fee paid by the aggregator is related to the discharge price and discharge power. It is related to the amount of electricity charged and discharged by the participating electric vehicles;

[0013] The charging state of the electric vehicle s(i V ,t-1) changes with time and frequency modulation instructions:

[0014]

[0015] Among them, SOC(i V ,t)∈[0,1] is the battery state of the electric vehicle, and is the charging pile k coming from i at time t A a represents the charge / discharge power, and b represents the battery capacity.

[0016] As a preferred solution of the electric vehicle frequency modulation transaction optimization method under the multi-chain structure described in the present invention, the electric vehicle frequency modulation transaction contract designed for the smart contract part also includes:

[0017] The grid earns revenue by selling electricity to aggregators and also needs to pay frequency regulation incentives to aggregators. Electric vehicles participating in frequency regulation will incur additional costs, so the total revenue of the grid is It is expressed as:

[0018]

[0019] in, represents the revenue of the grid when supplying electricity to aggregators, represents the frequency regulation service revenue obtained by the power grid from the aggregator, and Represents the discharge and incentive fees paid by the grid to the aggregator; the discharge fee paid by the grid to the aggregator With discharge power and discharge price Regarding the incentive fees paid by the grid to the aggregator The frequency regulation service revenue that the power grid obtains from the aggregator is related to the frequency regulation power provided by the aggregator and the frequency regulation service price set by the power grid. With aggregators A It is related to the FM power provided at time t.

[0020] As a preferred solution of the electric vehicle frequency modulation transaction optimization method under the multi-chain structure described in the present invention, the electric vehicle frequency modulation transaction contract designed for the smart contract part also includes:

[0021] Aggregator The total revenue of is expressed as:

[0022]

[0023] Wherein, represents the charging fee paid from the electric vehicle to the aggregator, and represents the discharging and incentive fees obtained by the aggregator from the power grid for its participation in frequency regulation, represents the discharging fee of the electric vehicle paid by the aggregator to the electric vehicle, represents the charging fee paid by the aggregator to the power grid, represents the frequency regulation incentive fee paid by the aggregator to the electric vehicle.

[0024] As a preferred solution of the electric vehicle frequency regulation trading optimization method under the multi-chain structure described in the present invention, wherein: the solving of the objective function includes:

[0025] Based on the mathematical model between the designed trading entities, the dynamic multi-objective optimization problem is transformed into a single-objective problem, and the formula is expressed as:

[0026]

[0027] Wherein, O(·) represents the objective function, and the optimization variables are the charging / discharging prices within the system and the charging / discharging prices of each aggregator

[0028] For a set of reference solutions can be taken as the historical minimum value of the objective function, and each sub-problem is set to be expressed as g i (x). When the reference solution takes 0, each g i (x) can be scalarized as:

[0029]

[0030] Wherein, λ1 + λ2 + λ3 = 1;

[0031] The correlation between sub-problems is reflected by the Euclidean distance between weight vectors. Assuming there are N sub-problems, the neighborhood B(i) of each sub-problem is defined as the T weight vectors closest to the weight vector of the current sub-problem, B(i) = {j1, j2,..., j T};

[0032] Cross and mutation operations are used to generate candidate solutions, and according to the newly generated candidate solution y′, the reference solution z * ;

[0033] If f(y′|λ,z * )>f(x|λ,z * ), then update the solution, x = y′.

[0034] As a preferred solution of the electric vehicle frequency regulation transaction optimization method under the multi-chain structure of the present invention, wherein: the electric vehicle frequency regulation transaction model based on the multi-chain structure includes a power grid node, an aggregator node, a supervision node, a charging pile operator node and an electric vehicle;

[0035] The power grid nodes, aggregator nodes, and supervisory nodes jointly participate in the operation of the main blockchain, which adopts a two-layer architecture, that is, the main chain provides services for aggregators and power grid nodes, and any updates to the transaction rules will be responsible for consensus, publicity, and recording by the smart contract chain; the side chain is jointly maintained by the aggregators and the charging pile operators they aggregate, and electric vehicles participate in the side chain as flexible nodes.

[0036] As a preferred solution of the electric vehicle frequency modulation transaction optimization method under the multi-chain structure of the present invention, the electric vehicle frequency modulation transaction process includes:

[0037] Electric vehicle users can choose the depth of frequency modulation, expected frequency modulation period and battery status information according to their own wishes. Charging station operators will report their expected charging load capacity for the next day to the aggregator based on historical charging data;

[0038] The aggregator generates the expected frequency regulation capacity and price for each time period of the next day based on the data uploaded by the underlying layer, and uploads it to the grid node;

[0039] The grid node sorts the reported data from low to high, generates a sequence of aggregators that are qualified for frequency regulation in each period, and returns the results to each aggregator. The aggregator forms a pre-dispatch plan for the next day based on the results and the expected status of each charging pile operator and electric vehicle, and sends it to each sub-unit;

[0040] The aggregator updates the frequency regulation reserve capacity for the next period based on the current location, SOC status and charging pile status of the electric vehicle. The grid node sends a frequency regulation instruction to the aggregator, which decomposes the frequency regulation instruction to form a frequency regulation plan for the electric vehicles on the grid in the current period. The charging pile operator will adjust the charging power of the electric vehicles on the station in response to the plan for the current period.

[0041] Electric vehicles and smart charging piles will upload their own recorded response data, which will be verified by the aggregator and consensus node and then reported to the grid node by the aggregator.

[0042] The grid nodes form an aggregator frequency regulation evaluation based on the data, which is certified by the supervision nodes and consensus nodes and then announced to the entire network. The aggregator distributes frequency regulation revenue to electric vehicle and charging pile operators based on their response speed during the frequency regulation stage.

[0043] In a second aspect, the present invention provides an optimized system for electric vehicle frequency regulation trading under a multi-chain structure, including:

[0044] A frequency regulation trading model construction module, configured to construct an electric vehicle frequency regulation trading model based on a multi-chain structure according to the operating characteristics of electric vehicles in the electricity market;

[0045] A chain formation process acquisition module, configured to obtain an electric vehicle frequency regulation trading data deposit model and a chain formation mechanism based on a blockchain based on the electric vehicle frequency regulation trading model;

[0046] An optimization solving module, configured to design an electric vehicle frequency regulation trading contract for the smart contract part through the electric vehicle frequency regulation trading data deposit model and the chain formation mechanism, and complete the optimization of the electric vehicle frequency regulation trading under the multi-chain structure by solving the objective function.

[0047] In a third aspect, the present invention provides an electronic device, including:

[0048] A memory and a processor;

[0049] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for optimizing electric vehicle frequency regulation trading under a multi-chain structure are implemented.

[0050] In a fourth aspect, the present invention provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the steps of the method for optimizing electric vehicle frequency regulation trading under the multi-chain structure are implemented.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides a method and system for optimizing electric vehicle frequency regulation trading under a multi-chain structure. By establishing an electric vehicle frequency regulation trading model under a multi-chain structure, it not only ensures the data transparency and immutability of electric vehicles participating in frequency regulation services in the electricity market, but also realizes the efficient recording and management of the whole process from declaration, execution to evaluation by defining a detailed frequency regulation trading data deposit process. Moreover, the present invention enhances the stability and reliability of the system while ensuring flexibility by designing a smart contract chain and clearly defining the editable part in the smart contract and its corresponding relationship with the mathematical models of each frequency regulation entity in the system. In addition, the adopted hierarchical blockchain architecture has the characteristics of modularity and automated operation, and can automatically execute optimization strategies based on smart contracts, making the interest distribution among different participants more reasonable, not only improving the efficiency of the entire frequency regulation trading process, but also promoting the healthy development of the electricity market, and finally realizing the effective combination of technological innovation and market demand. Description of the Drawings

[0052] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0053] Figure 1 It is a schematic diagram of the overall process logic of the electric vehicle frequency regulation trading optimization method under the multi-chain structure according to an embodiment of the present invention;

[0054] Figure 2 It is the electric vehicle frequency regulation trading architecture based on the multi-chain structure of the electric vehicle frequency regulation trading optimization method according to an embodiment of the present invention;

[0055] Figure 3 It is a schematic diagram of the electric vehicle frequency regulation trading process of the electric vehicle frequency regulation trading optimization method under the multi-chain structure according to an embodiment of the present invention;

[0056] Figure 4 It is a framework diagram of the electric vehicle frequency regulation trading data deposit and proof model based on the blockchain of the electric vehicle frequency regulation trading optimization method under the multi-chain structure according to an embodiment of the present invention;

[0057] Figure 5 It is a schematic diagram of the process of uploading the electric vehicle frequency regulation trading data to the blockchain of the electric vehicle frequency regulation trading optimization method under the multi-chain structure according to an embodiment of the present invention;

[0058] Figure 6 It is an optimization flow chart for solving the objective function of the electric vehicle frequency regulation trading optimization method under the multi-chain structure according to an embodiment of the present invention. Specific Embodiments

[0059] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will provide a detailed description of the specific embodiments of the present invention in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0060] Embodiment 1

[0061] Referring to Figure 1 For an embodiment of the present invention, an electric vehicle frequency regulation trading optimization method under a multi-chain structure is provided. As Figure 1 shown, it specifically includes the following steps:

[0062] S100: Construct an electric vehicle frequency regulation trading model based on a multi-chain structure according to the operating characteristics of electric vehicles in the power market;

[0063] S200: Based on the electric vehicle frequency regulation trading model, obtain an electric vehicle frequency regulation trading data deposit and certification model and a chain formation mechanism based on blockchain;

[0064] S300: Through the electric vehicle frequency regulation trading data deposit and certification model and the chain formation mechanism, design an electric vehicle frequency regulation trading contract for the smart contract part, and complete the optimization of the electric vehicle frequency regulation trading under the multi-chain structure by solving the objective function.

[0065] It should be noted that there are problems of information asymmetry, privacy security, and interest conflicts between aggregators and users in the existing technology, and the implementation details of smart contracts and the transaction settlement mechanism are not yet perfect. The above steps S100 to S300 not only ensure the data transparency and immutability of electric vehicles participating in frequency regulation services in the power market by establishing a multi-chain structure electric vehicle frequency regulation trading model, but also realize efficient recording and management of the whole process from declaration, execution to evaluation by defining a detailed frequency regulation trading data deposit and certification process. Moreover, the present invention enhances the stability and reliability of the system while ensuring flexibility by designing a smart contract chain and clearly defining the editable part in the smart contract and its corresponding relationship with the mathematical models of each frequency regulation entity in the system. In addition, the adopted hierarchical blockchain architecture has the characteristics of modularization and automated operation, and can automatically execute optimization strategies based on smart contracts, making the interest distribution between different participants more reasonable, not only improving the efficiency of the whole frequency regulation trading process, but also promoting the healthy development of the power market, and finally realizing the effective combination of technological innovation and market demand.

[0066] Embodiment 2

[0067] Refer to Figures 2 to 6 For an embodiment of the present invention, based on the previous embodiment, an optimization method for electric vehicle frequency regulation trading under a multi-chain structure is provided, which specifically includes:

[0068] In the embodiment of the present application, the above step S100 of constructing an electric vehicle frequency regulation trading model based on a multi-chain structure according to the operating characteristics of electric vehicles in the power market includes:

[0069] Specifically, the electric vehicle frequency regulation trading architecture with a multi-chain structure is as Figure 2As shown in the figure, the frequency regulation trading model for electric vehicles based on a multi-chain structure includes a grid node, an aggregator node, a supervision node, a charging pile operator node, and electric vehicles. Among them, the grid node, the aggregator node, and the supervision node jointly participate in the operation of the main blockchain. The main blockchain adopts a two-layer architecture, that is, the main chain provides services for aggregators and grid nodes. At the same time, any update to the trading rules will be responsible for consensus, publicity, and recording by the smart contract chain. The side chain is jointly maintained by each aggregator and the charging pile operators aggregated by it, and electric vehicles participate in the side chain as flexible nodes.

[0070] Specifically, for the grid node: At the business level, the grid dispatching center can review the frequency regulation capacity declared by each aggregator for the next day through this node, verify its frequency regulation qualification through the frequency regulation evaluation of each aggregator, and issue the next-day pre-frequency regulation plan to each aggregator. The grid trading center can review the frequency regulation quotes submitted by aggregators through this node. The review results of both will be summarized into the next-day frequency regulation sequence of aggregators. At the same time, at the real-time stage, this node is responsible for the release of frequency regulation signals and marginal clearing prices, and issues real-time frequency regulation adjustment tasks to each aggregator. From the perspective of system maintenance, the grid node mainly operates on the main chain, responsible for reviewing the access qualifications of aggregators, packaging transaction blocks and sending them to the main chain consensus nodes, receiving consensus receipts, broadcasting the consensus results across the network, and uploading the consensus blocks to the chain, etc.

[0071] Specifically, for the aggregator node: From a business perspective, the aggregator predicts its own frequency regulation ability in advance, declares trading information such as frequency regulation capacity and frequency regulation price to the grid node. After obtaining the frequency regulation qualification, it issues the next-day pre-frequency regulation plan downward. During the day, the aggregator is mainly responsible for responding to the frequency regulation instructions in the real-time stage upward, decomposing the frequency regulation instructions and sending them to each frequency regulation electric vehicle, matching suitable charging piles for electric vehicles according to vehicle and charging pile conditions, correcting the frequency regulation incentives, and controlling the frequency regulation error. From the perspective of system maintenance, some aggregator nodes act as consensus nodes on the main chain, conduct consensus on newly generated blocks on the main chain and return the consensus results with digital signatures. At the same time, the behavior of each aggregator to correct the frequency regulation incentives must generate its own block and broadcast it to the consensus nodes (excluding itself). After consensus, it is broadcast across the network, and only then can this correction take effect. On the side chain, each aggregator node acts as the main node to package and generate blocks, broadcast them to the side chain consensus nodes, receive side chain consensus receipts, and complete the operation of uploading side chain blocks to the chain.

[0072] Specifically, for the supervision node: It maintains the normal operation of the system, has the power of punishment, and has the ability to broadcast across the main and side chains. It is mainly responsible for supervising node behaviors on the main and side chains, such as whether aggregators participate in frequency regulation declarations on time, whether the declared content meets system constraints, whether grid nodes correctly perform their node duties, and whether electric vehicles participating in frequency regulation fail to perform frequency regulation during the specified period. Punishment measures will be taken against malicious action nodes.

[0073] Specifically, for the charging pile operator node: At the business level, it provides the real-time available status of charging piles in the station to the superior aggregator, provides charging services to electric vehicles, and opens the real-time power data of the charging piles participating in frequency regulation. At the system operation level, some charging pile operators serve as consensus nodes to provide consensus services for the main bodies of each side chain, and return the consensus results with digital signatures to the superior aggregator node.

[0074] Specifically, for electric vehicles: Also known as free nodes, electric vehicles participating in frequency regulation services need to log in to the blockchain network during the specified period to participate in frequency regulation operations. At the business level, in a certain frequency regulation operation, electric vehicles need to open their own privacy data to the aggregator to different degrees according to the depth of participation in frequency regulation. The declarations of electric vehicles participating in active frequency regulation need to comply with system constraints. At the system maintenance level, electric vehicle nodes need to maintain network connection and data sharing during the frequency regulation service, and cannot go offline privately or disconnect the connection with the charging pile within the frequency regulation service period.

[0075] Furthermore, in the embodiment of the present application, a business process for electric vehicles to participate in the frequency regulation market includes two stages: day-ahead and intra-day. Among them, in the day-ahead stage, the aggregator will declare the frequency regulation plan to the power grid according to the regulation ability of its aggregated resources. The power grid will issue the pre-frequency regulation plan for the next day according to the frequency regulation capabilities of each aggregator. In the intra-day stage, the aggregator responds to each frequency regulation signal of the power grid and completes the frequency regulation task during each frequency regulation period. Finally, the power grid evaluates and clears and settles the completion degree of the aggregator's frequency regulation task. The trading process is as Figure 3 shown, and the specific process includes:

[0076] Underlying data upload: Since some vehicles do not support external power discharge, and external power discharge has certain damage to the electric vehicle battery, electric vehicle users first need to select information such as the depth of participation in frequency regulation, the expected frequency regulation period, and the battery status according to their own wishes. This selection will have a greater impact on the frequency regulation ability of the aggregator. Secondly, the charging pile operator will report the expected charging load capacity for the next day to the aggregator according to historical charging data.

[0077] Frequency regulation ability reporting: The aggregator forms the expected frequency regulation capacity and frequency regulation price for each period of the next day based on the data uploaded from the bottom layer and uploads them to the power grid node.

[0078] Pre-frequency regulation plan generation: The power grid node sorts the aggregators by period from low to high according to the frequency regulation prices reported by each aggregator, generates the aggregator sequence eligible for frequency regulation in each period, and returns the result to each aggregator. The aggregator forms the next-day pre-scheduling plan according to the result and the expected status of each charging pile operator and electric vehicle, and issues it to each subunit.

[0079] Real-time frequency modulation: The aggregator updates the frequency modulation reserve capacity for the next time period based on the current location, SOC status, and charging pile status of electric vehicles. The grid node sends a frequency modulation command to the aggregator. After decomposing the frequency modulation command, the aggregator forms a frequency modulation plan for the electric vehicles connected to the grid during the current time period. The charging pile operator will respond to the plan during the current time period and adjust the charging power of the electric vehicles at the station.

[0080] Response data reporting: Electric vehicles and intelligent charging piles will each upload the response data they record. After being authenticated by the aggregator and the consensus nodes without error, the aggregator will summarize and report it to the grid node.

[0081] Settlement and clearing: The grid node forms an aggregator frequency modulation evaluation based on data such as the frequency modulation response speed and frequency modulation deviation of each aggregator. This evaluation is authenticated by the supervision node and the consensus node and then publicly displayed to the whole network. The frequency modulation evaluation of the aggregator is updated, and the frequency modulation income is settled to the aggregator according to the frequency modulation market price. The aggregator distributes the frequency modulation income to the electric vehicles and the charging pile operator according to their response speeds during the frequency modulation stage.

[0082] It should be noted that the above step S100 not only enhances the flexibility and response speed of the system, but also ensures the security, transparency, and immutability of all transactions through blockchain technology, laying a solid foundation for subsequent data storage, smart contract design, and transaction optimization.

[0083] In the embodiment of the present application, the above step S200 is based on the electric vehicle frequency modulation trading model, and the data storage model and chain formation mechanism for electric vehicle frequency modulation trading based on blockchain include:

[0084] Specifically, due to the differences in the participating entities of each blockchain and the different functions of each blockchain, the chain formation methods of each blockchain also vary. This difference will further affect the methods of data storage in the system, such as Figure 4 The figure shows a schematic diagram of the data storage model designed in this embodiment. The chain formation process of each blockchain will be described below.

[0085] In the embodiment of the present application, as Figure 5The main chain shown is mainly jointly operated by grid nodes, aggregator nodes, and supervision nodes. After receiving data reports from electric vehicle and charging pile operators, the aggregator summarizes them to form its own frequency regulation plan, attaches its own digital signature, and uploads it to the grid node. The grid node reviews the frequency regulation plans reported by each aggregator and sorts them by price to form the pre-frequency regulation plans of each aggregator, attaches its own digital signature, and broadcasts them to the consensus nodes served by some aggregator nodes for verification. After each consensus node verifies without error, it attaches its own digital signature and broadcasts it to the supervision node. If the supervision node has no objection to the process of the corresponding data from reporting to passing the consensus, it attaches its own digital signature, generates a new block, which is temporarily managed by the supervision node, and the corresponding pre-frequency regulation plan will be sent to each aggregator node. After the aggregator completes the frequency regulation task in the real-time stage, it submits information such as the actual frequency regulation capacity, frequency regulation price, and frequency regulation time period to the grid node. The grid node checks the aggregator information according to the system operation conditions, attaches its own digital signature, and broadcasts it to the consensus node. After the consensus is passed, the consensus node attaches its digital signature and broadcasts it to the supervision node. After the supervision node confirms, the system will generate the frequency regulation evaluation of each aggregator according to the corresponding information, and the data will finally be stored in the block generated on the day by the supervision node, and the blockchain will be linked to the main chain.

[0086] In the embodiment of the present application, the side chain is mainly jointly maintained by aggregator nodes, charging pile operator nodes, and supervision nodes. Electric vehicles participate in the side chain frequency regulation response as free nodes. After receiving the pre-frequency regulation plan, the aggregator node will plan according to the expected status of electric vehicles and charging pile operators in each period and form a preliminary lower-level frequency regulation plan, attach a digital signature, and broadcast it to the consensus node served by the charging pile operator for consensus. After the consensus node verifies without error, it is handed over to the supervision node for confirmation. After confirmation, each attaches its own digital signature. After the above process, this pre-frequency regulation plan is recorded in the new block, and at the same time, the pre-frequency regulation plan is sent to each electric vehicle and charging pile operator. After the electric vehicle and the charging pile operator digitally sign the real-time frequency regulation data respectively, they upload it to the aggregator node. After the aggregator compares and confirms, it attaches its own digital signature and broadcasts it to the consensus node served by the charging pile operator. After the consensus node reaches a consensus and attaches a digital signature, it broadcasts it to the supervision node. After the supervision node confirms, the system will generate the frequency regulation evaluation of the electric vehicle and the charging pile operator. The supervision node stores the corresponding data of each node in the new block generated on the day and links the block to the side chain.

[0087] In the embodiment of the present application, the smart contract chain is jointly maintained by main chain nodes, side chain nodes, and supervision nodes. Free nodes also have the right to review the public information of this chain. Here, it should be noted that Figure 3The data recorded in the block shown is not the entire content of the smart contract. The data shown in the figure is only the adjustable part of the smart contract, and does not involve the specific values ​​of the node's income and frequency evaluation, but the parameter changes in the calculation of income and frequency evaluation. It should be clear that such adjustments are not frequent in the system and have strict time and frequency limits. The grid nodes in the system have the right to submit adjustment applications to the supervisory nodes, but all nodes still need to pass (considering the free characteristics of electric vehicle nodes, this clause can be appropriately relaxed, and other nodes need to pass all nodes, and the top 90% of the nodes in the frequency evaluation of electric vehicle nodes can pass); for nodes outside the grid nodes, their frequency evaluation needs to meet the system-set standards before they can submit change requests to the supervisory nodes. The passing conditions of the adjustment details are the same as above, and then they can be checked by the supervisory nodes and broadcast to the consensus nodes. After being correct, this content will form a new smart contract block of the whole network consensus together with the unchangeable part of the smart contract, and the contract block is linked to the smart contract chain by the supervisory node.

[0088] It should be noted that the above step S200 ensures that the entire process from data generation to recording on the chain is transparent, secure and cannot be tampered with, providing reliable audit tracking and evidence support for frequency modulation transactions at all stages, while simplifying the data management and verification process, enhancing the trust of all parties involved and the overall reliability of the system.

[0089] In the embodiment of the present application, the above step S300 designs an electric vehicle frequency modulation transaction contract for the smart contract part through the electric vehicle frequency modulation transaction data notarization model and chain formation mechanism, and completes the optimization of the electric vehicle frequency modulation transaction under the multi-chain structure by solving the objective function, including:

[0090] Specifically, the electric vehicle contract cost model includes:

[0091] EV owners should pay charging fees to aggregators during EV charging and receive benefits from aggregators when EVs feed power back to the grid to achieve grid frequency regulation. In addition, the resulting battery losses will cause potential costs, while EVs can receive incentive income from aggregators participating in frequency regulation. Therefore, the total cost of EV charging / discharging behavior is It can be described as:

[0092]

[0093] in, represents the charging cost, represents the battery loss cost, represents the discharge profit, Represents the incentive fee paid by the aggregator; Charging cost Related to charging price and charging power, battery loss Related to the charging amount, discharging amount, and unit capacity loss cost w loss (i V ) Related, the discharging profit Is related to the discharging price and discharging power, and the reward cost paid by the aggregator Is related to the charging and discharging power of the electric vehicles participating, and is expressed by the formula:

[0094]

[0095]

[0096] Among them, And Represent the charging / discharging power of charging pile k from aggregator i at time t, A The charging / discharging power, And Represent the charging / discharging price at time t, [T s , T e Represents the charging / discharging time interval, [T s1 , T e1 And [T s2 , T e2 Represent the charging and discharging time intervals, η + And η - Represent the incentive prices for upward / downward frequency modulation;

[0097] It should be noted that the electric vehicle has three states: charging, waiting to charge, and discharging, which can be represented by state variables of 1, 0, and -1. The charging state s(i V , t - 1) changes with time and the frequency modulation command:

[0098]

[0099] Among them, SOC(i V , t) ∈ [0, 1] is the state of the electric vehicle battery, And Are the charging / discharging power of charging pile k from aggregator i at time t, b represents the battery capacity, and each electric vehicle user expects to charge the battery to the maximum allowable value SOC A During charging, and only discharge the battery to the minimum allowable value SOC max (i V ) During discharging, and only discharge the battery to the minimum allowable value SOC min (i V ).

[0100] Furthermore, the grid contract cost model includes:

[0101] As a power supplier, the power grid can obtain revenue by selling electricity to aggregators, while also paying the aggregators for frequency regulation incentives. Due to the possible frequency fluctuations caused by electric vehicles participating in frequency regulation, additional costs will be incurred. Therefore, the total revenue of the power grid can be summarized as:

[0102]

[0103] where, represents the revenue of the power grid when supplying electricity to the aggregator, represents the revenue from frequency regulation services obtained by the power grid from the aggregator, and represent the discharge and incentive fees paid by the power grid to the aggregator; the discharge fee paid by the power grid to the aggregator is related to the discharge power and the discharge price ; the incentive fee paid by the power grid to the aggregator is related to the frequency regulation power provided by the aggregator and the frequency regulation service price set by the power grid. The revenue from frequency regulation services obtained by the power grid from the aggregator is related to the frequency regulation power provided by aggregator i A at time t. It is expressed by the formula:

[0104]

[0105]

[0106] where, represents the charging power of aggregator i A at time t, represents the charging price at time t, p prov (i A ,t) represents the frequency regulation power provided by aggregator i A at time t, ρ(i A ,t) represents the incentive price set by the power grid for aggregator i A . A quadratic function with parameters α and β is used to describe for simplicity and the required frequency regulation power p req (t) relationship.

[0107] Furthermore, the aggregator contract cost model includes:

[0108] The aggregator is the medium between its subordinate nodes and the power grid. It not only makes a profit by providing electric energy for electric vehicles to participate in frequency regulation to the charging pile operator, but also obtains benefits from the power grid by providing frequency regulation services to the power grid. At the same time, the aggregator should pay the reward fees for electric vehicles to participate in frequency regulation. Therefore, the aggregator 's total revenue can be calculated as:

[0109]

[0110] Among them, represents the charging cost paid by the electric vehicle to the aggregator, and represents the discharging and incentive costs obtained by the aggregator from the power grid for its participation in frequency regulation, represents the discharging cost of the electric vehicle paid by the aggregator to the electric vehicle, represents the charging fee paid by the aggregator to the power grid, represents the frequency regulation incentive cost paid by the aggregator to the electric vehicle;

[0111] As mentioned in the contract The sum of And the constitutes From the above analysis of the electric vehicle cost and the power grid benefit, the entire involved cost can be described as:

[0112]

[0113] Furthermore, solving the objective function includes:

[0114] Based on the mathematical model between the trading entities designed above, the dynamic multi-objective optimization problem of maximizing the interests of each participant can be transformed into a single-objective problem, and the solution process is as Figure 6 shown, and the formula is expressed as:

[0115]

[0116] Among them, O(·) represents the objective function, and the optimization variables are the charging / discharging prices within the system and the charging / discharging prices of each aggregator During the charging and discharging process, the aggregator can obtain profits through the price difference ;

[0117] For a set of reference solutions It can be taken as the historical minimum value of the objective function. Assuming that each sub-problem is expressed as g i (x), when the reference solution takes 0, each g i (x) can be scalarized as:

[0118]

[0119] Among them, λ1 + λ2 + λ3 = 1;

[0120] The correlation between sub-problems is reflected by the Euclidean distance between weight vectors. Suppose there are N sub-problems, and the neighborhood B(i) of each sub-problem is defined as the T weight vectors closest to the weight vector of the current sub-problem, B(i) = {j1, j2,..., j T}, and the Euclidean distance can be expressed as follows:

[0121]

[0122] Crossover and mutation operations are used to generate candidate solutions:

[0123] y = Crossover(g i (x), g j (x)), j ∈ B(i)

[0124] y′ = Mutation(y)

[0125] According to the newly generated candidate solution y′, the reference solution z is updated * :

[0126]

[0127] If then update the solution, x = y′.

[0128] It should be noted that the above step S300 is solved through the smart contract mechanism and the objective function, and directly optimizes the frequency regulation trading of electric vehicles under the multi-chain structure, ensuring that the trading process is not only efficient and transparent, but also automatically executed, reducing the possibility of human intervention. Using smart contracts can automatically trigger and execute preset rules, making the decomposition and response of frequency regulation instructions faster and more accurate. At the same time, through the optimization of the objective function, while meeting the grid demand, the benefit distribution of aggregators and participating electric vehicles is maximized, improving the flexibility and resource utilization rate of the entire power system.

[0129] Embodiment 3

[0130] In this embodiment, an optimization system for frequency regulation trading of electric vehicles under a multi-chain structure is provided, including:

[0131] A frequency regulation trading model construction module for constructing a frequency regulation trading model of electric vehicles based on a multi-chain structure according to the operating characteristics of electric vehicles in the power market;

[0132] A chain formation process acquisition module for obtaining a blockchain-based data deposit model and chain formation mechanism for frequency regulation trading of electric vehicles based on the frequency regulation trading model of electric vehicles;

[0133] An optimization solving module is used to design an electric vehicle frequency regulation trading contract for the smart contract part through an electric vehicle frequency regulation trading data deposit and chain formation mechanism, and complete the optimization of the electric vehicle frequency regulation trading under the multi-chain structure by solving the objective function.

[0134] It should be noted that the technical solution of the system for optimizing the electric vehicle frequency regulation trading under the multi-chain structure belongs to the same concept as the technical solution of the above-mentioned method for optimizing the electric vehicle frequency regulation trading under the multi-chain structure. For the details not described in detail in the technical solution of the system for optimizing the electric vehicle frequency regulation trading under the multi-chain structure in this embodiment, reference can be made to the description of the technical solution of the method for optimizing the electric vehicle frequency regulation trading under the multi-chain structure.

[0135] The above-mentioned unit modules can be embedded in the processor in the computer device in hardware form or be independent of the processor, or can be stored in the memory in the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to the above-mentioned modules.

[0136] This embodiment also provides an electronic device, which includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication) or other technologies. When the computer program is executed by the processor, it realizes a method for optimizing the electric vehicle frequency regulation trading under a multi-chain structure. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or can also be a button, a trackball or a touchpad set on the shell of the computer device, or can also be an external keyboard, a touchpad or a mouse, etc.

[0137] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by the processor, it realizes the method proposed in the above-mentioned embodiment.

[0138] The storage medium proposed in this embodiment and the method proposed in the above-mentioned embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above-mentioned embodiment, and this embodiment has the same beneficial effects as the above-mentioned embodiment.

[0139] From the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software and the necessary general-purpose hardware. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disc of a computer, and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the method of the embodiments of the present invention.

[0140] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

[0141] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, system, or computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages.

[0142] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the function specified in the flowchart(s) Figure 1 a flowchart or flowcharts and / or block(s) Figure 1 a block or blocks.

[0144] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the function specified in the flowchart(s) Figure 1 a flowchart or flowcharts and / or block(s) Figure 1 a block or blocks.

[0145] Although the preferred embodiments of the present application have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0146] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A method for optimizing electric vehicle frequency modulation transactions under a multi-chain structure, characterized in that: include: According to the operating characteristics of electric vehicles in the power market, an electric vehicle frequency regulation trading model based on a multi-chain structure is constructed; Based on the electric vehicle frequency modulation transaction model, obtain the electric vehicle frequency modulation transaction data notarization model and chain formation mechanism based on blockchain; Through the electric vehicle frequency modulation transaction data notarization model and chain mechanism, an electric vehicle frequency modulation transaction contract for the smart contract part is designed, and the optimization of electric vehicle frequency modulation transaction under the multi-chain structure is completed by solving the objective function.

2. The electric vehicle frequency modulation transaction optimization method under the multi-chain structure according to claim 1 is characterized in that: The electric vehicle frequency regulation trading contract designed for the smart contract part includes: The battery loss caused by electric vehicles feeding power back to the grid will cause potential costs. Electric vehicles receive incentive income from aggregators participating in frequency regulation. The total cost of electric vehicle charging / discharging behavior is It is expressed as: in, represents the charging cost, represents the battery loss cost, represents the discharge profit, represents the incentive fee paid by the aggregator; the charging cost The battery loss is related to the charging price and charging power. The cost of charging, discharging and unit capacity loss w loss (i V ) is related to the discharge profit The incentive fee paid by the aggregator is related to the discharge price and discharge power. It is related to the amount of electricity charged and discharged by the participating electric vehicles; The charging state of the electric vehicle s(i V ,t-1) changes with time and frequency modulation instructions: Among them, SOC(i V ,t)∈[0,1] is the battery state of the electric vehicle, and is the charging pile k coming from i at time t A a represents the charge / discharge power, and b represents the battery capacity.

3. The electric vehicle frequency modulation transaction optimization method under the multi-chain structure as claimed in claim 2 is characterized in that: The electric vehicle frequency regulation transaction contract designed for the smart contract part also includes: The grid earns revenue by selling electricity to aggregators and also needs to pay frequency regulation incentives to aggregators. Electric vehicles participating in frequency regulation will incur additional costs, so the total revenue of the grid is It is expressed as: in, represents the revenue of the grid when supplying electricity to aggregators, represents the frequency regulation service revenue obtained by the power grid from the aggregator, and Represents the discharge and incentive fees paid by the grid to the aggregator; the discharge fee paid by the grid to the aggregator With discharge power and discharge price Regarding the incentive fees paid by the grid to the aggregator The frequency regulation service revenue that the power grid obtains from the aggregator is related to the frequency regulation power provided by the aggregator and the frequency regulation service price set by the power grid. With aggregators A It is related to the FM power provided at time t.

4. The electric vehicle frequency modulation transaction optimization method under the multi-chain structure as claimed in claim 3 is characterized in that: The electric vehicle frequency regulation transaction contract designed for the smart contract part also includes: Aggregators The total revenue is expressed as: in, represents the charging fee paid from the EV to the aggregator, and represents the discharge and incentive fees that the aggregator receives from the grid for participating in frequency regulation, represents the EV discharge fee paid by the aggregator to the EV, represents the charging fee paid by the aggregator to the grid, Represents the frequency regulation incentive fee paid by aggregators to EVs.

5. The electric vehicle frequency modulation transaction optimization method under the multi-chain structure as claimed in claim 4 is characterized in that: The solving of the objective function comprises: Based on the mathematical model between the designed transaction entities, the dynamic multi-objective optimization problem is transformed into a single-objective problem, which is expressed as follows: Where O(·) represents the objective function, and the optimization variable is the charging / discharging price in the system and the charging / discharging prices of each aggregator For a set of reference solutions It can be taken as the historical minimum value of the objective function, and each sub-problem is represented by g i (x), when the reference solution is 0, each g i (x) can be scalarized as: Among them, λ1+λ2+λ3=1; The Euclidean distance between weight vectors reflects the correlation between subproblems. Assuming there are N subproblems, define the neighborhood B(i) of each subproblem as the T weight vectors closest to the weight vector of the current subproblem, B(i) = {j1, j2, ..., j T }; Use crossover and mutation operations to generate candidate solutions, and update the reference solution z according to the newly generated candidate solution y′ * ; If f(y′|λ,z * )>f(x|λ,z * ), then update the solution, x = y′.

6. The electric vehicle frequency modulation transaction optimization method under the multi-chain structure as claimed in claim 1, characterized in that: The electric vehicle frequency modulation trading model based on the multi-chain structure includes a grid node, an aggregator node, a supervision node, a charging pile operator node and an electric vehicle; The power grid nodes, aggregator nodes, and supervisory nodes jointly participate in the operation of the main blockchain, which adopts a two-layer architecture, that is, the main chain provides services for aggregators and power grid nodes, and any updates to the transaction rules will be responsible for consensus, publicity, and recording by the smart contract chain; the side chain is jointly maintained by the aggregators and the charging pile operators they aggregate, and electric vehicles participate in the side chain as flexible nodes.

7. The electric vehicle frequency modulation transaction optimization method under the multi-chain structure as claimed in claim 6, characterized in that: The electric vehicle frequency regulation transaction process includes: Electric vehicle users can choose the depth of frequency modulation, expected frequency modulation period and battery status information according to their own wishes. Charging station operators will report their expected charging load capacity for the next day to the aggregator based on historical charging data; The aggregator generates the expected frequency regulation capacity and price for each time period of the next day based on the data uploaded by the underlying layer, and uploads it to the grid node; The grid node sorts the reported data from low to high, generates a sequence of aggregators that are qualified for frequency regulation in each period, and returns the results to each aggregator. The aggregator forms a pre-dispatch plan for the next day based on the results and the expected status of each charging pile operator and electric vehicle, and sends it to each sub-unit; The aggregator updates the frequency regulation reserve capacity for the next period based on the current location, SOC status and charging pile status of the electric vehicle. The grid node sends a frequency regulation instruction to the aggregator, which decomposes the frequency regulation instruction to form a frequency regulation plan for the electric vehicles on the grid in the current period. The charging pile operator will adjust the charging power of the electric vehicles on the station in response to the plan for the current period. Electric vehicles and smart charging piles will upload their own recorded response data, which will be verified by the aggregator and consensus node and then reported to the grid node by the aggregator. The grid nodes form an aggregator frequency regulation evaluation based on the data, which is certified by the supervision nodes and consensus nodes and then announced to the entire network. The aggregator distributes frequency regulation revenue to electric vehicle and charging pile operators based on their response speed during the frequency regulation stage.

8. A system using the electric vehicle frequency modulation transaction optimization method under the multi-chain structure as described in any one of claims 1 to 7, characterized in that: include: The frequency regulation trading model building module is used to build an electric vehicle frequency regulation trading model based on a multi-chain structure according to the operating characteristics of electric vehicles in the power market; A chaining process acquisition module, used to acquire a blockchain-based electric vehicle frequency modulation transaction data notarization model and a chaining mechanism based on the electric vehicle frequency modulation transaction model; The optimization solution module is used to design the electric vehicle frequency modulation transaction contract for the smart contract part through the electric vehicle frequency modulation transaction data notarization model and chain mechanism, and complete the optimization of the electric vehicle frequency modulation transaction under the multi-chain structure by solving the objective function.

9. An electronic device, comprising a memory and a processor, characterized in that: The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method according to claims 1 to 7 are implemented.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer executable instructions are executed by a processor, the steps of the method according to claims 1 to 7 are implemented.

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