Method, system and device for managing flexible resource participation in green electricity trading and medium

Abstract

The present application relates to the technical field of green electricity transaction management, and discloses a management method, system and device for flexible resources participating in green electricity transaction and a medium, real-time operation data of each flexible resource subject available for green electricity transaction is acquired; a charging and discharging multi-period optimization model is constructed based on a preset charging and discharging benefit objective function to obtain the charging and discharging benefit of the flexible resource subject; a frequency modulation capacity allocation model is constructed based on a preset power grid frequency modulation benefit objective function to obtain the frequency modulation service benefit of the flexible resource subject; according to the charging and discharging benefit and the frequency modulation service benefit, when the preset power grid frequency modulation triggering condition is met or the frequency modulation service benefit is greater than the charging and discharging benefit, the power grid frequency modulation mode is switched to, and when the flexible resource subject is in a power price low valley period and the state of charge of the flexible resource subject is less than a preset power price low valley charging threshold, the green electricity transaction mode is returned to. The method of the present application improves the supply and demand matching capability and power supply reliability of green electricity transaction.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of green electricity transaction management, and particularly relates to a management method, system and device for flexible resources participating in green electricity transaction and a medium. BACKGROUND

[0002] With the emphasis on environmental protection worldwide, green electricity transaction has become an important part of the electricity market. Through green electricity transaction, power producers can obtain carbon emission reduction certificates to quantify the contribution of their clean energy production to the environment, and consumers can also meet their own environmental protection needs by choosing green electricity.

[0003] However, the existing green electricity transaction mode mainly relies on static matching between the power generation side and the user side, that is, the power producers and the power users directly reach a transaction agreement. This transaction mode leads to insufficient real-time balancing capability of supply and demand, resulting in low matching rate of green electricity transaction supply and demand. Especially in the scenario of wall sales, users have high requirements for continuous and stable power supply, which conflicts with the intermittent and volatile characteristics of renewable energy, making it difficult to guarantee power supply reliability. This contradiction leads to the fact that the electricity market cannot fully play the advantages of green electricity, limits the improvement of green electricity consumption capacity, and hinders the further promotion and application of clean energy.

[0004] Therefore, how to improve the supply and demand matching capability and power supply reliability of green electricity transaction has become a technical problem to be solved by those skilled in the art. SUMMARY

[0005] The present application provides a management method, system, device and medium for flexible resources participating in green electricity transaction to solve the technical problem of how to improve the supply and demand matching capability and power supply reliability of green electricity transaction, realize dynamic switching and collaborative scheduling between flexible resources in the green electricity transaction market and the grid frequency regulation service, optimize resource allocation, and improve the supply and demand matching capability and power supply reliability of green electricity transaction.

[0006] In a first aspect, the present application provides a management method for flexible resources participating in green electricity transaction, which comprises: determining flexible resource subjects available for green electricity transaction, and acquiring real-time operation data of each flexible resource subject;

[0007] Based on a preset charge-discharge benefit objective function of the flexible resource subject, a charge-discharge multi-period optimization model is constructed, and the real-time operation data and real-time acquired green electricity transaction market data are input into the charge-discharge multi-period optimization model to obtain the charge-discharge benefit of the flexible resource subject;

[0008] construct a frequency modulation capacity allocation model based on a preset frequency modulation benefit objective function of the flexible resource subject, and input the real-time operation data and real-time acquired frequency modulation service data into the frequency modulation capacity allocation model to obtain frequency modulation service benefits of the flexible resource subject;

[0009] According to the charge-discharge benefits and the frequency modulation service benefits, control the operation mode of the flexible resource subject based on a pre-constructed real-time switching strategy, the operation mode including a green electricity transaction mode and a power grid frequency modulation mode, the real-time switching strategy being set to switch the flexible resource subject to the power grid frequency modulation mode when a preset power grid frequency modulation triggering condition is met or the frequency modulation service benefits are greater than the charge-discharge benefits, and the flexible resource subject returning to the green electricity transaction mode when in a low electricity price period and the state of charge of the flexible resource subject is less than a preset low electricity price charging threshold.

[0010] Preferably, a charge-discharge multi-period optimization model is constructed based on a preset charge-discharge benefit objective function of the flexible resource subject, including:

[0011] A charge-discharge benefit objective function of the flexible resource subject is set with the maximum charge-discharge benefit of the flexible resource subject as the target according to first income and cost data of the flexible resource subject, the first income and cost data including discharge income and discharge power charging cost;

[0012] A charge-discharge constraint condition is set, the charge-discharge constraint condition including state of charge dynamic constraint, upper and lower limit constraint of state of charge, charge-discharge power constraint and charge-discharge mutual exclusion constraint;

[0013] A charge-discharge multi-period optimization model is constructed by using a dynamic programming algorithm and a mixed integer linear programming algorithm according to the charge-discharge benefit objective function and the charge-discharge constraint condition.

[0014] Preferably, the charge-discharge benefit objective function is expressed as follows:

[0015]

[0016] wherein, represents a charge-discharge benefit objective function, represents a period, represents a total period, represents discharge power of the flexible resource subject in a period, represents green electricity transaction market electricity price in a period, represents charge-discharge loss cost of the flexible resource subject, represents charging power of the flexible resource subject in a period.

[0017] Preferably, the preset grid frequency modulation benefit objective function of the flexible resource subject is used to construct a frequency modulation capacity allocation model, which includes:

[0018] The grid frequency modulation benefit objective function of the flexible resource subject is set according to the second benefit-cost data of the flexible resource subject, wherein the second benefit-cost data includes the participation benefit of the grid frequency modulation service and the charging cost of the grid frequency modulation power;

[0019] The grid frequency modulation constraint condition is set, and the frequency modulation constraint condition includes the grid frequency modulation capacity constraint and the grid frequency modulation trigger condition constraint;

[0020] The frequency modulation capacity allocation model is constructed according to the frequency modulation benefit objective function and the frequency modulation constraint condition.

[0021] Preferably, the frequency modulation benefit objective function is expressed as:

[0022]

[0023] Wherein, The frequency modulation benefit objective function is represented as: The grid frequency modulation service price per unit capacity in the period is represented as: The total grid frequency modulation capacity that can be provided by the flexible resource subject in the period is represented as: The green electricity charging cost per unit capacity in the period is represented as:

[0024] Preferably, the management method further includes:

[0025] The historical data of the green electricity trading market and the historical data of the grid frequency modulation service are obtained;

[0026] The historical data of the green electricity trading market and the historical data of the grid frequency modulation service are stratified sampled and probability distribution analyzed to obtain an initial scenario library;

[0027] The initial scenario library is cluster analyzed to obtain a key scenario library and a key scenario probability;

[0028] The real-time switching strategy is optimized according to the key scenario library and the key scenario probability to obtain an optimized real-time switching strategy.

[0029] Preferably, the management method further includes:

[0030] ​​​In the flexible resource subject charging phase, the charging electric energy source type of the flexible resource subject is acquired, and the green electricity charging electric quantity, green certificate information and charging time of the charging electric energy source type being green electricity are acquired;

[0031] The green certificate information, the green electricity charging electric quantity and the charging time are uploaded to a block chain node to obtain a charging traceability chain;

[0032] In the flexible resource subject discharging phase, according to the charging traceability chain, a discharging electric quantity corresponding discharging electric energy source type is determined according to a preset rule, when the discharging electric energy source type is the green electricity, a green certificate transfer request of green electricity discharging electric quantity is generated through a block chain smart contract to trigger the block chain smart contract, so as to realize the circulation of the green certificate.

[0033] In a second aspect, the present application further provides a management system for flexible resources participating in green electricity transactions, which realizes the management method for flexible resources participating in green electricity transactions as described above, and the system comprises a flexible resource subject determination module, a green electricity charging and discharging management module, a frequency modulation service management module and a collaborative management module.

[0034] The flexible resource subject determination module is used to determine flexible resource subjects available for green electricity transactions, and acquire real-time operation data of each flexible resource subject.

[0035] The green electricity charging and discharging management module is used to construct a charging and discharging multi-period optimization model based on a preset charging and discharging benefit objective function of the flexible resource subject, and input the real-time operation data and real-time acquired green electricity transaction market data into the charging and discharging multi-period optimization model to obtain the charging and discharging benefit of the flexible resource subject.

[0036] The frequency modulation service management module is used to construct a frequency modulation capacity allocation model based on a preset power grid frequency modulation benefit objective function of the flexible resource subject, and input the real-time operation data and real-time acquired power grid frequency modulation service data into the frequency modulation capacity allocation model to obtain the frequency modulation service benefit of the flexible resource subject.

[0037] The collaborative management module is used to control the operation mode of the flexible resource subject based on a pre-constructed real-time switching strategy according to the charging and discharging benefit and the frequency modulation service benefit, the operation mode comprising a green electricity transaction mode and a power grid frequency modulation mode, the real-time switching strategy being set to switch the flexible resource subject to the power grid frequency modulation mode when a preset power grid frequency modulation triggering condition is met or the frequency modulation service benefit is greater than the charging and discharging benefit, and the flexible resource subject returning to the green electricity transaction mode when in a low electricity price period and the state of charge of the flexible resource subject is less than a preset low electricity price charging threshold.

[0038] In a third aspect, the present application further provides a computer device, comprising a memory, a processor and a transceiver connected through a bus; the memory is used for storing a set of computer program instructions and data, and transmitting the stored data to the processor; the processor executes the computer program instructions stored in the memory to execute the management method of green electricity transaction of flexible resources.

[0039] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program, and when the computer program is executed, the management method of green electricity transaction of flexible resources is realized.

[0040] The present application provides a management method, system, device and medium of green electricity transaction of flexible resources, and the beneficial effects of the embodiments of the present application are as follows:

[0041] The management method of green electricity transaction of flexible resources disclosed in the present application realizes the dynamic switching and collaborative scheduling between the green electricity transaction market and the grid frequency regulation service of flexible resources, optimizes resource allocation, and improves the supply-demand matching capability and power supply reliability of green electricity transaction. Based on the real-time frequency regulation signal of the power grid and the state of charge of the flexible resource subject, the frequency regulation capacity of the flexible resource subject is dynamically calculated to ensure that the frequency regulation demand of the power system is met while the grid frequency regulation benefit of the flexible resource subject is maximized. The green certificate circulation is transparently traced throughout the whole link, which significantly improves the credibility, transparency and market efficiency of green electricity transaction. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 is a management method of green electricity transaction of flexible resources provided by a preferred embodiment of the present application;

[0043] Figure 2 is a structure diagram of a management system of green electricity transaction of flexible resources provided by a preferred embodiment of the present application;

[0044] Figure 3 is an internal structure diagram of a computer device provided by a preferred embodiment of the present application;

[0045] REFERENCE NUMERALS:

[0046] 1-flexible resource subject determination module, 2-green electricity charging and discharging management module, 3-frequency regulation service management module, 4-collaborative management module. DETAILED DESCRIPTION

[0047] The embodiments of the present application will be described below in detail with reference to the drawings. The embodiments are given only for the purpose of illustration and should not be understood as limiting the present application. The accompanying drawings are referred to, and are given only for reference and illustration, and do not constitute a limitation on the scope of patent protection of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application. In the description of the present application, the terms "first", "second", "third" and the like are used only for the purpose of description, and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second", "third" and the like can be explicitly or implicitly included. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0048] In the description of the present application, it should be noted that, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be direct connection, or indirect connection through intermediate medium, or internal communication of two elements. The terms "vertical", "horizontal", "left", "right", "up", "down" and similar expressions used herein are only for the purpose of illustration, and should not be understood as indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present application. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those skilled in the art, the specific meaning of the above terms in the present application can be understood in specific cases.

[0049] In the description of the present application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present application have the same meaning as understood by those skilled in the art. The terms used in the specification of the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the present application. For those skilled in the art, the specific meaning of the above terms in the present application can be understood in specific cases.

[0050] Please refer to Figure 1 The management method for flexible resources participating in green electricity transaction is shown in the step schematic diagram. In the embodiments of the present application, a management method for flexible resources participating in green electricity transaction is provided, which comprises:

[0051] S1, determine the flexible resource subject available for green electricity transaction, obtain real-time operation data of each flexible resource subject; at present, the green power certification mechanism allows green power producers to sell green power and certificates, and consumers can choose to buy green power or / and certificates to achieve the carbon emission reduction target. The traditional power transaction mechanism mainly focuses on the fixed power production and consumption mode, and the flexible resource is usually a passive participant, lacking effective integration of flexible resources. In the preferred embodiment of the present application, the flexible resource subject available for green electricity transaction is determined, and the flexible resource subject refers to the adjustable power demand or supply resource, including adjustable load, energy storage system, electric vehicle and demand response, etc. In the existing power market application, flexible resources are generally used for frequency regulation of power grid, and can be charged or discharged when power supply and demand are unbalanced, playing a role in balancing the frequency of power grid. In the present application, the flexible resource is used as a power user participating in green electricity transaction.

[0052] The flexible resource subject can actively declare and register as a power user. In the registration declaration process, the capacity, charging and discharging efficiency and SOC (state of charge) management capability of the flexible resource need to be provided. In terms of capacity, the flexible resource subject needs to meet the minimum capacity requirement to ensure that it can provide sufficient power to participate in green electricity market transaction. The capacity size needs to be set according to the size of the power market, the type of transaction and the dispatching demand of the power grid, for example, a single energy storage system needs to reach a certain megawatt level to cope with the short-term load change and green electricity demand fluctuation of the power grid. In terms of charging and discharging efficiency, the charging and discharging efficiency of the flexible resource subject should meet the established standard. The high-efficiency flexible resource subject can maximize the reduction of energy loss and improve resource utilization efficiency. The charging and discharging efficiency is provided by the equipment manufacturer and strictly tested and verified to ensure that it is within the specified range. The flexible resource subject needs to have accurate SOC management capability. The SOC management system monitors the battery charging and discharging state in real time to avoid overcharging or overdischarging, and needs to meet the market requirements for stability and accuracy, and realizes real-time data docking with the dispatching system and the power market. After passing the above audit requirements, the flexible resource can become a flexible resource subject that can participate in green electricity transaction, and a green electricity transaction account corresponding to the flexible resource subject is established. The green electricity transaction account is used to record the participation of the flexible resource subject in green electricity transaction and power grid frequency modulation service, such as charging and discharging capacity, transaction power, frequency modulation service power, etc., and also records green electricity market transaction history, green electricity consumption certificate, etc. The flexible resource subject can check its power transaction record and settlement result through the green electricity transaction account.

[0053] The flexible resource subject mainly includes two ways to participate in green electricity transaction: centralized bidding and bilateral agreement. The centralized bidding is to declare the saleable electricity and price in the green electricity transaction market in day-ahead or real-time, and the transaction electricity and price are determined according to the market clearing result. The bilateral agreement is to directly sign a long-term electricity purchase agreement with the electricity purchaser, and the fixed price, delivery period and electricity quantity are agreed. The delivery period needs to match the peak period of wind power generation and / or photovoltaic power generation in priority, so as to improve the green electricity proportion and reduce the electricity purchase cost. After the transaction is reached, the real-time recording of the green electricity charging and discharging quantity of the flexible resource subject is realized through the time-of-use meter, and the discharging quantity is regarded as green electricity sales, and the charging quantity is calculated into the cost according to the market price.

[0054] After the discharging quantity of the flexible resource subject is measured, the green electricity data is synchronized to the green certificate issuing agency. After the audit is passed, the green certificate with unique code is generated according to the rule of “1 MWh green electricity = 1 green certificate”, and is initially registered to the flexible resource subject. The flexible resource subject can choose to sell the green certificate on the green certificate trading platform, or sell it in combination with the electricity trading.

[0055] After the green electricity purchaser purchases the green electricity in the green electricity transaction market, the green certificate matching the consumption electricity quantity needs to be purchased in the green certificate platform. The platform automatically verifies the consistency of the time period and electricity quantity of the green certificate and the green electricity, completes the ownership transfer, and registers the green certificate to the account of the green electricity purchaser. The green certificate can be used to fulfill the renewable energy quota requirement. If the green certificate source and the green electricity consumption data do not match, such as time period deviation exceeding the limit, it will be regarded as a violation and be punished.

[0056] The flexible resource subject also needs to participate in the grid frequency modulation service. The flexible resource subject reports the grid frequency modulation data to the grid dispatching agency, including the technical parameters such as the controllable capacity, response speed and duration, and participates in the grid frequency modulation service market bidding. After winning the bid, the grid dispatching agency issues real-time frequency modulation instructions through the automatic generation control (AGC) system, and the flexible resource subject dynamically adjusts the charging and discharging power according to the real-time frequency modulation instructions to maintain the stability of the grid frequency.

[0057] In the real-time operation process of the flexible resource subject, the real-time operation data of each flexible resource is collected, including performance data and operation state data. The performance data mainly includes the capacity, charging and discharging efficiency and SOC management capability of the flexible resource subject; the operation state data includes the charging and discharging state, real-time charging power, real-time discharging power and real-time state of charge of the flexible resource subject, so as to facilitate the management of the flexible resource subject.

[0058] S2, based on the preset charging and discharging benefit objective function of the flexible resource subject, construct a charging and discharging multi-period optimization model, and input the real-time running data and the real-time acquired green electricity trading market data into the charging and discharging multi-period optimization model to obtain the charging and discharging benefit of the flexible resource subject; in the preferred embodiments of the present application, for the green electricity trading market, a dynamic programming algorithm and a mixed integer linear programming algorithm are used to construct the charging and discharging multi-period optimization model to maximize the charging and discharging benefit. The dynamic programming algorithm is an algorithm strategy of decomposing a complex problem into overlapping sub-problems and storing the solutions of the sub-problems to avoid repeated calculation. The mixed integer linear programming algorithm is used to solve the problem of a linear objective function and a constraint condition containing continuous variables and integer variables at the same time, and under the premise of meeting the linear constraint, a linear objective function is optimized, wherein part of the variables are limited to integers.

[0059] Specifically, taking the maximum charging and discharging benefit of the flexible resource as the target, the charging and discharging benefit objective function of the flexible resource is set according to the first income and cost data of the flexible resource subject, and the first income and cost data includes the green electricity discharge income and the green electricity discharge capacity charging cost. The charging and discharging benefit objective function is set by comprehensively considering the charging cost and the discharging benefit, and the charging and discharging benefit objective function is represented as follows:

[0060]

[0061] wherein, represents the charging and discharging benefit objective function, represents a period, represents a total period, represents discharge power of the flexible resource subject in the period, represents green electricity trading market price of the period, represents charging and discharging loss cost of the flexible resource subject, represents charging power of the flexible resource subject in the period. In the process of participating in the green electricity transaction, the flexible resource subject trades the green electricity obtained through the renewable energy power system, and the discharge capacity is limited by the charging capacity received from the renewable energy power system.

[0062] Further, the charging and discharging constraint condition is set, and the charging and discharging constraint condition includes the state of charge dynamic constraint, the state of charge upper and lower limit constraint, the charging and discharging power constraint and the charging and discharging mutual exclusion constraint, wherein the state of charge dynamic constraint is represented as:

[0063]

[0064] wherein, represents state of charge of the flexible resource subject in the period, denotes state of charge of the period flexible resource subject, denotes charging efficiency, denotes discharging efficiency, denotes period step length.

[0065] The state of charge dynamic constraint of the flexible resource subject indicates that the state of charge of the flexible resource subject in the next period is determined by the state of charge in the current period, charging efficiency, discharging efficiency, charging power and discharging power, so as to ensure the dynamic balance of the state of charge of the flexible resource subject.

[0066] The upper and lower limits of the state of charge are represented as:

[0067]

[0068] wherein, denotes the lower limit of the state of charge of the flexible resource subject, denotes the lower limit of the state of charge of the flexible resource subject.

[0069] The charging and discharging power constraint is represented as:

[0070]

[0071]

[0072] wherein, denotes the maximum charging and discharging power of the flexible resource subject, and the setting of the charging and discharging power constraint effectively avoids overloading of the flexible resource subject during charging and discharging.

[0073] The charging and discharging mutual exclusion constraint is represented as:

[0074]

[0075] The charging and discharging mutual exclusion constraint indicates that charging or discharging can only be performed in the same period, which can effectively avoid power loss caused by simultaneous charging and discharging of the flexible resource subject, and ensure that only one of charging and discharging can be selected in any period.

[0076] According to the charging and discharging benefit objective function and the charging and discharging constraint condition, a dynamic programming algorithm and a mixed integer linear programming algorithm are used to construct a charging and discharging multi-period optimization model. In the preferred embodiment of the present application, a multi-stage decision problem is processed by a dynamic programming algorithm and a mixed integer linear programming algorithm through a time period rolling optimization strategy, a charging and discharging multi-period optimization model is constructed, real-time green electricity trading market data and real-time operation data of the flexible resource subject are input into the charging and discharging multi-period optimization model, the green electricity trading market data at least includes real-time electricity price and green electricity trading demand of the green electricity trading market, and finally the optimal charging and discharging power of the flexible resource subject in each period and the charging and discharging benefit are output, thereby providing a decision basis for green electricity trading.

[0077] S3, based on the preset grid frequency modulation benefit objective function of the flexible resource subject, a frequency modulation capacity allocation model is constructed, and the real-time operation data and the real-time acquired grid frequency modulation data are input into the frequency modulation capacity allocation model to obtain the frequency modulation service benefit of the flexible resource subject; in the preferred embodiment of the present application, for the grid frequency modulation service market, the maximum frequency modulation benefit of the flexible resource subject is taken as the target, the frequency modulation benefit objective function of the flexible resource is set according to the second income and cost data of the flexible resource subject, the second income and cost data includes the income of participating in the grid frequency modulation service and the charging cost of the grid frequency modulation capacity, and the frequency modulation benefit objective function is expressed as:

[0078]

[0079] Among them, indicates the frequency modulation benefit objective function, indicates the grid frequency modulation service price per unit capacity of the period, indicates the total grid frequency modulation capacity that can be provided by the flexible resource subject in the period, indicates the green electricity charging cost per unit capacity of the period.

[0080] Further, the grid frequency modulation constraint condition is set, the grid frequency modulation constraint condition includes the grid frequency modulation capacity constraint and the grid frequency modulation trigger condition constraint, wherein the grid frequency modulation capacity constraint is expressed as:

[0081]

[0082] Among them, indicates the frequency modulation uplink reservation coefficient of the flexible resource subject, that is, the capacity proportion in the charge of the flexible resource subject that can be used for the grid frequency modulation uplink, indicates the frequency modulation downlink reservation coefficient of the flexible resource subject, that is, the capacity proportion in the charge of the flexible resource subject that can be used for the grid frequency modulation downlink, indicates the rated capacity of the flexible resource subject.

[0083] The frequency modulation trigger condition constraint is represented as:

[0084]

[0085] wherein, represents the frequency modulation signal strength, represents the frequency modulation trigger threshold.

[0086] The frequency modulation trigger condition constraint can ensure that when the frequency modulation signal strength is greater than or equal to the frequency modulation trigger threshold, the flexible resource subject responds to the power grid frequency modulation service demand in time, and ensures the priority of the power grid frequency modulation service.

[0087] According to the power grid frequency modulation benefit objective function and the power grid frequency modulation constraint condition, a frequency modulation capacity allocation model is constructed to dynamically calculate the frequency modulation capacity that can be provided by the flexible resource subject based on the real-time frequency modulation signal of the power grid and the state of charge of the flexible resource subject. The frequency modulation capacity is limited by the current state of charge of the flexible resource subject, ensuring that the power system frequency regulation demand is met while maximizing the power grid frequency modulation benefit of the flexible resource subject. The real-time acquired power grid frequency modulation service data and the real-time operation data of the flexible resource subject are input into the frequency modulation capacity allocation model, the power grid frequency modulation service data at least including the power grid frequency modulation service price per unit capacity and the total power grid frequency modulation capacity that can be provided by the flexible resource subject, and finally outputting the frequency modulation service benefit of the flexible resource subject to provide a decision basis for the power grid frequency modulation service.

[0088] S4, based on the charging and discharging benefit and the frequency regulation service benefit, controlling the operation mode of the flexible resource subject based on a pre-constructed real-time switching strategy, the operation mode including a green electricity transaction mode and a power grid frequency regulation mode, the real-time switching strategy being set to switch the flexible resource subject to the power grid frequency regulation mode when a preset power grid frequency regulation triggering condition is met or the frequency regulation service benefit is greater than the charging and discharging benefit, and the flexible resource subject returning to the green electricity transaction mode when in a power price valley period and the state of charge of the flexible resource subject being less than a preset power price valley charging threshold; the existing mechanism is not perfect in terms of the coordinated management mechanism of the green electricity transaction market and the power grid frequency regulation service market of the flexible resource subject, and it is difficult to realize efficient connection of green electricity transaction and power grid frequency regulation service, so in the preferred embodiments of the present application, the priority of the power grid frequency regulation service should be higher than that of the green electricity transaction, and therefore it is necessary to coordinate the participation of the flexible resource subject in the green electricity transaction and the power grid frequency regulation service for real-time switching. In the preferred embodiments of the present application, a real-time switching strategy based on a double-layer decision tree is constructed to realize switching of the flexible resource subject between the green electricity transaction mode and the power grid frequency regulation mode, the green electricity transaction mode being controlled by a charging and discharging multi-period optimization model for the flexible resource subject, and the power grid frequency regulation mode being controlled by a frequency regulation capacity allocation model for the flexible resource subject. The condition for entering the power grid frequency regulation mode is that the power grid frequency regulation triggering condition is met or the frequency regulation service benefit is greater than the charging and discharging benefit, and because the priority of the power grid frequency regulation service is higher than that of the green electricity transaction, as long as the power grid frequency regulation triggering condition is met, that is, the frequency regulation signal strength is greater than or equal to the frequency regulation triggering threshold, the flexible resource subject needs to be switched to the power grid frequency regulation mode, or when the frequency regulation service benefit is greater than the charging and discharging benefit, the flexible resource subject is switched to the power grid frequency regulation mode, so as to maximize the benefit of the flexible resource subject. When the flexible resource subject participates in the power grid frequency regulation service, the state of charge of the flexible resource subject should meet the upper and lower limit constraints to ensure that the flexible resource subject operates in a safe range and avoids extreme charging and discharging. The condition for returning to the green electricity transaction mode is that the flexible resource subject is in a power price valley period and the state of charge of the flexible resource subject is less than a preset power price valley charging threshold. Because the price is low in the power price valley period, charging in the power price valley period can effectively reduce the charging cost of the flexible resource subject, and the power price valley period is generally a period when green electricity supply is sufficient, so charging in the power price valley period can effectively improve the green electricity supply and demand matching rate, reduce renewable energy output fluctuation, and avoid the phenomenon of wind curtailment and power curtailment. The setting of the power price valley charging threshold can enable the flexible resource subject to preferentially charge when the state of charge is less than the power price valley charging threshold, thereby ensuring energy reserves of the flexible resource subject.

[0089] In the preferred embodiment of the present application, based on the real-time obtained charging and discharging benefits and frequency regulation service benefits of the flexible resource subject, combined with the safe operation of the flexible resource subject, the operation mode of the flexible resource subject is controlled, the green electricity trading market data, the power grid frequency regulation service data and the real-time operation data of the flexible resource subject are updated every 5 minutes, and the charging and discharging benefits and the frequency regulation service benefits of the flexible resource subject are updated. According to the real-time switching strategy, the flexible resource subject is controlled to switch the operation mode, so as to avoid the device life attenuation caused by frequent switching.

[0090] The green electricity trading market and the power grid frequency regulation service have the characteristics of uncertainty. In the preferred embodiment of the present application, the robustness of the green electricity trading and the power grid frequency regulation service control is enhanced by Monte Carlo simulation. Monte Carlo simulation is a method for solving complex problems by random sampling and statistical analysis. Its core idea is to use probability models to simulate the influence of uncertain factors, so as to predict and analyze the behavior of the system, and improve the efficiency, accuracy and stability of the model control. Specifically, the green electricity trading market historical data and the power grid frequency regulation service historical data are obtained. The green electricity trading market historical data includes green electricity trading market price historical data and green electricity trading demand historical data. The power grid frequency regulation service historical data includes unit capacity power grid frequency regulation service price historical data and power grid frequency regulation capacity historical data. The green electricity trading market historical data and the power grid frequency regulation service historical data are stratified sampled, and the sampling results are analyzed for probability distribution to generate a large number of initial scenario library. The initial scenario library is analyzed for clustering to obtain a key scenario library and a key scenario probability. The key scenario probability is taken as a key scenario weight corresponding to the key scenario. The key scenario library and the key scenario weight are introduced into the real-time switching strategy as range limits to obtain an optimized real-time switching strategy. In actual operation, the operation mode of the flexible resource subject is predicted to improve the efficiency of switching the different operation modes of the flexible resource subject and to improve the expected income and extreme risk resistance of the flexible resource subject. A rolling optimization framework is adopted to update the key scenario library and the key scenario probability every 15 minutes, dynamically trigger the key scenario library correction and the real-time switching strategy adjustment, quantify the influence of market uncertainty, and ensure that the flexible resource subject can still maximize the benefits of the flexible resource subject under the fluctuation of green electricity market data and the mutation of power grid frequency regulation demand.

[0091] The existing green certificate issuing and transfer mechanism has the problems of dispersed transaction links and difficult information tracing. In traditional green electricity transactions, the generation, distribution and consumption links of green certificates lack a unified dynamic monitoring platform, resulting in unclear green certificate rights and interests and insufficient transaction process transparency. In addition, when flexible resource subjects participate in green electricity transactions, the green certificate rights and interests corresponding to the discharged electricity of the flexible resource subjects are not effectively distinguished from the green certificates on the power generation side of the renewable energy power system, which easily leads to repeated calculation or rights and interests disputes, hindering the efficient and fair transfer of green electricity rights and interests. In the preferred embodiments of the present application, the blockchain technology is used to store the whole life cycle data of the green certificate on the chain, support multi-node verification and real-time query, and ensure the transparency and traceability of the whole green electricity process. Specifically, during the charging phase of the flexible resource subject, the intelligent electric meter is used to obtain the charging source type of the flexible resource subject, such as green electricity or non-green electricity. If the charging source type is green electricity, the part of the charging electricity is marked as "green electricity charging", and the corresponding electricity is green electricity charging electricity. The green electricity charging electricity, green certificate information and charging time are uploaded to the blockchain node to form an unalterable charging traceability chain to prevent repeated transactions. The green certificate information includes green certificate number, power generation subject and power generation time. During the discharging phase of the flexible resource subject, the charging traceability chain is used to determine the discharging source type of the discharging electricity according to the preset rules, the preset rules include first-in first-out, proportional distribution and other principles, the discharging electricity and the green electricity source in the charging phase are bound, the discharging source type is determined, when the discharging source type is green electricity, the part of the discharging electricity is marked as "green electricity discharging", the corresponding electricity is green electricity discharging electricity, the blockchain smart contract is triggered, the green certificate transfer request of the green electricity discharging electricity is generated through the blockchain smart contract, and the original green certificate information in the charging phase is associated. The corresponding number of green certificates is transferred to the user account receiving the discharging of the flexible resource subject, and the original green certificate information of the flexible resource subject is cancelled, so as to realize the uniqueness of the green certificate circulation.

[0092] In the preferred embodiment of the present application, the flexible resource subject available for green electricity transaction is determined, real-time operation data of each flexible resource subject is acquired; a charging and discharging multi-period optimization model is constructed based on a preset charging and discharging benefit objective function of the flexible resource subject, and real-time operation data and real-time acquired green electricity transaction market data are input into the charging and discharging multi-period optimization model to obtain charging and discharging benefit of the flexible resource subject; a frequency modulation capacity allocation model is constructed based on a preset frequency modulation benefit objective function of the flexible resource subject, and real-time operation data and real-time acquired frequency modulation data of the power grid are input into the frequency modulation capacity allocation model to obtain frequency modulation service benefit of the flexible resource subject; the operation mode of the flexible resource subject is controlled based on the pre-constructed real-time switching strategy according to the charging and discharging benefit and the frequency modulation service benefit, the operation mode includes a green electricity transaction mode and a power grid frequency modulation mode, the real-time switching strategy is set to switch the flexible resource subject to the power grid frequency modulation mode when a preset power grid frequency modulation triggering condition is met or the frequency modulation service benefit is greater than the charging and discharging benefit, and the flexible resource subject returns to the green electricity transaction mode when in a low electricity price period and the state of charge of the flexible resource subject is less than a preset low electricity price charging threshold. The management method of the flexible resource participating in the green electricity transaction disclosed in the present application realizes dynamic switching and collaborative scheduling between the flexible resource in the green electricity transaction market and the power grid frequency modulation service, optimizes resource allocation, and improves the supply and demand matching capability and power supply reliability of the green electricity transaction. Based on the real-time frequency modulation signal of the power grid and the state of charge of the flexible resource subject, the frequency modulation capacity that can be provided by the flexible resource subject is dynamically calculated to ensure that the power system frequency regulation demand is met while the frequency modulation benefit of the flexible resource subject is maximized. The green certificate circulation full-link transparent tracing significantly improves the credibility, transparency and market efficiency of the green electricity transaction.

[0093] Correspondingly, as Figure 2 shown in the structural schematic diagram of the management system of the flexible resource participating in the green electricity transaction, based on the management method of the flexible resource participating in the green electricity transaction, the embodiment of the present application further provides a management system of the flexible resource participating in the green electricity transaction, realizes the management method of the flexible resource participating in the green electricity transaction disclosed in the embodiment of the present application, and the system comprises a flexible resource subject determination module 1, a green electricity charging and discharging management module 2, a frequency modulation service management module 3 and a collaborative management module 4.

[0094] The flexible resource subject determination module 1 is used for determining the flexible resource subject available for green electricity transaction, and acquiring real-time operation data of each flexible resource subject.

[0095] The green electricity charging and discharging management module 2 is used for constructing a charging and discharging multi-period optimization model based on a preset charging and discharging benefit objective function of the flexible resource subject, and inputting the real-time operation data and real-time acquired green electricity transaction market data into the charging and discharging multi-period optimization model to obtain charging and discharging benefit of the flexible resource subject.

[0096] The frequency modulation service management module 3 is configured to construct a frequency modulation capacity allocation model based on a preset grid frequency modulation benefit objective function of the flexible resource subject, and input the real-time operation data and real-time acquired grid frequency modulation service data into the frequency modulation capacity allocation model to obtain a frequency modulation service benefit of the flexible resource subject.

[0097] The cooperative management module 4 is configured to control an operation mode of the flexible resource subject based on the pre-constructed real-time switching strategy according to the charge-discharge benefit and the frequency modulation service benefit, the operation mode including a green electricity transaction mode and a grid frequency modulation mode, and the real-time switching strategy being set to switch the flexible resource subject to the grid frequency modulation mode when a preset grid frequency modulation triggering condition is met or the frequency modulation service benefit is greater than the charge-discharge benefit, and the flexible resource subject returning to the green electricity transaction mode when in a low electricity price period and a state of charge of the flexible resource subject is less than a preset low electricity price charging threshold.

[0098] The specific limitation of the management system of the flexible resource participating in the green electricity transaction can refer to the limitation of the management method of the flexible resource participating in the green electricity transaction described above, which will not be repeated here. Those skilled in the art can understand that the various modules and steps described in combination with the embodiments disclosed in the present application can be realized in hardware, software or a combination of both. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0099] As shown in Figure 3 , the embodiment of the present application provides a computer device, which includes a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the steps in the embodiments of the management method of the flexible resource participating in the green electricity transaction when executing the computer program, such as the steps S1-S4 in Figure 1 .

[0100] Those skilled in the art can understand that the schematic Figure 3 structure of the computer device is only an example of the internal structure of the computer device and does not constitute a limitation on the computer device, which can include more or fewer components than the diagram, or combine certain components, or different components, for example, the computer device can also include an input and output device, a network access device, a bus, etc.

[0101] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The processor is a control center of the computer device, and connects various parts of the computer device through various interfaces and lines.

[0102] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the computer device by running or executing the computer program and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area. The program storage area can store an operating system, at least one application program required for a function (such as a sound playing function, an image playing function, etc.), etc.; and the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory device.

[0103] If the modules integrated in the computer device are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0104] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the program can be stored in a computer readable storage medium. The program can include the processes of each method embodiment when executed.

[0105] Correspondingly, the embodiment of the present application provides a computer readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer readable storage medium is located to perform the steps in the management method of flexible resource participating in green electricity transaction as described in the above embodiment, for example, the steps S1-S4 described in the above embodiment. Figure 1

[0106] ​In summary, the embodiment of the present application provides a flexible resource participating in green electricity transaction management method, system, device and medium, which solves the technical problem of how to improve the supply and demand matching capability and power supply reliability of green electricity transaction. The method comprises: determining a flexible resource subject available for green electricity transaction, and acquiring real-time operation data of each flexible resource subject; based on a preset charging and discharging benefit objective function of the flexible resource subject, a charging and discharging multi-period optimization model is constructed, and the real-time operation data and real-time acquired green electricity transaction market data are input into the charging and discharging multi-period optimization model to obtain the charging and discharging benefit of the flexible resource subject; based on a preset power grid frequency modulation benefit objective function of the flexible resource subject, a frequency modulation capacity allocation model is constructed, and the real-time operation data and real-time acquired power grid frequency modulation service data are input into the frequency modulation capacity allocation model to obtain the frequency modulation service benefit of the flexible resource subject; based on the pre-constructed real-time switching strategy, the operation mode of the flexible resource subject is controlled according to the charging and discharging benefit and the frequency modulation service benefit, the operation mode includes a green electricity transaction mode and a power grid frequency modulation mode, the real-time switching strategy is set to switch the flexible resource subject to the power grid frequency modulation mode when the preset power grid frequency modulation triggering condition is met or the frequency modulation service benefit is greater than the charging and discharging benefit, and the flexible resource subject returns to the green electricity transaction mode when in a low electricity price period and the state of charge of the flexible resource subject is less than a preset low electricity price charging threshold. The flexible resource participating in green electricity transaction management method disclosed in the present application realizes dynamic switching and collaborative scheduling of the flexible resource between the green electricity transaction market and the power grid frequency modulation service, optimizes resource allocation, and improves the supply and demand matching capability and power supply reliability of green electricity transaction. Based on the real-time frequency modulation signal of the power grid and the state of charge of the flexible resource subject, the frequency modulation capacity that can be provided by the flexible resource subject is dynamically calculated to ensure that the power system frequency regulation demand is met while the power grid frequency modulation benefit of the flexible resource subject is maximized. The green certificate circulation is transparently traced throughout the chain, which significantly improves the credibility, transparency and market efficiency of green electricity transaction.

[0107] Each of the embodiments in the specification is described in a progressive manner, and the directly same or similar parts of each of the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. Especially, for the system embodiment, since it is basically similar to the method embodiment, it is described more simply, and the related parts can be referred to the part of the description of the method embodiment. It should be noted that, each of the technical features of the above-mentioned embodiments can be combined arbitrarily, in order to make the description simple, not all possible combinations of the technical features in the above-mentioned embodiments are described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the description.

[0108] The above-described embodiments are merely illustrative of several preferred embodiments of the present application, which are described in more detail and in a more specific and detailed manner, but should not be construed as limiting the scope of the patent application. It should be noted that for those skilled in the art, several improvements and replacements can be made without departing from the technical principles of the present application, and these improvements and replacements should also be considered as the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the protection scope of the claims.

Claims

1. A method for managing flexible resource participation in green electricity trading, characterized in that, The method comprises: determining flexible resource subjects available for green electricity transactions, and acquiring real-time operation data of each flexible resource subject; based on a preset charge-discharge benefit objective function of the flexible resource subject, constructing a charge-discharge multi-period optimization model, and inputting the real-time operation data and real-time acquired green electricity transaction market data into the charge-discharge multi-period optimization model to obtain the charge-discharge benefit of the flexible resource subject, specifically comprising: taking the maximum charge-discharge benefit of the flexible resource subject as the target, setting the charge-discharge benefit objective function of the flexible resource subject according to first revenue and cost data of the flexible resource subject, the first revenue and cost data including discharge revenue and discharge power charging cost; setting charge-discharge constraint conditions, the charge-discharge constraint conditions including state of charge dynamic constraint, state of charge upper and lower limit constraint, charge-discharge power constraint and charge-discharge mutual exclusion constraint; constructing a charge-discharge multi-period optimization model according to the charge-discharge benefit objective function and the charge-discharge constraint conditions by using a dynamic programming algorithm and a mixed integer linear programming algorithm; based on a preset grid frequency modulation benefit objective function of the flexible resource subject, constructing a frequency modulation capacity allocation model, and inputting the real-time operation data and real-time acquired grid frequency modulation service data into the frequency modulation capacity allocation model to obtain the frequency modulation service benefit of the flexible resource subject, specifically comprising: taking the maximum grid frequency modulation benefit of the flexible resource subject as the target, setting the grid frequency modulation benefit objective function of the flexible resource subject according to second revenue and cost data of the flexible resource subject, the second revenue and cost data including participation in grid frequency modulation service revenue and grid frequency modulation power charging cost; setting grid frequency modulation constraint conditions, the frequency modulation constraint conditions including grid frequency modulation capacity constraint and grid frequency modulation trigger condition constraint; constructing a frequency modulation capacity allocation model according to the frequency modulation benefit objective function and the frequency modulation constraint conditions; based on a pre-constructed real-time switching strategy, controlling the operation mode of the flexible resource subject according to the charge-discharge benefit and the frequency modulation service benefit, the operation mode including a green electricity transaction mode and a grid frequency modulation mode, the real-time switching strategy being set to switch the flexible resource subject to the grid frequency modulation mode when a preset grid frequency modulation trigger condition is met or the frequency modulation service benefit is greater than the charge-discharge benefit, and the flexible resource subject returns to the green electricity transaction mode when in a low electricity price period and the state of charge of the flexible resource subject is less than a preset low electricity price charging threshold. 2.The method of claim 1, wherein, The frequency modulation benefit objective function is expressed as: wherein, represents a frequency modulation benefit objective function, represents a price of frequency modulation service per unit capacity of the power grid for the period, represents a total capacity of frequency modulation that can be provided by the flexible resource subject for the period, represents a green electricity charging cost per unit capacity for the period. 3.The method of claim 1, wherein, The management method further comprises: acquiring green electricity transaction market historical data and grid frequency modulation service historical data; performing stratified sampling and probability distribution analysis on the green electricity transaction market historical data and the grid frequency modulation service historical data to obtain an initial scenario library; performing clustering analysis on the initial scenario library to obtain a key scenario library and a key scenario probability; optimizing the real-time switching strategy according to the key scenario library and the key scenario probability to obtain an optimized real-time switching strategy. 4.The method of claim 1, wherein, The management method further comprises: In the flexible resource subject charging stage, the charging electric energy source type of the flexible resource subject is acquired, and the green electricity charging electric quantity, green certificate information and charging time of the charging electric energy source type being green electricity are acquired; The green certificate information, the green electricity charging electric quantity and the charging time are uploaded to a block chain node to obtain a charging traceability chain; In the flexible resource subject discharging stage, according to the charging traceability chain, a discharging electric quantity corresponding discharging electric energy source type is determined according to a preset rule, when the discharging electric energy source type is the green electricity, a green certificate transfer request of green electricity discharging electric quantity is generated through a block chain smart contract to trigger the block chain smart contract, so as to realize the circulation of the green certificate.

5. A management system for flexible resources participating in green electricity trading, used to implement the management method for flexible resources participating in green electricity trading according to any one of claims 1-4, characterized in that, The system comprises a flexible resource subject determination module, a green electricity charging and discharging management module, a frequency modulation service management module and a collaborative management module; The flexible resource subject determination module is used to determine the flexible resource subject available for green electricity transaction, and acquire real-time operation data of each flexible resource subject; The green electricity charging and discharging management module is used to construct a charging and discharging multi-period optimization model based on a preset charging and discharging benefit objective function of the flexible resource subject, and input the real-time operation data and real-time acquired green electricity transaction market data into the charging and discharging multi-period optimization model to obtain the charging and discharging benefit of the flexible resource subject, specifically comprising: Taking the maximum charging and discharging benefit of the flexible resource subject as the target, setting the charging and discharging benefit objective function of the flexible resource subject according to first income and cost data of the flexible resource subject, the first income and cost data comprising discharging income and discharging electric quantity charging cost; Setting charging and discharging constraint conditions, the charging and discharging constraint conditions comprising state of charge dynamic constraint, state of charge upper and lower limit constraint, charging and discharging power constraint and charging and discharging mutual exclusion constraint; According to the charging and discharging benefit objective function and the charging and discharging constraint conditions, a dynamic programming algorithm and a mixed integer linear programming algorithm are used to construct a charging and discharging multi-period optimization model; The frequency modulation service management module is used to construct a frequency modulation capacity allocation model based on a preset grid frequency modulation benefit objective function of the flexible resource subject, and input the real-time operation data and real-time acquired grid frequency modulation service data into the frequency modulation capacity allocation model to obtain the frequency modulation service benefit of the flexible resource subject, specifically comprising: Taking the maximum grid frequency modulation benefit of the flexible resource subject as the target, setting the grid frequency modulation benefit objective function of the flexible resource subject according to second income and cost data of the flexible resource subject, the second income and cost data comprising participation in grid frequency modulation service income and grid frequency modulation electric quantity charging cost; Setting grid frequency modulation constraint conditions, the frequency modulation constraint conditions comprising grid frequency modulation capacity constraint and grid frequency modulation trigger condition constraint; According to the frequency modulation benefit objective function and the frequency modulation constraint conditions, a frequency modulation capacity allocation model is constructed; The cooperative management module is configured to control an operation mode of the flexible resource subject based on a pre-constructed real-time switching strategy according to the charging / discharging benefit and the frequency regulation service benefit, the operation mode including a green electricity transaction mode and a power grid frequency regulation mode, and the real-time switching strategy being set to switch the flexible resource subject to the power grid frequency regulation mode when a preset power grid frequency regulation triggering condition is met or the frequency regulation service benefit is greater than the charging / discharging benefit, and the flexible resource subject returning to the green electricity transaction mode when a power price low valley period is present and a state of charge of the flexible resource subject is less than a preset power price low valley charging threshold.

6. A computer device, characterized by: The computer device comprises a memory, a processor and a transceiver which are connected through a bus; the memory is configured to store a set of computer program instructions and data, and transmit the stored data to the processor; the processor executes the computer program instructions stored in the memory to execute the management method for flexible resource participating in green electricity transaction according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, and when the computer program is executed, the management method for flexible resource participating in green electricity transaction according to any one of claims 1 to 4 is implemented.

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