Distributed resource aggregation management method and device, electronic equipment and storage medium

Abstract

The invention provides a distributed resource aggregation management method and device, electronic equipment and a storage medium, and relates to the technical field of electric power. According to the specific implementation scheme, a main output curve function is determined based on output functions of all distributed photovoltaic stations, all distributed wind power stations and all hydropower stations in an aggregation area so as to determine an auxiliary adjustment output curve; and based on the auxiliary adjustment output curve, an output function of each energy storage point and an output function of each flexible load point are determined. Further, based on the main output curve function, the output function of each energy storage point, the output function of each flexible load point and the electricity price at each moment, determining an objective function representing economic benefits; and solving the maximum value of the target function to obtain a target output curve of each target distributed resource. By adopting the method, the power generation economic benefit of the aggregation region can be maximized, and the main output and the aggregation output of the region respectively meet the corresponding expected requirements.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a distributed resource aggregation management method, device, electronic equipment and storage medium. Background Art

[0002] With the advancement of new power systems, a large number of distributed energy sources are connected to the power grid, which brings a series of stability problems and renewable energy absorption problems to the power grid. Therefore, how to aggregate and dispatch distributed energy sources is one of the technical problems to be solved in this field. Summary of the invention

[0003] The present invention provides a distributed resource aggregation management method, device, electronic device and storage medium, which can solve at least one of the above technical problems.

[0004] According to one aspect of the present invention, a distributed resource aggregation management method is provided, comprising: Based on the geographic location information of the first aggregation area and the geographic location information of the plurality of distributed resources, a plurality of target distributed resources participating in the aggregation management are determined from the plurality of distributed resources, wherein the target distributed resources include distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points and flexible load points; Determine a main output curve function based on the output function of each of the distributed photovoltaic stations, the output function of each of the distributed wind power stations, and the output function of each of the hydropower stations; Based on the main output curve function and a preset main output target curve, determining an auxiliary adjustment output curve; Based on the auxiliary adjustment output curve, determining the output function of each of the energy storage points and the output function of each of the flexible load points; Determine an aggregate output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points; Based on the aggregated output curve function and the electricity price at each moment, determining an objective function for characterizing the economic benefits of the first aggregated area; Determining an aggregate output curve constraint based on the aggregate output curve function and a preset aggregate output target curve; Based on the aggregate output curve constraint, solving the objective function for the maximum value to obtain the target output curve of each target distributed resource in the first aggregation area; Based on the target output curve of each target distributed resource, output scheduling is performed on each target distributed resource in the first aggregation area.

[0005] According to another aspect of the present invention, there is provided a distributed resource aggregation management device, comprising: An aggregated resource determination module, configured to determine, based on geographic location information of a first aggregated area and geographic location information of a plurality of distributed resources, a plurality of target distributed resources participating in aggregated management from the plurality of distributed resources, wherein the target distributed resources include distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points, and flexible load points; A first function determination module, configured to determine a main output curve function based on an output function of each of the distributed photovoltaic stations, an output function of each of the distributed wind power stations, and an output function of each of the hydropower stations; An auxiliary output determination module, used to determine an auxiliary adjustment output curve based on the main output curve function and a preset main output target curve; A second function determination module, used to determine the output function of each of the energy storage points and the output function of each of the flexible load points based on the auxiliary adjustment output curve; A third function determination module is used to determine an aggregate output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points; An objective function determination module, configured to determine an objective function for characterizing the economic benefits of the first aggregation area based on the aggregate output curve function and the electricity prices at various times; An output constraint determination module, configured to determine an aggregate output curve constraint based on the aggregate output curve function and a preset aggregate output target curve; an objective function solving module, configured to solve the objective function for a maximum value based on the aggregate output curve constraint, and obtain a target output curve of each target distributed resource in the first aggregation area; The output scheduling module is used to schedule the output of each of the target distributed resources in the first aggregation area based on the target output curve of each of the target distributed resources.

[0006] According to another aspect of the present invention, there is provided an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any distributed resource aggregation management method in the embodiments of the present invention.

[0007] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any distributed resource aggregation management method according to the embodiments of the present invention.

[0008] By adopting the technical solution of the present invention, based on the geographical location information of the first aggregation area and the geographical location information of multiple distributed resources, multiple target distributed resources participating in the aggregation management can be determined from multiple distributed resources, such as distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points and flexible load points. Then, based on the output function of each distributed photovoltaic station, the output function of each distributed wind power station, and the output function of each hydropower station, the main output curve function is determined; based on the main output curve function and the preset main output target curve, the auxiliary adjustment output curve is determined; and based on the auxiliary adjustment output curve, the output function of each energy storage point and the output function of each flexible load point are determined. In this way, the main output curve can match the main output target curve as much as possible to avoid the situation where the peak value of the main output is too high.

[0009] Furthermore, based on the main output curve function, the output functions of each energy storage point, and the output functions of each flexible load point, the aggregate output curve function is determined; based on the aggregate output curve function and the electricity price at each moment, the objective function used to characterize the economic benefits of the first aggregate area is determined; based on the aggregate output curve function and the preset aggregate output target curve, the aggregate output curve constraint is determined; based on the aggregate output curve constraint, the maximum value of the objective function is solved to obtain the target output curve of each target distributed resource in the first aggregate area. In this way, the output of the resources in the first aggregate area is dispatched according to the target output curves of each target distributed resource obtained by the solution, which can not only maximize the economic benefits of power generation in the first aggregate area, but also make the aggregate output of the area meet the expected output requirements.

[0010] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to better understand the present invention and do not constitute a limitation of the present invention. Figure 1 is a flow chart of a distributed resource aggregation management method according to an embodiment of the present invention; Figure 2 is a processing flow chart of an aggregation management module according to an embodiment of the present invention; Figure 3This is a structural block diagram of a distributed resource aggregation trading platform based on blockchain technology according to an embodiment of the present disclosure; Figure 4 It is a schematic diagram of the process of storing a contract on a blockchain according to an embodiment of the present invention; Figure 5 This is a structural block diagram of an intelligent terminal based on a blockchain chip according to an embodiment of the present invention; Figure 6 is a structural block diagram of a distributed resource aggregation management device according to an embodiment of the present invention; Figure 7 It is a block diagram of an electronic device used to implement the distributed resource aggregation management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be appreciated by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0013] Figure 1 It is a flow chart of a distributed resource aggregation management method according to an embodiment of the present invention.

[0014] like Figure 1 As shown, the distributed resource aggregation management method may include: S110, based on the geographic location information of the first aggregation area and the geographic location information of the plurality of distributed resources, determining a plurality of target distributed resources participating in the aggregation management from the plurality of distributed resources, wherein the target distributed resources include a distributed photovoltaic station, a distributed wind power station, a hydropower station, an energy storage point, and a flexible load point; S120, determining a main output curve function based on the output function of each of the distributed photovoltaic stations, the output function of each of the distributed wind power stations, and the output function of each of the hydropower stations; S130, determining an auxiliary adjustment output curve based on the main output curve function and a preset main output target curve; S140, determining an output function of each of the energy storage points and an output function of each of the flexible load points based on the auxiliary adjustment output curve; S150, determining an aggregated output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points; S160, determining an objective function for characterizing the economic benefits of the first aggregation area based on the aggregated output curve function and the electricity prices at various times; S170, determining an aggregate output curve constraint based on the aggregate output curve function and a preset aggregate output target curve; S180, based on the aggregate output curve constraint, solving the maximum value of the objective function to obtain a target output curve of each target distributed resource in the first aggregation area; S190: Perform output scheduling on each of the target distributed resources in the first aggregation area based on the target output curve of each of the target distributed resources.

[0015] According to the above implementation, based on the geographic location information of the first aggregation area and the geographic location information of multiple distributed resources, multiple target distributed resources participating in the aggregation management can be determined from the multiple distributed resources, such as distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points and flexible load points. Then, based on the output function of each distributed photovoltaic station, the output function of each distributed wind power station, and the output function of each hydropower station, the main output curve function is determined; based on the main output curve function and the preset main output target curve, the auxiliary adjustment output curve is determined; and based on the auxiliary adjustment output curve, the output function of each energy storage point and the output function of each flexible load point are determined. In this way, the main output curve can match the main output target curve as much as possible to avoid the peak of the main output being too high.

[0016] Furthermore, based on the main output curve function, the output functions of each energy storage point, and the output functions of each flexible load point, the aggregate output curve function is determined; based on the aggregate output curve function and the electricity price at each moment, the objective function used to characterize the economic benefits of the first aggregate area is determined; based on the aggregate output curve function and the preset aggregate output target curve, the aggregate output curve constraint is determined; based on the aggregate output curve constraint, the maximum value of the objective function is solved to obtain the target output curve of each target distributed resource in the first aggregate area. In this way, the output of the resources in the first aggregate area is dispatched according to the target output curves of each target distributed resource obtained by the solution, which can not only maximize the economic benefits of power generation in the first aggregate area, but also make the aggregate output of the area meet the expected output requirements.

[0017] In one embodiment, based on the geographic location information of the first aggregation area and the geographic location information of multiple distributed resources, the distance between each distributed resource and the first aggregation area can be calculated, and thus, based on the distance between each distributed resource and the first aggregation area, multiple target distributed resources participating in aggregation management can be determined from the multiple distributed resources.

[0018] For example, the distributed resources are sorted according to the distance from the first aggregation area from near to far, and the distributed resources ranked in the first N are selected as the target distributed resources. N is a positive integer greater than 1.

[0019] In this example, aggregation management gives priority to regional aggregation and the geographical location of each distributed resource. Distributed resources with closer geographical locations will be given priority to participate in aggregation and scheduling, while resources with farther geographical locations than other distributed resources will be ranked lower or not selected to participate in aggregation scheduling and transactions.

[0020] In one embodiment, based on the output function of each distributed photovoltaic station, the output function of each distributed wind power station, and the output function of each hydropower station, a main output curve function is determined, including: summing the output function of each distributed photovoltaic station, the output function of each distributed wind power station, and the output function of each hydropower station to obtain the main output curve function in which the main output changes with time.

[0021] Exemplarily, the output function of a distributed photovoltaic station may be as follows: in, represents the photovoltaic power generation of the distributed photovoltaic station at time t, represents the installed capacity of distributed photovoltaic stations, Indicates the sunshine conditions at the location of the distributed photovoltaic station at time t, Represents the photovoltaic power generation efficiency of distributed photovoltaic stations.

[0022] Exemplarily, the output function of a distributed wind power station may be as follows: in, represents the wind power generation of the distributed wind power station at time t, represents the air density at the location of the distributed wind power station at time t, represents the power generation efficiency of the wind turbines in the distributed wind power station, represents the wind speed at the location of the distributed wind power station at time t, Represents the rotor area of ​​a wind turbine in a distributed wind power plant.

[0023] Exemplarily, the output function of a hydropower station may be as follows: In one embodiment, based on the main output curve function and the preset main output target curve, an auxiliary adjustment output curve is determined, including: based on the deviation between the main output at each moment in the main output curve function and the main output at the corresponding moment in the main output target curve, the auxiliary adjustment output curve is determined.

[0024] Exemplarily, if the deviation is greater than a preset threshold, the deviation value is used as the auxiliary adjustment output at that moment; if the deviation is less than the preset threshold, the auxiliary adjustment output at that moment is zero.

[0025] According to the above implementation, the auxiliary adjustment output curve can be accurately determined.

[0026] In practical applications, in addition to distributed photovoltaics, distributed wind power and small hydropower, the aggregated distributed resources also include energy storage and flexible loads. Among them, distributed photovoltaics, distributed wind power and small hydropower bear the main output, and energy storage and flexible loads are used to assist in output adjustment. Because in aggregation, distributed photovoltaics, distributed wind power and small hydropower should be fully output as much as possible, that is, there is no restriction on their output, but sometimes they need to meet the output curve restrictions and the output peak cannot be too high. Therefore, energy storage and flexible loads are needed to assist in adjusting the aggregate output. For example, energy storage stores energy when the aggregate output is too high and releases energy when the aggregate output is too low. For another example, the flexible load increases the load and uses more electricity when the output is too high, and reduces the load and uses less electricity when the aggregate output is too low.

[0027] In one embodiment, based on the auxiliary regulation output curve, the output function of each energy storage point and the output function of each flexible load point are determined, including: based on the auxiliary regulation output curve, determining the charging energy or discharging energy of each energy storage point at each moment, and the regulated output of each flexible load point at each moment; based on the charging energy or discharging energy of each energy storage point at each moment, determining the output function of each energy storage point; based on the regulated output of each flexible load point at each moment, and the basic output of each flexible load point, determining the output function of each flexible load point.

[0028] Exemplarily, the output function of the energy storage point may be as follows: in, represents the charging power or discharging power of the energy storage point at time t, Represents the charging energy or discharging energy of the energy storage point at time t.

[0029] Exemplarily, the output function of the flexible load point may be as follows: in, represents the load output of the flexible load point at time t, represents the basic output of the flexible load point at time t, Represents the regulation output of the flexible load point at time t.

[0030] According to the above implementation, the auxiliary regulation output at each moment in the auxiliary regulation output curve can be used to determine the output function of each energy storage point and the output function of each flexible load point.

[0031] In one embodiment, based on the main output curve function, the output functions of each energy storage point, and the output function of each flexible load point, an aggregate output curve function is determined, including: summing the main output curve function, the output functions of each energy storage point, and the output function of each flexible load point to obtain the aggregate output curve function.

[0032] Exemplarily, the aggregate output curve function E may be as follows: in, represents the output of the i-th distributed photovoltaic station at time t, represents the output of the i-th distributed wind power station at time t, represents the output of the i-th hydropower station at time t, represents the output of the i-th energy storage point at time t, Represents the output of the i-th flexible load point at time t.

[0033] According to the above implementation, the main output curve function, the output functions of each energy storage point, and the output functions of each flexible load point may be summed to obtain an aggregated output curve function.

[0034] In one embodiment, based on the aggregate output curve function and the electricity price at each moment, an objective function for characterizing the economic benefits of the first aggregation area is determined, including: determining the economic benefit dependent variable at each moment based on the product of the aggregate output independent variable at each moment in the aggregate output curve function and the electricity price at the corresponding moment; determining the objective function based on the economic benefit dependent variable at each moment.

[0035] For example, the objective function for: in, represents the electricity price at time t.

[0036] According to the above-mentioned embodiments, the objective function can be determined.

[0037] In one embodiment, the aggregate output curve is constrained by the following formula: in, represents the output of the i-th distributed photovoltaic station at time t, represents the output of the i-th distributed wind power station at time t, represents the output of the i-th hydropower station at time t, represents the output of the i-th energy storage point at time t, represents the output of the i-th flexible load point at time t, Represents the target output at time t in the aggregate output target curve.

[0038] In some implementations, when solving the objective function, in addition to the aggregate output curve constraint, each target distributed resource has an upper and lower limit constraint on its output. In addition, the aggregated output after aggregation also needs to meet the grid security constraint, for example, the total amount of power that the grid can accept at each time.

[0039] In some embodiments, when solving the objective function, the following algorithms may be used: linear programming algorithm, integer programming algorithm (branch and bound method, cutting plane method, etc.), artificial intelligence algorithm (reinforcement learning algorithm, genetic algorithm, particle swarm optimization algorithm, deep learning algorithm, etc.

[0040] The above embodiments can be applied to the aggregation management module in the distributed resource aggregation trading platform based on blockchain technology, such as Figure 2 As shown in the figure, it can read the operating data of distributed energy equipment (such as distributed photovoltaic, distributed wind power, small hydropower, etc.), including power generation, power output, equipment status, etc., and optimize the scheduling according to the real-time data of energy production and the results of energy demand and supply predicted by the statistical analysis module, and reasonably allocate the power generation of distributed energy equipment to ensure efficient use of energy and balance between supply and demand. Aggregation management is generally an optimization problem. The optimization goal is generally economic benefits, and the constraints are output power constraints, grid security constraints, etc. The control variables are generally the matching, combination, and sorting of various distributed resources.

[0041] Figure 3 It is a structural block diagram of a distributed resource aggregation trading platform based on blockchain technology according to an embodiment of the present disclosure.

[0042] like Figure 3 As shown, this example involves multiple functional modules, including a front-end application module, a load balancing module, an identity management module, a contract management module, an aggregation management module, a statistical analysis module, an intelligent control module, a transaction settlement module, a smart contract module, a blockchain platform module, and a smart terminal module based on a blockchain chip.

[0043] Front-end application module: The front-end application module refers to the part directly facing users in the distributed resource aggregation trading platform based on blockchain technology, which usually runs on the user's browser or mobile device. It is responsible for interacting with users, displaying data, and passing user operations to the back-end server for processing.

[0044] Load balancing: The load balancing module is deployed between the front-end and back-end. The front-end user's request first reaches the load balancing module, which can evenly distribute these requests to the various servers on the back-end according to the preset strategy. This can prevent a single back-end server from responding slowly or crashing due to excessive load, ensuring the stability and performance of the entire system.

[0045] Back-end application module: The back-end application module is the module responsible for the main functions in the distributed resource aggregation trading platform system based on blockchain technology, including identity management module, contract management module, aggregation management module, statistical analysis module, intelligent control module, and transaction settlement module.

[0046] Identity management module: The identity management module is mainly responsible for the authentication, authorization and management of user identities in the distributed resource aggregation trading platform system based on blockchain technology. The identity information of distributed energy entities will be stored on the chain through the smart contract module.

[0047] Contract management module: The contract management module is a software tool used to manage the contracts of various distributed energy entities. The contract management module can store the contracts of various distributed energy entities on the chain through smart contracts.

[0048] like Figure 4 As shown in the figure, the process of storing the contract on the chain is as follows: the distributed resource subject declares the contract through the contract management module, and the contract management module stores the contract data on the chain through the smart contract module. It requires four steps: subject identity authentication, contract data review, obtaining the logical contract address and uploading the contract data to the chain. Finally, the contract data is written into the blockchain for permanent storage.

[0049] Statistical analysis module: The statistical analysis module reads data installed on intelligent terminals of distributed photovoltaic, distributed wind power, small hydropower, etc., counts the power generation of different types of distributed energy equipment, including daily power generation, monthly power generation, annual power generation, etc., analyzes the changing trends of energy production in different time periods, such as seasonal changes, day and night changes, etc., cleans, organizes and classifies the collected data, and predicts the output of each distributed energy entity. The statistical analysis module can load algorithms such as time series analysis algorithms, regression analysis algorithms or machine learning algorithms to predict the output of each distributed resource entity, providing a basis for distributed resource aggregation management.

[0050] Aggregation management module: The aggregation management module is a key module for the effective integration and management of distributed energy systems. It can read the operating data of distributed energy equipment (such as distributed photovoltaic, distributed wind power, small hydropower, etc.), including power generation, power output, equipment status, etc., and optimize the scheduling according to the real-time data of energy production and the results of energy demand and supply predicted by the statistical analysis module, and reasonably allocate the power generation of distributed energy equipment to ensure efficient use of energy and balance between supply and demand. Aggregation management is generally an optimization problem. The optimization goal is generally economic benefits, and the constraints are output power constraints, grid security constraints, etc. The control variables are generally the matching, combination, and sorting of various distributed resources.

[0051] Intelligent control module: The intelligent control module analyzes the instructions issued by the dispatch system and decomposes them into instructions for controlling each distributed energy entity. The intelligent control module also stores the instruction information on the chain through the smart contract module. At the same time, when a distributed resource device fails, the intelligent control module can issue instructions in time to disconnect the faulty entity and adjust the output of other distributed resource entities to meet the instruction requirements.

[0052] Transaction settlement module: The transaction settlement module needs to accurately measure the energy provided or consumed by the distributed energy entities participating in the transaction, and calculate the price of the transaction according to the market price and transaction rules. Fees are settled based on the metering data and price calculation results. The transaction settlement module needs to manage various data in the transaction process, including energy metering data, price information, settlement records, etc., and store the above data on the chain through the smart contract module.

[0053] Smart contract module: The smart contract module plays an important role in the distributed resource aggregation trading platform. The key information in the identity management module, contract management module, statistical analysis module, aggregation management module, intelligent control module and transaction settlement module will be automatically stored on the chain through the smart contract module without manual intervention, which greatly improves the efficiency and reliability of transactions. In addition, the smart contract code is jointly maintained and executed by multiple nodes to ensure the fairness and reliability of the contract.

[0054] Blockchain platform module: All key data and process information of distributed resource aggregation participating in transactions are recorded on the blockchain. Each distributed resource subject can view the detailed information of the transaction at any time. The blockchain platform stores the relevant data and process information in multiple nodes, avoiding the risk of data loss caused by the failure of a single central node. This decentralized storage method ensures the security and reliability of data, making it difficult for relevant records to be tampered with or deleted.

[0055] Smart terminal module based on blockchain chip: The smart terminal module can collect real-time operating data of distributed energy equipment, such as power generation, power consumption, power, etc. At the same time, it can also monitor the status of the equipment, such as whether the equipment is operating normally, whether there is a fault, etc., and store these data on the chain in real time. like Figure 5 As shown in the figure, the smart terminal based on blockchain chip consists of sampling module, blockchain chip, communication interface and power module. The sampling module can collect power generation data, power consumption data or power of distributed resources; the blockchain chip can organize and standardize the collected data, and store it on the chain, and can receive instructions sent by the distributed resource aggregation trading platform, and send the instructions to the distributed resource subject through the communication interface module; the communication interface module is responsible for sending the instruction information to the distributed resource subject; the power module supplies power to the sampling module, blockchain chip and communication interface module in the smart terminal. The smart terminal module based on blockchain chip also has a powerful security authentication function, which ensures the authenticity, integrity and security of data through digital signature, encryption and other technologies. Only authorized users can access and operate the smart terminal to prevent illegal tampering and theft of data.

[0056] Each blockchain chip has a unique identifier. The blockchain platform can distinguish the data uploaded by different blockchain chips based on the identifier and bind the blockchain chip to the distributed resource subject. The smart terminal based on the blockchain chip can upload the collected distributed resource output data (including voltage and current data) to the blockchain platform. The whole process is automated without manual operation, ensuring the accuracy of the distributed resource subject output data and the fairness of distributed resource aggregation transactions.

[0057] In general, the distributed resource aggregation trading platform based on blockchain technology consists of two major parts, namely, the intelligent terminal based on blockchain chip (hardware part) and the distributed resource aggregation trading platform based on blockchain technology (software part). The intelligent terminal based on blockchain chip is responsible for recording the output data of each distributed resource subject on the chain in a real and reliable manner. The distributed resource aggregation trading platform based on blockchain technology includes front-end application module, load balancing module, back-end application module, smart contract module and blockchain platform module, among which the back-end application module includes identity management module, contract management module, aggregation management module, statistical analysis module, intelligent control module and transaction settlement module. The front-end application module provides users with an interactive operation interface and passes the user's operation to the back-end application module. The load balancing module evenly distributes the user's request to the back-end server. The back-end application module provides users with identity management, contract management, aggregation management, statistical analysis, intelligent control and transaction settlement services, and stores identity information, contract information, aggregation information, statistical data, control information and transaction settlement information on the chain through the smart contract module, and records the key data and information in the distributed resource aggregation transaction process through the blockchain platform.

[0058] The following is an example of an aggregate transaction process according to an embodiment of the present disclosure: Step 1: Identity Registration Each distributed resource subject first needs to register its identity on the distributed resource aggregation trading platform. This process involves the front-end application module, load balancing module, identity management module in the back-end application module, smart contract module and blockchain platform module. The user initiates the operation from the front-end application module, which goes through the load balancing module to the identity management module in the back-end application module to review and manage the identity information, and then uploads it to the blockchain platform module for evidence storage through the smart contract module. Step 2: Sign the contract Distributed resource entities that intend to participate in distributed resource aggregation transactions sign contracts on the distributed resource aggregation trading platform and store evidence on the chain through the smart contract module; Step 3: Transaction reporting According to the data obtained by the smart terminal based on the blockchain chip and the statistical analysis module, the aggregation management module matches, sorts and combines the distributed resources, forms the declaration curve and declaration capacity, and reports to the trading center; Step 4: Safety Check The trading center submits the pre-transaction results to the power grid dispatcher for safety verification. The power grid dispatcher returns the safety verification results to the trading center, and the trading center clears the transaction. Step 5: Aggregate and participate in the transaction In the process of distributed resource aggregation and transaction, the smart terminal based on blockchain chip collects the output of each distributed resource in real time. The distributed resource aggregation trading platform reports the aggregated output data to the power grid dispatcher, and the power grid dispatcher issues a dispatch instruction. The intelligent control module in the distributed resource aggregation trading platform determines the output of each distributed resource according to the dispatch instruction, and issues a power instruction to each distributed resource. The relevant instructions are recorded on the chain through the smart contract module; Step 6: Transaction Settlement The transaction settlement module of the distributed resource aggregation trading platform reads the output data of each distributed resource on the blockchain platform based on the settlement information of the power trading center, comprehensively considers the settlement information of the power trading center and the output data of each distributed resource, conducts transaction settlement for each distributed resource entity, divides the income according to the output situation, and stores the transaction settlement data in the blockchain platform through the smart contract module.

[0059] According to the above implementation methods, in order to solve the problems faced by distributed energy aggregation in participating in power trading, such as data authenticity and credibility, fair and just trading environment, and insufficient efficiency of multi-subject collaboration, a distributed resource aggregation trading platform based on blockchain technology is proposed. The system includes a smart terminal based on a blockchain chip and a distributed resource aggregation trading platform based on blockchain technology. The smart terminal based on a blockchain chip ensures that the source of each distributed resource output data is credible. The distributed resource aggregation trading platform based on blockchain technology ensures that the key data and information in the distributed resource aggregation transaction process are fully stored on the chain, ensuring the transparency, fairness and interests of all parties in the aggregation transaction.

[0060] Figure 6 It is a structural block diagram of a distributed resource aggregation management device according to an embodiment of the present disclosure.

[0061] like Figure 6 As shown, the distributed resource aggregation management device may include: The aggregated resource determination module 610 is used to determine a plurality of target distributed resources participating in the aggregated management from the plurality of distributed resources based on the geographic location information of the first aggregated area and the geographic location information of the plurality of distributed resources, wherein the target distributed resources include distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points and flexible load points; A first function determination module 620, configured to determine a main output curve function based on an output function of each of the distributed photovoltaic stations, an output function of each of the distributed wind power stations, and an output function of each of the hydropower stations; The auxiliary output determination module 630 is used to determine the auxiliary adjustment output curve based on the main output curve function and the preset main output target curve; A second function determination module 640, configured to determine an output function of each of the energy storage points and an output function of each of the flexible load points based on the auxiliary adjustment output curve; A third function determination module 650 is used to determine an aggregate output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points; An objective function determination module 660, configured to determine an objective function for characterizing the economic benefits of the first aggregation area based on the aggregated output curve function and the electricity prices at various times; An output constraint determination module 670, configured to determine an aggregate output curve constraint based on the aggregate output curve function and a preset aggregate output target curve; An objective function solving module 680 is used to solve the objective function for a maximum value based on the aggregate output curve constraint to obtain a target output curve of each target distributed resource in the first aggregation area; The output scheduling module 690 is used to schedule the output of each of the target distributed resources in the first aggregation area based on the target output curve of each of the target distributed resources.

[0062] In one implementation, the first function determination module 620 is specifically configured to: The output functions of each of the distributed photovoltaic stations, the output functions of each of the distributed wind power stations, and the output functions of each of the hydropower stations are summed to obtain a main output curve function of the main output varying with time.

[0063] In one implementation, the auxiliary output determination module 630 is specifically configured to: The auxiliary adjustment output curve is determined based on the deviation between the main output at each moment in the main output curve function and the main output at the corresponding moment in the main output target curve.

[0064] In one implementation, the second function determination module 640 is specifically configured to: Based on the auxiliary regulation output curve, determining the charging energy or discharging energy of each of the energy storage points at each moment, and the regulation output of each of the flexible load points at each moment; Determine the output function of each energy storage point based on the charging energy or discharging energy of each energy storage point at each moment; Based on the regulated output of each of the flexible load points at each moment and the basic output of each of the flexible load points, the output function of each of the flexible load points is determined.

[0065] In one implementation, the third function determination module 650 is specifically configured to: The main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points are summed to obtain the aggregate output curve function.

[0066] In one implementation, the objective function determination module 660 is specifically configured to: Determine the economic benefit dependent variable at each moment based on the product of the aggregate output independent variable at each moment in the aggregate output curve function and the electricity price at the corresponding moment; The objective function is determined based on the economic benefit dependent variable at each moment.

[0067] In one embodiment, the aggregate output curve is constrained by the following formula: in, represents the output of the i-th distributed photovoltaic station at time t, represents the output of the i-th distributed wind power station at time t, represents the output of the i-th hydropower station at time t, represents the output of the i-th energy storage point at time t, represents the output of the i-th flexible load point at time t, Represents the target output at time t in the aggregate output target curve.

[0068] For the description of specific functions and examples of each module and submodule of the device in the embodiment of the present invention, reference can be made to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0069] In the technical solution of the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0070] According to an embodiment of the present invention, the present invention also provides an electronic device and a readable storage medium.

[0071] Figure 7A schematic block diagram of an example electronic device 800 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0072] like Figure 7 As shown, the device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 to a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0073] A number of components in the device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0074] The computing unit 801 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above, such as the distributed resource aggregation management method. For example, in some embodiments, the distributed resource aggregation management method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the distributed resource aggregation management method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the distributed resource aggregation management method in any other appropriate manner (e.g., by means of firmware).

[0075] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0076] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0077] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0078] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0079] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0080] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0081] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0082] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed resource aggregation management method, characterized in that: include: Based on the geographic location information of the first aggregation area and the geographic location information of the plurality of distributed resources, a plurality of target distributed resources participating in the aggregation management are determined from the plurality of distributed resources, wherein the target distributed resources include distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points and flexible load points; Determine a main output curve function based on the output function of each of the distributed photovoltaic stations, the output function of each of the distributed wind power stations, and the output function of each of the hydropower stations; Based on the main output curve function and a preset main output target curve, determining an auxiliary adjustment output curve; Based on the auxiliary adjustment output curve, determining the output function of each of the energy storage points and the output function of each of the flexible load points; Determine an aggregate output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points; Based on the aggregated output curve function and the electricity price at each moment, determining an objective function for characterizing the economic benefits of the first aggregated area; Determining an aggregate output curve constraint based on the aggregate output curve function and a preset aggregate output target curve; Based on the aggregate output curve constraint, solving the objective function for the maximum value to obtain the target output curve of each target distributed resource in the first aggregation area; Based on the target output curve of each target distributed resource, output scheduling is performed on each target distributed resource in the first aggregation area.

2. The method according to claim 1, characterized in that Determining the main output curve function based on the output function of each of the distributed photovoltaic stations, the output function of each of the distributed wind power stations, and the output function of each of the hydropower stations includes: The output functions of each of the distributed photovoltaic stations, the output functions of each of the distributed wind power stations, and the output functions of each of the hydropower stations are summed to obtain a main output curve function of the main output varying with time.

3. The method according to claim 1, characterized in that The determining of the auxiliary adjustment output curve based on the main output curve function and the preset main output target curve includes: The auxiliary adjustment output curve is determined based on the deviation between the main output at each moment in the main output curve function and the main output at the corresponding moment in the main output target curve.

4. The method according to claim 1, characterized in that The determining of the output function of each of the energy storage points and the output function of each of the flexible load points based on the auxiliary adjustment output curve includes: Based on the auxiliary regulation output curve, determining the charging energy or discharging energy of each of the energy storage points at each moment, and the regulation output of each of the flexible load points at each moment; Determine the output function of each energy storage point based on the charging energy or discharging energy of each energy storage point at each moment; Based on the regulated output of each of the flexible load points at each moment and the basic output of each of the flexible load points, the output function of each of the flexible load points is determined.

5. The method according to claim 1, characterized in that: The determining of the aggregated output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points includes: The main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points are summed to obtain the aggregate output curve function.

6. The method according to claim 1, characterized in that The determining, based on the aggregated output curve function and the electricity prices at various times, an objective function for characterizing the economic benefits of the first aggregated area includes: Determine the economic benefit dependent variable at each moment based on the product of the aggregate output independent variable at each moment in the aggregate output curve function and the electricity price at the corresponding moment; The objective function is determined based on the economic benefit dependent variable at each moment.

7. The method according to claim 1, characterized in that The aggregate output curve constraint is as follows: in, represents the output of the i-th distributed photovoltaic station at time t, represents the output of the i-th distributed wind power station at time t, represents the output of the i-th hydropower station at time t, represents the output of the i-th energy storage point at time t, represents the output of the i-th flexible load point at time t, Represents the target output at time t in the aggregate output target curve.

8. A distributed resource aggregation management device, characterized in that: include: An aggregated resource determination module, configured to determine, based on geographic location information of a first aggregated area and geographic location information of a plurality of distributed resources, a plurality of target distributed resources participating in aggregated management from the plurality of distributed resources, wherein the target distributed resources include distributed photovoltaic stations, distributed wind power stations, hydropower stations, energy storage points, and flexible load points; A first function determination module, configured to determine a main output curve function based on an output function of each of the distributed photovoltaic stations, an output function of each of the distributed wind power stations, and an output function of each of the hydropower stations; An auxiliary output determination module, used to determine an auxiliary adjustment output curve based on the main output curve function and a preset main output target curve; A second function determination module, used to determine the output function of each of the energy storage points and the output function of each of the flexible load points based on the auxiliary adjustment output curve; A third function determination module is used to determine an aggregate output curve function based on the main output curve function, the output functions of each of the energy storage points, and the output functions of each of the flexible load points; An objective function determination module, configured to determine an objective function for characterizing the economic benefits of the first aggregation area based on the aggregate output curve function and the electricity prices at various times; An output constraint determination module, configured to determine an aggregate output curve constraint based on the aggregate output curve function and a preset aggregate output target curve; an objective function solving module, configured to solve the objective function for a maximum value based on the aggregate output curve constraint, and obtain a target output curve of each target distributed resource in the first aggregation area; The output scheduling module is used to schedule the output of each of the target distributed resources in the first aggregation area based on the target output curve of each of the target distributed resources.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

Images