Load-side transaction scheduling method and related products based on smart contracts

Abstract

The embodiment of the present invention discloses a load-side transaction scheduling method based on smart contracts and related products, the method comprising: constructing an optimized scheduling contract; obtaining target data of each prosumer among multiple prosumers in a historical time period to obtain multiple target data; predicting the reference power generation and reference power consumption of each prosumer in a future time period based on power generation data and power consumption data to obtain multiple reference power generation and multiple reference power consumption; obtaining electricity price data of a distribution network in a future time period; determining an optimized scheduling plan between a prosumer system, an energy storage system and a distribution network in a future time period based on the optimized scheduling contract, multiple reference power generation, multiple reference power consumption and electricity price data; controlling the energy storage system to charge and discharge based on a charging and discharging operation plan; generating an electricity trading contract based on a first power purchase and sale plan and a second power purchase and sale plan; and controlling transaction scheduling between a prosumer system, an energy storage system and a distribution network based on the electricity trading contract.

Description

Technical Field

[0001] The present invention relates to the technical field of load-side energy scheduling, and in particular to a load-side transaction scheduling method based on smart contracts and related products. Background Art

[0002] In recent years, with the widespread application of energy resources, prosumers with both power generation and power consumption attributes have emerged on the load side, and they exist widely in the form of microgrids, virtual power plants, integrated energy systems, etc. The collaborative interaction between prosumers can optimize the allocation of power resources and support the safe and stable operation of the power grid, and its optimized dispatch is a key link.

[0003] In the energy supply system of prosumers, the power supply of prosumer loads is usually jointly undertaken by the corresponding renewable energy generation and regional distribution networks. Renewable energy generation gives priority to meeting load demand, and the remaining electricity is purchased by the regional distribution network. However, the regional distribution network purchases electricity at a low price and prosumers purchase electricity at a time-of-use price. Due to the mismatch between load demand and the timing of renewable energy generation, prosumers have higher energy costs when using electric energy.

[0004] Therefore, there is an urgent need for a load-side transaction scheduling method based on smart contracts to optimize the allocation and use of power resources when performing energy scheduling on the load side, reduce the dependence of prosumers on regional distribution networks, and reduce the energy costs of prosumers when using electric energy. Summary of the invention

[0005] In order to solve the above problems, the embodiments of the present invention provide a load-side transaction scheduling method and related products based on smart contracts. When performing energy scheduling on the load side, it can optimize the allocation and use of power resources, reduce the dependence of producers and consumers on regional distribution networks, and reduce the energy costs of producers and consumers when using electric energy.

[0006] In a first aspect, an embodiment of the present invention provides a load-side transaction scheduling method based on a smart contract, the method is applied to a blockchain system, the blockchain system includes multiple nodes, and the method includes:

[0007] Constructing an optimization dispatching contract, and constructing an energy storage control contract and a power purchase and sale contract generation contract; the optimization dispatching contract is used to dispatch power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the energy storage system to charge and discharge, the prosumer system includes a plurality of prosumers, each prosumer corresponds to a power generation device and a power consumption device;

[0008] Acquire data of each of the multiple nodes to obtain multiple node data;

[0009] When the plurality of node data satisfy the first trigger condition corresponding to the optimization scheduling contract, the target data of each of the plurality of prosumers in the historical time period is obtained to obtain a plurality of target data, wherein the target data includes the power generation data of the power generation equipment and the power consumption data of the power consumption equipment;

[0010] Based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period are predicted to obtain multiple reference power generation and multiple reference power consumption;

[0011] Obtaining electricity price data of the distribution network in the future time period, the electricity price data including electricity purchase price data and electricity sales price data;

[0012] Determine an optimal scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal scheduling contract, the multiple reference power generation, the multiple reference power consumption and the electricity price data, wherein the optimal scheduling plan includes a first power purchase and sale plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sale plan between the energy storage system and the distribution network;

[0013] When the plurality of node data satisfy the second trigger condition corresponding to the energy storage control contract, controlling the energy storage system to charge and discharge based on the charge and discharge operation plan;

[0014] When the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, generating a power transaction contract based on the first power purchase and sale plan and the second power purchase and sale plan;

[0015] Based on the power trading contract, trading scheduling is controlled among the prosumer system, the energy storage system and the distribution network.

[0016] In a second aspect, an embodiment of the present invention provides a load-side transaction scheduling device based on a smart contract, the device is applied to a blockchain system, the blockchain system includes multiple nodes, and the device includes a construction unit, an acquisition unit, and a processing unit;

[0017] The construction unit is used to construct an optimization scheduling contract, and to construct an energy storage control contract and a power purchase and sale contract generation contract; the optimization scheduling contract is used to schedule power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the energy storage system to charge and discharge, and the prosumer system includes a plurality of prosumers, each prosumer corresponds to a power generation device and an electric power consumption device;

[0018] The acquisition unit is used to acquire data of each of the multiple nodes to obtain multiple node data;

[0019] The processing unit is configured to obtain target data of each of the multiple prosumers in a historical time period when the multiple node data meet the first trigger condition corresponding to the optimization scheduling contract, and obtain multiple target data, wherein the target data includes power generation data of the power generation equipment and power consumption data of the power consumption equipment;

[0020] Predicting a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, to obtain multiple reference power generation and multiple reference power consumption; the start time of the future time period is later than the end time of the historical time period;

[0021] Obtaining electricity price data of the distribution network in the future time period, the electricity price data including electricity purchase price data and electricity sales price data;

[0022] Determine an optimal scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal scheduling contract, the multiple reference power generation, the multiple reference power consumption and the electricity price data, wherein the optimal scheduling plan includes a first power purchase and sale plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sale plan between the energy storage system and the distribution network;

[0023] When the plurality of node data satisfy the second trigger condition corresponding to the energy storage control contract, controlling the energy storage system to charge and discharge based on the charge and discharge operation plan;

[0024] When the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, generating a power transaction contract based on the first power purchase and sale plan and the second power purchase and sale plan;

[0025] Based on the power trading contract, trading scheduling is controlled among the prosumer system, the energy storage system and the distribution network.

[0026] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device performs the method described in the first aspect.

[0027] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method as described in the first aspect.

[0028] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer is operable to cause the computer to execute the method described in the first aspect.

[0029] Implementing the embodiments of the present application has the following beneficial effects:

[0030] In the implementation mode of the present application, an optimization scheduling contract is first constructed, and an energy storage control contract and a power purchase and sale contract generation contract are constructed, wherein the optimization scheduling contract is used to schedule power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the energy storage system to charge and discharge, and the prosumer system includes multiple prosumers, each prosumer corresponds to a power generation device and an electric power consumption device, then, data of each of the multiple nodes is obtained to obtain multiple node data, when the multiple node data meet the first trigger condition corresponding to the optimization scheduling contract, the target data of each of the multiple prosumers in the historical time period is obtained to obtain multiple target data, wherein the target data includes the power generation data of the power generation device and the power consumption data of the electric power consumption device, then, based on the power generation data of each power generation device and the power consumption data of each electric power consumption device in the multiple target data, the reference power generation and reference power consumption of each of the multiple prosumers in the future time period are predicted to obtain multiple reference power generation and multiple reference power consumptions, and obtaining electricity price data of the distribution network in a future time period, wherein the electricity price data includes electricity purchase price data and electricity sales price data, and then determining an optimized scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimized scheduling contract, multiple reference power generation, multiple reference power consumptions and electricity price data, wherein the optimized scheduling plan includes a first power purchase and sales plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sales plan between the energy storage system and the distribution network; when multiple node data meet the second trigger condition corresponding to the energy storage control contract, the energy storage system is controlled to charge and discharge based on the charge and discharge operation plan; when multiple node data meet the third trigger condition corresponding to the power purchase and sales contract generation contract, a power trading contract is generated based on the first power purchase and sales plan and the second power purchase and sales plan, and trading scheduling between the prosumer system, the energy storage system and the distribution network is controlled based on the power trading contract. Therefore, by constructing an optimized scheduling contract and predicting reference power generation and reference power consumption, and determining the optimized scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimized scheduling contract, and controlling the charging and discharging of the energy storage system and the transaction scheduling between the prosumer system, the energy storage system and the distribution network according to the optimized scheduling plan, when performing energy scheduling on the load side, it is possible to optimize the allocation and use of power resources, reduce the dependence of prosumers on regional distribution networks, and reduce the energy costs of prosumers when using electric energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 This is a schematic diagram of the architecture of a blockchain system provided by an embodiment of the present application;

[0033] Figure 2 It is a schematic diagram of a topological architecture between a prosumer system, an energy storage system and a distribution network provided in an embodiment of the present application;

[0034] Figure 3 It is a flow chart of a load-side transaction scheduling method based on a smart contract provided in an embodiment of the present application;

[0035] Figure 4 It is a smart contract-based energy management flow chart provided in an embodiment of the present application;

[0036] Figure 5 This is a data privacy protection strategy flow chart of a blockchain system provided by an embodiment of the present application;

[0037] Figure 6 It is a schematic diagram of a prediction result of power consumption and power generation of a prosumer system and power price data of a distribution network provided in an embodiment of the present application;

[0038] Figure 7 is a schematic diagram of a first electricity purchase and sales plan provided in an embodiment of the present application;

[0039] Figure 8 is a schematic diagram of a charging and discharging operation plan provided in an embodiment of the present application;

[0040] Fig. 9 is a schematic diagram of a second electricity purchase and sales plan provided in an embodiment of the present application;

[0041] Fig.10 It is a schematic diagram of charging and discharging power change and capacity change of an energy storage system provided in an embodiment of the present application;

[0042] Fig.11 This is a schematic diagram showing the effect of a data privacy protection strategy provided by an embodiment of the present application;

[0043] Fig.12 It is a structural diagram of a load-side transaction scheduling device based on a smart contract provided in an embodiment of the present application;

[0044] Fig.13 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but optionally includes steps or modules that are not listed, or optionally includes other steps or modules inherent to these processes, methods, products or devices.

[0047] Reference to "embodiments" herein means that a particular feature, result, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0048] Since the prosumers in the prosumer system and the prosumer system and the regional energy service providers belong to different interest entities, there is a strong trust requirement when formulating energy management strategies. Therefore, in order to improve the efficiency and transparency of energy scheduling and ensure data security and privacy protection during the scheduling process, the load-side transaction scheduling method based on smart contracts provided in the embodiment of the present application is applied to the blockchain system, and the prosumer system and the energy storage system are jointly operated in a decentralized manner, and an optimized scheduling plan is formulated for the prosumer system and the energy storage system with the goal of optimizing overall economic efficiency. Figure 1 , Figure 1 This is a schematic diagram of the architecture of a blockchain system provided by an embodiment of the present application. Figure 1As shown in FIG. 1 , the blockchain system includes multiple nodes. Multiple prosumers in the prosumer system, energy storage devices in the energy storage system, power grid operators corresponding to the regional distribution network, regional energy service providers, distributed resource owners and government regulatory departments, etc. can all be connected through multiple nodes of the blockchain system. The blockchain system provides a multi-party co-governance collaboration model based on a decentralized approach, wherein the energy storage device can be a shared energy storage device. There are consensus nodes among the multiple nodes. The consensus nodes are used to perform consensus verification on the initial data uploaded by multiple nodes. The smart contracts and other data records on the chain need consensus nodes to verify their legitimacy and correctness. Nodes that meet the requirements can be extracted from prosumers, distributed resource owners, regional energy service providers, power grid companies and government regulatory departments as consensus nodes, and form an energy dispatch consensus committee to ensure that representatives of all parties participate. The energy dispatch consensus committee is responsible for executing the data information consensus of the blockchain system, ensuring that each dispatch instruction and transaction result is verified and recorded by the committee node. Each consensus node and other nodes maintain a copy of the blockchain ledger, thereby greatly increasing the transparency and trust of the data.

[0049] See also Figure 2 , Figure 2 Schematic diagram of a topological architecture between a prosumer system, an energy storage system and a distribution network provided in an embodiment of the present application. Figure 2 As shown, the regional distribution network is connected to each prosumer in the prosumer system, each prosumer is connected to the energy storage system, the energy storage system may include a shared energy storage device, and the energy storage system is connected to the regional distribution network. Since each prosumer in the prosumer system has the characteristics of both generating and consuming electricity, and the electricity price of the regional distribution network when purchasing and selling electricity is a time-of-use electricity price, the regional distribution network, the energy storage system and the prosumer system can trade and dispatch power resources.

[0050] See also Figure 3 , Figure 3 : is a flow chart of a load side transaction scheduling method based on smart contracts provided in an embodiment of the present application. Figure 3 As shown, the load-side transaction scheduling method based on smart contracts provided in the embodiment of the present application includes but is not limited to the following steps:

[0051] Step S101: construct an optimization dispatch contract, and construct an energy storage control contract and a power purchase and sales contract generation contract;

[0052] Among them, the optimization scheduling contract is used to schedule the power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the charging and discharging of the energy storage system. The prosumer system includes multiple prosumers, each of which corresponds to a power generation device and an electricity consumption device;

[0053] Step S102: acquiring data of each of the multiple nodes to obtain multiple node data;

[0054] Step S103: when the plurality of node data satisfy the first trigger condition corresponding to the optimization scheduling contract, the target data of each of the plurality of prosumers in the historical time period is obtained to obtain a plurality of target data;

[0055] The target data includes power generation data of power generation equipment and power consumption data of power consumption equipment;

[0056] Step S104: predicting a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, to obtain multiple reference power generation and multiple reference power consumption;

[0057] Step S105: Obtaining electricity price data of the distribution network in a future time period;

[0058] Among them, electricity price data includes electricity purchase price data and electricity sales price data;

[0059] Step S106: Determine an optimal dispatch plan between the prosumer system, the energy storage system and the distribution network in a future time period based on the optimal dispatch contract, multiple reference power generation, multiple reference power consumption and electricity price data;

[0060] The optimized dispatching plan includes a first power purchase and sales plan between each of the multiple prosumers and the distribution network, a charging and discharging operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sales plan between the energy storage system and the distribution network.

[0061] Step S107: When the data of multiple nodes meet the second trigger condition corresponding to the energy storage control contract, the energy storage system is controlled to charge and discharge based on the charge and discharge operation plan;

[0062] Step S108: when the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, a power transaction contract is generated based on the first power purchase and sale plan and the second power purchase and sale plan;

[0063] Step S109: Control the transaction scheduling between the prosumer system, the energy storage system and the distribution network based on the power transaction contract.

[0064] In one possible embodiment, the prosumer system and the energy storage system automatically generate and execute energy dispatch instructions through preset smart contracts. The preset smart contracts include optimized dispatch contracts, energy storage control contracts, and power purchase and sales contract generation contracts. Smart contracts can ensure that all operations are executed according to established rules, thereby reducing the possibility of misoperation and fraud. Smart contracts are self-executing programs deployed on the blockchain that can automatically execute preset energy management strategies when specific conditions are met. The introduction of smart contracts provides great convenience for automated management and can achieve efficient energy dispatch and energy storage management.

[0065] In a possible embodiment, the energy storage control smart contract is combined with the controller to jointly manage the charging and discharging process of the energy storage system, and automatically generates control signals according to the charging and discharging operation plan for the future time period. The energy storage control smart contract receives the charging and discharging operation plan, which includes the charging or discharging behavior and its charging and discharging power for each time period. Based on the energy storage control smart contract, the corresponding control signal is calculated and sent to the controller of the energy storage system to achieve optimal management of the energy storage system. The power purchase and sales contract generation contract is used to process the power transaction between the prosumer system and the distribution network, and automatically generates the power transaction contract. The power purchase and sales contract generation contract receives the power purchase and sales plan of the prosumer system in the future time period. The generated contract records the power purchase and sales amount, power sales amount and quotation at each time point in detail for subsequent settlement and execution.

[0066] In a possible embodiment, the first trigger condition corresponding to the optimized scheduling contract can be a specific time of the day, such as midnight, or automatically triggered when the energy market price is updated, or triggered when the energy scheduling consensus committee receives new energy demand forecasts or market supply and demand changes. After the first trigger condition is met, data input from the energy market and real-time energy demand is received, and the optimal power purchase and sales plan and charging and discharging operation plan for the next day are calculated based on the input data and the preset optimization model. The optimized scheduling plan is encoded into a contract form and recorded on the blockchain to ensure the immutability and transparency of the data, and an execution signal is sent to the relevant energy equipment and systems to execute the power purchase and sales and energy storage operations as planned.

[0067] In a possible embodiment, the second trigger condition corresponding to the energy storage control contract can be automatically triggered according to the charge and discharge operation plan generated by the energy optimization scheduling contract before a specific time every day, or it can be urgently triggered when the system detects a change or abnormality in the state of the energy storage device. After the second trigger condition is met, the charge and discharge operation plan transmitted from the energy optimization scheduling contract is received, the charging or discharging requirements of each time period in the charge and discharge operation plan are analyzed, and a corresponding control signal is generated, and the control signal is sent to the controller of the energy storage system, so that the energy storage device is charged and discharged according to the plan, and the control activities and their effects are recorded on the blockchain for subsequent audit and verification.

[0068] In a possible embodiment, the third trigger condition corresponding to the power purchase and sales contract generation contract can be triggered immediately after a new power purchase and sales plan is generated daily according to the output of the energy optimization scheduling contract, or when the prosumer or distribution network operator updates the power trading demand. After the third trigger condition is met, the power purchase and sales plan transmitted from the energy optimization scheduling contract is received, and the power purchase, sales and electricity prices at each time point are recorded in detail according to the power purchase and sales plan, and a legally enforceable power trading contract is generated. The generated contract is recorded on the blockchain to ensure that the transaction record cannot be tampered with and is highly transparent. After the contract is generated, a notification is sent to both parties to the transaction to confirm the transaction and perform subsequent settlement operations.

[0069] In one possible embodiment, see Figure 4 , Figure 4 This is a flow chart of energy management based on smart contracts provided by the embodiment of the present application. Figure 4 As shown, a charging and discharging operation plan and a power purchase and sales plan are generated according to decision cycle switching, electricity price fluctuations, load power fluctuations, energy storage equipment status and optimized scheduling contracts. The power purchase and sales plan includes a first power purchase and sales plan and a second power purchase and sales plan. Automatic control of energy storage equipment is achieved through the charging and discharging operation plan and the energy storage control contract. A power purchase and sales contract is generated through the power purchase and sales plan and the power purchase and sales contract generation contract.

[0070] In addition, all participants can view the energy dispatch situation in real time through the blockchain browser or customized monitoring interface. The blockchain browser provides a transparent display of data, including power consumption, energy storage status, power purchase and sales records, etc. The data on the blockchain can also be detected for anomalies through the preset anomaly detection mechanism, abnormal situations can be discovered in time, and early warning notifications can be sent to relevant managers to ensure that problems can be handled quickly.

[0071] Optionally, in step S101, constructing an optimized scheduling contract may include the following steps:

[0072] Step S201: obtaining a first cost relationship between a first cost of transaction scheduling between the prosumer system and the distribution network and the purchase and sale price of electricity of the distribution network, the power purchased by the prosumer system from the distribution network, and the power sold by the prosumer system to the distribution network;

[0073] Step S202: determining a first cost formula for transaction scheduling between the prosumer system and the distribution network based on the first cost relationship;

[0074] Step S203: Obtain a second cost relationship between the second cost of transaction scheduling between the energy storage system and the distribution network and the purchase and sale price of electricity of the distribution network, the power purchased by the energy storage system from the distribution network, and the power sold by the energy storage system to the distribution network;

[0075] Step S204: determining a second cost formula for transaction scheduling between the energy storage system and the distribution network based on the second cost relationship;

[0076] Step S205: obtaining a third cost relationship between the third cost of charging and discharging the energy storage system and the power purchased by the energy storage system from the distribution network, the power sold to the distribution network, the charging power obtained from the prosumer system, the discharging power output to the prosumer system, and the charging and discharging cost of the energy storage system;

[0077] Step S206: determining a third cost formula for charging and discharging the energy storage system based on the third cost relationship;

[0078] Step S207: determining the total operating cost based on the first cost formula, the second cost formula and the third cost formula;

[0079] Step S208: Determine the objective function of the total operating cost;

[0080] Step S209: constructing the first equilibrium constraint condition of the prosumer system;

[0081] Step S210: constructing a second balance constraint condition of the energy storage system;

[0082] Step S211: construct an optimization scheduling contract based on the objective function, the first balance constraint condition and the second balance constraint condition.

[0083] In a possible embodiment, a first cost relationship between a first cost of transaction scheduling between the prosumer system and the distribution network and the purchase and sale price of electricity of the distribution network, the power purchased by the prosumer system from the distribution network, and the power sold by the prosumer system to the distribution network is obtained, and a first cost formula for transaction scheduling between the prosumer system and the distribution network is determined based on the first cost relationship. The first cost formula can be expressed by formula (1):

[0084] ………… (1)

[0085] in, is the first cost of transaction scheduling between the prosumer system and the distribution network, N is the number of prosumers in the prosumer system, T is the number of time periods in the target time period, n is the variable of the number of prosumers, t is the variable of the number of time periods, is the electricity price purchased from the distribution network during period t, is the power purchased by the nth prosumer from the distribution network during period t, is the electricity price sold to the distribution network during period t, It is the power sold by the nth prosumer to the distribution network in period t.

[0086] In a possible embodiment, a second cost relationship between the second cost of transaction scheduling between the energy storage system and the distribution network and the purchase and sale price of electricity of the distribution network, the power purchased by the energy storage system from the distribution network, and the power sold by the energy storage system to the distribution network is obtained, and a second cost formula for transaction scheduling between the energy storage system and the distribution network is determined based on the second cost relationship. The second cost formula can be expressed by formula (2):

[0087] …………(2)

[0088] in, is the second cost of transaction scheduling between the energy storage system and the distribution network, is the power purchased by the energy storage system from the distribution network during period t, is the power sold by the energy storage system to the distribution network during period t.

[0089] In a possible embodiment, a third cost relationship between the third cost of charging and discharging the energy storage system and the power purchased by the energy storage system from the distribution network, the power sold to the distribution network, the charging power obtained from the prosumer system, the discharging power output to the prosumer system, and the charging and discharging cost of the energy storage system is obtained, and a third cost formula for charging and discharging the energy storage system is determined based on the third cost relationship. The third cost formula can be expressed by formula (3):

[0090] ………… (3)

[0091] in, The third cost of charging and discharging the energy storage system is is the charging and discharging cost per unit power of the energy storage system, , They are respectively the charging power and discharging power of the energy storage system to the nth prosumer in period t.

[0092] In one possible embodiment, the objective function can be defined as minimizing the total operating cost of the prosumer system and the energy storage system. The objective function can be expressed as ,in, is the total operating cost, .

[0093] In a possible embodiment, a first balance constraint condition of the prosumer system is constructed based on the power balance purpose of each prosumer in the prosumer system. The first balance constraint condition can be expressed by formula (4) and formula (5):

[0094] …………(4)

[0095] ………… (5)

[0096] in, , , are the photovoltaic power generation and wind power generation of the nth prosumer in period t, , are the discharge power and charging power of the energy storage system to the nth prosumer during period t, is the load power of the nth prosumer in period t.

[0097] In a possible embodiment, a second balance constraint condition of the energy storage system is constructed based on the power interaction balance purpose between the prosumer system and the energy storage system. The first balance constraint condition can be expressed by formula (6) to formula (12):

[0098] …………(6)

[0099] …………(7)

[0100] in, , are the total charging power and total discharging power of the energy storage system respectively.

[0101] …………(8)

[0102] …………(9)

[0103] ………… (10)

[0104] in, is the remaining capacity of the energy storage system in period t, , are the charging and discharging efficiency coefficients of the energy storage system respectively; is the maximum power capacity of the energy storage system.

[0105] …………(11)

[0106] …………(12)

[0107] in, It is the charging and discharging power limit of the energy storage system.

[0108] In one possible embodiment, an optimization scheduling contract is constructed based on the objective function, the first balance constraint and the second balance constraint so that the optimization scheduling plan between the prosumer system, the energy storage system and the distribution network satisfies the objective function, the first balance constraint and the second balance constraint at the same time.

[0109] Optionally, step S104, based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, predicting the reference power generation and reference power consumption of each of the multiple prosumers in the future time period to obtain multiple reference power generation and multiple reference power consumption, may include the following steps:

[0110] Step S301: Acquire multiple power generation devices and multiple power consumption devices corresponding to multiple prosumers;

[0111] Step S302: Acquire the device status of each power generation device among the multiple power generation devices to obtain multiple device statuses;

[0112] Step S303: determining a plurality of first adjustment amounts based on a plurality of power generation equipment status data;

[0113] Step S304: determining the power generation characteristics of each power generation device among the multiple power generation devices to obtain multiple power generation characteristics, where the power generation characteristics include photovoltaic power generation and wind power generation;

[0114] Step S305: determining influencing factors related to weather trends based on multiple power generation characteristics, and obtaining multiple influencing factors, wherein the influencing factors include at least one of the following: light intensity, precipitation, temperature, and wind speed;

[0115] Step S306: Obtain weather data for a future time period;

[0116] Step S307: determining a plurality of second adjustment amounts based on weather data and a plurality of influencing factors;

[0117] Step S308: determining a plurality of reference power generation amounts based on the plurality of first adjustment amounts, the plurality of second adjustment amounts, and the power generation amount data of each power generation device in the plurality of target data;

[0118] Step S309: Obtaining time characteristics of future time periods;

[0119] Step S310: determining an adjustment factor corresponding to a time trend for each of a plurality of electrical devices, and obtaining a plurality of adjustment factors;

[0120] Step S311: determining a plurality of third adjustment amounts based on the time feature and a plurality of adjustment factors;

[0121] Step S312: determining a plurality of reference power consumptions based on the plurality of third adjustment amounts and the power consumption data of each power-consuming device in the plurality of target data.

[0122] In a possible embodiment, multiple power generation equipment and multiple power consumption equipment corresponding to multiple prosumers are obtained, and the equipment status of each of the multiple power generation equipment is obtained to obtain multiple equipment statuses. The multiple equipment statuses are used to reflect the power generation status of the power generation equipment. For solar power generation equipment, the light intensity, operating temperature and power generation data of the solar panel can be collected through light sensors, temperature sensors and power monitoring instruments. For wind power generation equipment, wind speed, wind direction and power generation information can be obtained through wind speed sensors, wind direction sensors and power monitoring devices, and then multiple equipment statuses are determined. The obtained power generation equipment status data is analyzed to determine the statistical indicators such as the average power generation power and power fluctuation range of each power generation equipment within a preset time, and by comparing with the historical average data of the equipment and the normal operation data of the same type of equipment, it is detected whether there is an abnormal situation. If the performance of the power generation equipment declines, a corresponding first adjustment amount is determined based on the operating conditions of the equipment and the degree of change in performance indicators. For example, if the conversion efficiency of the photovoltaic panel of a solar power generation equipment declines, the power loss caused by the decline in conversion efficiency is calculated based on its rated power and lighting conditions. Then, a first adjustment amount is determined based on this loss amount, and compensation or adjustment is made through the first adjustment amount in the subsequent power generation forecast.

[0123] In a possible embodiment, power generation characteristics of each power generation device among a plurality of power generation devices are determined to obtain a plurality of power generation characteristics, the power generation characteristics include photovoltaic power generation and wind power generation, influencing factors related to weather trends are determined based on the plurality of power generation characteristics to obtain a plurality of influencing factors, the influencing factors include at least one of the following: light intensity, precipitation, temperature, wind speed, weather data in a future time period is obtained, and a plurality of second adjustment amounts are determined based on the weather data and the plurality of influencing factors. For photovoltaic power generation, if the light intensity in the future time period is weak and there is precipitation, the expected reduction in photovoltaic power generation power in the time period is calculated according to a pre-established light intensity and power generation power relationship model and an attenuation model of precipitation on light intensity, and then the second adjustment amount is determined, and a plurality of reference power generation amounts are determined based on the power generation data of each power generation device in the plurality of first adjustment amounts, the plurality of second adjustment amounts, and the plurality of target data.

[0124] In a possible embodiment, time characteristics of a future time period are obtained, and an adjustment factor corresponding to the time trend of each of a plurality of power users is determined, that is, an adjustment factor corresponding to different time scales in the future time period for each power user, the adjustment factors of some devices correspond to short-term time characteristics, such as morning, noon, and evening, the adjustment factors of some devices correspond to medium-term time characteristics, such as different seasons, and the adjustment factors of some devices correspond to long-term time characteristics, such as different years, to obtain multiple adjustment factors, determine multiple third adjustment amounts based on the time characteristics and the multiple adjustment factors, and determine multiple reference power consumptions based on the multiple third adjustment amounts and the power consumption data of each power user in the multiple target data.

[0125] Optionally, step S106, determining an optimal dispatch plan between the prosumer system, the energy storage system and the distribution network in a future time period based on the optimal dispatch contract, multiple reference power generation, multiple reference power consumption and electricity price data, may include the following steps:

[0126] Step S401: determining the electricity sales demand and electricity consumption demand of each of the multiple prosumers in each period of the future time period based on multiple reference power generation and multiple reference power consumption, and obtaining multiple electricity sales demands and multiple electricity consumption demands;

[0127] Step S402: Based on the optimized scheduling contract, multiple electricity sales demands and multiple electricity consumption demands, determine the first electricity sales power sold to the distribution network, the first electricity purchase power purchased from the distribution network, the charging power output to the energy storage system and the discharging power obtained from the energy storage system by each of the multiple prosumers in each period in the future time period, and obtain multiple first electricity sales power sets, multiple first electricity purchase power sets, multiple charging power sets and multiple discharging power sets;

[0128] Step S403: Acquire energy storage status data of the energy storage system;

[0129] Step S404: determining the second sold power sold by the energy storage system and the distribution network to the distribution network and the second purchased power purchased from the distribution network in each period in the future time period based on the optimized scheduling contract and the energy storage status data, and obtaining multiple second sold power sets and multiple second purchased power sets;

[0130] Step S405: determining a first power purchase and sale plan based on a plurality of first power sales power sets and a plurality of first power purchase power sets;

[0131] Step S406: determining a charge and discharge operation plan based on the multiple charging power sets and the multiple discharging power sets;

[0132] Step S407: determining a second power purchase and sale plan based on the plurality of second power sales power sets and the plurality of second power purchase power sets;

[0133] Step S408: Integrate the first power purchase and sales plan, the charge and discharge operation plan, and the second power purchase and sales plan to obtain an optimized scheduling plan.

[0134] In a possible embodiment, the number of prosumers in the prosumer system is three, namely prosumer 1, prosumer 2 and prosumer 3, the number of shared energy storage devices in the energy storage system is one, prosumer 1 is configured as a photovoltaic generator set with an installed capacity of 750kW, prosumer 2 is configured as a wind power generator set with an installed capacity of 1000kW, prosumer 3 is configured with 600kW photovoltaic power generation and 500kW wind power generation, and the configuration capacity of the shared energy storage device is 400kW and 1000kWh. Figure 6 , Figure 6 Schematic diagram of the prediction results of the power consumption and power generation of a prosumer system and the power price data of the distribution network provided in an embodiment of the present application. Figure 6 The multiple reference power generation, multiple reference power consumption and electricity price data shown can determine the power sales demand and power consumption demand of each of the multiple prosumers in each time period in the future time period, and obtain multiple power sales demands and multiple power consumption demands. Then, based on the optimized scheduling contract, multiple power sales demands and multiple power consumption demands, determine the first power sales power sold to the distribution network, the first power purchase power purchased from the distribution network, the charging power output to the energy storage system, and the discharging power obtained from the energy storage system by each of the multiple prosumers in each time period in the future time period, and obtain multiple first power sales power sets, multiple first power purchase power sets, multiple charging power sets and multiple discharging power sets. Based on the multiple first power sales power sets and the multiple first power purchase power sets, the first power purchase and sales plan is determined in combination with the time data, see Figure 7 , Figure 7 : is a schematic diagram of a first power purchase and sale plan provided in an embodiment of the present application. The first power purchase and sale plan between each of the three prosumers and the distribution network is as follows: Figure 7 Determine the charging and discharging operation plan based on multiple charging power sets and multiple discharging power sets, Figure 8 is a schematic diagram of a charging and discharging operation plan provided in an embodiment of the present application. The charging and discharging operation plan between each of the three prosumers and the shared energy storage device is as follows: Figure 8 As shown. Based on the optimized scheduling contract and the energy storage status data, the energy storage system and the distribution network determine the second power sold to the distribution network and the second power purchased from the distribution network in each period of the future time period, and obtain multiple second power sales power sets and multiple second power purchase power sets. Based on the multiple second power sales power sets and multiple second power purchase power sets, the second power purchase and sale plan is determined. Fig. 9 is a schematic diagram of a second power purchase and sale plan provided in an embodiment of the present application. The second power purchase and sale plan between the shared energy storage device and the distribution network is as follows: Fig. 9After trading scheduling based on the optimized scheduling plan, the charging and discharging power and capacity changes of the energy storage system are shown in Fig.10 As shown, Fig.10 It is a schematic diagram of the charging and discharging power change and capacity change of an energy storage system provided in an embodiment of the present application.

[0135] Optionally, step S102, obtaining data of each of the multiple nodes to obtain multiple node data, may include the following steps:

[0136] Step S501: Acquire initial data of each of a plurality of nodes to obtain a plurality of initial data;

[0137] Step S502: encrypting each of the multiple initial data to obtain multiple encrypted data;

[0138] Step S503: performing consensus verification on each encrypted data in the multiple encrypted data through a consensus node among the multiple nodes to determine whether the multiple encrypted data are valid;

[0139] Step S504: Acquire additional data corresponding to each of the multiple nodes to obtain multiple additional data;

[0140] Step S505: Integrate the encrypted data verified as valid by consensus in the multiple encrypted data with the corresponding additional data in the multiple additional data to obtain multiple node data.

[0141] In a possible embodiment, initial data of each of the multiple nodes is obtained to obtain multiple initial data, which may include power consumption data, power generation data, equipment status data of the prosumer system, and energy storage status data of the energy storage system. For the prosumer system, each prosumer may correspond to at least one power-consuming device and at least one power-generating device. The power-generating device may be a distributed power-generating device, and power consumption data may be collected in real time through smart meters and sensors corresponding to each power-consuming device. For shared energy storage devices in the energy storage system, energy storage status data is collected through a monitoring system, and the energy storage status data may include charging and discharging power and remaining capacity, etc.

[0142] In a possible embodiment, the key data in the multiple initial data is encrypted by a preset encryption algorithm at the node corresponding to each of the multiple initial data to obtain multiple encrypted data, and then the consensus node in the multiple nodes, that is, the energy scheduling consensus committee, performs consensus verification on each of the multiple encrypted data to determine whether the multiple encrypted data are valid. After the consensus verification, the energy scheduling consensus committee broadcasts to each node of the blockchain system, and each node receives and stores a copy of these data to ensure the reliability of distributed storage. The energy scheduling consensus committee can use the Proof of Authority (PoA) consensus mechanism to verify the data. The consensus node has a high reputation and computing power to ensure the speed and accuracy of data verification. The consensus node verifies the encrypted data to confirm the legitimacy of its source and the integrity of the data. If the data is valid, the data is written into a new block through the consensus mechanism. The verified data will be packaged into a block, attached with a timestamp and other necessary metadata, that is, additional data. The encrypted data that is verified as valid by consensus in the multiple encrypted data is integrated with the corresponding additional data in the multiple additional data to obtain multiple node data, and then the multiple node data is added to the blockchain. Each node of the blockchain updates its own account book to ensure the data consistency of all nodes.

[0143] Optionally, step S502, encrypting each of the multiple initial data to obtain multiple encrypted data, may include the following steps:

[0144] Step S601: determining the usage frequency of each of the multiple initial data to obtain multiple usage frequencies;

[0145] Step S602: determining a data feature of each of the multiple initial data to obtain multiple data features, where the multiple data features are used to reflect the data types of the multiple initial data and the degree of association between the multiple initial data;

[0146] Step S603: determining an importance score of each of the multiple initial data based on the multiple usage frequencies and the multiple data features to obtain multiple importance scores, where the multiple importance scores are used to reflect the encryption requirement degree of the multiple initial data;

[0147] Step S604: determining an encryption method for each of the multiple initial data to obtain multiple encryption methods;

[0148] Step S605: Determine the encryption order of the multiple initial data based on the multiple importance scores;

[0149] Step S606: Encrypt the multiple initial data based on the encryption order and multiple encryption methods to obtain multiple encrypted data.

[0150] In a possible embodiment, due to the openness and transparency of the data on the blockchain, the information of each prosumer user may be accessed by other nodes, resulting in the risk of privacy leakage. Therefore, a privacy protection mechanism is formulated to ensure data security, that is, each of the multiple initial data is encrypted. For the initial data with a higher frequency of use, an encryption method with a shorter decryption time is adopted to improve the data flow efficiency of the blockchain system. For two groups of initial data with a high degree of correlation, they can be encrypted simultaneously or in adjacent order to increase the convenience of data use. For the initial data with an importance score lower than the preset importance score threshold, it can be not encrypted, and the initial data with an importance score higher than or equal to the preset importance score threshold is used as secret information.

[0151] For example, when encrypting the initial data, a finite field is first selected , , let the set of k consensus nodes be , set the threshold value m, the secret information is .choose k different non-zero elements on , and make these elements public. Then, the data provider randomly selects m Polynomial ,in , which is the secret information, and the rest Randomly selected from , respectively calculated , ,Will Distributed to consensus nodes as sub-secrets , and destroy the polynomial to complete the encryption process of the secret information.

[0152] See also Figure 5 , Figure 5 This is a data privacy protection strategy flow chart of a blockchain system provided by an embodiment of the present application. Figure 5 As shown, the secret information of the prosumers in the prosumer system is the new energy power generation forecast, load power forecast and other data that need to be protected. After the secret information is encrypted, it is shared with the energy scheduling consensus committee. According to the sharing aggregation of at least m consensus nodes in the energy scheduling consensus committee, the encrypted data is secretly reconstructed, the secret data is parsed, and then the optimized scheduling plan is generated according to the secret data.

[0153] In the embodiment of the present application, the data processing efficiency of the blockchain system is improved by determining the encryption method and encryption order of each initial data.

[0154] Optionally, step S503, performing consensus verification on each encrypted data in the multiple encrypted data by a consensus node among the multiple nodes to determine whether the multiple encrypted data are valid, may include the following steps:

[0155] Step S701: Obtain the system architecture of the blockchain system;

[0156] Step S702: determining a node type of each of the multiple nodes based on the system architecture to obtain multiple node types, where the multiple node types are used to reflect node functions of the multiple nodes;

[0157] Step S703: determining the reputation score and data processing capability score of each of the multiple nodes, and obtaining multiple reputation scores and multiple data processing capability scores;

[0158] Step S704: determining a consensus node among the multiple nodes based on the multiple node types, the multiple reputation scores, and the multiple data processing capability scores;

[0159] Step S705: determining a decryption method based on the encryption method corresponding to each encrypted data in the plurality of encrypted data, and obtaining a plurality of decryption methods;

[0160] Step S706: decrypting the multiple encrypted data based on multiple decryption methods to obtain multiple decrypted data;

[0161] Step S707: consensus verification is performed on multiple decrypted data through consensus nodes among multiple nodes. If the target decrypted data passes the consensus verification, it is determined that the encrypted data corresponding to the target decrypted data is valid. Otherwise, it is determined that the encrypted data corresponding to the target decrypted data is invalid, and the target decrypted data is any decrypted data among the multiple decrypted data.

[0162] In a possible embodiment, the system architecture of the blockchain system is obtained, the access subject of the blockchain system is determined based on the system architecture, and the node type of each of the multiple nodes in the system architecture is determined according to the access subject, and multiple node types are obtained. The historical transaction scheduling record of each of the multiple nodes is obtained, and the number of transactions and transaction success rate of each node are determined based on the historical transaction scheduling record, and the feedback evaluation of other nodes in the blockchain system is obtained. The reputation score of each of the multiple nodes is determined based on the feedback evaluation, the number of transactions, the transaction success rate and the preset first scoring weight, and multiple reputation scores are obtained. The performance data of each node is obtained, and the performance data includes the node memory capacity and reading speed. The network bandwidth of each node is obtained, and the data processing capacity score is determined based on the performance data, the network bandwidth and the preset second scoring weight, and multiple data processing capacity scores are obtained. According to the needs and application scenarios of the blockchain system, determine the importance of node type, reputation score and data processing capability score in the selection of consensus nodes. For example, for a financial blockchain system with high security requirements, it may be more inclined to select nodes with high reputation scores as consensus nodes, even if their data processing capabilities are relatively weak. For an IoT blockchain system with extremely high transaction processing speed requirements, it may pay more attention to the data processing capabilities of the nodes, but also require the reputation to meet certain standards. Determine the weight ratio of node type, reputation score and data processing capability score according to the degree of importance, and then obtain the consensus node score. The nodes with higher than the preset node score in the consensus node score are used as consensus nodes.

[0163] In a possible embodiment, for each encrypted data, its related metadata or tag is obtained to determine the encryption algorithm it adopts, and a decryption method is determined based on the encryption method corresponding to each encrypted data in the multiple encrypted data to obtain multiple decryption methods, and then the multiple encrypted data are decrypted based on the multiple decryption methods to obtain multiple decrypted data, which can be decrypted based on the simultaneous collaboration of at least m consensus nodes in the energy scheduling consensus committee, and the secret parts held by each of them are collected.

[0164] For example, the secret values ​​corresponding to any m consensus nodes are obtained and reconstructed by Lagrange interpolation method. , the reconstruction process can be expressed by formula (13), let x = 0, then we can get the secret .

[0165] …………(13)

[0166] See also Fig.11 , Fig.11 Schematic diagram showing the effect of a data privacy protection strategy provided by an embodiment of the present application. Fig.11As shown, the figure shows the encryption and decryption effect. Taking the load forecast power of prosumer 1 as an example, the load forecast power of 24 points a day ago is encrypted and sent to 5 members of the energy scheduling consensus committee. The load power curves received by the 5 members are shown in the curves s1 to s5 in the figure. It can be seen that the encrypted power data received by the committee members is irregular and has a large difference from the actual power value. In the decryption stage, the secret part held by any 3 member sets is decrypted. The curve in the figure shows that the correct actual power value can be obtained through the decryption algorithm. The encryption and decryption of the embodiment of the present application is feasible and superior.

[0167] In the embodiment of the present application, by having multiple consensus nodes participate in the decryption process, the transparency of data processing is enhanced, and through the mutual supervision mechanism, it is effectively prevented that a single node may formulate a false scheduling plan, thereby ensuring the correctness and fairness of the scheduling results.

[0168] To summarize, in the embodiment of the present application, an optimization scheduling contract is first constructed, and an energy storage control contract and a power purchase and sale contract generation contract are constructed, wherein the optimization scheduling contract is used to schedule power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the energy storage system to charge and discharge, and the prosumer system includes multiple prosumers, each prosumer corresponds to a power generation device and a power consumption device, then, data of each of the multiple nodes is obtained to obtain multiple node data, and when the multiple node data meet the first trigger condition corresponding to the optimization scheduling contract, target data of each of the multiple prosumers in the historical time period is obtained to obtain multiple target data, wherein the target data includes power generation data of the power generation device and power consumption data of the power consumption device, and then, based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, the reference power generation and reference power consumption of each of the multiple prosumers in the future time period are predicted to obtain multiple reference power generation and reference power consumption, The method comprises the following steps: obtaining electricity price data of the distribution network in a future time period, wherein the electricity price data includes electricity purchase price data and electricity sales price data, and then determining an optimized scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimized scheduling contract, the multiple reference power generation amounts, the multiple reference electricity consumption amounts and the electricity price data, wherein the optimized scheduling plan includes a first electricity purchase and sales plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second electricity purchase and sales plan between the energy storage system and the distribution network; when the multiple node data meet the second trigger condition corresponding to the energy storage control contract, the energy storage system is controlled to charge and discharge based on the charge and discharge operation plan; when the multiple node data meet the third trigger condition corresponding to the power purchase and sales contract generation contract, an electricity trading contract is generated based on the first power purchase and sales plan and the second power purchase and sales plan; and trading scheduling between the prosumer system, the energy storage system and the distribution network is controlled based on the power trading contract. Therefore, by constructing an optimized scheduling contract and predicting reference power generation and reference power consumption, and determining the optimized scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimized scheduling contract, and controlling the charging and discharging of the energy storage system and the transaction scheduling between the prosumer system, the energy storage system and the distribution network according to the optimized scheduling plan, when performing energy scheduling on the load side, it is possible to optimize the allocation and use of power resources, reduce the dependence of prosumers on regional distribution networks, and reduce the energy costs of prosumers when using electric energy.

[0169] The method of the embodiment of the present invention is described in detail above, and the device of the embodiment of the present invention is provided below.

[0170] See also Fig.12 , Fig.12800 is a structural diagram of a load-side transaction scheduling device based on a smart contract provided in an embodiment of the present application. The load-side transaction scheduling device based on a smart contract 800 is applied to a blockchain system, the blockchain system includes multiple nodes, and the load-side transaction scheduling device based on a smart contract 800 includes a construction unit 801, an acquisition unit 802, and a processing unit 803;

[0171] The construction unit 801 is used to construct an optimization scheduling contract, and to construct an energy storage control contract and a power purchase and sale contract generation contract; the optimization scheduling contract is used to schedule power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the energy storage system to charge and discharge. The prosumer system includes multiple prosumers, and each prosumer corresponds to a power generation device and an electric power device;

[0172] An acquisition unit 802 is used to acquire data of each of the multiple nodes to obtain multiple node data;

[0173] The processing unit 803 is configured to obtain target data of each of the multiple prosumers in the historical time period when the multiple node data meet the first trigger condition corresponding to the optimization scheduling contract, and obtain multiple target data, wherein the target data includes power generation data of the power generation equipment and power consumption data of the power consumption equipment;

[0174] Based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period are predicted to obtain multiple reference power generation and multiple reference power consumption;

[0175] Obtain the electricity price data of the distribution network in the future time period, which includes the electricity purchase price data and the electricity sales price data;

[0176] Determine an optimal dispatch plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal dispatch contract, multiple reference power generation, multiple reference power consumption and electricity price data, wherein the optimal dispatch plan includes a first power purchase and sale plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sale plan between the energy storage system and the distribution network;

[0177] When the data of multiple nodes meet the second trigger condition corresponding to the energy storage control contract, the energy storage system is controlled to charge and discharge based on the charge and discharge operation plan;

[0178] When the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, a power transaction contract is generated based on the first power purchase and sale plan and the second power purchase and sale plan;

[0179] The transaction scheduling between the producer and consumer system, energy storage system and distribution network is controlled based on the electricity trading contract.

[0180] In some possible embodiments, in terms of constructing an optimized scheduling contract, the construction unit 801 is specifically used to:

[0181] Obtaining a first cost relationship between a first cost of transaction scheduling between the prosumer system and the distribution network, a first cost price of electricity purchased and sold by the distribution network, the power purchased by the prosumer system from the distribution network, and the power sold by the prosumer system to the distribution network;

[0182] Determine a first cost formula for transaction scheduling between the prosumer system and the distribution network based on the first cost relationship;

[0183] Obtaining a second cost relationship between the second cost of transaction scheduling between the energy storage system and the distribution network and the purchase and sale price of electricity of the distribution network, the power purchased by the energy storage system from the distribution network, and the power sold by the energy storage system to the distribution network;

[0184] Determine a second cost formula for transaction scheduling between the energy storage system and the distribution network based on the second cost relationship;

[0185] Obtaining the third cost relationship between the energy storage system's charging and discharging costs and the power the energy storage system purchases from the distribution network, the power it sells to the distribution network, the charging power obtained from the prosumer system, the discharging power output to the prosumer system, and the energy storage system's charging and discharging costs;

[0186] Determine a third cost formula for charging and discharging the energy storage system based on the third cost relationship;

[0187] determining a total operating cost based on the first cost formula, the second cost formula, and the third cost formula;

[0188] Determine the objective function for total operating cost;

[0189] Construct the first equilibrium constraint of the prosumer system;

[0190] Construct the second balance constraint of the energy storage system;

[0191] An optimization scheduling contract is constructed based on the objective function, the first balance constraint and the second balance constraint.

[0192] In some possible embodiments, in terms of predicting a reference power generation and a reference power consumption of each of a plurality of prosumers in a future time period based on the power generation data of each power generation device and the power consumption data of each power consumption device in a plurality of target data, and obtaining a plurality of reference power generation and a plurality of reference power consumption, the processing unit 803 is specifically configured to:

[0193] Acquire multiple power generation devices and multiple power consumption devices corresponding to multiple prosumers;

[0194] Acquire a device state of each power generation device among a plurality of power generation devices to obtain a plurality of device states;

[0195] Determining a plurality of first adjustment amounts based on a plurality of power generation equipment status data;

[0196] Determine a power generation characteristic of each power generation device among a plurality of power generation devices to obtain a plurality of power generation characteristics, the power generation characteristics including photovoltaic power generation and wind power generation;

[0197] Determine influencing factors related to weather trends based on multiple power generation characteristics to obtain multiple influencing factors, where the influencing factors include at least one of the following: light intensity, precipitation, temperature, and wind speed;

[0198] Get weather data for a future time period;

[0199] determining a plurality of second adjustment amounts based on weather data and a plurality of influencing factors;

[0200] Determine a plurality of reference power generation amounts based on a plurality of first adjustment amounts, a plurality of second adjustment amounts, and power generation amount data of each power generation device in a plurality of target data;

[0201] Get the time characteristics of the future time period;

[0202] Determine an adjustment factor corresponding to the time trend for each of the plurality of electrical devices to obtain a plurality of adjustment factors;

[0203] Determine a plurality of third adjustment amounts based on the time characteristic and a plurality of adjustment factors;

[0204] A plurality of reference power consumptions are determined based on the plurality of third adjustment amounts and the power consumption data of each power-consuming device in the plurality of target data.

[0205] In some possible embodiments, in determining an optimal scheduling plan between a prosumer system, an energy storage system, and a distribution network in a future time period based on an optimal scheduling contract, multiple reference power generation, multiple reference power consumption, and electricity price data, the processing unit 803 is specifically configured to:

[0206] Determine the electricity sales demand and electricity consumption demand of each of the multiple prosumers in each period of the future time period based on the multiple reference power generation and the multiple reference power consumption, and obtain multiple electricity sales demands and multiple electricity consumption demands;

[0207] Based on the optimized scheduling contract, multiple electricity sales demands and multiple electricity consumption demands, determine the first electricity sales power sold to the distribution network, the first electricity purchase power purchased from the distribution network, the charging power output to the energy storage system and the discharging power obtained from the energy storage system by each of the multiple prosumers in each period in the future time period, and obtain multiple first electricity sales power sets, multiple first electricity purchase power sets, multiple charging power sets and multiple discharging power sets;

[0208] Obtain energy storage status data of the energy storage system;

[0209] Based on the optimized dispatch contract and the energy storage status data, determine the second sold power sold by the energy storage system and the distribution network to the distribution network and the second purchased power purchased from the distribution network in each period in the future time period, and obtain multiple second sold power sets and multiple second purchased power sets;

[0210] Determining a first electricity purchase and sale plan based on a plurality of first electricity sales power sets and a plurality of first electricity purchase power sets;

[0211] determining a charge and discharge operation plan based on a plurality of charging power sets and a plurality of discharging power sets;

[0212] determining a second electricity purchase and sale plan based on the plurality of second electricity sales power sets and the plurality of second electricity purchase power sets;

[0213] The first power purchase and sales plan, the charging and discharging operation plan and the second power purchase and sales plan are integrated to obtain an optimized dispatching plan.

[0214] In some possible embodiments, in terms of obtaining data of each of the multiple nodes, the obtaining unit 802 is specifically configured to:

[0215] Acquire initial data of each of the multiple nodes to obtain multiple initial data;

[0216] Encrypting each of the multiple initial data to obtain multiple encrypted data;

[0217] Performing consensus verification on each encrypted data in the multiple encrypted data through a consensus node among the multiple nodes to determine whether the multiple encrypted data are valid;

[0218] Obtain additional data corresponding to each of the multiple nodes to obtain multiple additional data;

[0219] The encrypted data verified as valid by consensus in the multiple encrypted data are integrated with the corresponding additional data in the multiple additional data to obtain multiple node data.

[0220] In some possible embodiments, in encrypting each of the multiple initial data to obtain the multiple encrypted data, the acquiring unit 802 is specifically configured to:

[0221] Determine the usage frequency of each of the plurality of initial data to obtain a plurality of usage frequencies;

[0222] Determine a data feature of each of the plurality of initial data to obtain a plurality of data features, wherein the plurality of data features are used to reflect the data types of the plurality of initial data and the degree of association between the plurality of initial data;

[0223] Determine an importance score of each of the multiple initial data based on multiple usage frequencies and multiple data features to obtain multiple importance scores, where the multiple importance scores are used to reflect the encryption requirement degree of the multiple initial data;

[0224] Determine an encryption method for each of the plurality of initial data to obtain a plurality of encryption methods;

[0225] Determining an encryption order of the plurality of initial data based on the plurality of importance scores;

[0226] A plurality of initial data are encrypted based on an encryption order and a plurality of encryption methods to obtain a plurality of encrypted data.

[0227] In some possible embodiments, in terms of performing consensus verification on each encrypted data in the multiple encrypted data by a consensus node in the multiple nodes to determine whether the multiple encrypted data are valid, the acquisition unit 802 is specifically used to:

[0228] Obtain the system architecture of the blockchain system;

[0229] Determine a node type of each of the multiple nodes based on the system architecture to obtain multiple node types, where the multiple node types are used to reflect node functions of the multiple nodes;

[0230] Determining a reputation score and a data processing capability score of each of the multiple nodes to obtain multiple reputation scores and multiple data processing capability scores;

[0231] Determining a consensus node among the plurality of nodes based on a plurality of node types, a plurality of reputation scores, and a plurality of data processing capability scores;

[0232] Determine a decryption method based on an encryption method corresponding to each encrypted data in the plurality of encrypted data, and obtain a plurality of decryption methods;

[0233] Decrypting the multiple encrypted data based on multiple decryption methods to obtain multiple decrypted data;

[0234] Consensus verification is performed on multiple decrypted data through consensus nodes among multiple nodes. If the target decrypted data passes the consensus verification, it is determined that the encrypted data corresponding to the target decrypted data is valid. Otherwise, it is determined that the encrypted data corresponding to the target decrypted data is invalid, and the target decrypted data is any decrypted data among the multiple decrypted data.

[0235] See also Fig.13 , Fig.13 Schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig.13 As shown, the electronic device 900 includes a transceiver 901, a processor 902 and a memory 903, which are connected via a bus 904. The memory 903 is used to store computer programs and data, and can transmit the data stored in the memory 903 to the processor 902. The electronic device can be the information age analysis device in the power line communication scenario described above, and the processor 902 can be the construction unit 801, the acquisition unit 802 and the processing unit 803 described above.

[0236] The processor 902 is used to read the computer program in the memory 903 and perform the following operations:

[0237] Construct an optimization dispatch contract, an energy storage control contract, and a power purchase and sales contract generation contract; the optimization dispatch contract is used to dispatch power resources between the prosumer system, the energy storage system, and the distribution network, and the energy storage control contract is used to control the charging and discharging of the energy storage system. The prosumer system includes multiple prosumers, each of which corresponds to a power generation device and an electricity consumption device;

[0238] Obtain data of each node among multiple nodes to obtain multiple node data;

[0239] When the data of multiple nodes meet the first trigger condition corresponding to the optimization scheduling contract, the target data of each of the multiple prosumers in the historical time period is obtained to obtain multiple target data, where the target data includes the power generation data of the power generation equipment and the power consumption data of the power consumption equipment;

[0240] Based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period are predicted to obtain multiple reference power generation and multiple reference power consumption;

[0241] Obtain the electricity price data of the distribution network in the future time period, which includes the electricity purchase price data and the electricity sales price data;

[0242] Determine an optimal dispatch plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal dispatch contract, multiple reference power generation, multiple reference power consumption and electricity price data, wherein the optimal dispatch plan includes a first power purchase and sale plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sale plan between the energy storage system and the distribution network;

[0243] When the data of multiple nodes meet the second trigger condition corresponding to the energy storage control contract, the energy storage system is controlled to charge and discharge based on the charge and discharge operation plan;

[0244] When the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, a power transaction contract is generated based on the first power purchase and sale plan and the second power purchase and sale plan;

[0245] The transaction scheduling between the producer and consumer system, energy storage system and distribution network is controlled based on the electricity trading contract.

[0246] In some possible embodiments, in terms of constructing an optimized scheduling contract, the processor 902 is specifically configured to perform the following operations:

[0247] Obtaining a first cost relationship between a first cost of transaction scheduling between the prosumer system and the distribution network, a first cost price of electricity purchased and sold by the distribution network, the power purchased by the prosumer system from the distribution network, and the power sold by the prosumer system to the distribution network;

[0248] Determine a first cost formula for transaction scheduling between the prosumer system and the distribution network based on the first cost relationship;

[0249] Obtaining a second cost relationship between the second cost of transaction scheduling between the energy storage system and the distribution network and the purchase and sale price of electricity of the distribution network, the power purchased by the energy storage system from the distribution network, and the power sold by the energy storage system to the distribution network;

[0250] Determine a second cost formula for transaction scheduling between the energy storage system and the distribution network based on the second cost relationship;

[0251] Obtaining the third cost relationship between the energy storage system's charging and discharging costs and the power the energy storage system purchases from the distribution network, the power it sells to the distribution network, the charging power obtained from the prosumer system, the discharging power output to the prosumer system, and the energy storage system's charging and discharging costs;

[0252] Determine a third cost formula for charging and discharging the energy storage system based on the third cost relationship;

[0253] determining a total operating cost based on the first cost formula, the second cost formula, and the third cost formula;

[0254] Determine the objective function for total operating cost;

[0255] Construct the first equilibrium constraint of the prosumer system;

[0256] Construct the second balance constraint of the energy storage system;

[0257] An optimization scheduling contract is constructed based on the objective function, the first balance constraint and the second balance constraint.

[0258] In some possible embodiments, in terms of predicting a reference power generation and a reference power consumption of each of a plurality of prosumers in a future time period based on the power generation data of each power generation device and the power consumption data of each power consumption device in a plurality of target data, and obtaining a plurality of reference power generation and a plurality of reference power consumption, the processor 902 is specifically configured to perform the following operations:

[0259] Acquire multiple power generation devices and multiple power consumption devices corresponding to multiple prosumers;

[0260] Acquire a device state of each power generation device among a plurality of power generation devices to obtain a plurality of device states;

[0261] Determining a plurality of first adjustment amounts based on a plurality of power generation equipment status data;

[0262] Determine a power generation characteristic of each power generation device among a plurality of power generation devices to obtain a plurality of power generation characteristics, the power generation characteristics including photovoltaic power generation and wind power generation;

[0263] Determine influencing factors related to weather trends based on multiple power generation characteristics to obtain multiple influencing factors, where the influencing factors include at least one of the following: light intensity, precipitation, temperature, and wind speed;

[0264] Get weather data for a future time period;

[0265] determining a plurality of second adjustment amounts based on weather data and a plurality of influencing factors;

[0266] Determine a plurality of reference power generation amounts based on a plurality of first adjustment amounts, a plurality of second adjustment amounts, and power generation amount data of each power generation device in a plurality of target data;

[0267] Get the time characteristics of the future time period;

[0268] Determine an adjustment factor corresponding to the time trend for each of the plurality of electrical devices to obtain a plurality of adjustment factors;

[0269] Determine a plurality of third adjustment amounts based on the time characteristic and a plurality of adjustment factors;

[0270] A plurality of reference power consumptions are determined based on the plurality of third adjustment amounts and the power consumption data of each power-consuming device in the plurality of target data.

[0271] In some possible embodiments, in determining an optimal scheduling plan between a prosumer system, an energy storage system, and a distribution network in a future time period based on an optimal scheduling contract, multiple reference power generation amounts, multiple reference power consumption amounts, and electricity price data, the processor 902 is specifically configured to perform the following operations:

[0272] Determine the electricity sales demand and electricity consumption demand of each of the multiple prosumers in each period of the future time period based on the multiple reference power generation and the multiple reference power consumption, and obtain multiple electricity sales demands and multiple electricity consumption demands;

[0273] Based on the optimized scheduling contract, multiple electricity sales demands and multiple electricity consumption demands, determine the first electricity sales power sold to the distribution network, the first electricity purchase power purchased from the distribution network, the charging power output to the energy storage system and the discharging power obtained from the energy storage system by each of the multiple prosumers in each period in the future time period, and obtain multiple first electricity sales power sets, multiple first electricity purchase power sets, multiple charging power sets and multiple discharging power sets;

[0274] Obtain energy storage status data of the energy storage system;

[0275] Based on the optimized dispatch contract and the energy storage status data, determine the second sold power sold by the energy storage system and the distribution network to the distribution network and the second purchased power purchased from the distribution network in each period in the future time period, and obtain multiple second sold power sets and multiple second purchased power sets;

[0276] Determining a first electricity purchase and sale plan based on a plurality of first electricity sales power sets and a plurality of first electricity purchase power sets;

[0277] determining a charge and discharge operation plan based on a plurality of charging power sets and a plurality of discharging power sets;

[0278] determining a second electricity purchase and sale plan based on the plurality of second electricity sale power sets and the plurality of second electricity purchase power sets;

[0279] The first power purchase and sales plan, the charging and discharging operation plan and the second power purchase and sales plan are integrated to obtain an optimized dispatching plan.

[0280] In some possible embodiments, in terms of obtaining data of each of the multiple nodes, the processor 902 is specifically configured to perform the following operations:

[0281] Acquire initial data of each of the multiple nodes to obtain multiple initial data;

[0282] Encrypting each of the multiple initial data to obtain multiple encrypted data;

[0283] Performing consensus verification on each encrypted data in the multiple encrypted data through a consensus node among the multiple nodes to determine whether the multiple encrypted data are valid;

[0284] Obtain additional data corresponding to each of the multiple nodes to obtain multiple additional data;

[0285] The encrypted data verified as valid by consensus in the multiple encrypted data are integrated with the corresponding additional data in the multiple additional data to obtain multiple node data.

[0286] In some possible embodiments, in terms of encrypting each of the multiple initial data to obtain the multiple encrypted data, the processor 902 is specifically configured to perform the following operations:

[0287] Determine the usage frequency of each of the plurality of initial data to obtain a plurality of usage frequencies;

[0288] Determine a data feature of each of the plurality of initial data to obtain a plurality of data features, wherein the plurality of data features are used to reflect the data types of the plurality of initial data and the degree of association between the plurality of initial data;

[0289] Determine an importance score of each of the multiple initial data based on multiple usage frequencies and multiple data features to obtain multiple importance scores, where the multiple importance scores are used to reflect the encryption requirement degree of the multiple initial data;

[0290] Determine an encryption method for each of the plurality of initial data to obtain a plurality of encryption methods;

[0291] Determining an encryption order of the plurality of initial data based on the plurality of importance scores;

[0292] A plurality of initial data are encrypted based on an encryption order and a plurality of encryption methods to obtain a plurality of encrypted data.

[0293] In some possible embodiments, in terms of performing consensus verification on each encrypted data in the multiple encrypted data through a consensus node in the multiple nodes to determine whether the multiple encrypted data are valid, the processor 902 is specifically configured to perform the following operations:

[0294] Obtain the system architecture of the blockchain system;

[0295] Determine a node type of each of the multiple nodes based on the system architecture to obtain multiple node types, where the multiple node types are used to reflect node functions of the multiple nodes;

[0296] Determining a reputation score and a data processing capability score of each of the multiple nodes to obtain multiple reputation scores and multiple data processing capability scores;

[0297] Determining a consensus node among the plurality of nodes based on a plurality of node types, a plurality of reputation scores, and a plurality of data processing capability scores;

[0298] Determine a decryption method based on an encryption method corresponding to each encrypted data in the plurality of encrypted data, and obtain a plurality of decryption methods;

[0299] Decrypting the multiple encrypted data based on multiple decryption methods to obtain multiple decrypted data;

[0300] Consensus verification is performed on multiple decrypted data through consensus nodes among multiple nodes. If the target decrypted data passes the consensus verification, it is determined that the encrypted data corresponding to the target decrypted data is valid. Otherwise, it is determined that the encrypted data corresponding to the target decrypted data is invalid, and the target decrypted data is any decrypted data among the multiple decrypted data.

[0301] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement part or all of the steps of any method for implementing load-side transaction scheduling based on smart contracts as recorded in the above method embodiments.

[0302] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps of any one of the load-side transaction scheduling methods based on smart contracts as recorded in the above method embodiments.

[0303] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0304] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0305] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the modules, which is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or module can be electrical or other forms.

[0306] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0307] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or software program modules.

[0308] If the integrated module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0309] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A load-side transaction scheduling method based on smart contracts, characterized in that: Applied to a blockchain system, the blockchain system includes multiple nodes, and the method includes: Construct an optimization scheduling contract, and construct an energy storage control contract and a power purchase and sale contract generation contract; the optimization scheduling contract is used to schedule power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the charging and discharging of the energy storage system. The prosumer system includes multiple prosumers, and each prosumer corresponds to a power generation device and an electrical device; wherein, the construction of the optimization scheduling contract specifically includes: obtaining a first cost relationship between the first cost of transaction scheduling between the prosumer system and the distribution network and the power purchase and sale price of the distribution network, the power purchased by the prosumer system from the distribution network, and the power sold by the prosumer system to the distribution network; determining a first cost formula for transaction scheduling between the prosumer system and the distribution network based on the first cost relationship; obtaining a second cost of transaction scheduling between the energy storage system and the distribution network and the power purchase and sale price of the distribution network, the power purchased by the energy storage system from the distribution network power, and the second cost relationship between the power sold by the energy storage system to the distribution network; based on the second cost relationship, determine the second cost formula for transaction scheduling between the energy storage system and the distribution network; obtain the third cost of charging and discharging the energy storage system and the third cost relationship between the power purchased by the energy storage system from the distribution network, the power sold to the distribution network, the charging power obtained from the prosumer system, the discharging power output to the prosumer system and the charging and discharging cost of the energy storage system; determine the third cost formula for charging and discharging the energy storage system based on the third cost relationship; determine the total operating cost based on the first cost formula, the second cost formula and the third cost formula; determine the objective function of the total operating cost; construct the first balance constraint condition of the prosumer system; construct the second balance constraint condition of the energy storage system; construct the optimized scheduling contract based on the objective function, the first balance constraint condition and the second balance constraint condition; Acquire data of each of the multiple nodes to obtain multiple node data; When the plurality of node data satisfy the first trigger condition corresponding to the optimization scheduling contract, the target data of each of the plurality of prosumers in the historical time period is obtained to obtain a plurality of target data, wherein the target data includes the power generation data of the power generation equipment and the power consumption data of the power consumption equipment; Based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period are predicted to obtain multiple reference power generation and multiple reference power consumption; Obtaining electricity price data of the distribution network in the future time period, the electricity price data including electricity purchase price data and electricity sales price data; Determine an optimal scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal scheduling contract, the multiple reference power generation, the multiple reference power consumption and the electricity price data, wherein the optimal scheduling plan includes a first power purchase and sale plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sale plan between the energy storage system and the distribution network; When the plurality of node data satisfy the second trigger condition corresponding to the energy storage control contract, controlling the energy storage system to charge and discharge based on the charge and discharge operation plan; When the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, generating a power transaction contract based on the first power purchase and sale plan and the second power purchase and sale plan; Based on the power trading contract, trading scheduling is controlled among the prosumer system, the energy storage system and the distribution network.

2. The method according to claim 1, characterized in that The method of predicting a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data to obtain multiple reference power generation and multiple reference power consumption includes: Acquire a plurality of power generation devices and a plurality of power consumption devices corresponding to the plurality of prosumers; Acquire a device state of each of the plurality of power generation devices to obtain a plurality of device states; Determine a plurality of first adjustment amounts based on the plurality of power generation equipment status data; Determine a power generation characteristic of each power generation device among the plurality of power generation devices to obtain a plurality of power generation characteristics, wherein the power generation characteristics include photovoltaic power generation and wind power generation; Determine influencing factors related to weather trends based on the multiple power generation characteristics to obtain multiple influencing factors, wherein the influencing factors include at least one of the following: light intensity, precipitation, temperature, and wind speed; Obtaining weather data for the future time period; determining a plurality of second adjustment amounts based on the weather data and the plurality of influencing factors; Determine the plurality of reference power generation amounts based on the plurality of first adjustment amounts, the plurality of second adjustment amounts, and the power generation amount data of each power generation device in the plurality of target data; Obtaining time characteristics of the future time period; Determine an adjustment factor corresponding to the time trend for each of the plurality of electrical devices to obtain a plurality of adjustment factors; determining a plurality of third adjustment amounts based on the time characteristic and the plurality of adjustment factors; The plurality of reference power consumptions are determined based on the plurality of third adjustment amounts and the power consumption data of each power-consuming device in the plurality of target data.

3. The method according to claim 2, characterized in that The step of determining the optimal dispatching plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal dispatching contract, the multiple reference power generation amounts, the multiple reference power consumption amounts and the electricity price data includes: Determine the electricity sales demand and electricity consumption demand of each of the multiple prosumers in each period of the future time period based on the multiple reference power generation amounts and the multiple reference power consumption amounts, and obtain multiple electricity sales demands and multiple electricity consumption demands; Based on the optimized scheduling contract, the multiple electricity sales demands and the multiple electricity consumption demands, determine the first electricity sales power sold to the distribution network, the first electricity purchase power purchased from the distribution network, the charging power output to the energy storage system and the discharging power obtained from the energy storage system by each of the multiple prosumers in each period of the future time period, and obtain multiple first electricity sales power sets, multiple first electricity purchase power sets, multiple charging power sets and multiple discharging power sets; Acquiring energy storage status data of the energy storage system; Based on the optimized scheduling contract and the energy storage status data, determine the second sold power sold by the energy storage system and the distribution network to the distribution network and the second purchased power purchased from the distribution network in each period of the future time period, and obtain multiple second sold power sets and multiple second purchased power sets; Determining the first electricity purchase and sale plan based on the multiple first electricity sales power sets and the multiple first electricity purchase power sets; determining the charge and discharge operation plan based on the multiple charging power sets and the multiple discharging power sets; Determining the second power purchase and sale plan based on the plurality of second power sales power sets and the plurality of second power purchase power sets; The first power purchase and sale plan, the charging and discharging operation plan and the second power purchase and sale plan are integrated to obtain the optimized scheduling plan.

4. The method according to any one of claims 1 to 3, characterized in that: The acquiring data of each of the multiple nodes to obtain multiple node data includes: Acquire initial data of each of the multiple nodes to obtain multiple initial data; Encrypting each of the multiple initial data to obtain multiple encrypted data; Performing consensus verification on each of the plurality of encrypted data by a consensus node among the plurality of nodes to determine whether the plurality of encrypted data is valid; Acquire additional data corresponding to each of the multiple nodes to obtain multiple additional data; The encrypted data verified as valid by consensus in the multiple encrypted data are integrated with the corresponding additional data in the multiple additional data to obtain the multiple node data.

5. The method according to claim 4, characterized in that The step of encrypting each of the plurality of initial data to obtain a plurality of encrypted data includes: Determine the usage frequency of each of the plurality of initial data to obtain a plurality of usage frequencies; Determine a data feature of each of the plurality of initial data to obtain a plurality of data features, wherein the plurality of data features are used to reflect the data types of the plurality of initial data and the degree of association between the plurality of initial data; Determine an importance score of each of the plurality of initial data based on the plurality of usage frequencies and the plurality of data features to obtain a plurality of importance scores, wherein the plurality of importance scores are used to reflect the degree of encryption requirement of the plurality of initial data; Determine an encryption method for each of the plurality of initial data to obtain a plurality of encryption methods; determining an encryption order of the plurality of initial data based on the plurality of importance scores; The plurality of initial data are encrypted based on the encryption order and the plurality of encryption methods to obtain the plurality of encrypted data.

6. The method according to claim 4, characterized in that The step of performing consensus verification on each of the plurality of encrypted data by a consensus node among the plurality of nodes to determine whether the plurality of encrypted data are valid includes: Obtaining the system architecture of the blockchain system; Determine a node type of each of the multiple nodes based on the system architecture to obtain multiple node types, where the multiple node types are used to reflect node functions of the multiple nodes; Determining a reputation score and a data processing capability score of each of the plurality of nodes to obtain a plurality of reputation scores and a plurality of data processing capability scores; determining a consensus node among the plurality of nodes based on the plurality of node types, the plurality of reputation scores, and the plurality of data processing capability scores; Determine a decryption method based on the encryption method corresponding to each encrypted data in the plurality of encrypted data to obtain a plurality of decryption methods; Decrypting the plurality of encrypted data based on the plurality of decryption methods to obtain a plurality of decrypted data; The multiple decrypted data are consensus-verified by consensus nodes among the multiple nodes. If the target decrypted data passes the consensus verification, it is determined that the encrypted data corresponding to the target decrypted data is valid; otherwise, it is determined that the encrypted data corresponding to the target decrypted data is invalid, and the target decrypted data is any decrypted data among the multiple decrypted data.

7. A load-side transaction scheduling device based on smart contracts, characterized in that: Applied to a blockchain system, the blockchain system includes a plurality of nodes, and the device includes a construction unit, an acquisition unit, and a processing unit; The construction unit is used to construct an optimization scheduling contract, and to construct an energy storage control contract and a power purchase and sale contract generation contract; the optimization scheduling contract is used to schedule power resources between the prosumer system, the energy storage system and the distribution network, and the energy storage control contract is used to control the charging and discharging of the energy storage system. The prosumer system includes multiple prosumers, and each prosumer corresponds to a power generation device and an electrical device; wherein, the construction of the optimization scheduling contract specifically includes: obtaining a first cost relationship between a first cost of transaction scheduling between the prosumer system and the distribution network and the power purchase and sale price of the distribution network, the power purchased by the prosumer system from the distribution network, and the power sold by the prosumer system to the distribution network; determining a first cost formula for transaction scheduling between the prosumer system and the distribution network based on the first cost relationship; obtaining a second cost of transaction scheduling between the energy storage system and the distribution network and the power purchase and sale price of the distribution network, the power purchased by the energy storage system from the distribution network, and the power sold by the energy storage system to the distribution network A second cost relationship between the power of electricity purchased from the network and the power of electricity sold by the energy storage system to the distribution network; based on the second cost relationship, a second cost formula for transaction scheduling between the energy storage system and the distribution network is determined; obtaining a third cost relationship between the third cost of charging and discharging the energy storage system and the power of electricity purchased from the distribution network, the power sold to the distribution network, the charging power obtained from the prosumer system, the discharging power output to the prosumer system and the charging and discharging cost of the energy storage system; determining a third cost formula for charging and discharging the energy storage system based on the third cost relationship; determining the total operating cost based on the first cost formula, the second cost formula and the third cost formula; determining the objective function of the total operating cost; constructing a first balance constraint condition for the prosumer system; constructing a second balance constraint condition for the energy storage system; constructing the optimization scheduling contract based on the objective function, the first balance constraint condition and the second balance constraint condition; The acquisition unit is used to acquire data of each of the multiple nodes to obtain multiple node data; The processing unit is configured to obtain target data of each of the multiple prosumers in a historical time period when the multiple node data meet the first trigger condition corresponding to the optimization scheduling contract, and obtain multiple target data, wherein the target data includes power generation data of the power generation equipment and power consumption data of the power consumption equipment; Predicting a reference power generation and a reference power consumption of each of the multiple prosumers in a future time period based on the power generation data of each power generation device and the power consumption data of each power consumption device in the multiple target data, to obtain multiple reference power generation and multiple reference power consumption; the start time of the future time period is later than the end time of the historical time period; Obtaining electricity price data of the distribution network in the future time period, the electricity price data including electricity purchase price data and electricity sales price data; Determine an optimal scheduling plan between the prosumer system, the energy storage system and the distribution network in the future time period based on the optimal scheduling contract, the multiple reference power generation, the multiple reference power consumption and the electricity price data, wherein the optimal scheduling plan includes a first power purchase and sale plan between each of the multiple prosumers and the distribution network, a charge and discharge operation plan between the multiple prosumers and the energy storage system, and a second power purchase and sale plan between the energy storage system and the distribution network; When the plurality of node data satisfy the second trigger condition corresponding to the energy storage control contract, controlling the energy storage system to charge and discharge based on the charge and discharge operation plan; When the plurality of node data satisfy the third trigger condition corresponding to the power purchase and sale contract generation contract, generating a power transaction contract based on the first power purchase and sale plan and the second power purchase and sale plan; Based on the power trading contract, trading scheduling is controlled among the prosumer system, the energy storage system and the distribution network.

8. An electronic device, characterized in that: include: A processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 6.

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