Multi-energy scheduling method and system for coupling energy storage

Abstract

The invention provides a coupling energy storage multi-energy scheduling method and system, and relates to the technical field of multi-energy scheduling, and the coupling energy storage multi-energy scheduling method comprises the steps: obtaining historical energy data and energy association data; determining electricity price characteristic data according to the historical energy data and the energy association data; determining a target energy scheduling strategy from a strategy set based on the electricity price characteristic data, wherein the strategy set comprises first energy scheduling strategies corresponding to different triggering conditions and second energy scheduling strategies in different time periods; and performing energy scheduling according to the target energy scheduling strategy. The technical problems of unstable energy supply and low energy utilization rate in the prior art are solved.

Description

Technical Field

[0001] The present application relates to the technical field of multi-energy scheduling, and in particular to a multi-energy scheduling method and system coupled with energy storage. Background Art

[0002] With the continuous growth of energy demand, the traditional single thermal power energy supply mode can no longer meet the needs of modern society; wind energy and solar energy, as renewable energy, have the advantages of being clean and sustainable, but their power generation has the significant disadvantages of intermittent and unstable, and the problems of wind and solar abandonment are prominent. The wind abandonment rate of typical wind farms in the northwest region is more than 15%; although thermal power has high stability, it faces the problems of resource consumption and environmental pollution, and when thermal power units are deeply peaked, their heating capacity is greatly reduced. Therefore, the single thermal power energy supply will inevitably have problems such as unstable energy supply, low energy utilization and environmental pollution. There is an urgent need for a multi-energy, low-carbon and efficient scheduling method that adapts to the new power system. Summary of the Invention

[0003] The present application aims to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first purpose of this application is to propose a multi-energy scheduling method coupled with energy storage to achieve efficient and stable energy supply and reduce the impact on fossil energy consumption and environmental pollution.

[0005] The second objective of this application is to propose a multi-energy scheduling system coupled with energy storage.

[0006] The third objective of this application is to provide an electronic device.

[0007] The fourth object of this application is to provide a computer-readable storage medium.

[0008] A fifth object of this application is to provide a computer program product.

[0009] To achieve the above objectives, the first embodiment of the present application proposes a multi-electric energy scheduling method coupled with energy storage, comprising:

[0010] Obtain historical energy data and energy-related data;

[0011] determining electricity price characteristic data based on the historical energy data and the energy-related data;

[0012] Determining a target energy scheduling strategy from a strategy set based on the electricity price characteristic data, the strategy set including first energy scheduling strategies corresponding to different trigger conditions and second energy scheduling strategies under different time periods;

[0013] Energy scheduling is performed according to the target energy scheduling strategy.

[0014] To achieve the above objectives, the second embodiment of the present application proposes a multi-energy scheduling system coupled with energy storage, including:

[0015] Data collection module, energy management module and energy scheduling module;

[0016] The data collection module is used to obtain historical energy data and energy-related data, and determine electricity price characteristic data based on the historical energy data and the energy-related data;

[0017] The energy management module is configured to determine a target energy scheduling strategy from a strategy set based on the electricity price characteristic data, wherein the strategy set includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy under different time periods;

[0018] The energy scheduling module is used to perform energy scheduling according to the target energy scheduling strategy.

[0019] To achieve the above-mentioned purpose, a third embodiment of the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0020] The memory stores computer-executable instructions;

[0021] The processor executes the computer-executable instructions stored in the memory to implement the method according to the embodiment of the first aspect.

[0022] To achieve the above-mentioned purpose, the fourth embodiment of the present application proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method described in the first embodiment.

[0023] To achieve the above-mentioned purpose, the fifth embodiment of the present application proposes a computer program product, including a computer program, which implements the method described in the first embodiment when executed by a processor.

[0024] The present application provides a multi-energy scheduling method and system coupled with energy storage, which determines electricity price characteristic data through historical energy data and energy-related data. The electricity price characteristic data includes one or more characteristic data that affect energy scheduling. The target energy scheduling strategy is determined through the electricity price characteristic data. In this embodiment, the energy scheduling strategy includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy under different time periods, covering energy scheduling strategies for various situations, better adapting to different scenarios, ensuring that the best energy scheduling can be achieved according to the target energy scheduling strategy, and improving energy scheduling and energy supply efficiency.

[0025] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0027] Figure 1 A flow chart of a multi-energy scheduling method coupled with energy storage provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a process for determining a target energy scheduling strategy provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of an energy scheduling process provided in an embodiment of the present application;

[0030] Figure 4 A flow chart of another multi-energy scheduling method coupled with energy storage provided in an embodiment of the present application;

[0031] Figure 5 A schematic diagram of the structure of a multi-energy scheduling system coupled with energy storage provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0033] This application can be applied to the flexibility transformation scenario of thermal power units. As the proportion of new energy installed capacity gradually increases, the main role of thermal power units in the power system is mainly ballast, which is used to serve the power auxiliary service market. Its main role is peak regulation and frequency regulation, and it is restricted by factors such as minimum load output and coal-fired power generation costs. The use of this process can solve the problems of thermal power units to a certain extent; for example, thermal power units are coupled with energy storage / electricity storage modules for flexibility transformation; for example, after the transformation, it can be achieved that during the off-peak period with low electricity prices, when the wind power / photovoltaic units are in operation, the power grid is mainly powered by new energy, and the thermal power grid is mainly powered by new energy. With electricity as a supplement, thermal power units mostly maintain minimum load output, with part of the energy going online and part of it supplying heat users. In addition, heat storage / electricity storage modules can be combined to store the surplus energy generated by the thermal power units, or the heat storage / electricity storage modules can take advantage of the low-cost electricity prices of the power grid to store energy. During peak hours when electricity prices are relatively high and when wind power / photovoltaic power is not working, the power grid is dominated by thermal power, the electricity generated by thermal power units is used for the power grid, and the heat storage / electricity storage modules release energy. The heat storage modules can provide heat energy for heat users, and the electricity storage modules can be connected to the grid to supply power / provide electricity for electricity users. In addition, photovoltaic panels can be arranged on idle land in thermal power plants to achieve integrated comprehensive regulation.

[0034] This application can also be applied to the consumption of new energy by wind power / photovoltaic units; new energy has the disadvantages of significant intermittency and instability, is greatly affected by weather, and has a strong impact on the power grid; in order to reduce the impact on the power grid, maintain stable output, and reduce the wind / light abandonment rate, this process can be achieved to a certain extent; for example, wind power / photovoltaic units are coupled with energy storage / electricity storage modules for transformation; after the transformation, it can be achieved that during the wind power / photovoltaic working period, when the power grid is overloaded, part of the power is connected to the grid, and part of the power is stored in the heat storage / electricity storage module; during the non-wind power / photovoltaic working period, the heat storage / electricity storage module releases energy, the heat storage module can provide heat energy for heat users, and the electricity storage module can be connected to the grid to supply power / provide electricity to electricity users, which can alleviate the pressure on the power grid to a certain extent.

[0035] This application can also be applied to cost reduction, efficiency improvement, energy conservation and carbon reduction for heat / electricity users; heat / electricity users are more concerned about their own cost issues and concerns such as carbon emission footprint tracking; heat / electricity users can use their own idle space to arrange photovoltaic panels / wind turbines to meet part of their own electricity needs; they can also combine heat / electricity storage modules to store energy during off-peak periods and release energy during other periods to save costs; in addition, the combination of the two can also more flexibly meet the environmental protection, cost reduction and efficiency improvement needs of heat / electricity users.

[0036] The following describes a multi-energy scheduling method and system coupled with energy storage according to an embodiment of the present application with reference to the accompanying drawings.

[0037] Figure 1This is a flow chart of a multi-energy scheduling method coupled with energy storage provided in an embodiment of the present application. Figure 1 As shown, the multi-energy scheduling method coupled with energy storage includes the following steps:

[0038] S101, acquiring historical energy data and energy-related data.

[0039] Optionally, the historical energy data may be historical data generated in different periodic time periods, and may include real-time electricity price data of the power grid in different periodic time periods, the heat demand of heat-consuming devices, the electricity demand of electricity-consuming devices, the amount of wind power abandoned after wind power supply, and the amount of photovoltaic power abandoned after photovoltaic supply.

[0040] Optionally, the energy-related data may be data that affects energy supply or energy use, such as wind speed and photovoltaic irradiation data, or user-side thermal power load data, and may also include data such as heat storage efficiency conversion parameters and energy storage efficiency conversion parameters.

[0041] S102: Determine electricity price characteristic data based on historical energy data and energy-related data.

[0042] In some implementations, electricity price characteristic data can be determined based on a pre-trained model. For example, historical energy data and energy-related data are input into the pre-trained model to output electricity price characteristic data. The electricity price characteristic data may include predicted real-time electricity prices, thermal power load demand on the user side, the amount of wind power and photovoltaic power that is abandoned after wind power and photovoltaic power supply the thermal power demand on the user side, and the non-essential output power of thermal power units. It may also include data such as the output of thermal power units, grid frequency, and main grid voltage.

[0043] S103: Determine a target energy scheduling strategy from a strategy set based on the electricity price characteristic data.

[0044] The strategy set includes first energy scheduling strategies corresponding to different trigger conditions and second energy scheduling strategies under different time periods.

[0045] In some implementations, different time periods may refer to different time periods within a day, such as the peak power period when electricity demand is highest, the valley power period when electricity demand is lowest, the wind power period for wind power generation, the photovoltaic period for solar power generation, and other time periods, such as the flat power period when electricity demand is stable or the short peak period when electricity demand reaches extremely high.

[0046] It is understandable that the electricity prices in different time periods are different and the power supply conditions of power plants are different. Therefore, different energy scheduling strategies can be used for different periods of user electricity consumption. For example, when the electricity price is high, users can give priority to using the energy of the electricity storage / energy storage unit, and purchase electricity from the power grid when the energy of the electricity storage / energy storage unit cannot meet the demand; when the electricity price is low, users can directly consider purchasing electricity from the power grid.

[0047] Optionally, energy scheduling strategies for different time periods can be pre-executed, and corresponding second energy scheduling strategies can be determined according to different electricity users in different time periods and stored in a strategy set. After determining the user type and electricity usage time period, the corresponding second energy scheduling strategy can be queried from the strategy set as the target energy scheduling strategy.

[0048] In some implementations, special circumstances may arise during energy utilization, and the judgment conditions for these special circumstances may be used as trigger conditions. For example, a trigger condition may include the special situation where the real-time electricity price is lower than the preset electricity price. In this case, users may be more inclined to choose electricity at a more economical real-time price. Therefore, when the real-time electricity price is lower than the preset electricity price, the economic energy storage strategy can be prioritized, that is, prioritizing electricity and heat storage. In some implementations, trigger conditions may also include but are not limited to low grid frequency, main grid voltage drop, and excessive thermal power output.

[0049] It is understandable that all trigger conditions and corresponding first energy scheduling strategies can also be determined and summarized and stored in a strategy set. When it is determined that the real-time situation meets a certain trigger condition, the first energy scheduling strategy corresponding to the trigger condition is determined as the target energy scheduling strategy.

[0050] S104: Perform energy scheduling according to the target energy scheduling strategy.

[0051] It is understandable that the target energy scheduling strategy may include strategy steps that need to be executed, such as energy storage / energy storage or purchasing electricity from thermal power, photovoltaic / wind power, so the strategy steps in the target energy scheduling strategy can be executed in sequence to achieve efficient energy scheduling and management.

[0052] In this embodiment, electricity price characteristic data is determined through historical energy data and energy-related data. The electricity price characteristic data includes one or more characteristic data that affect energy scheduling. The target energy scheduling strategy is determined through the electricity price characteristic data. In this embodiment, the energy scheduling strategy includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy under different time periods. It more comprehensively includes energy scheduling under different situations, better adapts to energy scheduling scenarios under different situations, and ensures that the best energy scheduling can be achieved according to the target energy scheduling strategy. The multi-source energy supply solves the problem of unstable single energy supply in the existing technology and improves the energy supply efficiency.

[0053] Based on the above embodiments, Figure 2 A flow chart of determining a target energy scheduling strategy provided in an embodiment of the present application. Figure 2 As shown, the method includes the following steps:

[0054] S201: Determine whether electricity price characteristic data meets at least one condition in a trigger condition set.

[0055] Optionally, the trigger condition set includes: a first trigger condition based on real-time electricity price judgment, a second trigger condition based on grid frequency judgment, a third trigger condition based on thermal power unit output judgment, and a fourth trigger condition based on main grid voltage drop.

[0056] In some implementations, the first trigger condition can be specifically determined by whether the real-time electricity price is lower than the preset electricity price. If the real-time electricity price is lower than the preset electricity price, the first trigger condition is triggered; the second trigger condition can be specifically determined by whether the grid frequency is lower than a preset threshold value. The preset threshold value can be 49.5Hz. If the grid frequency is lower than the preset threshold value 49.5Hz, the second trigger condition is triggered; the third trigger condition can be determined by whether the output of the thermal power unit is greater than the preset output. The preset output can be 85% of the rated capacity. If the output of the thermal power unit is greater than 85% of the rated capacity, the third trigger condition is triggered; the fourth trigger condition can be specifically determined by whether the main grid voltage drop is greater than a preset drop degree. For example, the preset drop degree is 30%. If the main grid voltage drop is greater than 30%, the fourth trigger condition is triggered.

[0057] In this embodiment, the electricity price characteristic data includes at least the real-time electricity price, grid frequency, thermal power unit output and main grid voltage; therefore, it can be determined based on the electricity price characteristic data whether at least one trigger condition in the trigger condition set is met.

[0058] S202 : In response to the electricity price characteristic data satisfying at least one trigger condition, determining a first energy scheduling strategy corresponding to the at least one trigger condition as a target energy scheduling strategy.

[0059] In some implementations, the mapping relationship between the trigger condition and the first energy scheduling strategy may be as shown in Table 1:

[0060] Table 1

[0061]

[0062] That is, when the first trigger condition is met, it indicates that the power supply is sufficient and the cost is low, so the first energy scheduling strategy is to store electricity, and continue to start heat storage when the power storage is full or cannot meet the demand. The strategy goal is economical energy storage and optimization of energy utilization efficiency; when the second trigger condition is met, it indicates that the power supply and demand are unbalanced and the power generation is insufficient to meet the demand, so the first energy scheduling strategy is to give priority to releasing electricity to quickly restore the grid frequency, and start heat release when the power release cannot meet the demand, and release the stored heat energy for output. The strategy goal is emergency energy supply to make the grid stable; when the third trigger condition is met, It indicates that the thermal power unit is in a high-load operation state. Therefore, the first energy scheduling strategy is to extract steam and store heat and electricity for the thermal power unit, store part of the steam heat energy and store excess electricity at the same time. The strategy aims to operate at peak load to improve the flexibility and energy utilization efficiency of the thermal power unit. When the fourth trigger condition is met, it indicates that a serious fault may occur in the power grid. Therefore, the first energy scheduling strategy is black start + island operation. The strategy aims to operate off the grid and use backup power supplies or energy storage equipment to restore local power supply. At the same time, it enters the island operation mode to isolate the fault area from the main grid, ensure the continuous power supply to critical loads, and avoid large-scale power outages.

[0063] It is understandable that electricity price characteristic data may meet multiple trigger conditions at the same time. When multiple trigger conditions are met, the first energy scheduling strategy of multiple trigger conditions is determined as the target energy scheduling strategy to ensure that there is a corresponding strategy for energy scheduling when any trigger condition occurs.

[0064] S203 : In response to the electricity price characteristic data not satisfying any trigger condition in the trigger condition set, determining the target time period to which the current electricity price characteristic data belongs.

[0065] When the electricity price characteristic data does not meet any trigger condition, the second energy scheduling strategy is determined. The second energy scheduling strategy is constructed based on different time periods. In this embodiment, a day is divided into 5 time periods, namely, peak power period, valley power period, wind power working period, photovoltaic working period and other time periods, to determine the target time period to which the current electricity price characteristic data belongs.

[0066] S204 , obtaining the type of the current electricity user, and determining a matching second energy scheduling strategy in the second energy scheduling strategy set as the target energy scheduling strategy according to the user type and the target time period.

[0067] In some implementations, the second energy scheduling set includes: a first sub-energy scheduling set for peak power periods, a second sub-energy scheduling set for valley power periods, a third sub-energy set for wind power working periods, a fourth sub-energy set for photovoltaic working periods, and a fifth sub-energy set for other periods; each sub-energy scheduling set includes sub-energy scheduling strategies corresponding to different user types.

[0068] Specifically, the second energy scheduling strategy set may be as shown in Table 2. Different time periods correspond to sub-energy scheduling sets, and the sub-energy scheduling sets correspond to specific second energy scheduling strategies according to different users:

[0069] Table 2

[0070]

[0071] Based on Table 2 above, it can be seen that the second energy scheduling strategy can be determined according to the target period and the acquired user type. Specifically, during the peak power period:

[0072] When the user type is a thermal power unit, the second energy scheduling strategy is to use the thermal power unit to generate electricity in combination with the heat storage / electricity storage unit to release heat and electricity. The distribution ratio and adjustment form of the two need to be based on actual conditions and adjusted with the goal of maximizing benefits.

[0073] When the user type is a wind power / photovoltaic unit, priority is given to using the wind power / photovoltaic unit for power generation. When it cannot meet the demand, the heat / electricity storage unit is used to release heat and electricity as a guarantee for maintaining stability.

[0074] When the user type is a heat / electricity user, the electricity / heat storage unit is used to release heat and electricity first. When it cannot meet the demand, electricity is purchased from the power grid. The power grid can purchase electricity mainly from thermal power and supplemented by wind power / photovoltaic power.

[0075] During off-peak hours:

[0076] When the user type is a thermal power unit, the thermal power unit is used to generate electricity and the heat / electricity storage unit is used to release heat and electricity to meet the user's heat / electricity needs, and the excess energy is used to store energy in the heat / electricity storage unit.

[0077] When the user type is a wind power / photovoltaic unit, the wind power / photovoltaic unit is used to generate electricity first. When it cannot meet the demand, the heat storage / electricity storage unit is used to release heat and electricity as a stability maintenance guarantee. When there is excess energy, the heat storage / electricity storage unit is used to store energy.

[0078] When the user type is a heat / electricity user, the grid is given priority to purchasing electricity to meet its heat / electricity needs, and heat / electricity storage units are used for energy storage. At this time, the grid purchases electricity mainly from wind power / photovoltaic power, supplemented by thermal power.

[0079] During wind power operation period:

[0080] When the user type is a thermal power unit, ① when the wind turbine unit can meet the user's requirements, it operates at the lowest load, and the heat / electricity storage unit stores heat and electricity; ② when the wind turbine unit cannot meet the user's requirements, the thermal power unit is used to generate electricity and the heat / electricity storage unit is used to release heat and electricity to meet the user's heat / electricity needs, and there is still excess energy that can be used for energy storage in the heat / electricity storage unit.

[0081] When the user type is a wind power / photovoltaic unit, ① when there is sufficient wind power, the wind turbine is used to generate electricity first, and when there is excess energy, the heat storage / electricity storage unit is used to store energy; ② when the wind turbine cannot meet the demand, the heat storage / electricity storage unit is added to release heat and electricity as a stability maintenance guarantee.

[0082] When the user type is a heat / electricity user, ① when the wind power price is lower than the off-peak power price, electricity is purchased from the power grid to meet its heat / electricity needs, and heat / energy storage units are used for energy storage; ② when the wind power price is higher than the off-peak power price, heat / energy storage units are used to release heat and electricity, and when the user's heat / electricity needs cannot be met, electricity is purchased from the power grid to meet the user's energy needs. At this time, the power grid purchases mainly wind power, supplemented by thermal power.

[0083] During the photovoltaic working period:

[0084] When the user type is a thermal power unit, ① when the photovoltaic unit can meet the user's requirements, it operates at the lowest load and the heat / electricity storage unit stores heat and electricity; ② when the photovoltaic unit cannot meet the user's requirements, the thermal power unit is used to generate electricity and the heat / electricity storage unit is used to release heat and electricity to meet the user's heat / electricity needs, and there is still excess energy that can be used for energy storage in the heat / electricity storage unit.

[0085] When the user type is a wind power / photovoltaic unit, photovoltaic units are used to generate electricity first. When they cannot meet the demand, heat storage / electricity storage units are used to release heat and electricity as a guarantee of stability. When there is excess energy, heat storage / electricity storage is used for energy storage.

[0086] When the user type is a heat / electricity user, ① the photovoltaic electricity price is lower than the off-peak electricity price, and electricity is purchased from the power grid to meet the user's heat / electricity needs, and there is still excess energy for heat and electricity storage; ② when the photovoltaic electricity price is higher than the off-peak electricity price, the heat / electricity storage unit is used to release heat and electricity. If it still cannot meet the demand, electricity is purchased from the power grid. At this time, the power grid purchases electricity mainly from photovoltaic power, supplemented by thermal power.

[0087] During other periods:

[0088] When the user type is a thermal power unit, ① when the wind power / photovoltaic unit can meet the user's requirements, it operates at the lowest load and the heat / electricity storage unit stores heat and electricity; ② when the wind power / photovoltaic unit cannot meet the user's requirements, the thermal power unit is used to generate electricity and the heat / electricity storage unit is used to release heat and electricity to meet the user's heat / electricity needs, and there is still excess energy that can be used for energy storage in the heat / electricity storage unit.

[0089] When the user type is a wind power / photovoltaic unit, the wind power / photovoltaic unit is used for power generation first. When it cannot meet the demand, the heat / electricity storage unit is used to release heat and electricity as a guarantee for maintaining stability. When there is excess energy, heat / electricity storage is used for energy storage.

[0090] When the user type is a heat / electricity user, ① when it is determined that the electricity price in this period is lower than the off-peak electricity price, electricity is purchased from the grid to meet the user's heat / electricity needs, and there is still excess energy for heat and electricity storage; ② when the electricity price in this period is higher than the off-peak electricity price, heat / electricity storage units are used to release heat and electricity. If this still cannot meet the demand, electricity is purchased from the grid. At this time, the grid purchases electricity mainly from wind power / photovoltaic power, supplemented by thermal power; in some implementations, the second energy scheduling strategy for each user type in other time periods can also be flexibly adjusted according to real-time electricity price information and user-side thermal power load demand to ensure the lowest energy consumption cost.

[0091] After determining the current electricity user type and the target time period, a matching second energy scheduling strategy can be determined in the second energy scheduling strategy according to the target time period and user type, and the second energy scheduling strategy is used as the target energy scheduling strategy.

[0092] In this embodiment, it is determined based on the electricity price characteristic data whether at least one condition in the trigger condition set is met. The trigger condition set includes four different special situations, such as economic energy storage, emergency energy supply, peak-shaving operation, and off-grid operation. When the electricity price characteristic data meets any trigger condition, the corresponding first energy scheduling strategy is determined as the target energy scheduling strategy for energy scheduling. The energy scheduling is more efficient and adapted to the current scenario. When the trigger condition is not met, the target energy scheduling strategy is determined from the second energy scheduling strategy set. The second energy scheduling strategy set includes multiple time periods such as peak power period, valley power period, wind power working period, photovoltaic working period and other time periods, and different second energy scheduling strategies are formulated for different user types in each time period. Therefore, when determining the target time period and user type of current energy consumption, the corresponding second energy scheduling strategy can be queried from the second energy scheduling strategy set as the target energy scheduling strategy. The determination of the target energy scheduling strategy is more efficient, and the energy scheduling strategy in this embodiment is more in line with the current scenario, and the energy scheduling is more efficient.

[0093] Based on the above embodiments, Figure 3This is a flow chart of energy scheduling provided by an embodiment of the present application. Figure 3 As shown, the method includes:

[0094] S301, determining the energy supply unit in the target energy scheduling strategy.

[0095] The energy supply unit includes an energy storage unit and / or a power generation unit; in this embodiment, the energy storage unit includes a heat storage unit and an electricity storage unit, and the power generation unit includes a thermal power unit, a wind power / photovoltaic unit; it can be understood that the heat storage unit and the electricity storage unit can also release heat and electricity.

[0096] S302: Obtain the priority of each energy supply unit in the current target energy scheduling strategy.

[0097] In some implementations, in the first energy scheduling strategy set corresponding to different trigger conditions, the energy supply unit in the first energy scheduling strategy corresponding to the first trigger condition is an energy storage unit, wherein the priority of the electricity storage unit is higher than the priority of the energy storage unit; the energy supply unit in the first energy scheduling strategy corresponding to the second trigger condition is an energy storage unit, wherein electricity release takes precedence over heat release; the first energy scheduling strategy corresponding to the third trigger condition simultaneously performs gas extraction, heat storage, and electricity storage by the energy storage unit; and the first energy scheduling strategy corresponding to the fourth trigger condition simultaneously performs black start and island operation.

[0098] In the second energy scheduling strategy set, the mapping relationship between the priorities of the energy supply units in different second energy scheduling strategies is shown in Table 3:

[0099] Table 3

[0100]

[0101] It can be understood that in this embodiment, priority 3 is greater than priority 2, which is greater than priority 1. After determining the energy supply unit in the second energy scheduling strategy, the priority of each energy supply unit is determined through the above priority mapping relationship.

[0102] S303: Scheduling energy supply units in order of priority until the energy demand is met.

[0103] During peak power periods, when the user type is a thermal power unit, the energy supply units in the second energy scheduling strategy are the production unit and the energy storage unit, and the priority of the production unit and the energy storage unit is the same as 2. Therefore, at this time, the energy supply unit is scheduled according to the priority, which is to use the thermal power unit in the production unit to generate electricity and the heat and electricity release energy of the heat / electricity storage unit. The distribution ratio and adjustment form of the two need to be carried out according to the actual situation, and adjusted with the goal of maximizing benefits. At the same time, the output power of the thermal power unit is adjusted to ensure that the heat / electricity consumption on the user side meets the demand.

[0104] During peak power periods, when the user type is a wind power / photovoltaic unit, the energy supply units in the second energy scheduling strategy are the production unit and the energy storage unit. According to the specific scheduling of priority, the wind power / photovoltaic unit in the production unit with a priority of 3 is used first to generate electricity. When the demand on the user side can be met, the excess electricity is stored, but the input power and heat storage capacity of the heat / electricity storage unit need to be controlled to ensure its safe operation; when it cannot meet the demand, the heat / electricity storage unit with a priority of 2 is used to release heat and electricity as a stability maintenance guarantee; the output power of heat / electricity release is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the heat / electricity storage unit.

[0105] During peak power periods, when the user type is a heat / electricity user, the energy storage / heat storage unit with a priority of 3 is used to release heat and electricity. When it cannot meet the demand, electricity is purchased from the power grid. The power grid purchases electricity mainly from thermal power with a priority of 2, supplemented by wind power / photovoltaic power with a priority of 1. During the energy scheduling process, the output power of the energy storage / heat storage unit is controlled to ensure that the heat / electricity load demand of the heat / electricity user during this period is met. When the user's demand cannot be met, electricity is purchased from the power grid to supplement the power supply and heating.

[0106] During off-peak hours, when the user type is a thermal power unit, the thermal power unit with the same priority of 2 is used to generate electricity and the heat / electricity storage unit is used to release heat and electricity to meet the user's heat / electricity needs. The excess energy is used for energy storage in the heat / electricity storage unit with a priority of 1, but the input power and heat storage capacity of the heat / electricity storage unit need to be controlled to ensure its safe operation. That is, when the power generation of the thermal power unit cannot meet the user's side demand, the first strategy is to switch the heat / electricity storage unit from energy storage mode to energy release mode, and its output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the heat / electricity storage unit. The second strategy is to increase the output of the thermal power unit (combined with the energy release of the heat / electricity storage unit, depending on whether there is heat / electricity storage).

[0107] During off-peak hours, when the user type is a wind power / photovoltaic unit, priority 3 wind power / photovoltaic units are used for power generation to ensure that the heat / electricity load demand on the user side is met. When it cannot meet the demand, priority 2 heat / electricity storage units are used to release heat and electricity as a stability guarantee. Their output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the heat / electricity storage unit. When there is excess energy, priority 1 heat / electricity storage units are used for energy storage, but the input power and heat storage capacity of the heat / electricity storage unit need to be controlled to ensure its safe operation.

[0108] During off-peak hours, when the user type is a heat / electricity user, the grid is prioritized for purchasing electricity to meet their heat / electricity needs, while a heat / electricity storage unit with a priority of 3 is used for energy storage. At this time, the grid purchases electricity mainly from wind power / photovoltaic power with a priority of 3, supplemented by thermal power with a priority of 2. That is, on the basis of meeting the heat / electricity load needs of heat / electricity users during this period, for economic considerations, the heat / electricity storage unit is used for energy storage, and the input power of the heat / electricity storage unit is controlled to meet the heat / electricity needs during non-off-peak hours.

[0109] During the wind power operation period, when the user type is a thermal power unit, if the wind turbine can meet the user's requirements, it operates at the lowest load, and the thermal / electricity storage unit stores heat and electricity. If the wind turbine cannot meet the user's requirements, the thermal power unit with a priority of 2 is used to generate electricity, and the thermal / electricity storage unit with a priority of 1 is used to release heat and electricity to meet the user's heat / electricity needs. There is still excess energy that can be used for energy storage in the thermal / electricity storage unit with a priority of 1. In other words, when the wind turbine and its supporting thermal / electricity storage unit can meet the user's needs, the thermal power unit adopts a low-load operation mode, generating energy for energy storage in the thermal / electricity storage unit, but the input power and heat storage capacity of the thermal / electricity storage unit must be controlled to ensure its safe operation. If the demand cannot be met, the first strategy is to switch the thermal / electricity storage unit from energy storage mode to energy release mode, and its output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the thermal / electricity storage unit. The second strategy is to increase the output of the thermal power unit (combined with the energy release of the thermal / electricity storage unit, depending on whether there is heat / electricity storage).

[0110] When the user type is a wind power / photovoltaic unit, priority 3 wind turbines are used for power generation. When there is excess energy, priority 2 heat storage / electricity storage units are used for energy storage. When it cannot meet the demand, the heat storage / electricity storage unit is used to release heat and electricity as a stability maintenance guarantee. Ensure that the heat / electricity load demand on the user side is met, and the excess energy is used for energy storage in the heat storage / electricity storage unit, but the input power and heat storage capacity of the heat storage / electricity storage unit need to be controlled to ensure its safe operation. When the wind turbine cannot meet the demand, the heat storage / electricity storage unit switches from energy storage mode to energy release mode, and its output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the heat storage / electricity storage unit.

[0111] When the user type is a heat / electricity user, when the wind power price is lower than the off-peak power price, electricity is purchased from the grid to meet its heat / electricity needs, and a heat / electricity storage unit with a priority of 3 is used for energy storage. However, when the wind power price is higher than the off-peak power price, the heat / energy storage unit is used to release heat and electricity. When the user's heat / electricity needs cannot be met, electricity is purchased from the grid to meet the user's energy needs. At this time, the grid purchases electricity mainly from wind power with a priority of 3, supplemented by thermal power with a priority of 2; that is, the output power of the heat / electricity storage unit is controlled to ensure the heat / electricity load needs of the heat / electricity user during this period; when the heat / electricity storage unit cannot meet the user's needs, it is necessary to purchase electricity from the grid to supplement the power supply and heating.

[0112] During the photovoltaic working period, when the user type is a thermal power unit, when the photovoltaic unit can meet the user's requirements, it operates at the lowest load, and the heat storage / electricity storage unit stores heat and electricity; when the photovoltaic unit cannot meet the user's requirements, the thermal power unit with a priority of 2 is used to generate power and the heat storage / electricity storage unit is used to release heat and electricity to meet the user's heat / electricity needs, and there is still excess energy that can be used for energy storage in the heat storage / electricity storage unit; the energy storage mode and the energy release mode have the same priority, that is, when the photovoltaic unit and its supporting heat storage / electricity storage unit can meet the user's needs, The thermal power unit adopts a low-load operation mode to generate energy for storage in the heat / electricity storage unit, but the input power and heat storage amount of the heat / electricity storage unit need to be controlled to ensure its safe operation; when the photovoltaic unit cannot meet the demand, the first strategy is for the heat / electricity storage unit to switch from energy storage mode to energy release mode, and its output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the heat / electricity storage unit; the second strategy is to increase the output of the thermal power unit (combined with the energy release of the heat / electricity storage unit, depending on whether there is heat / electricity storage).

[0113] When the user type is a wind power / photovoltaic unit, the photovoltaic unit with a priority of 3 is used to generate electricity first. When it cannot meet the demand, the heat storage / electricity storage unit with a priority of 2 is used to release heat and electricity as a stability guarantee. When there is excess energy, heat storage / electricity storage is used for energy storage; that is, the output power of the photovoltaic unit is controlled to ensure that the heat / electricity load demand on the user side is met, and the excess power is used for energy storage in the heat storage / electricity storage unit, but the input power and heat storage capacity of the heat storage / electricity storage unit need to be controlled to ensure its safe operation; when the photovoltaic unit cannot meet the demand, the heat storage / electricity storage unit switches from energy storage mode to energy release mode, and its output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the heat storage / electricity storage unit.

[0114] When the user type is a heat / electricity user, the photovoltaic electricity price is lower than the off-peak electricity price, and electricity is purchased from the grid to meet the user's heat / electricity needs, and there is still excess energy for heat and electricity storage; when the photovoltaic electricity price is higher than the off-peak electricity price, the heat / electricity storage unit with a priority of 3 is used to release heat and electricity. If it still cannot meet the demand, electricity is purchased from the grid. At this time, the grid purchases electricity mainly from photovoltaic power with a priority of 3, supplemented by thermal power with a priority of 2; that is, the output power of the heat / electricity storage unit is controlled to ensure the heat / electricity load demand of the heat / electricity user during this period; when the heat / electricity storage unit cannot meet the user's demand, it is necessary to purchase electricity from the grid to supplement the power supply.

[0115] Furthermore, during other time periods, the target energy scheduling strategy can flexibly adjust the energy control strategy based on real-time electricity price information and user-side thermal and electric load demand to ensure that the energy consumption cost is minimized while meeting the heat / electricity needs of energy users.

[0116] In this embodiment, the energy supply units in the target energy scheduling strategy set are prioritized, that is, the execution actions such as thermal power, photovoltaic, wind power, energy storage and energy release are prioritized. When actually performing energy scheduling, each execution action is executed in sequence according to its priority in the target energy scheduling strategy to ensure that the user's heat / electricity needs are met, avoid insufficient single energy supply and energy waste, maximize the use of wind power / photovoltaic units for power generation, reduce dependence on thermal power, reduce carbon emissions, meet environmental protection requirements, and alleviate the pressure on the power grid to a certain extent. At the same time, it effectively solves the intermittent and instability problems of renewable energy, improves the absorption rate of renewable energy, and realizes the energy scheduling process more flexibly.

[0117] Based on the above embodiments, Figure 4 This is a flow chart of another multi-energy scheduling method coupled with energy storage provided in an embodiment of the present application. Figure 4 As shown, the method includes the following steps:

[0118] S401, acquiring historical energy data and energy-related data.

[0119] In the embodiment of the present application, the implementation method of step S401 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0120] S402: Determine electricity price characteristic data based on historical energy data and energy-related data.

[0121] In some implementations, energy-related data includes at least: environmental data, user-side energy consumption data, and efficiency conversion parameter data of energy storage units; wherein the environmental data may include wind speed and solar radiation intensity. Wind speed can be predicted by weather radar with a prediction error of less than 1.5m / s, and solar radiation intensity can be measured by photovoltaic irradiance meter with an error of ±5W / m 2 .

[0122] In some implementations, the energy consumption data on the user side may be the thermal power load on the user side. The historical thermal power load data on the user side may be obtained, and the current thermal power load data may be predicted based on the historical thermal power load data. The predicted thermal power load data may be used as the energy consumption data on the user side. For example, a pre-trained neural network model may be used to make a prediction based on the historical thermal power load data on the user side, and the predicted thermal power load data may be obtained as the energy consumption data. The pre-trained neural network model may be a long short-term memory network (LSTM), and the prediction error may be less than 8%.

[0123] Furthermore, historical energy data and energy-related data can be input into a pre-trained prediction model; the predicted electricity price characteristic data is output based on the prediction model, and the electricity price characteristic data at least includes real-time electricity price, grid frequency, thermal power unit output and main grid voltage; in some implementations, the amount of wind and solar power abandoned after wind power and photovoltaic power supply the user-side thermal power demand, as well as data such as non-essential output power of thermal power units can also be predicted, and the details will not be elaborated here.

[0124] In the embodiment of the present application, the implementation method of step S402 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0125] S403: Determine whether the electricity price characteristic data satisfies at least one condition in a trigger condition set.

[0126] In the embodiment of the present application, the implementation method of step S403 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0127] S404 : In response to the electricity price characteristic data satisfying at least one trigger condition, determining a first energy scheduling strategy corresponding to the at least one trigger condition as a target energy scheduling strategy.

[0128] In the embodiment of the present application, the implementation method of step S404 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0129] S405 : In response to the electricity price characteristic data not satisfying any trigger condition in the trigger condition set, determining the target time period to which the current electricity price characteristic data belongs.

[0130] In the embodiment of the present application, the implementation method of step S405 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0131] S406 , obtaining the type of the current electricity user, and determining a matching second energy scheduling strategy in the second energy scheduling strategy set as the target energy scheduling strategy according to the user type and the target time period.

[0132] In the embodiment of the present application, the implementation method of step S406 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0133] S407: Determine the energy supply unit in the target energy scheduling strategy.

[0134] In the embodiment of the present application, the implementation method of step S407 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0135] S408: Obtain the priority of each energy supply unit in the current target energy scheduling strategy.

[0136] In the embodiment of the present application, the implementation method of step S408 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be described in detail.

[0137] S409: Scheduling energy supply units in order of priority until the energy demand is met.

[0138] In the embodiment of the present application, the implementation method of step S409 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0139] In this embodiment, historical energy data and energy-related data are processed by a pre-trained model to obtain electricity price characteristic data, which includes one or more characteristic data that affect energy scheduling. The target energy scheduling strategy is determined by the electricity price characteristic data. In this embodiment, the energy scheduling strategy includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy under different time periods. It more comprehensively includes energy scheduling under different situations, better adapts to energy scheduling scenarios under different situations, and ensures that the best energy scheduling can be achieved according to the target energy scheduling strategy. When actually performing energy scheduling, the energy supply units in the target energy scheduling strategy set are prioritized, that is, execution actions such as thermal power, photovoltaics, wind power, energy storage, and energy release are prioritized. When actually performing energy scheduling, each execution action is executed in sequence according to its priority in the target energy scheduling strategy to ensure that the user's heat / electricity needs are met while reducing insufficient energy supply or energy waste, and more flexibly implement the energy scheduling process to improve energy supply efficiency.

[0140] In order to implement the above embodiments, the present application also proposes a multi-energy scheduling system coupled with energy storage.

[0141] Figure 5 This is a schematic diagram of the structure of a multi-energy scheduling system coupled with energy storage provided in an embodiment of the present application. Figure 5 As shown, the multi-energy scheduling system coupled with energy storage includes:

[0142] Data collection module 501, energy management module 502 and energy scheduling module 503;

[0143] The data collection module 501 is used to obtain historical energy data and energy-related data, and determine electricity price characteristic data based on the historical energy data and energy-related data;

[0144] An energy management module 502 is configured to determine a target energy scheduling strategy from a strategy set based on electricity price characteristic data, where the strategy set includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy for different time periods;

[0145] The energy scheduling module 503 is used to perform energy scheduling according to the target energy scheduling strategy.

[0146] In some implementations, the multi-energy scheduling system coupled with energy storage further includes:

[0147] Multiple input module 504 and energy storage module 505;

[0148] The multi-input module 504 is used to provide the energy scheduling module with at least one type of energy, including thermal power generation, wind power generation and photovoltaic power generation;

[0149] The energy storage module 505 is used to store heat and electricity, and provide electrical energy and thermal energy to the energy scheduling module.

[0150] In some implementations, before energy scheduling is performed based on the energy management system, the multi-energy scheduling system coupled with energy storage can perform a self-check to ensure that each module is operating normally; after the self-check is completed, the data collection module 501, the energy management module 502 and the energy scheduling module 503 execute the energy scheduling process in sequence to ensure stable operation of the power grid, maximum proportion of new energy consumption, and user-side thermal power load demand is met, while reducing operating costs.

[0151] In some implementations, the multi-input module 504 covers wind power access (including wind power converter (doubly fed type)), photovoltaic access (including photovoltaic direct current (DC) / alternating current (AC) converter), thermal power coupling (including thermal power unit steam extraction interface), and is equipped with a grid-connected interface, an integrated reactive power compensation device (Static VarGenerator, SVG) and an active power filter (Active Power Filter, APF) to ensure that the total harmonic distortion (THD) is less than 3%.

[0152] In some implementations, the energy storage module 505 includes various types of heat storage devices such as solid electric thermal storage boiler heat storage and electrode boiler heat storage to provide heat for heat-using devices; and includes various types of energy storage modules such as electrochemical energy storage and compressed air energy storage to provide power for electrical devices.

[0153] In some implementations, the modules of the multi-energy dispatching system coupled with energy storage can also include power generation devices such as photovoltaic, wind power, and thermal power, as well as heat storage devices and electricity storage devices. Energy supply between users is realized through heating pipelines and power grids, achieving efficient energy dispatch and management, and avoiding the problem of insufficient energy supply of a single energy source in existing technologies.

[0154] In some implementations, the energy management module 502 is further configured to:

[0155] Determining whether the electricity price characteristic data satisfies at least one condition in a trigger condition set;

[0156] In response to the electricity price characteristic data satisfying at least one trigger condition, determining a first energy scheduling strategy corresponding to the at least one trigger condition as a target energy scheduling strategy;

[0157] In response to the electricity price characteristic data not satisfying any trigger condition in the trigger condition set, determining the target time period to which the current electricity price characteristic data belongs;

[0158] The type of the current electricity user is obtained, and a matching second energy scheduling strategy is determined in the second energy scheduling strategy set as the target energy scheduling strategy according to the user type and the target time period.

[0159] In some implementations, the energy management module 502 is configured to:

[0160] The first trigger condition is based on the real-time electricity price, the second trigger condition is based on the grid frequency, the third trigger condition is based on the output of the thermal power unit, and the fourth trigger condition is based on the main grid voltage drop.

[0161] In some implementations, the energy management module 502 is configured to:

[0162] The first sub-energy scheduling set for the peak power period, the second sub-energy scheduling set for the valley power period, the third sub-energy set for the wind power working period, the fourth sub-energy set for the photovoltaic working period, and the fifth sub-energy set for other periods; each sub-energy scheduling set includes sub-energy scheduling strategies corresponding to different user types.

[0163] In some implementations, the energy scheduling module 503 is configured to:

[0164] Determine the energy supply unit in the target energy scheduling strategy, where the energy supply unit includes an energy storage unit and / or a power generation unit;

[0165] Obtain the priority of each energy supply unit in the current target energy scheduling strategy;

[0166] The energy supply units are dispatched in order of priority until the energy demand is met.

[0167] In some implementations, the data collection module 501 is configured to:

[0168] Input historical energy data and energy correlation data into the pre-trained prediction model;

[0169] The predicted electricity price characteristic data is output according to the prediction model, and the electricity price characteristic data at least includes real-time electricity price, grid frequency, thermal power unit output and main grid voltage.

[0170] In some implementations, the energy-related data includes at least: environmental data, user-side energy usage data, and efficiency conversion parameter data of the energy storage unit.

[0171] In some implementations, the multi-energy dispatch system coupled with energy storage is further used to:

[0172] Obtain historical thermal power load data on the user side and predict current thermal power load data based on the historical thermal power load data;

[0173] The predicted thermal power load data is used as the energy consumption data on the user side.

[0174] It should be noted that the above explanation of an embodiment of a multi-energy scheduling method coupled with energy storage is also applicable to a multi-energy scheduling system coupled with energy storage in this embodiment, and will not be repeated here.

[0175] In an embodiment of the present application, historical energy data and energy-related data are processed by a pre-trained model to obtain electricity price characteristic data, which includes one or more characteristic data that affect energy scheduling. The target energy scheduling strategy is determined by the electricity price characteristic data. In this embodiment, the energy scheduling strategy includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy under different time periods. It more comprehensively includes energy scheduling under different circumstances, better adapts to energy scheduling scenarios under different circumstances, and ensures that the best energy scheduling can be achieved according to the target energy scheduling strategy. When actually performing energy scheduling, the energy supply units in the target energy scheduling strategy set are prioritized, that is, the execution actions such as thermal power, photovoltaic power, wind power, energy storage, and energy release are prioritized. When actually performing energy scheduling, each execution action is executed in sequence according to its priority in the target energy scheduling strategy to ensure that the user's heat / electricity needs are met while reducing insufficient energy supply or energy waste. It is suitable for the user side, the power generation side, and combined scenarios, has a wide range of application scenarios, and more flexibly implements the energy scheduling process, thereby improving energy supply efficiency.

[0176] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0177] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0178] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0179] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0180] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal information and ensure that others with access to personal information comply with its privacy policy and procedures.

[0181] This application contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0182] In the descriptions of the foregoing embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0183] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0184] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0185] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

[0186] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0187] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0188] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0189] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A multi-energy scheduling method coupled with energy storage, characterized in that: The method comprises: Obtain historical energy data and energy-related data; determining electricity price characteristic data based on the historical energy data and the energy-related data; Determining a target energy scheduling strategy from a strategy set based on the electricity price characteristic data, the strategy set including first energy scheduling strategies corresponding to different trigger conditions and second energy scheduling strategies under different time periods; Energy scheduling is performed according to the target energy scheduling strategy.

2. A multi-energy scheduling method coupled with energy storage according to claim 1, characterized in that: The determining of a target energy scheduling strategy from a strategy set based on the electricity price characteristic data includes: Determining whether the electricity price characteristic data satisfies at least one condition in a trigger condition set; In response to the electricity price characteristic data satisfying at least one trigger condition, determining a first energy scheduling strategy corresponding to the at least one trigger condition as the target energy scheduling strategy; In response to the electricity price characteristic data not satisfying any trigger condition in the trigger condition set, determining a target time period to which the current electricity price characteristic data belongs; The type of user currently using electricity is obtained, and a matching second energy scheduling strategy is determined in a second energy scheduling strategy set as a target energy scheduling strategy according to the user type and the target time period.

3. A multi-energy scheduling method coupled with energy storage according to claim 2, characterized in that: The trigger condition set includes: The first trigger condition is based on the real-time electricity price, the second trigger condition is based on the grid frequency, the third trigger condition is based on the output of the thermal power unit, and the fourth trigger condition is based on the main grid voltage drop.

4. A multi-energy scheduling method coupled with energy storage according to claim 2, characterized in that: The second energy scheduling set includes: The first sub-energy scheduling set for the peak power period, the second sub-energy scheduling set for the valley power period, the third sub-energy set for the wind power working period, the fourth sub-energy set for the photovoltaic working period, and the fifth sub-energy set for other periods; each sub-energy scheduling set includes sub-energy scheduling strategies corresponding to different user types.

5. A multi-energy scheduling method coupled with energy storage according to claim 3 or 4, characterized in that: The performing energy scheduling according to the target energy scheduling strategy includes: Determining an energy supply unit in the target energy scheduling strategy, wherein the energy supply unit includes an energy storage unit and / or a power generation unit; Obtaining the priority of each of the energy supply units in the current target energy scheduling strategy; The energy supply units are scheduled in sequence according to the priorities until the energy demand is met.

6. A multi-energy scheduling method coupled with energy storage according to claim 1, characterized in that: The determining of electricity price characteristic data based on the historical energy data and the energy-related data includes: Inputting the historical energy data and the energy-related data into a pre-trained prediction model; The predicted electricity price characteristic data is output according to the prediction model, and the electricity price characteristic data at least includes real-time electricity price, grid frequency, thermal power unit output and main grid voltage.

7. A multi-energy scheduling method coupled with energy storage according to claim 6, characterized in that: The energy-related data includes at least: environmental data, user-side energy consumption data, and efficiency conversion parameter data of the energy storage unit.

8. A multi-energy scheduling method coupled with energy storage according to claim 7, characterized in that: The method for acquiring energy consumption data includes: Obtaining historical thermal power load data on the user side, and predicting current thermal power load data based on the historical thermal power load data; The predicted thermal power load data is used as energy consumption data on the user side.

9. A multi-energy dispatching system coupled with energy storage, characterized in that: The system comprises: Data collection module, energy management module and energy scheduling module; The data collection module is used to obtain historical energy data and energy-related data, and determine electricity price characteristic data based on the historical energy data and the energy-related data; The energy management module is configured to determine a target energy scheduling strategy from a strategy set based on the electricity price characteristic data, wherein the strategy set includes a first energy scheduling strategy corresponding to different trigger conditions and a second energy scheduling strategy under different time periods; The energy scheduling module is used to perform energy scheduling according to the target energy scheduling strategy.

10. A multi-energy dispatching system coupled with energy storage according to claim 9, characterized in that: The system further comprises: Multiple input modules and energy storage modules; The multi-input module is used to provide at least one type of energy to the energy scheduling module, the type including thermal power generation, wind power generation and photovoltaic power generation; The energy storage module is used to store heat and electricity, and provide electrical energy and thermal energy to the energy scheduling module.

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