A multi-energy scheduling method and system coupled with energy storage

Abstract

The application provides a multi-energy scheduling method and system coupled with energy storage, and relates to the technical field of multi-energy scheduling.The multi-energy scheduling method coupled with energy storage comprises the following steps: obtaining historical energy data and energy correlation data; determining electricity price characteristic data according to the historical energy data and the energy correlation 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 trigger conditions and second energy scheduling strategies in different time periods; and performing energy scheduling according to the target energy scheduling strategy, so as to solve the technical problems of unstable power supply and low energy utilization rate in the prior art.

Description

Technical Field

[0001] This application relates to the field of multi-energy dispatching technology, and in particular to a multi-energy dispatching method and system with coupled energy storage. Background Technology

[0002] With the continuous growth of energy demand, the traditional single thermal power energy supply method can no longer meet the needs of modern society. Wind and solar energy, as renewable energy sources, have the advantages of being clean and sustainable, but their power generation has significant shortcomings such as intermittency and instability, and the problems of wind and solar curtailment are prominent. The wind curtailment rate of typical wind farms in Northwest China is over 15%. Although thermal power has higher stability, it faces the problems of resource consumption and environmental pollution. Moreover, when thermal power units carry out deep peak shaving, their heating capacity is greatly reduced. Therefore, the single thermal power energy supply inevitably leads to problems of unstable energy supply, low energy utilization rate and environmental pollution. There is an urgent need for a multi-energy, low-carbon and efficient dispatching method that is adapted to the new power system. Summary of the Invention

[0003] This application aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, the first objective of this application is to propose a multi-energy dispatching method that couples 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 dispatch system with coupled energy storage.

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

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

[0008] The fifth objective of this application is to provide a computer program product.

[0009] To achieve the above objectives, the first aspect of this application proposes a multi-energy dispatching method with coupled energy storage, comprising:

[0010] Acquire historical energy data and energy correlation data;

[0011] Based on the historical energy data and the energy correlation data, determine the electricity price characteristic data;

[0012] Based on the electricity price characteristic data, a target energy dispatch strategy is determined from the strategy set, which includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch strategy under different time periods.

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

[0014] To achieve the above objectives, a second aspect of this application proposes a multi-energy dispatch system coupled with energy storage, comprising:

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

[0016] The data collection module is used to acquire 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 used to determine a target energy dispatch strategy from a strategy set based on the electricity price characteristic data. The strategy set includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch 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 objectives, a third aspect of this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0020] The memory stores computer-executed instructions;

[0021] The processor executes computer execution instructions stored in the memory to implement the method as described in the first aspect embodiment.

[0022] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method described in the first aspect embodiment.

[0023] To achieve the above objectives, a fifth aspect of this application provides a computer program product including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0024] This application provides a multi-energy dispatching method and system with coupled energy storage. It determines electricity price characteristic data through historical energy data and energy correlation data. The electricity price characteristic data includes one or more characteristic data that affect energy dispatching. The target energy dispatching strategy is determined through the electricity price characteristic data. In this embodiment, the energy dispatching strategy includes a first energy dispatching strategy corresponding to different triggering conditions and a second energy dispatching strategy under different time periods. It covers energy dispatching strategies for multiple situations, better adapts to different scenarios, ensures that the optimal energy dispatching can be achieved according to the target energy dispatching strategy, and improves energy dispatching and power supply efficiency.

[0025] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

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

[0027] Figure 1 A flowchart illustrating a multi-energy dispatching method with coupled energy storage provided in an embodiment of this application;

[0028] Figure 2 This is a flowchart illustrating a method for determining a target energy scheduling strategy, as provided in an embodiment of this application.

[0029] Figure 3 This is a schematic diagram of an energy scheduling process provided in an embodiment of this application;

[0030] Figure 4 A flowchart illustrating another multi-energy dispatching method with coupled energy storage provided in an embodiment of this application;

[0031] Figure 5 This is a schematic diagram of a multi-energy dispatch system with coupled energy storage provided in an embodiment of this application. Detailed Implementation

[0032] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0033] This application can be applied to the flexibility retrofitting of thermal power units. As the proportion of renewable energy installed capacity gradually increases, the main role of thermal power units in the power system is as a ballast, serving the power ancillary services market, primarily for peak shaving and frequency regulation. However, they are constrained by factors such as minimum load output and the cost of coal-fired power generation. This technology can, to some extent, solve the problems of thermal power units. Specifically, for example, thermal power units can be coupled with energy storage / storage modules for flexibility retrofitting. For example, after the retrofit, during off-peak electricity hours when electricity prices are low, and when wind / solar power units are operating, the grid primarily uses renewable energy output, and thermal power units... With electricity as a supplement, thermal power units mostly maintain minimum load output, with some going to the grid and some supplying heat users. In addition, thermal / electricity storage modules can be integrated to store the surplus energy generated by thermal power units, or the thermal / electricity storage modules can take advantage of off-peak electricity prices to store energy. During peak electricity periods when electricity prices are higher and it is not the wind / solar power operating period, the grid is dominated by thermal power. The electricity generated by thermal power units is used for the grid, and the thermal / electricity storage modules release energy. The thermal storage modules can provide heat energy to heat users, and the electricity storage modules can supply electricity to the grid or provide electricity to users. In addition, photovoltaic panels can be installed on idle land in thermal power plants to achieve integrated regulation.

[0034] This application can also be applied to the consumption of new energy sources by wind power / photovoltaic units. New energy sources have significant disadvantages in terms of intermittency and instability, are greatly affected by weather, and have a strong impact on the power grid. In order to reduce the impact on the power grid, maintain stable output, and reduce the curtailment rate of wind / solar power, this technology can achieve this to a certain extent. For example, wind power / photovoltaic units can be retrofitted by coupling energy storage / electricity storage modules. After the retrofit, during the wind power / photovoltaic operating period, when the power grid is overloaded, part of the power can be fed into the grid, and part of the power can be stored in the thermal / electricity storage modules. During the non-wind power / photovoltaic operating period, the thermal / electricity storage modules release energy. The thermal storage modules can provide heat energy to heat users, and the electricity storage modules can supply power to the grid / supply electricity to power 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 heating / electricity users. Heating / electricity users are more concerned about their own costs and carbon emission footprint tracking. They can use their idle space to install photovoltaic panels / wind turbine generators to meet part of their electricity needs. They can also combine thermal storage / electricity storage modules to store energy during off-peak hours and release it at other times to save costs. In addition, the combination of the two can more flexibly meet the environmental protection, cost reduction, and efficiency improvement needs of heating / electricity users.

[0036] The following description, with reference to the accompanying drawings, illustrates a multi-energy dispatching method and system for coupled energy storage, according to embodiments of this application.

[0037] Figure 1This is a flowchart illustrating a multi-energy dispatching method with coupled energy storage provided in an embodiment of this application. Figure 1 As shown, the multi-energy dispatch method for coupled energy storage includes the following steps:

[0038] S101, acquire historical energy data and energy correlation data.

[0039] Optionally, historical energy data can be historical data generated in different periodic periods, including real-time grid electricity price data, heat demand of heating devices, electricity demand of electrical devices, wind power curtailment after wind power supply, and solar power curtailment after photovoltaic supply in different periodic periods.

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

[0041] S102, Determine electricity price characteristic data based on historical energy data and energy correlation data.

[0042] In some implementations, electricity price characteristic data can be determined based on pre-trained models. For example, historical energy data and energy correlation data can be input into a pre-trained model to output electricity price characteristic data. The electricity price characteristic data may include predicted real-time electricity prices, user-side heat and power load demand, wind and solar power curtailment after supplying user-side heat and power demand, and non-essential power output of thermal power units. It may also include data such as thermal power unit output, grid frequency, and main grid voltage.

[0043] S103, determine the target energy dispatch strategy from the strategy set based on electricity price characteristic data.

[0044] The strategy set includes a first energy scheduling strategy corresponding to different triggering conditions and a second energy scheduling strategy for different time periods.

[0045] In some implementations, different time periods can refer to different times of the day, such as peak electricity demand, off-peak electricity demand, wind power generation, photovoltaic power generation, and other times, such as stable electricity demand or short-term peak periods when electricity demand is extremely high.

[0046] It is understandable that electricity prices and power supply conditions vary at different times. Therefore, different energy dispatch strategies can be applied to different times of user electricity consumption. For example, when electricity prices are high, users can prioritize the use of energy storage units. When the energy storage units cannot meet the demand, users can purchase electricity from the grid. When electricity prices are low, users can directly consider purchasing electricity from the grid.

[0047] Optionally, energy scheduling strategies for different time periods can be pre-executed, and corresponding second energy scheduling strategies can be determined for different electricity users at different time periods and stored in the strategy set. After determining the user type and electricity consumption 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. These special circumstances can be used as trigger conditions. For example, trigger conditions might include situations where the real-time electricity price is lower than a preset price. In such cases, users may be more inclined to purchase electricity at the more economical real-time price. Therefore, when the real-time electricity price is lower than the preset price, an economical energy storage strategy can be prioritized, that is, prioritizing electricity and thermal energy storage. In some implementations, trigger conditions may also include, but are not limited to, situations where the grid frequency is too low, the main grid voltage drops, and the thermal power output is too high.

[0049] It is understandable that all triggering conditions and their corresponding first energy scheduling strategies can be determined and summarized, and stored in a strategy set. When it is determined that a certain triggering condition is met in real time, the first energy scheduling strategy corresponding to that triggering 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 dispatch strategy may include strategy steps that need to be executed, such as energy storage or purchasing electricity from thermal power, photovoltaic / wind power. Therefore, the strategy steps in the target energy dispatch strategy can be executed sequentially to achieve efficient energy dispatch and management.

[0052] In this embodiment, electricity price characteristic data is determined through historical energy data and energy correlation data. This electricity price characteristic data includes one or more characteristic data that affect energy dispatch. The target energy dispatch strategy is determined through the electricity price characteristic data. In this embodiment, the energy dispatch strategy includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch strategy under different time periods. This more comprehensively includes energy dispatch under different conditions, better adapts to energy dispatch scenarios under different conditions, and ensures that optimal energy dispatch can be achieved according to the target energy dispatch strategy. The multi-source energy supply solves the problem of unstable single energy supply in the prior art and improves energy supply efficiency.

[0053] Based on the above embodiments, Figure 2 This is a schematic flowchart illustrating a method for determining a target energy scheduling strategy, as provided in an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0054] S201, determine whether the electricity price characteristic data satisfies at least one condition in the set of triggering conditions.

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

[0056] In some implementations, the first triggering condition can be 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 triggering condition is triggered. The second triggering condition can be determined by whether the grid frequency is lower than a preset threshold, which can be 49.5Hz. If the grid frequency is lower than the preset threshold of 49.5Hz, the second triggering condition is triggered. The third triggering condition can be determined by whether the output of the thermal power unit is greater than a preset output, which 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 triggering condition is triggered. The fourth triggering condition can be determined by whether the voltage drop of the main grid is greater than a preset drop level, for example, the preset drop level is 30%. If the voltage drop of the main grid is greater than 30%, the fourth triggering condition is triggered.

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

[0058] S202, in response to the electricity price characteristic data satisfying at least one triggering condition, determine the first energy dispatching strategy corresponding to the at least one triggering condition as the target energy dispatching strategy.

[0059] In some implementations, the mapping relationship between the triggering conditions and the first energy scheduling strategy can be shown in Table 1:

[0060] Table 1

[0061]

[0062] In other words, when the first triggering condition is met, it indicates that the power supply is sufficient and the cost is low. Therefore, the first energy dispatch strategy is to store electricity, and when the storage is full or unable to meet demand, to activate thermal energy storage. The purpose of this strategy is economical energy storage and optimization of energy utilization efficiency. When the second triggering condition is met, it indicates that there is an imbalance between power supply and demand, and power generation is insufficient to meet demand. Therefore, the first energy dispatch strategy is to prioritize the release of electricity to quickly restore the grid frequency. When the release of electricity also fails to meet demand, to activate thermal energy release, to release and output the stored heat energy. The purpose of this strategy is to provide emergency energy and stabilize the grid operation. When the third triggering condition is met... This indicates that the thermal power unit is operating under high load. Therefore, the first energy dispatch strategy is to extract steam from the thermal power unit for heat storage and electricity storage, storing some of the steam heat energy and storing excess electrical energy. The purpose of this strategy is to operate during peak shaving to improve the flexibility and energy utilization efficiency of the thermal power unit. When the fourth triggering condition is met, it indicates that a serious grid fault may occur. Therefore, the first energy dispatch strategy is to start the grid and then operate in an islanded manner. The purpose of this strategy is to operate off-grid, using backup power or energy storage equipment to restore local power supply, while entering islanded operation mode to isolate the faulty area from the main grid, ensuring continuous power supply to critical loads and avoiding large-scale power outages.

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

[0064] S203, in response to the fact that the electricity price feature data does not meet any of the triggering conditions in the triggering condition set, determine the target time period to which the current electricity price feature data belongs.

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

[0066] S204: Obtain the current user type for electricity consumption, and determine the matching second energy dispatch strategy from the second energy dispatch strategy set as the target energy dispatch strategy based on the user type and target time period.

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

[0068] Specifically, the second energy scheduling strategy set can be as shown in Table 2, with different time periods corresponding to sub-energy scheduling sets, and each sub-energy scheduling set corresponding to a specific second energy scheduling strategy based on different users:

[0069] Table 2

[0070]

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

[0072] When the user type is a thermal power unit, the second energy dispatch strategy is to use the energy released by the thermal power unit's power generation combined with the heat and electricity released by the thermal storage / electricity storage unit. The allocation ratio and adjustment method of the two should be carried out according to the actual situation, with the goal of maximizing benefits.

[0073] When the user type is a wind power / photovoltaic unit, wind power / photovoltaic units will be used to generate electricity first. When they cannot meet the demand, thermal storage / electricity storage units will be used to release heat and electricity as a guarantee for stability.

[0074] When the user type is a heat / electricity user, the energy storage / thermal storage unit should be used first for heat and electricity release. When it cannot meet the demand, electricity should be purchased from the grid. The grid-purchased electricity can be mainly thermal power, supplemented by wind / solar power.

[0075] During off-peak electricity hours:

[0076] When the user type is a thermal power unit, the thermal power unit generates electricity and releases heat and electricity in combination with the thermal / electricity storage unit to meet the user's heat / electricity needs. Excess energy is used for energy storage in the thermal / electricity storage unit.

[0077] When the user type is wind power / photovoltaic unit, wind power / photovoltaic unit power generation is given priority. When it cannot meet the demand, thermal storage / electricity storage unit is used for heat release and electricity release as a stability guarantee. When there is excess energy, thermal storage / electricity storage unit is used for energy storage.

[0078] When the user type is a heat / electricity user, the grid purchase of electricity will be given priority to meet their heat / electricity needs. At the same time, thermal / electricity storage units will be used for energy storage. In this case, the grid purchase of electricity will mainly be wind power / solar power, with thermal power as a supplement.

[0079] During wind power operating hours:

[0080] When the user type is a thermal power unit, ① if the wind power unit can meet the user's requirements, it will operate at the minimum load, and the thermal / electricity storage unit will store heat and electricity; ② if the wind power unit cannot meet the user's requirements, the thermal power unit will be used to generate electricity in combination with the thermal / electricity storage unit to release heat and electricity to meet the user's heat / electricity needs, and there will still be excess energy that can be used for energy storage in the thermal / electricity storage unit.

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

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

[0083] During photovoltaic operating hours:

[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 thermal / electricity storage unit stores heat and electricity; ② when the photovoltaic unit cannot meet the user's requirements, the thermal power unit generates electricity and releases heat and electricity in combination with the thermal / electricity storage unit to meet the user's heat / electricity needs, and there is still excess energy that can be used for energy storage in the thermal / electricity storage unit.

[0085] When the user type is wind power / solar power unit, solar power generation is given priority. When it cannot meet the demand, thermal storage / electricity storage unit is used to release heat and electricity as a stability guarantee. When there is excess energy, thermal storage / electricity storage is used for energy storage.

[0086] When the user type is a heat / electricity user, ① if the photovoltaic electricity price 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 surplus energy for heat and electricity storage; ② if the photovoltaic electricity price is higher than the off-peak electricity price, heat and electricity storage units are used to release heat and electricity, and if the demand is still not met, electricity is purchased from the grid. In this case, the grid purchases mainly consist of photovoltaic power and supplemented by thermal power.

[0087] At other times:

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

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

[0090] When the user type is a heat / electricity user, ① if the electricity price during 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 surplus energy for heat and electricity storage; ② if the electricity price during this period is higher than the off-peak electricity price, heat and electricity storage units are used to release heat and electricity, and if the demand still cannot be met, electricity is purchased from the grid. In this case, the grid purchase of electricity is mainly wind power / solar power, supplemented by thermal power. In some implementations, the second energy dispatch strategy for each user type in other time periods can also be flexibly adjusted according to real-time electricity price information and user-side heat and power load demand to ensure the lowest energy consumption cost.

[0091] After determining the current electricity user type and target time period, a matching second energy dispatch strategy can be determined in the second energy dispatch strategy based on the target time period and user type, and this second energy dispatch strategy can be used as the target energy dispatch strategy.

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

[0093] Based on the above embodiments, Figure 3This is a schematic diagram of an energy scheduling process provided in an embodiment of this application. Figure 3 As shown, the method includes:

[0094] S301, Determine the energy supply unit in the target energy dispatch 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 thermal storage unit and an electric storage unit, and the power generation unit includes a thermal power unit and a wind power / photovoltaic unit; it is understood that the thermal storage unit and the electric storage unit can also release heat and electricity.

[0096] S302, obtain the priority of each power supply unit in the current target energy dispatch strategy.

[0097] In some implementations, within the set of first energy dispatch strategies corresponding to different triggering conditions, the energy supply unit in the first energy dispatch strategy corresponding to the first triggering condition is an energy storage unit, where the priority of the electricity storage unit is higher than that of the energy storage unit; in the first energy dispatch strategy corresponding to the second triggering condition, the energy supply unit is an energy storage unit, where electricity release takes priority over heat release; in the first energy dispatch strategy corresponding to the third triggering condition, the gas pumping and heat storage of the energy storage unit and electricity storage are carried out simultaneously; and in the first energy dispatch strategy corresponding to the fourth triggering condition, black start and islanded operation are carried out simultaneously.

[0098] In the second energy dispatch strategy set, the mapping relationship of the priority of the energy supply unit in different second energy dispatch strategies is shown in Table 3:

[0099] Table 3

[0100]

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

[0102] S303 schedules energy supply units according to 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 dispatch strategy are the production capacity unit and the energy storage unit. The priority of both the production capacity unit and the energy storage unit is 2. Therefore, the energy supply unit is dispatched according to priority, which uses the energy released by the thermal power unit in the production capacity unit through the combination of heat and electricity release from the thermal storage / electricity storage unit. The allocation ratio and adjustment method of the two need to be adjusted according to the actual situation, with the goal of maximizing benefits. At the same time, the output power of the thermal power unit is adjusted to ensure that the user's heat / electricity demand is met.

[0104] During peak power periods, when the user type is a wind / solar turbine, the energy supply units in the second energy dispatch strategy are the production capacity unit and the energy storage unit. According to priority, the specific dispatch is to prioritize the use of wind / solar turbines in the production capacity unit with priority 3. When the user's demand can be met, the excess electricity is stored, but the input power and heat storage of the thermal / electrical storage unit need to be controlled to ensure its safe operation. When it cannot meet the demand, the thermal / electrical storage unit with priority 2 is used to release heat and electricity as a stability guarantee. The output power of the heat / electricity release is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the thermal / electrical storage unit.

[0105] During peak power periods, when the user type is a heat / electricity user, the energy storage / thermal storage unit with priority 3 is used first for heat and electricity release. When it cannot meet the demand, electricity is purchased from the grid, with thermal power (priority 2) as the main source and wind / solar power (priority 1) as a supplement. During energy dispatch, the output power of the heat / electricity storage unit is controlled to ensure that the heat / electricity load demand of the heat / electricity user is met during this period. When the user demand cannot be met, electricity is purchased from the 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 priority 2 generates electricity and releases heat and electricity in conjunction with the thermal / electrical storage unit to meet the user's heat / electricity demand. Excess energy is used for energy storage in the thermal / electrical storage unit with priority 1. However, it is necessary to control the input power and heat storage capacity of the thermal / electrical storage unit to ensure its safe operation. That is, when the thermal power unit cannot meet the user's demand, the first strategy is for the thermal / electrical storage unit to switch from energy storage mode to energy release mode. Its output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the thermal / electrical storage unit. The second strategy is to increase the output of the thermal power unit (in conjunction with the energy release of the thermal / electrical storage unit, depending on whether there is heat / electricity stored).

[0107] During off-peak hours, when the user type is a wind / solar turbine, the wind / solar turbine with priority 3 is used first to ensure that the user's heat / electric load demand is met. When the demand cannot be met, the thermal / electric storage unit with priority 2 is used to release heat and electricity as a stabilization guarantee. Its output power is determined by the heat / electric load demand of the heat / electricity user and the maximum output power of the thermal / electric storage unit. When there is excess energy, the thermal / electric storage unit with priority 1 is used for energy storage, but the input power and heat storage of the thermal / electric storage unit must be controlled to ensure its safe operation.

[0108] During off-peak hours, when the user type is a heat / electricity user, the grid purchase of electricity is given priority to meet their heat / electricity needs. At the same time, thermal / electricity storage units with priority 3 are used for energy storage. In this case, the grid purchase of electricity is mainly wind / solar power with priority 3, and thermal power with priority 2 is used as a supplement. That is, on the basis of meeting the heat / electricity load demand of the heat / electricity user during this period, for economic reasons, thermal / electricity storage units are used for energy storage, and the input power of thermal / electricity storage units is controlled to meet the heat / electricity demand during non-off-peak hours.

[0109] During wind power operation periods, when the user type is a thermal power unit, if the wind turbine can meet the user's requirements, it operates at the minimum load, with the thermal / electrical storage unit storing heat and electricity. If the wind turbine cannot meet the user's requirements, the thermal power unit with priority 2 generates electricity in conjunction with the thermal / electrical storage unit with priority 1 to release heat and electricity to meet the user's heat / electricity needs. There is still surplus energy available for energy storage in the thermal / electrical storage unit with priority 1. In other words, when the wind turbine and its associated thermal / electrical storage unit can meet the user's needs, the thermal power unit adopts a low-load operation mode, generating energy for the thermal / electrical storage unit to store energy, but the input power and heat storage capacity of the thermal / electrical storage unit need to be controlled to ensure its safe operation. If the needs cannot be met, the first strategy is for the thermal / electrical 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 thermal / electrical storage unit. The second strategy is to increase the output of the thermal power unit (in conjunction with the energy release of the thermal / electrical storage unit, depending on whether there is stored heat / electricity).

[0110] When the user type is wind power / solar power generation, wind turbines with priority 3 are used first for power generation. When there is excess energy, thermal / electrical storage units with priority 2 are used for energy storage. When the demand cannot be met, thermal / electrical storage units are used for heat and electricity release as a stabilization guarantee. It is ensured that the user's heat / electricity load demand is met, and excess energy is used for energy storage in thermal / electrical storage units. However, the input power and heat storage capacity of thermal / electrical storage units must be controlled to ensure their safe operation. When wind turbines cannot meet the demand, thermal / electrical storage units switch from energy storage mode to energy release mode. Their output power is determined by the heat / electricity load demand of the heat / electricity user and the maximum output power of the thermal / electrical storage unit.

[0111] When the user type is a heat / electricity user, if the wind power price is lower than the off-peak electricity price, electricity is purchased from the grid to meet their heat / electricity needs, and a thermal / electricity storage unit with priority 3 is used for energy storage. However, if the wind power price is higher than the off-peak electricity price, the thermal / electricity storage unit is used to release heat and electricity. If this cannot meet the user's heat / electricity needs, electricity is purchased from the grid to meet the user's energy needs. In this case, the grid purchases electricity mainly from wind power (priority 3) and supplemented by thermal power (priority 2). In other words, the output power of the thermal / electricity storage unit is controlled to ensure the heat / electricity load needs of the user during this period. When the thermal / electricity storage unit cannot meet the user's needs, electricity needs to be purchased from the grid to supplement the power supply and heating.

[0112] During photovoltaic (PV) operation periods, when the user type is a thermal power unit, the PV unit operates at its minimum load if it can meet the user's requirements, with the thermal / electrical storage unit storing heat and electricity. If the PV unit cannot meet the user's requirements, the thermal / electrical storage unit, with priority level 2, releases heat and electricity to meet the user's heat / electricity needs, and any surplus energy can still be used for energy storage. The energy storage mode and energy release mode have the same priority; that is, when the PV unit and its associated thermal / electrical storage unit can meet the user's needs... Thermal power units operate in a low-load mode, generating energy for energy storage in thermal / electricity storage units. However, the input power and heat storage capacity of these units must be controlled to ensure their safe operation. When photovoltaic units cannot meet the demand, the first strategy is for the thermal / electricity storage units to switch from energy storage mode to energy release mode. The output power of these units is determined by the heat / electricity load demand of the users and the maximum output power of the thermal / electricity storage units. The second strategy is to increase the output of the thermal power units (in conjunction with the energy release from the thermal / electricity storage units, depending on whether there is stored heat / electricity).

[0113] When the user type is wind power / solar power units, the solar power units with priority 3 are used first to generate electricity. When they cannot meet the demand, the thermal / electrical storage units with priority 2 are used to release heat and electricity as a stabilization guarantee. When there is excess energy, thermal / electrical storage is used for energy storage. In other words, the output power of the solar power units is controlled to ensure that the user's heat / electric load demand is met. Excess electricity is used for energy storage by the thermal / electrical storage units, but the input power and heat storage capacity of the thermal / electrical storage units must be controlled to ensure their safe operation. When the solar power units cannot meet the demand, the thermal / electrical storage units switch from energy storage mode to energy release mode. Their output power is determined by the heat / electric load demand of the heat / electricity users and the maximum output power of the thermal / electrical storage units.

[0114] When the user type is a heat / electricity user, if the photovoltaic electricity price 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 surplus energy for heat and electricity storage. When the photovoltaic electricity price is higher than the off-peak electricity price, heat / electricity storage units with priority 3 are used for heat and electricity release. If this still cannot meet the demand, electricity is purchased from the grid. At this time, the grid purchases electricity mainly from photovoltaic units with priority 3, and thermal power units with priority 2 as a supplement. In other words, the output power of the heat / electricity storage units is controlled to ensure the heat / electricity load demand of the user during this period. When the heat / electricity storage units cannot meet the user's demand, electricity needs to be purchased from the grid to supplement the power supply.

[0115] Furthermore, at other times, the target energy dispatch strategy can flexibly adjust the energy control strategy based on real-time electricity price information and user-side heat and power load demand to ensure that energy consumption costs are minimized while meeting the heat / electricity needs of energy users.

[0116] In this embodiment, the energy supply units in the target energy dispatch strategy set are prioritized, that is, the execution actions such as thermal power, photovoltaic, wind power, energy storage, and energy release are prioritized. During actual energy dispatch, each execution action is executed sequentially according to its priority in the target energy dispatch 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, alleviate grid pressure to a certain extent, effectively solve the problems of intermittency and instability of renewable energy, improve the renewable energy absorption rate, and realize the energy dispatch process more flexibly.

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

[0118] S401, acquire historical energy data and energy correlation data.

[0119] In this application embodiment, the implementation method of step S401 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0120] S402, Determine electricity price characteristic data based on historical energy data and energy correlation data.

[0121] In some implementations, energy-related data includes at least: environmental data, user-side energy consumption data, and energy storage unit efficiency conversion parameter data; among which, 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 1.5 m / s, and solar radiation intensity can be measured by a photovoltaic irradiance meter with an error of ±5 W / m. 2 .

[0122] In some implementations, the energy consumption data on the user side can be the user's thermoelectric load. Historical thermoelectric load data on the user side can be obtained, and the current thermoelectric load data can be predicted based on the historical thermoelectric load data. The predicted thermoelectric load data is then used as the energy consumption data on the user side. For example, a pre-trained neural network model can make predictions based on the historical thermoelectric load data on the user side to obtain the predicted thermoelectric load data as the energy consumption data. The pre-trained neural network model can be a Long Short-Term Memory (LSTM) network, and the prediction error can be less than 8%.

[0123] Furthermore, historical energy data and energy correlation data can be input into the pre-trained prediction model; the prediction model outputs predicted electricity price characteristic data, which includes at least real-time electricity price, grid frequency, thermal power unit output, and main grid voltage; in some implementations, it can also predict the amount of wind and solar power curtailment after wind and solar power supply to users' thermal power demand, as well as the amount of non-essential output of thermal power units, etc., which will not be elaborated on in detail.

[0124] In this application embodiment, the implementation method of step S402 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0125] S403, determine whether the electricity price characteristic data satisfies at least one condition in the set of triggering conditions.

[0126] In this application embodiment, the implementation method of step S403 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0127] S404, in response to the electricity price characteristic data satisfying at least one triggering condition, determine the first energy dispatching strategy corresponding to the at least one triggering condition as the target energy dispatching strategy.

[0128] In this application embodiment, the implementation method of step S404 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0129] S405, in response to the fact that the electricity price feature data does not meet any of the triggering conditions in the triggering condition set, determines the target time period to which the current electricity price feature data belongs.

[0130] In this application embodiment, the implementation method of step S405 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0131] S406: Obtain the current user type for electricity consumption, and determine the matching second energy dispatch strategy from the second energy dispatch strategy set as the target energy dispatch strategy based on the user type and target time period.

[0132] In this application embodiment, the implementation method of step S406 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0133] S407, Identify the energy supply units in the target energy dispatch strategy.

[0134] In this application embodiment, the implementation method of step S407 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0135] S408, obtain the priority of each power supply unit in the current target energy dispatch strategy.

[0136] In this application embodiment, the implementation method of step S408 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0137] S409 dispatches energy supply units sequentially according to priority until the energy demand is met.

[0138] In this application embodiment, the implementation method of step S409 can be implemented in any of the various embodiments of this disclosure, and no limitation is made here, nor will it be described in detail.

[0139] In this embodiment, historical energy data and energy-related data are processed by a pre-trained model to obtain electricity price feature data. This electricity price feature data includes one or more feature data that affect energy dispatch. The target energy dispatch strategy is determined based on the electricity price feature data. In this embodiment, the energy dispatch strategy includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch strategy under different time periods, which more comprehensively covers energy dispatch under different conditions and better adapts to energy dispatch scenarios under different conditions. This ensures that the optimal energy dispatch can be achieved according to the target energy dispatch strategy. When actually performing energy dispatch, the energy supply units in the target energy dispatch strategy set are prioritized. That is, the execution actions of thermal power, photovoltaic, wind power, energy storage, and energy release are prioritized. When actually performing energy dispatch, each execution action is executed sequentially according to its priority in the target energy dispatch strategy. This ensures that the user's heat / electricity needs are met while reducing insufficient energy supply or energy waste, realizing a more flexible energy dispatch process and improving energy supply efficiency.

[0140] To achieve the above embodiments, this application also proposes a multi-energy dispatch system with coupled energy storage.

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

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

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

[0144] The energy management module 502 is used to determine the target energy dispatch strategy from the strategy set based on electricity price characteristic data. The strategy set includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch strategy under 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, this coupled energy storage multi-energy dispatch system also includes:

[0147] Multi-input module 504 and energy storage module 505;

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

[0149] Energy storage module 505 is used for thermal and electrical storage and provides electrical and thermal energy to the energy dispatch module.

[0150] In some implementations, before energy dispatching is carried out based on the energy management system, the multi-energy dispatching system with coupled 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 dispatching module 503 execute the energy dispatching process in sequence to ensure the stable operation of the power grid, the maximum proportion of new energy consumption, the satisfaction of user-side thermal and power load demand, and the reduction of operating costs.

[0151] In some implementations, the multi-input module 504 covers wind power access (including wind power converter (doubly fed)), photovoltaic access (including photovoltaic DC / AC converter), and thermal power coupling (including thermal power unit extraction interface). It is also equipped with a grid connection interface, and integrates a static var generator (SVG) and an active power filter (APF) to ensure that the total harmonic distortion (THD) is <3%.

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

[0153] In some implementations, the modules of a multi-energy dispatch system coupled with energy storage can also include photovoltaic, wind power, thermal power and other power generation devices, as well as thermal storage devices and electric storage devices. Energy supply between the system and users is achieved through heating pipe networks and power grids, realizing efficient energy dispatch and management, and avoiding the problem of insufficient energy supply caused by a single energy source in existing technologies.

[0154] In some implementations, the energy management module 502 is also used for:

[0155] Determine whether the electricity price characteristic data satisfies at least one condition in the set of triggering conditions;

[0156] In response to the electricity price characteristic data satisfying at least one triggering condition, the first energy dispatching strategy corresponding to at least one triggering condition is determined as the target energy dispatching strategy;

[0157] In response to the fact that the electricity price feature data does not meet any of the trigger conditions in the trigger condition set, the target time period to which the current electricity price feature data belongs is determined;

[0158] Obtain the current user type for electricity consumption, and determine the matching second energy dispatch strategy from the second energy dispatch strategy set as the target energy dispatch strategy based on the user type and target time period.

[0159] In some implementations, the energy management module 502 is used for:

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

[0161] In some implementations, the energy management module 502 is used for:

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

[0163] In some implementations, the energy dispatch module 503 is used for:

[0164] Identify the energy supply units in the target energy dispatch strategy, including energy storage units and / or production capacity units;

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

[0166] Energy supply units are dispatched sequentially according to priority until the energy demand is met.

[0167] In some implementations, the data collection module 501 is used for:

[0168] Historical energy data and energy correlation data are input into a pre-trained prediction model;

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

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

[0171] In some implementations, multi-energy dispatch systems with coupled energy storage are also used for:

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

[0173] The predicted thermal and electrical load data will be used as the energy consumption data on the user side.

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

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

[0176] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0177] To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0178] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

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

[0180] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted 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 authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0181] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0182] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[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 technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0184] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0185] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing 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 (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs 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: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0186] It should be understood that various parts of this 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 memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0187] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

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

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

Claims

1. A multi-energy scheduling method of coupling energy storage, characterized in that, The method includes: Acquire historical energy data and energy correlation data; Based on the historical energy data and the energy correlation data, determine the electricity price characteristic data; Based on the electricity price characteristic data, a target energy dispatch strategy is determined from the strategy set, which includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch strategy under different time periods. Energy scheduling is performed according to the target energy scheduling strategy. The step of determining the target energy dispatch strategy from the strategy set based on the electricity price characteristic data includes: Determine whether the electricity price feature data satisfies at least one condition in the set of triggering conditions; In response to the electricity price feature data satisfying at least one triggering condition, the first energy scheduling strategy corresponding to the at least one triggering condition is determined as the target energy scheduling strategy; In response to the fact that the electricity price feature data does not meet any of the triggering conditions in the set of triggering conditions, the target time period to which the current electricity price feature data belongs is determined; Obtain the current user type for electricity consumption, and determine the matching second energy scheduling strategy from the second energy scheduling strategy set as the target energy scheduling strategy based on the user type and the target time period.

2. The multi-energy dispatching method with coupled energy storage according to claim 1, characterized in that, The set of triggering conditions includes: The first triggering condition is based on real-time electricity price, the second triggering condition is based on grid frequency, the third triggering condition is based on thermal power unit output, and the fourth triggering condition is based on grid voltage drop.

3. The multi-energy dispatching method with coupled energy storage according to claim 1, characterized in that, The second set of energy scheduling strategies includes: The first sub-energy dispatch set for peak power periods, the second sub-energy dispatch set for off-peak power periods, the third sub-energy set for wind power operating periods, the fourth sub-energy set for photovoltaic operating periods, and the fifth sub-energy set for other periods; each sub-energy dispatch set includes sub-energy dispatch strategies corresponding to different user types.

4. A multi-energy dispatching method for coupled energy storage according to claim 2 or 3, characterized in that, The energy scheduling according to the target energy scheduling strategy includes: Determine the energy supply units in the target energy dispatch strategy, wherein the energy supply units include energy storage units and / or production capacity units; Obtain the priority of each of the energy supply units in the current target energy scheduling strategy; The energy supply units are scheduled sequentially according to the stated priority until the energy demand is met.

5. A multi-energy dispatching method with coupled energy storage according to claim 1, characterized in that, The step of determining electricity price characteristic data based on the historical energy data and the energy correlation data includes: The historical energy data and the energy correlation data are input into the pre-trained prediction model; The predicted electricity price characteristic data output by the prediction model includes at least real-time electricity price, grid frequency, thermal power unit output, and main grid voltage.

6. A multi-energy dispatching method for coupled energy storage according to claim 5, characterized in that, The energy-related data includes at least: environmental data, user-side energy consumption data, and energy storage unit efficiency conversion parameter data.

7. A multi-energy dispatching method for coupled energy storage according to claim 6, characterized in that, The method for acquiring energy consumption data includes: Obtain historical thermoelectric load data from the user side, and predict the current thermoelectric load data based on the historical thermoelectric load data; The predicted thermoelectric load data will be used as the energy consumption data on the user side.

8. A multi-energy dispatch system with coupled energy storage, characterized in that, The system includes: Data collection module, energy management module, and energy dispatch module; The data collection module is used to acquire 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 used to determine a target energy dispatch strategy from a strategy set based on the electricity price characteristic data. The strategy set includes a first energy dispatch strategy corresponding to different triggering conditions and a second energy dispatch strategy under different time periods. The energy scheduling module is used to perform energy scheduling according to the target energy scheduling strategy; The energy management module is further configured to: determine whether the electricity price feature data satisfies at least one condition in the trigger condition set; in response to the electricity price feature data satisfying at least one trigger condition, determine the first energy scheduling strategy corresponding to the at least one trigger condition as the target energy scheduling strategy; in response to the electricity price feature data not satisfying any trigger condition in the trigger condition set, determine the target time period to which the current electricity price feature data belongs; obtain the current electricity user type, and determine a matching second energy scheduling strategy in the second energy scheduling strategy set as the target energy scheduling strategy based on the user type and the target time period.

9. A multi-energy dispatch system with coupled energy storage according to claim 8, characterized in that, The system also includes: Multi-input module and energy storage module; The multi-input module is used to provide at least one type of energy to the energy dispatch module, the type including thermal power generation, wind power generation and photovoltaic power generation; The energy storage module is used for thermal and electrical storage, and provides electrical and thermal energy to the energy dispatch module.

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