Adiabatic compressed air energy storage multi-energy supply dispatching method and device

Abstract

The application provides an adiabatic compressed air energy storage multi-energy supply scheduling method and device, and relates to the technical field of energy storage. The method comprises the following steps: constructing respective operation characteristics corresponding to charge-discharge working conditions, electric heat supplement working conditions and external heat supply working conditions; the operation characteristics are used for representing the change of the target state of charge corresponding to the adiabatic compressed air energy storage (A-CAES) system under different working conditions; the target state of charge is used for representing the air storage and the heat conducting oil storage in the A-CAES system; the operation boundary of the A-CAES system in multi-energy supply is constructed; the operation boundary is used for representing the differential operation constraints of the A-CAES system under different operation modes; and the A-CAES system multi-energy supply scheduling optimization strategy is determined based on all the operation characteristics and the operation boundary. The application can comprehensively depict the operation characteristics under different working conditions and the operation boundary under different operation modes, and improve the accuracy of multi-energy supply scheduling.

Description

Technical Field

[0001] This invention relates to the field of energy storage technology, and in particular to a method and apparatus for scheduling multi-energy combined heat and power (CHP) using adiabatic compressed air energy storage. Background Technology

[0002] In the process of building a new power system, the large-scale grid connection of highly volatile wind and solar power poses a severe challenge to the stability of the power system. Therefore, developing energy storage technology has become one of the key paths to support the achievement of the "dual carbon" goal. In particular, adiabatic compressed air energy storage (A-CAES) has attracted much attention as a large-scale physical energy storage method with broad application prospects. The core advantage of the A-CAES system lies in recovering and storing the heat of compression during the charging phase, and using the stored heat energy to heat the compressed air during the discharging phase, thereby driving turbine power generation. This eliminates the dependence of traditional compressed air energy storage on fossil fuels, achieving efficient recycling of energy within the system and zero carbon emissions throughout the entire process. In addition, the A-CAES system can not only realize the spatiotemporal transfer of electrical energy, but also provide users with multiple energy forms such as electricity and heat by expanding the interface of the thermal storage system, building an efficient multi-energy supply system and significantly improving the overall energy utilization efficiency.

[0003] Currently, when the A-CAES system provides combined energy supply services, its internal state changes frequently with the progress of multiple physical processes, resulting in diverse operational characteristics. To flexibly adjust the A-CAES system's support for the power grid and heating network during combined energy supply, its operation is subdivided into two modes: coordinated electricity and heat supply, and electricity-dominant. The operational boundaries differ between these different modes. However, existing A-CAES systems provide a rather one-sided and inaccurate characterization of these diverse operational characteristics and the differentiated operational boundaries under different modes, leading to lower accuracy in combined energy supply scheduling. Summary of the Invention

[0004] This invention provides a method and apparatus for scheduling multi-energy supply using adiabatic compressed air energy storage, which solves the problem that the existing technology has a relatively one-sided and inaccurate characterization of diversified operating characteristics and differentiated operating boundaries under different modes, resulting in low accuracy of multi-energy supply scheduling.

[0005] This invention provides a method for scheduling multi-energy supply using adiabatic compressed air energy storage, comprising the following steps.

[0006] The operating characteristics corresponding to charging and discharging conditions, electric heating conditions, and external heating conditions are constructed. The operating characteristics are used to characterize the changes in the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions. The target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air mass of the gas storage tank and the heat transfer oil mass of the high-temperature heat storage tank. Construct the operational boundary of the A-CAES system when it is used for multi-energy supply; the operational boundary is used to characterize the differentiated operational constraints of the A-CAES system under different operating modes. Based on all operational characteristics and the aforementioned operational boundaries, a multi-energy supply scheduling optimization strategy for the A-CAES system is determined.

[0007] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the target state of charge includes a first state of charge and a second state of charge. The target state of charge is determined based on the following steps: Based on the current air quality of the gas storage facility, the minimum air quality of the gas storage facility, and the air quality difference of the gas storage facility, the first state of charge of the A-CAES system at the current moment is determined; the first state of charge is used to characterize the air storage status of the gas storage facility corresponding to the A-CAES system. Based on the current heat transfer oil mass of the high-temperature thermal storage tank, the minimum heat transfer oil mass of the high-temperature thermal storage tank, and the difference in heat transfer oil mass of the high-temperature thermal storage tank, the second state of charge of the A-CAES system at the current moment is determined; the second state of charge is used to characterize the heat transfer oil storage status of the high-temperature thermal storage tank corresponding to the A-CAES system.

[0008] The adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention further includes: The air quality of the gas storage facility at the current moment is determined based on the previous moment's air quality, changes in charging air quality, and changes in discharging air quality. Based on the previous moment's data on the heat transfer oil mass of the high-temperature heat storage tank, the change in the heat transfer oil mass during charging, the change in the heat transfer oil mass during discharging, the change in the heat transfer oil mass during electric heating, and the change in the heat transfer oil mass during external heating, the current moment's heat transfer oil mass is determined.

[0009] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the operating characteristics corresponding to the charging and discharging conditions include: charging operation sub-characteristics and discharging operation sub-characteristics, wherein: The charging operation sub-characteristics are used to characterize the correlation between the change in charging air mass and the charging power under charging conditions, as well as the correlation between the change in charging heat transfer oil mass and the charging power. The discharge operation sub-characteristics are used to characterize the correlation between the change in discharge air mass and discharge power under discharge conditions, as well as the correlation between the change in discharge heat transfer oil mass and discharge power.

[0010] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the operating characteristics corresponding to the electric heating condition are used to characterize the correlation between the change in the mass of the electric heating heat transfer oil and the power of the electric heating system under the electric heating condition.

[0011] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the operating characteristics corresponding to the external heating condition are used to characterize the correlation between the mass change of the external heating heat transfer oil and the mass flow rate of the external heating hot water under the external heating condition. The operating characteristics corresponding to the external heating condition are determined based on the mass change of the external heating heat transfer oil, the mass flow rate of the external heating hot water, the temperature of the heat transfer oil, the water temperature, the isobaric specific heat capacity of the heat transfer oil and water, the heat exchange efficiency of the oil-water heat exchanger, and the unit scheduling time.

[0012] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the operating boundaries include charge / discharge constraints, electric heating constraints, external heating constraints, shortest operating time constraints, state of charge constraints, and operating state constraints, wherein: The charge and discharge constraints are used to characterize the charge and discharge power range of the A-CAES system when multiple energy sources are supplied simultaneously. The electric heating constraint is used to characterize the range of electric heating power when the A-CAES system is used for multi-energy supply. The external heating constraint is used to characterize the water mass flow rate range when the A-CAES system is used for multi-energy combined supply. The minimum running time constraint is used to characterize the range of the shortest running time of the A-CAES system in different operating modes; The state of charge constraint is used to characterize the range of the state of charge of the A-CAES system in different operating modes. The operational state constraints are used to characterize the operational mutual exclusion constraints of the A-CAES system when multiple energy sources are supplied simultaneously.

[0013] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the state of charge constraint includes a first state of charge constraint and a second state of charge constraint, wherein: The first state of charge constraint is used to constrain the fixed range of the first state of charge of the A-CAES system under different operating modes; The second state of charge constraint is used to constrain the fixed range corresponding to the second state of charge of the A-CAES system in the electrothermal co-operation mode, and the dynamic range determined based on the first state of charge in the power-dominated operation mode.

[0014] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the operating state constraints include mutual exclusion constraints of charging and discharging states, mutual exclusion constraints of supplementary heating and heating conditions, and mutual exclusion constraints of operating modes. Specifically, the mutual exclusion constraints of charging and discharging states prevent the A-CAES system from operating simultaneously in both charging and discharging states; the mutual exclusion constraints of supplementary heating and heating conditions prevent the A-CAES system from operating simultaneously in both electric supplementary heating and external heating conditions; and the mutual exclusion constraints of operating modes prevent the A-CAES system from operating simultaneously in both electric-thermal synergistic operation mode and electric-dominant operation mode.

[0015] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the charging and discharging constraints include charging electron constraints and discharging electron constraints. The charging electron constraints are used to constrain the charging power range of the A-CAES system, and the discharging electron constraints are used to constrain the discharging power range of the A-CAES system.

[0016] According to the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the present invention, the step of determining the multi-energy supply scheduling optimization strategy of the A-CAES system based on all operating characteristics and the operating boundary includes: Input all operating characteristics and the operating boundary into the solver to obtain the A-CAES system multi-energy supply scheduling optimization strategy output by the solver.

[0017] The present invention also provides an adiabatic compressed air energy storage multi-energy supply scheduling device, which includes the following modules.

[0018] The first construction module is used to construct the operating characteristics corresponding to the charging and discharging conditions, the electric heating conditions, and the external heating conditions. The operating characteristics are used to characterize the changes in the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions. The target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank. The second construction module is used to construct the operating boundary of the A-CAES system when multiple energy sources are supplied simultaneously; the operating boundary is used to characterize the differentiated operating constraints of the A-CAES system under different operating modes. The first determining module is used to determine the multi-energy supply scheduling optimization strategy of the A-CAES system based on all operating characteristics and the operating boundaries.

[0019] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the adiabatic compressed air energy storage multi-energy supply scheduling method as described above.

[0020] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the adiabatic compressed air energy storage multi-energy supply scheduling method as described above.

[0021] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the adiabatic compressed air energy storage multi-energy supply scheduling method as described above.

[0022] The present invention provides a method and apparatus for scheduling multi-energy combined supply of adiabatic compressed air energy storage. It determines the target state of charge (SOC) of the A-CAES system based on the air quality in the gas storage tank and the heat transfer oil quality in the high-temperature thermal storage tank. The target SOC characterizes the air storage and heat transfer oil storage conditions within the A-CAES system. It then constructs the corresponding operating characteristics for charging / discharging, electric heating, and external heating conditions, and establishes the operating boundaries for multi-energy combined supply of the A-CAES system. Finally, based on all operating characteristics and operating boundaries, it determines the optimization strategy for multi-energy combined supply scheduling of the A-CAES system. In this invention, by constructing operating characteristics under different operating conditions, the changes in the target state of charge of the A-CAES system under charging and discharging conditions, electric heating conditions, and external heating conditions are comprehensively characterized. Furthermore, by constructing operating boundaries, the differentiated operating constraints of the A-CAES system under different operating modes are comprehensively characterized. This solves the problem of incomplete and inaccurate characterization of operating characteristics and differentiated operating boundaries under different modes caused by frequent changes in multiple operating conditions. Finally, based on the comprehensively characterized operating characteristics and operating boundaries, a scheduling optimization strategy is determined to improve the accuracy of multi-energy cogeneration scheduling. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the structure of the A-CAES system provided in an embodiment of the present invention.

[0025] Figure 2 This is a schematic flowchart of the multi-energy supply scheduling method for adiabatic compressed air energy storage provided in an embodiment of the present invention.

[0026] Figure 3 This is a schematic diagram of the structure of the thermal compressed air energy storage multi-energy supply scheduling device provided in the embodiment of the present invention.

[0027] Figure 4This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0029] To address the problem that existing technologies often provide only a superficial and inaccurate characterization of diverse operational characteristics and differentiated operational boundaries under different modes, leading to low accuracy in multi-energy supply scheduling, this invention provides a multi-energy supply scheduling method using adiabatic compressed air energy storage. This method is applied to A-CAES (Adiabatic Compressed Air Energy Storage) systems with multi-energy supply capabilities. Figure 1 This is a schematic diagram of the A-CAES system provided in an embodiment of the present invention, as shown below. Figure 1 As shown, the A-CAES system includes a compressor, a turbine, an air storage tank, a thermal storage and heat exchange system, an electric heating system, and an external heating system. The compressor is... Figure 1 The LPC and HPC shown in the image represent low-pressure compressors and high-pressure compressors, respectively. The turbine is... Figure 1 The LPT and HPT shown in the diagram represent a low-pressure turbine and a high-pressure turbine, respectively. The heat storage and exchange system includes a first heat exchanger group, a second heat exchanger group, a high-temperature heat storage tank, and a low-temperature heat storage tank. The first heat exchanger group is... Figure 1 The HEX1 and HEX2 shown in the figure represent the second heat exchanger group. Figure 1 The diagram shows HEX3 and HEX4, where M represents an electric motor and G represents a generator. During charging of the A-CAES system, air is compressed by a compressor, and after heat exchange with the first heat exchanger group, it is converted into low-temperature, high-pressure air and transported to the gas storage tank for storage. The heat transfer oil recovers the heat of compression of the air in the first heat exchanger group and is then pumped to the high-temperature heat storage tank for storage. During discharging of the A-CAES system, air is released from the gas storage tank, heated by the second heat exchanger group, and then enters the turbine to expand and perform work, thereby driving the generator to generate electricity. Furthermore, for the electric heating system, the A-CAES system can utilize off-peak electricity to heat the low-temperature heat transfer oil in the low-temperature heat storage tank and then transport it to the high-temperature heat storage tank for storage. For the external heating system, the A-CAES system can consume the high-temperature heat transfer oil in the high-temperature heat storage tank, heat room-temperature water through an oil-water heat exchanger to produce hot water, thereby achieving external heating.

[0030] Figure 2 This is a flowchart illustrating the multi-energy cogeneration scheduling method for adiabatic compressed air energy storage provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes steps 210 to 230.

[0031] Step 210: Construct the operating characteristics corresponding to the charging and discharging conditions, the electric heating conditions, and the external heating conditions; the operating characteristics are used to characterize the changes in the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions; the target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank.

[0032] Specifically, the air quality in the gas storage tank represents the quality of the air stored in the gas storage tank, and the heat transfer oil quality in the high-temperature heat storage tank represents the quality of the heat transfer oil stored in the high-temperature heat storage tank. Based on the current air quality in the gas storage tank and the heat transfer oil quality in the high-temperature heat storage tank, the target state of charge of the A-CAES system is determined. This target state of charge is used to characterize the air storage status in the gas storage tank and the heat transfer oil storage status in the high-temperature heat storage tank in the A-CAES system.

[0033] The A-CAES system includes charging and discharging conditions, electric heating conditions, and external heating conditions during operation. In this embodiment of the invention, the operating characteristics under different conditions are constructed. The operating characteristics corresponding to each condition represent the changes in the target state of charge under each condition, that is, the mapping relationship between the target state of charge and the control parameters of each condition.

[0034] Step 220: Construct the operating boundary of the A-CAES system when it is used for multi-energy supply; the operating boundary is used to characterize the differentiated operating constraints of the A-CAES system under different operating modes.

[0035] Specifically, the A-CAES system includes an electrothermal coordinated operation mode and an electrical energy-based operation mode. The operation boundaries of the different operation modes are different. Therefore, in this embodiment of the invention, the operation boundary of the A-CAES system when multiple energy sources are supplied is constructed. This operation boundary represents the differentiated operation constraints of the A-CAES system under different operation modes.

[0036] Step 230: Based on all operating characteristics and the operating boundaries, determine the multi-energy supply scheduling optimization strategy for the A-CAES system.

[0037] Specifically, after determining all operating characteristics and operating boundaries, the optimal solution is obtained based on all operating characteristics and operating boundaries to obtain the multi-energy supply scheduling optimization strategy of the A-CAES system, so as to guide the optimized operation of the A-CAES system in multi-energy supply.

[0038] The adiabatic compressed air energy storage multi-energy supply scheduling method provided in this invention determines the target state of charge (SOC) of the A-CAES system based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank. The target SOC characterizes the air storage and heat transfer oil storage conditions in the A-CAES system. The operating characteristics corresponding to the charging and discharging conditions, electric heating conditions, and external heating conditions are constructed respectively. The operating boundary of the A-CAES system during multi-energy supply is also constructed. Finally, based on all operating characteristics and operating boundaries, the multi-energy supply scheduling optimization strategy of the A-CAES system is determined. In this embodiment of the invention, by constructing the operating characteristics of different operating conditions, the changes in the target state of charge of the A-CAES system under charging and discharging conditions, electric heating conditions, and external heating conditions are comprehensively characterized. By constructing operating boundaries, the differentiated operating constraints of the A-CAES system under different operating modes are comprehensively characterized. This solves the problem of incomplete and low-accuracy characterization of operating characteristics and differentiated operating boundaries under different modes caused by frequent changes in multiple operating conditions. Then, based on the comprehensively characterized operating characteristics and operating boundaries, a scheduling optimization strategy is determined to improve the accuracy of multi-energy cogeneration scheduling.

[0039] In one embodiment, the target state of charge is determined based on the following steps: Based on the current air quality of the gas storage facility, the minimum air quality of the gas storage facility, and the air quality difference of the gas storage facility, the first state of charge of the A-CAES system at the current moment is determined; the first state of charge is used to characterize the air storage status of the gas storage facility corresponding to the A-CAES system. Based on the current heat transfer oil mass of the high-temperature thermal storage tank, the minimum heat transfer oil mass of the high-temperature thermal storage tank, and the difference in heat transfer oil mass of the high-temperature thermal storage tank, the second state of charge of the A-CAES system at the current moment is determined; the second state of charge is used to characterize the heat transfer oil storage status of the high-temperature thermal storage tank corresponding to the A-CAES system.

[0040] Specifically, the target state of charge includes a first state of charge and a second state of charge, wherein the first state of charge is used to characterize the air storage status of the gas storage tank in the A-CAES system, and the second state of charge is used to characterize the heat transfer oil storage status of the high-temperature heat storage tank in the A-CAES system.

[0041] Using equation (1), based on the current air mass of the gas storage facility, the minimum air mass of the gas storage facility, and the air mass difference of the gas storage facility, the first state of charge of the A-CAES system at the current moment is calculated. Equation (1) is: .

[0042] in, This represents the first state of charge of the A-CAES system at the current time (i.e., time t). This indicates the current air quality in the gas storage facility. This indicates the minimum air mass required for a gas storage facility, that is, the minimum amount of air that the facility must store. This represents the air quality difference in a gas storage facility, which is the difference between the maximum and minimum air quality that can be stored in the facility.

[0043] Using equation (2), based on the current heat transfer oil mass of the high-temperature heat storage tank, the minimum heat transfer oil mass of the high-temperature heat storage tank, and the difference in heat transfer oil mass of the high-temperature heat storage tank, the second state of charge of the A-CAES system at the current moment is calculated. Equation (2) is: .

[0044] in, This represents the second state of charge of the A-CAES system at the current time (i.e., time t). This indicates the current quality of the heat transfer oil in the high-temperature heat storage tank. This indicates the minimum mass of heat transfer oil in a high-temperature thermal storage tank, that is, the minimum mass of heat transfer oil stored in the high-temperature thermal storage tank. This indicates the mass difference of the heat transfer oil in the high-temperature thermal storage tank. The mass difference of the heat transfer oil in the high-temperature thermal storage tank is the difference between the maximum and minimum mass of heat transfer oil that can be stored in the high-temperature thermal storage tank.

[0045] In one embodiment, the method further includes: The air quality of the gas storage facility at the current moment is determined based on the previous moment's air quality, changes in charging air quality, and changes in discharging air quality. Based on the previous moment's data on the heat transfer oil mass of the high-temperature heat storage tank, the change in the heat transfer oil mass during charging, the change in the heat transfer oil mass during discharging, the change in the heat transfer oil mass during electric heating, and the change in the heat transfer oil mass during external heating, the current moment's heat transfer oil mass is determined.

[0046] Specifically, in step 110, as the A-CAES system charges and discharges, or as the heat storage and release process proceeds, the air quality in the gas storage tank and the heat transfer oil quality in the high-temperature heat storage tank will dynamically change, thereby affecting the target state of charge of the A-CAES system. Therefore, in this embodiment of the invention, using equation (3), the air quality in the gas storage tank at the current moment is calculated based on the air quality in the gas storage tank at the previous moment, the change in the air quality during charging at the previous moment, and the change in the air quality during discharging at the previous moment. Equation (3) is: .

[0047] in, This indicates the air quality in the gas storage facility at the previous moment (i.e., moment t-1). This indicates the change in air mass during charging at the previous moment, specifically the air mass that entered the storage tank due to charging by the A-CAES system at the previous moment. This represents the change in the mass of the discharged air at the previous moment, specifically the mass of air released from the gas storage tank due to the discharge of the A-CAES system at the previous moment. It is a non-negative number.

[0048] It should be noted that both the change in air mass during charging and the change in air mass during discharging pertain to changes in the first state of charge.

[0049] Using equation (4), the current mass of the heat transfer oil in the high-temperature heat storage tank is calculated based on the previous moment's mass of the heat transfer oil, the previous moment's change in the mass of the charging heat transfer oil, the previous moment's change in the mass of the discharging heat transfer oil, the previous moment's change in the mass of the electrically supplemented heat transfer oil, and the previous moment's change in the mass of the externally supplied heat transfer oil. Equation (4) is: .

[0050] in, This indicates the mass of the heat transfer oil in the high-temperature heat storage tank at the previous moment (i.e., moment t-1). This indicates the change in the mass of the heat transfer oil during charging at the previous moment, specifically the mass of heat transfer oil that entered the high-temperature heat storage tank due to charging by the A-CAES system at the previous moment. This indicates the change in the mass of the heat transfer oil at the previous moment, specifically the mass of the heat transfer oil that left the high-temperature heat storage tank due to the charging and discharging of the A-CAES system at the previous moment. It is a non-negative number. This indicates the change in the mass of the electrically supplemented heat transfer oil at the previous moment, specifically the mass of heat transfer oil that entered the high-temperature heat storage tank due to the electrically supplemented heat from the A-CAES system at the previous moment. It is a non-negative number. This indicates the change in the mass of the heat transfer oil supplied to the outside at the previous moment, specifically the mass of the heat transfer oil that left the high-temperature heat storage tank due to the A-CAES system supplying heat to the outside at the previous moment. It is a non-negative number.

[0051] It should be noted that the changes in the mass of the charging heat transfer oil, the discharge heat transfer oil, the electric heating heat transfer oil, and the external heating heat transfer oil all pertain to changes in the second state of charge.

[0052] In one embodiment, the operating characteristics corresponding to the charging and discharging conditions include: charging operation sub-characteristics and discharging operation sub-characteristics, wherein: The charging operation sub-characteristics are used to characterize the correlation between the change in charging air mass and the charging power under charging conditions, as well as the correlation between the change in charging heat transfer oil mass and the charging power. The discharge operation sub-characteristics are used to characterize the correlation between the change in discharge air mass and discharge power under discharge conditions, as well as the correlation between the change in discharge heat transfer oil mass and discharge power.

[0053] Specifically, the charging and discharging conditions include charging and discharging conditions. When the A-CAES system is in charging condition, the charging operation sub-characteristics corresponding to the charging condition are constructed using equation (5), which is: .

[0054] in, This indicates the change in air mass during charging at the current moment. This indicates the charging power of the A-CAES system at the current moment. This indicates whether the A-CAES system is currently in charging mode. For Boolean variables, and All represent fitting coefficients, used to fit the linear functional relationship between the change in charging air mass at the current moment and the charging power. This indicates the correlation between the change in air mass during charging and the charging power under charging conditions. This indicates the change in the mass of the charging heat transfer oil at the current moment. and All represent fitting coefficients, used to fit the linear functional relationship between the change in the mass of the charging heat transfer oil at the current moment and the charging power. This indicates the correlation between the change in the mass of the heat transfer oil during charging and the charging power.

[0055] When the A-CAES system is in discharge condition, the discharge operation sub-characteristics corresponding to the discharge condition are constructed using equation (6), which is: .

[0056] in, This represents the change in the mass of the discharged air at the current moment. This represents the discharge power of the A-CAES system at the current moment. This indicates whether the A-CAES system is currently operating in a discharge state. and All represent fitting coefficients, used to fit the linear functional relationship between the change in discharge air mass and discharge power at the current moment. This indicates the correlation between the change in discharge air mass and the discharge power under discharge conditions. This indicates the change in the mass of the heat transfer oil at the current moment. and All represent fitting coefficients, used to fit the linear functional relationship between the change in the mass of the heat transfer oil at the current moment and the discharge power. This indicates the correlation between the change in the mass of the heat transfer oil during discharge and the discharge power.

[0057] In one embodiment, the operating characteristics corresponding to the electric heating condition are used to characterize the correlation between the change in the mass of the electric heating heat transfer oil and the power of the electric heating system under the electric heating condition.

[0058] Specifically, under the electric heating condition of the A-CAES system, the operating characteristics corresponding to the electric heating condition are constructed using equation (7). These operating characteristics represent the correlation between the change in the mass of the electric heating heat transfer oil and the power of the electric heating system under the electric heating condition. That is, according to equation (7), the change in the mass of the heat transfer oil in the high-temperature heat storage tank under the electric heating condition at the current moment can be calculated. Equation (7) is: .

[0059] in, This indicates the change in the mass of the electrically supplemented heat transfer oil at the current moment. This indicates the current power of the electric heating system. The coefficient represents the fitting coefficient, used to fit the linear functional relationship between the change in the mass of the electrically supplemented heat transfer oil and the power of the electrically supplemented heating system at the current moment.

[0060] In one embodiment, the operating characteristics corresponding to the external heating condition are used to characterize the correlation between the change in the mass of the external heating heat transfer oil and the mass flow rate of the external hot water under the external heating condition. The operating characteristics corresponding to the external heating condition are determined based on the change in the mass of the external heating heat transfer oil, the mass flow rate of the external hot water, the heat transfer oil temperature, the water temperature, the specific heat capacity at constant pressure, the heat exchange efficiency of the oil-water heat exchanger, and the unit scheduling time.

[0061] Specifically, when the A-CAES system is in external heating operation, using equation (8), based on the change in the mass of the external heating heat transfer oil, the mass flow rate of the external heating hot water, the temperature of the heat transfer oil, the water temperature, the specific heat capacity at constant pressure, the heat exchange efficiency of the oil-water heat exchanger, and the unit scheduling time, the operating characteristics corresponding to the external heating operation are constructed. These operating characteristics corresponding to the external heating operation represent the correlation between the change in the mass of the external heating heat transfer oil and the mass flow rate of the external heating hot water under the external heating operation. That is, according to equation (8), the change in the mass of the heat transfer oil in the high-temperature heat storage tank under the external heating operation at the current moment can be calculated. Equation (8) is: .

[0062] in, This indicates the change in the mass of the heat transfer oil supplied to external heating systems at the current moment. Indicates the mass flow rate of hot water supplied to external users. This indicates the temperature of the heat transfer oil in the high-temperature heat storage tank. This indicates the temperature of the heat transfer oil in the low-temperature thermal storage tank. Indicates the temperature of the hot water after heating. This indicates the water temperature at room temperature. This indicates the specific heat capacity at constant pressure of the heat transfer oil. This represents the specific heat capacity of water at constant pressure. This indicates the heat exchange efficiency of the oil-water heat exchanger in the external heating system. Indicates the unit scheduling time.

[0063] In one embodiment, the operating boundaries include charge / discharge constraints, electric heating constraints, external heating constraints, minimum operating time constraints, state of charge constraints, and operating state constraints, wherein: The charge and discharge constraints are used to characterize the charge and discharge power range of the A-CAES system when multiple energy sources are supplied simultaneously. The electric heating constraint is used to characterize the range of electric heating power when the A-CAES system is used for multi-energy supply. The external heating constraint is used to characterize the water mass flow rate range when the A-CAES system is used for multi-energy combined supply. The minimum running time constraint is used to characterize the range of the shortest running time of the A-CAES system in different operating modes; The state of charge constraint is used to characterize the range of the state of charge of the A-CAES system in different operating modes. The operational state constraints are used to characterize the operational mutual exclusion constraints of the A-CAES system when multiple energy sources are supplied simultaneously.

[0064] Specifically, the charge / discharge constraint is used to ensure that the charging and discharging power of the A-CAES system remains within a normal range. The charge / discharge constraint includes charging electron constraint and discharging electron constraint. The charging electron constraint is used to constrain the charging power range of the A-CAES system, and the discharging electron constraint is used to constrain the discharging power range of the A-CAES system. This charge / discharge constraint is shown in equation (9), which is: .

[0065] in, This indicates the lower limit of the charging power of the A-CAES system when using multiple energy sources. This indicates the upper limit of the charging power of the A-CAES system when using multiple energy sources. This indicates the lower limit of the discharge power of the A-CAES system under combined energy supply conditions. This indicates the upper limit of the discharge power of the A-CAES system during multi-energy supply.

[0066] The electric heating constraint is used to ensure that the electric heating power in the A-CAES system remains within the normal range. This electric heating constraint is shown in equation (10), which is: .

[0067] in, This indicates the lower limit of the electric heating power supplied by the A-CAES system during combined energy supply. This indicates the upper limit of the electric heating power of the A-CAES system in combined energy supply. This indicates whether the A-CAES system is currently operating under electric heating conditions, and It is a Boolean variable.

[0068] The external heating constraint is used to ensure that the water mass flow rate of the A-CAES system remains within the normal range when providing external heating. This external heating constraint is shown in equation (11), which is: .

[0069] in, This indicates the lower limit of the water mass flow rate of the A-CAES system when supplying heat to the outside. This indicates the upper limit of the water mass flow rate of the A-CAES system when supplying heat to the outside. This indicates whether the A-CAES system is currently operating under external heating conditions, and that... It is a Boolean variable.

[0070] When the A-CAES system operates in a combined energy supply mode, it operates in two modes: an electrothermal co-operation mode and an electricity-dominant mode. In the electrothermal co-operation mode, the charging, discharging, and heat storage / release processes of the A-CAES system are relatively independent, with less constraint. In the electricity-dominant mode, the A-CAES system mainly realizes bidirectional energy interaction with the power grid. At this time, the heat storage / release process is constrained by the charging and discharging process. Therefore, to avoid frequent switching between the two operating modes of the A-CAES system, a minimum operating time constraint is constructed to constrain the minimum operating time range of the A-CAES system in different operating modes. This minimum operating time constraint is shown in equation (12), which is: .

[0071] in, This indicates whether the A-CAES system is currently operating in electrothermal co-operation mode, and For Boolean variables, Indicates the shortest operating time for the electrothermal co-operation mode. This indicates the first time starting from the current time (i.e., time t). At what moment is the A-CAES system operating in electrothermal co-operation mode? , Indicates starting from the current moment. The total duration of the A-CAES system in electrothermal coordinated operation mode within a consecutive time period. This indicates whether the A-CAES system was operating in electrothermal co-operation mode at the previous moment. (Hereinafter referred to as electrothermal difference) indicates whether the A-CAES system has switched to electrothermal coordinated operation mode from the previous moment to the current moment. For example, in It is 1, and When the value is 0, the electrothermal difference is 1, indicating that the A-CAES system switches to the electrothermal co-operation mode at the current time t. For example, in... and When both are 1, the electrothermal difference is 0, indicating that the A-CAES system is still in electrothermal coordinated operation mode at the current time t, and no switching has occurred. For example, in... It is 0, and When the value is 1, the electrothermal difference is -1, indicating that the A-CAES system switches to another operating mode at the current time t (e.g., the electric power-dominated operating mode). For example, in... and When both are 0, the electrothermal difference is 0, indicating that the A-CAES system is still in another operating mode (e.g., the power-dominated operating mode) at the current time t, and no switching has occurred. It is 1, and When the value is 0, that is, when the A-CAES system switches to the electrothermal co-operation mode at the current time t, the electrothermal difference is 1. This indicates that if the system switches to the electrothermal co-operation mode at the current moment, then in the following... The A-CAES system must always be in the electrothermal co-operation mode within a continuous moment to avoid frequent switching to the electric power-dominated operation mode. This indicates whether the A-CAES system is currently operating in an energy-dominant mode, and For Boolean variables, Indicates the shortest operating time in the electric power-dominated operation mode. Indicates the number of times starting from the current moment. At what moment does the A-CAES system operate in the power-dominant mode? , Indicates starting from the current moment. The total duration of time during which the A-CAES system operates in power-dominant mode within a consecutive time period. This indicates whether the A-CAES system was operating in the power-dominant mode at the previous moment. (Hereinafter referred to as the power difference) indicates whether the A-CAES system has switched to the power-dominant operation mode from the previous moment to the current moment. For example, in =1, When the value is 0, the energy difference is 1, indicating that the A-CAES system has switched to the energy-dominant operation mode at the current moment. This indicates that if the system switches to the electric power-dominant operating mode at the current moment, then in the following... The A-CAES system must always operate in the power-dominant mode within a continuous period of time to avoid frequent switching to the power-thermal co-operation mode.

[0072] In one embodiment, the state of charge constraint includes a first state of charge constraint and a second state of charge constraint, wherein: The first state of charge constraint is used to constrain the fixed range of the first state of charge of the A-CAES system under different operating modes; The second state of charge constraint is used to constrain the fixed range corresponding to the second state of charge of the A-CAES system in the electrothermal co-operation mode, and the dynamic range determined based on the first state of charge in the power-dominated operation mode.

[0073] Specifically, the range of the state of charge (SOC) of the A-CAES system differs depending on its operating mode. Therefore, in this embodiment of the invention, a SOC constraint is constructed to constrain the range of SOC of the A-CAES system operating in different modes. This SOC constraint includes a first SOC constraint and a second SOC constraint, wherein the first SOC constraint is shown in equation (13), which is: .

[0074] The first state of charge constraint is used to constrain the fixed range of the first state of charge of the A-CAES system under different operating modes. That is, regardless of whether the A-CAES system is operating in the electrothermal co-operation mode or the power-based operation mode, the range of the first state of charge is always [0,1], which ensures that the air quality stored in the gas storage is always kept within the normal range.

[0075] The second charge state constraint is shown in equation (14), which is: .

[0076] in, and All represent constants, and when the A-CAES system operates in electrothermal synergy mode, that is... When the value is 0, the second state-of-charge constraint can be converted to ,in, ,and Therefore, when the A-CAES system operates in electrothermal co-operation mode, this second state-of-charge constraint can be converted into... That is, the second state of charge constraint is used to ensure that the range of the second state of charge of the A-CAES system in the electrothermal co-operation mode is always [0,1], which means ensuring that the quality of the heat transfer oil stored in the high-temperature heat storage tank is within the normal range. When the A-CAES system operates in the electric power-dominated operation mode, that is... When the value is 1, the second state-of-charge constraint can be converted to That is, the range of the second state of charge is related to the value of the first state of charge at the current moment. This means that if the A-CAES system continues to discharge, the mass of heat transfer oil stored in the high-temperature thermal storage tank must be sufficient to support the A-CAES system's discharge until the air in the gas storage tank is depleted. This means that if the A-CAES system continues to be charged, the high-temperature heat storage tank needs to reserve enough space to absorb the high-temperature heat transfer oil after the off-peak electricity heat exchange, until the gas storage tank is full of air.

[0077] In one embodiment, the operating state constraints include mutual exclusion constraints for charge / discharge states, mutual exclusion constraints for supplementary heating conditions, and mutual exclusion constraints for operating modes. Specifically, the mutual exclusion constraints for charge / discharge states prevent the A-CAES system from operating simultaneously in both charging and discharging states; the mutual exclusion constraints for supplementary heating conditions prevent the A-CAES system from operating simultaneously in both electric supplementary heating and external heating conditions; and the mutual exclusion constraints for operating modes prevent the A-CAES system from operating simultaneously in both electric-thermal synergistic operation mode and electric-dominant operation mode.

[0078] Specifically, the operating state constraint is used to constrain the mutual exclusion constraints of the A-CAES system during multi-energy supply. This operating state constraint includes mutual exclusion constraints for charging / discharging states, mutual exclusion constraints for supplementary heating conditions, and mutual exclusion constraints for operating modes, wherein: The charge / discharge state mutual exclusion constraint is used to prevent the A-CAES system from operating in both the charging and discharging states simultaneously. The charge / discharge state mutual exclusion constraint is shown in equation (15), which is: .

[0079] The mutual exclusion constraint for supplementary heating and external heating modes is used to restrict the A-CAES system from operating simultaneously in both electric supplementary heating and external heating modes. This mutual exclusion constraint for supplementary heating and external heating modes is shown in equation (16), which is: .

[0080] The mutual exclusion constraint of the operating modes is used to restrict the A-CAES system from operating in both the electrothermal synergy mode and the power-dominant mode simultaneously. This mutual exclusion constraint of the operating modes is shown in equation (17), which is: .

[0081] In one embodiment, determining the multi-energy co-generation scheduling optimization strategy for the A-CAES system based on all operational characteristics and the operational boundaries includes: Input all operating characteristics and the operating boundary into the solver to obtain the A-CAES system multi-energy supply scheduling optimization strategy output by the solver.

[0082] Specifically, all operational characteristics and operational boundaries collectively constitute the A-CAES system multi-energy supply scheduling model, which adopts a mixed-integer linear programming framework. The solver is a software component used to solve specific types of mathematical optimization problems. The solver receives mathematical models defining problems such as linear programming, integer programming, and nonlinear programming, and uses advanced algorithms to automatically search for and return the optimal or near-optimal solution to the model. In this embodiment of the invention, all operational characteristics and the operational boundaries are input into the solver to obtain the optimal solution for the A-CAES system multi-energy supply scheduling optimization strategy, guiding the optimized operation of the A-CAES system multi-energy supply scheduling. The multi-energy supply scheduling optimization strategy of the A-CAES system includes the charging and discharging power command of the A-CAES system at each time, the power command of the electric heating system, the flow command of the external heating system, and the parameters involved under different operating conditions. Among them, the charging and discharging power command at each time includes the charging power and discharging power at each time. By inputting the charging and discharging power command at each time into the control system corresponding to the A-CAES system, the charging and discharging behavior of the A-CAES system at each time can be controlled. The power command of the electric heating system includes the electric heating power. By inputting the power command of the electric heating system into the control system corresponding to the A-CAES system, the input power of the electric heating system at each time can be controlled. The flow command of the external heating system includes the mass flow rate of water when providing external heating. By inputting the flow command of the external heating system into the control system corresponding to the A-CAES system, the hot water flow rate of the external heating system can be controlled. The parameters involved under different operating conditions are the parameters involved in equations (1) to (17).

[0083] Optionally, the solver can be a commercial solver such as Gurobi, Cplex, or COPT, and this embodiment of the invention does not limit this.

[0084] In this embodiment of the invention, a mixed-integer linear programming framework is used to construct the multi-energy supply scheduling model of the entire A-CAES system, which effectively balances the accuracy and complexity of the model and has the potential to be deployed in actual engineering applications.

[0085] The following describes the adiabatic compressed air energy storage multi-energy supply scheduling device provided by the present invention. The adiabatic compressed air energy storage multi-energy supply scheduling device described below can be referred to in correspondence with the adiabatic compressed air energy storage multi-energy supply scheduling method described above.

[0086] This invention also provides an adiabatic compressed air energy storage multi-energy supply scheduling device. Figure 3 This is a schematic diagram of the structure of the adiabatic compressed air energy storage multi-energy supply scheduling device provided in an embodiment of the present invention, as shown below. Figure 3 As shown, the adiabatic compressed air energy storage multi-energy supply scheduling device 300 includes: a first construction module 310, a second construction module 320 and a first determination module 330.

[0087] The first construction module 310 is used to construct the operating characteristics corresponding to the charging and discharging conditions, the electric heating conditions, and the external heating conditions. The operating characteristics are used to characterize the change of the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions. The target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank. The second construction module 320 is used to construct the operating boundary of the A-CAES system when multiple energy sources are supplied simultaneously; the operating boundary is used to characterize the differentiated operating constraints of the A-CAES system under different operating modes. The first determining module 330 is used to determine the multi-energy supply scheduling optimization strategy of the A-CAES system based on all operating characteristics and the operating boundaries.

[0088] The adiabatic compressed air energy storage multi-energy supply scheduling device provided in this embodiment of the invention determines the target state of charge (SOC) of the A-CAES system based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank. The target SOC characterizes the air storage and heat transfer oil storage conditions in the A-CAES system. The operating characteristics corresponding to the charging and discharging conditions, electric heating conditions, and external heating conditions are constructed respectively. The operating boundary of the A-CAES system during multi-energy supply is also constructed. Finally, based on all operating characteristics and operating boundaries, the multi-energy supply scheduling optimization strategy of the A-CAES system is determined. In this embodiment of the invention, by constructing the operating characteristics of different operating conditions, the changes in the target state of charge of the A-CAES system under charging and discharging conditions, electric heating conditions, and external heating conditions are comprehensively characterized. By constructing operating boundaries, the differentiated operating constraints of the A-CAES system under different operating modes are comprehensively characterized. This solves the problem of incomplete and low-accuracy characterization of operating characteristics and differentiated operating boundaries under different modes caused by frequent changes in multiple operating conditions. Then, based on the comprehensively characterized operating characteristics and operating boundaries, a scheduling optimization strategy is determined to improve the accuracy of multi-energy cogeneration scheduling.

[0089] Optionally, the target state of charge includes a first state of charge and a second state of charge.

[0090] Optionally, the first building module 310 is specifically used for: Based on the current air quality of the gas storage facility, the minimum air quality of the gas storage facility, and the air quality difference of the gas storage facility, the first state of charge of the A-CAES system at the current moment is determined; the first state of charge is used to characterize the air storage status of the gas storage facility corresponding to the A-CAES system. Based on the current heat transfer oil mass of the high-temperature thermal storage tank, the minimum heat transfer oil mass of the high-temperature thermal storage tank, and the difference in heat transfer oil mass of the high-temperature thermal storage tank, the second state of charge of the A-CAES system at the current moment is determined; the second state of charge is used to characterize the heat transfer oil storage status of the high-temperature thermal storage tank corresponding to the A-CAES system.

[0091] Optionally, the adiabatic compressed air energy storage multi-energy supply scheduling device 300 further includes a second determining module, which is specifically used for: The air quality of the gas storage facility at the current moment is determined based on the previous moment's air quality, changes in charging air quality, and changes in discharging air quality. Based on the previous moment's data on the heat transfer oil mass of the high-temperature heat storage tank, the change in the heat transfer oil mass during charging, the change in the heat transfer oil mass during discharging, the change in the heat transfer oil mass during electric heating, and the change in the heat transfer oil mass during external heating, the current moment's heat transfer oil mass is determined.

[0092] Optionally, the operating characteristics corresponding to the charging and discharging conditions include: charging operation sub-characteristics and discharging operation sub-characteristics, wherein: The charging operation sub-characteristics are used to characterize the correlation between the change in charging air mass and the charging power under charging conditions, as well as the correlation between the change in charging heat transfer oil mass and the charging power. The discharge operation sub-characteristics are used to characterize the correlation between the change in discharge air mass and discharge power under discharge conditions, as well as the correlation between the change in discharge heat transfer oil mass and discharge power.

[0093] Optionally, the operating characteristics corresponding to the electric heating condition are used to characterize the correlation between the change in the mass of the electric heating heat transfer oil and the power of the electric heating system under the electric heating condition.

[0094] Optionally, the operating characteristics corresponding to the external heating condition are used to characterize the correlation between the change in the mass of the external heating heat transfer oil and the mass flow rate of the external hot water under the external heating condition. The operating characteristics corresponding to the external heating condition are determined based on the change in the mass of the external heating heat transfer oil, the mass flow rate of the external hot water, the temperature of the heat transfer oil, the water temperature, the isobaric specific heat capacity of the heat transfer oil and water, the heat exchange efficiency of the oil-water heat exchanger, and the unit scheduling time.

[0095] Optionally, the operating boundaries include charge / discharge constraints, electric heating constraints, external heating constraints, minimum operating time constraints, state of charge constraints, and operating state constraints, wherein: The charge and discharge constraints are used to characterize the charge and discharge power range of the A-CAES system when multiple energy sources are supplied simultaneously. The electric heating constraint is used to characterize the range of electric heating power when the A-CAES system is used for multi-energy supply. The external heating constraint is used to characterize the water mass flow rate range when the A-CAES system is used for multi-energy combined supply. The minimum running time constraint is used to characterize the range of the shortest running time of the A-CAES system in different operating modes; The state of charge constraint is used to characterize the range of the state of charge of the A-CAES system in different operating modes. The operational state constraints are used to characterize the operational mutual exclusion constraints of the A-CAES system when multiple energy sources are supplied simultaneously.

[0096] Optionally, the state of charge constraint includes a first state of charge constraint and a second state of charge constraint, wherein: The first state of charge constraint is used to constrain the fixed range of the first state of charge of the A-CAES system under different operating modes; The second state of charge constraint is used to constrain the fixed range corresponding to the second state of charge of the A-CAES system in the electrothermal co-operation mode, and the dynamic range determined based on the first state of charge in the power-dominated operation mode.

[0097] Optionally, the operating state constraints include mutual exclusion constraints for charging and discharging states, mutual exclusion constraints for supplementary heating and heat supply conditions, and mutual exclusion constraints for operating modes. The mutual exclusion constraints for charging and discharging states are used to restrict the A-CAES system from operating in both charging and discharging states simultaneously. The mutual exclusion constraints for supplementary heating and heat supply conditions are used to restrict the A-CAES system from operating in both electric supplementary heating and external heating conditions simultaneously. The mutual exclusion constraints for operating modes are used to restrict the A-CAES system from operating in both electric-thermal synergistic operation mode and electric-dominant operation mode simultaneously.

[0098] Optionally, the charge and discharge constraints include charging electron constraints and discharging electron constraints, wherein the charging electron constraints are used to constrain the charging power range of the A-CAES system, and the discharging electron constraints are used to constrain the discharging power range of the A-CAES system.

[0099] Optionally, the first determining module 330 is specifically used for: Input all operating characteristics and the operating boundary into the solver to obtain the A-CAES system multi-energy supply scheduling optimization strategy output by the solver.

[0100] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present invention, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other through the communications bus 440. The processor 410 can call logic instructions in the memory 430 to execute a multi-energy supply scheduling method for adiabatic compressed air energy storage (A-CAES). This method includes: constructing operating characteristics corresponding to charging / discharging conditions, electric heating conditions, and external heating conditions; the operating characteristics characterize the changes in the target state of charge (SOC) of the A-CAES system under different operating conditions; the target SOC characterizes the air storage and heat transfer oil storage conditions in the A-CAES system, and the target SOC is determined based on the air quality in the gas storage tank and the heat transfer oil quality in the high-temperature heat storage tank; constructing the operating boundary for multi-energy supply of the A-CAES system; the operating boundary characterizes the differentiated operating constraints of the A-CAES system under different operating modes; and determining a multi-energy supply scheduling optimization strategy for the A-CAES system based on all operating characteristics and the operating boundary.

[0101] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0102] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the adiabatic compressed air energy storage multi-energy supply scheduling method provided by the above methods. This method includes: constructing the operating characteristics corresponding to charging and discharging conditions, electric heating conditions, and external heating conditions; the operating characteristics are used to characterize the change of the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions; the target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank; constructing the operating boundary of the A-CAES system for multi-energy supply; the operating boundary is used to characterize the differentiated operating constraints of the A-CAES system under different operating modes; and determining the multi-energy supply scheduling optimization strategy of the A-CAES system based on all operating characteristics and the operating boundary.

[0103] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the multi-energy co-generation scheduling method for adiabatic compressed air energy storage provided by the above methods. The method includes: constructing operating characteristics corresponding to charging and discharging conditions, electric heating conditions, and external heating conditions; the operating characteristics are used to characterize the changes in the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions; the target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality of the gas storage tank and the heat transfer oil quality of the high-temperature heat storage tank; constructing the operating boundary of the A-CAES system for multi-energy co-generation; the operating boundary is used to characterize the differentiated operating constraints of the A-CAES system under different operating modes; and determining the multi-energy co-generation scheduling optimization strategy of the A-CAES system based on all operating characteristics and the operating boundary.

[0104] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for scheduling multi-energy supply using adiabatic compressed air energy storage, characterized in that, include: Establish the corresponding operating characteristics for charging / discharging, electric heating, and external heating conditions; The operating characteristics are used to characterize the changes in the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions. The target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality in the gas storage tank and the heat transfer oil quality in the high-temperature heat storage tank. Construct the operational boundary of the A-CAES system when it is used for multi-energy supply; the operational boundary is used to characterize the differentiated operational constraints of the A-CAES system under different operating modes. Based on all operational characteristics and the aforementioned operational boundaries, a multi-energy supply scheduling optimization strategy for the A-CAES system is determined.

2. The method for multi-energy supply scheduling of adiabatic compressed air energy storage according to claim 1, characterized in that, The target state of charge includes a first state of charge and a second state of charge. The target state of charge is determined based on the following steps: Based on the current air quality of the gas storage, the minimum air quality of the gas storage, and the air quality difference of the gas storage, determine the first state of charge of the A-CAES system at the current moment; The first state of charge is used to characterize the air storage status of the gas storage tank corresponding to the A-CAES system; Based on the current heat transfer oil mass of the high-temperature thermal storage tank, the minimum heat transfer oil mass of the high-temperature thermal storage tank, and the difference in heat transfer oil mass of the high-temperature thermal storage tank, the second state of charge of the A-CAES system at the current moment is determined; the second state of charge is used to characterize the heat transfer oil storage status of the high-temperature thermal storage tank corresponding to the A-CAES system.

3. The method for multi-energy supply scheduling of adiabatic compressed air energy storage according to claim 2, characterized in that, The method further includes: The air quality of the gas storage facility at the current moment is determined based on the previous moment's air quality, changes in charging air quality, and changes in discharging air quality. Based on the previous moment's data on the heat transfer oil mass of the high-temperature heat storage tank, the change in the heat transfer oil mass during charging, the change in the heat transfer oil mass during discharging, the change in the heat transfer oil mass during electric heating, and the change in the heat transfer oil mass during external heating, the current moment's heat transfer oil mass is determined.

4. The method for cogeneration and scheduling of adiabatic compressed air energy storage according to claim 1, characterized in that, The operating characteristics corresponding to the charging and discharging conditions include: charging operation sub-characteristics and discharging operation sub-characteristics, wherein: The charging operation sub-characteristics are used to characterize the correlation between the change in charging air mass and the charging power under charging conditions, as well as the correlation between the change in charging heat transfer oil mass and the charging power. The discharge operation sub-characteristics are used to characterize the correlation between the change in discharge air mass and discharge power under discharge conditions, as well as the correlation between the change in discharge heat transfer oil mass and discharge power.

5. The method for multi-energy supply scheduling of adiabatic compressed air energy storage according to claim 1, characterized in that, The operating characteristics corresponding to the electric heating condition are used to characterize the correlation between the change in the mass of the electric heating heat transfer oil and the power of the electric heating system under the electric heating condition.

6. The method for cogeneration and scheduling of adiabatic compressed air energy storage according to claim 1, characterized in that, The operating characteristics corresponding to the external heating condition are used to characterize the correlation between the change in the mass of the external heating heat transfer oil and the mass flow rate of the external heating hot water under the external heating condition. The operating characteristics corresponding to the external heating condition are determined based on the change in the mass of the external heating heat transfer oil, the mass flow rate of the external heating hot water, the temperature of the heat transfer oil, the water temperature, the specific heat capacity of the heat transfer oil and water at constant pressure, the heat exchange efficiency of the oil-water heat exchanger, and the unit scheduling time.

7. The method for cogeneration and scheduling of adiabatic compressed air energy storage according to claim 1, characterized in that, The operating boundaries include charge / discharge constraints, electric heating constraints, external heating constraints, minimum operating time constraints, state of charge constraints, and operating state constraints, wherein: The charge and discharge constraints are used to characterize the charge and discharge power range of the A-CAES system when multiple energy sources are supplied simultaneously. The electric heating constraint is used to characterize the range of electric heating power when the A-CAES system is used for multi-energy supply. The external heating constraint is used to characterize the water mass flow rate range when the A-CAES system is used for multi-energy combined supply. The minimum running time constraint is used to characterize the range of the shortest running time of the A-CAES system in different operating modes; The state of charge constraint is used to characterize the range of the state of charge of the A-CAES system in different operating modes. The operational state constraints are used to characterize the operational mutual exclusion constraints of the A-CAES system when multiple energy sources are supplied simultaneously.

8. The method for cogeneration and scheduling of adiabatic compressed air energy storage according to claim 7, characterized in that, The state of charge constraints include a first state of charge constraint and a second state of charge constraint, wherein: The first state of charge constraint is used to constrain the fixed range of the first state of charge of the A-CAES system under different operating modes; The second state of charge constraint is used to constrain the fixed range corresponding to the second state of charge of the A-CAES system in the electrothermal co-operation mode, and the dynamic range determined based on the first state of charge in the power-dominated operation mode.

9. The method for cogeneration and scheduling of adiabatic compressed air energy storage according to claim 7, characterized in that, The operating state constraints include mutual exclusion constraints for charge / discharge states, mutual exclusion constraints for supplementary heating conditions, and mutual exclusion constraints for operating modes. Specifically, the mutual exclusion constraints for charge / discharge states prevent the A-CAES system from operating in both charging and discharging states simultaneously; the mutual exclusion constraints for supplementary heating conditions prevent the A-CAES system from operating in both electric supplementary heating and external heating conditions simultaneously; and the mutual exclusion constraints for operating modes prevent the A-CAES system from operating in both electric-thermal synergistic operation mode and electric-dominant operation mode simultaneously.

10. The method for scheduling multi-energy supply using adiabatic compressed air energy storage according to claim 7, characterized in that, The charge and discharge constraints include charging electron constraints and discharging electron constraints. The charging electron constraints are used to constrain the charging power range of the A-CAES system, and the discharging electron constraints are used to constrain the discharging power range of the A-CAES system.

11. The method for cogeneration and scheduling of adiabatic compressed air energy storage according to any one of claims 1-10, characterized in that, The determination of the multi-energy co-generation scheduling optimization strategy for the A-CAES system based on all operational characteristics and the operational boundaries includes: Input all operating characteristics and the operating boundary into the solver to obtain the A-CAES system multi-energy supply scheduling optimization strategy output by the solver.

12. A thermally adiabatic compressed air energy storage multi-energy supply and dispatching device, characterized in that, include: The first construction module is used to construct the corresponding operating characteristics of charging and discharging conditions, electric heating conditions, and external heating conditions. The operating characteristics are used to characterize the changes in the target state of charge of the adiabatic compressed air energy storage A-CAES system under different operating conditions. The target state of charge is used to characterize the air storage and heat transfer oil storage conditions in the A-CAES system, and the target state of charge is determined based on the air quality in the gas storage tank and the heat transfer oil quality in the high-temperature heat storage tank. The second construction module is used to construct the operating boundary of the A-CAES system when multiple energy sources are supplied simultaneously; the operating boundary is used to characterize the differentiated operating constraints of the A-CAES system under different operating modes. The first determining module is used to determine the multi-energy supply scheduling optimization strategy of the A-CAES system based on all operating characteristics and the operating boundaries.

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