Constant volume site selection and evaluation method for compressed air energy storage system

Abstract

The invention relates to a compressed air energy storage system constant volume site selection and evaluation method, and the method comprises the steps: building a wind and light storage system operation model based on a power distribution network system and a CAES system model; determining operation constraint conditions of each device and a power distribution network system and a system total cost objective function through a wind and light storage system operation model so as to construct a CAES constant volume site selection model; selecting different nodes in the power distribution network system according to the plurality of constant-capacity site selection strategies, and configuring a CAES system, so as to solve a system total cost objective function of each constant-capacity site selection strategy according to a CAES constant-capacity site selection model, and evaluating each constant-capacity site selection strategy to obtain the loss-of-load economic loss of the power distribution network system after a fault occurs, and determining a target constant-volume site selection strategy in the plurality of constant-volume site selection strategies so as to calculate the target configuration capacity and / or the target configuration position of the corresponding CAES system. Therefore, the problem that in the prior art, it is difficult to reasonably and effectively carry out constant volume site selection on stored energy in a novel electric power system is solved.

Description

Technical Field

[0001] The present application relates to the field of new energy technologies, and in particular to a method for determining the capacity, site selection and evaluation of a compressed air energy storage system. Background Art

[0002] In recent years, new energy power generation technologies represented by wind power and photovoltaic power generation have developed rapidly. However, the intermittent nature and uncertainty of wind and photovoltaic power generation have brought unprecedented challenges to the operation of the power system. To meet this challenge, the power system not only needs to accurately predict wind and photovoltaic power generation, but also needs to reserve sufficient backup resources.

[0003] As a flexible resource, energy storage technology can operate in coordination with wind and photovoltaic power generation to improve the dispatchability of renewable energy power generation, smooth output, and reduce wind and solar power curtailment. At the same time, improper configuration of energy storage scale and location selection will result in loss of economic benefits.

[0004] However, existing technologies cannot reasonably and effectively configure the capacity of the energy storage system and select the geographical location under the premise of ensuring the operation of the system, making it difficult to improve the economy of the system, which urgently needs to be solved. Summary of the invention

[0005] The present application provides a method for sizing and siting a compressed air energy storage system and for evaluating the same, in order to solve the problem that the prior art is difficult to reasonably and effectively sizing and siting energy storage in a new power system.

[0006] The first embodiment of the present application provides a method for determining the capacity of a compressed air energy storage system and selecting a site and evaluating the capacity of the compressed air energy storage system, comprising the following steps: based on a preset distribution network system and CAES (Compressed Air Energy Storage System) A wind-solar-storage system model is constructed to construct a wind-solar-storage system operation model for a target area; the operation constraints and the system total cost objective function corresponding to each device in the CAES system model and the distribution network system are determined through the wind-solar-storage system operation model, so as to construct a CAES fixed-capacity site selection model according to the system total cost objective function and the operation constraints; different nodes are selected in the distribution network system according to a plurality of preset fixed-capacity site selection strategies, and the CAES system is configured through the different nodes, so as to solve the system total cost objective function corresponding to each of the plurality of fixed-capacity site selection strategies according to the CAES fixed-capacity site selection model, and each fixed-capacity site selection strategy is evaluated according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed-capacity site selection strategy after a fault occurs in the distribution network system, and a target fixed-capacity site selection strategy among the plurality of fixed-capacity site selection strategies is determined according to the load loss economic loss, and the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed-capacity site selection strategy is calculated.

[0007] Optionally, in one embodiment of the present application, the operation constraints and the system total cost objective function corresponding to each device in the CAES system model and the distribution network system are determined through the wind-solar-storage system operation model, so as to construct a CAES fixed capacity site selection model according to the system total cost objective function and the operation constraints, including: solving the equipment capacity corresponding to each device in the wind-solar-storage system based on a preset optimization solution strategy, and calculating the equipment investment and operation and maintenance cost, electricity purchase and sales cost and wind and solar abandonment penalty of the CAES system according to the equipment capacity, so as to construct the system total cost objective function corresponding to the CAES system through the equipment investment and operation and maintenance cost, the electricity purchase and sales cost and the wind and solar abandonment penalty, wherein the equipment capacity includes the installed capacity of photovoltaic and wind turbines, the total power of compressors, the total power of expanders and the capacity of gas tanks; determining the line loss constraints of the CAES system connected to different locations of the distribution network, and calculating the line loss of the CAES system through the line loss constraints; calculating the time t The compression power of the CAES system, the expansion side power generation of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power and the sum of the wind and solar power abandonment, and based on the discharge power of the CAES system, the charging power of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power, the load value and the sum of the wind and solar power abandonment, determine the electric balance constraint of the CAES system in the operation constraint condition; obtain the energy storage state variable and the energy release state variable of the CAES system, and establish the coupling constraint of the CAES system in the operation constraint condition according to the energy storage state variable and the energy release state variable; obtain the lower limit and upper limit of the gas tank capacity of the CAES system, and determine the gas storage capacity constraint of the CAES system in the operation constraint condition based on the lower limit and upper limit of the gas tank capacity; construct the CAES fixed capacity site selection model based on the line loss constraint, the electric balance constraint, the coupling constraint, the gas storage capacity constraint and the system total cost objective function.

[0008] Optionally, in one embodiment of the present application, before constructing the wind, solar and storage system operation model of the target area based on the preset distribution network system and the CAES system model, it also includes: modeling the electric motor, multi-stage compressor, gas storage tank, multi-stage expander and generator in the CAES system respectively to construct the CAES system model.

[0009] Optionally, in one embodiment of the present application, the load loss economic loss corresponding to each fixed-capacity site selection strategy after a fault occurs in the distribution network system is obtained, and a target fixed-capacity site selection strategy among multiple fixed-capacity site selection strategies is determined based on the load loss economic loss, including: adding interference to the CAES system, and determining whether the CAES system meets a preset power supply fault condition, and when the CAES system meets the power supply fault condition, calculating the hourly load loss of the CAES system at time t; calculating the load loss economic loss of the CAES system based on the hourly load loss, a preset load loss penalty unit price and load loss duration, so as to determine the target fixed-capacity site selection strategy corresponding to the CAES system through the load loss economic loss.

[0010] Optionally, in one embodiment of the present application, the mathematical expression of the load loss economic loss of the CAES system is:

[0011]

[0012] Among them, C a Indicates the economic loss of load loss; represents the time-loss load of the CAES system at time t; C loss represents the load loss penalty unit price; T represents the load loss duration.

[0013] The second aspect of the present application provides a compressed air energy storage system capacity site selection and evaluation device, including: a first modeling module, which is used to construct a wind-solar-storage system operation model of a target area based on a preset distribution network system and a CAES system model; a second modeling module, which is used to determine the operation constraints corresponding to each device in the CAES system model and the distribution network system and the system total cost objective function through the wind-solar-storage system operation model, so as to construct a CAES capacity site selection model according to the system total cost objective function and the operation constraints; an evaluation module, which is used to determine the distribution network system according to a plurality of preset capacity site selection strategies. Different nodes are selected, and a CAES system is configured through the different nodes, so as to solve the system total cost objective function corresponding to each of the multiple fixed capacity location selection strategies according to the CAES fixed capacity location selection model, and each fixed capacity location selection strategy is evaluated according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed capacity location selection strategy after a fault occurs in the distribution network system, and a target fixed capacity location selection strategy among the multiple fixed capacity location selection strategies is determined according to the load loss economic loss, and the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed capacity location selection strategy is calculated.

[0014] Optionally, in one embodiment of the present application, the second modeling module includes: a first calculation unit, which is used to solve the equipment capacity corresponding to each device in the wind, solar and storage system based on a preset optimization solution strategy, and calculate the equipment investment and operation and maintenance costs, electricity purchase and sales costs and wind and solar power abandonment penalties of the CAES system according to the equipment capacity, so as to construct the system total cost objective function corresponding to the CAES system through the equipment investment and operation and maintenance costs, the electricity purchase and sales costs and the wind and solar power abandonment penalties, wherein the equipment capacity includes the installed capacity of photovoltaic and wind turbines, the total power of compressors, the total power of expanders and the capacity of gas tanks; a first constraint unit, which is used to determine the line loss constraints of the CAES system connected to different locations in the distribution network, and calculate the line loss of the CAES system through the line loss constraints; a second constraint unit, which is used to calculate the compression power of the CAES system, the expansion side power generation of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power and the wind power abandonment penalties at time t. and the sum of the abandoned wind and solar power, and based on the discharge power of the CAES system, the charging power of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power, the load value and the sum of the abandoned wind and solar power, determine the electric balance constraint of the CAES system in the operating constraint condition; a third constraint unit, used to obtain the energy storage state variable and the energy release state variable of the CAES system, and establish the coupling constraint of the CAES system in the operating constraint condition according to the energy storage state variable and the energy release state variable; a fourth constraint unit, used to obtain the lower limit and the upper limit of the gas tank capacity of the CAES system, and determine the gas storage capacity constraint of the CAES system in the operating constraint condition based on the lower limit and the upper limit of the gas tank capacity; a construction unit, used to construct the CAES fixed capacity site selection model based on the line loss constraint, the electric balance constraint, the coupling constraint, the gas storage capacity constraint and the system total cost objective function.

[0015] Optionally, in one embodiment of the present application, it also includes: a third modeling module, which is used to model the motor, multi-stage compressor, gas storage tank, multi-stage expander and generator in the CAES system respectively before building the wind, solar and storage system operation model of the target area based on the preset distribution network system and the CAES system model to build the CAES system model.

[0016] Optionally, in one embodiment of the present application, the evaluation module includes: an interference unit, used to add interference to the CAES system, and determine whether the CAES system meets a preset power supply fault condition, and when the CAES system meets the power supply fault condition, calculate the hourly load loss of the CAES system at time t; a determination unit, used to calculate the load loss economic loss of the CAES system based on the hourly load loss, a preset load loss penalty unit price and load loss duration, so as to determine the target capacity fixed-site selection strategy corresponding to the CAES system through the load loss economic loss.

[0017] Optionally, in one embodiment of the present application, the mathematical expression of the load loss economic loss of the CAES system is:

[0018]

[0019] Among them, C a Indicates the economic loss of load loss; represents the time-loss load of the CAES system at time t; C loss represents the load loss penalty unit price; T represents the load loss duration.

[0020] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for determining the capacity, site selection, and evaluation of a compressed air energy storage system as described in the above embodiment.

[0021] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned method for determining the capacity, site selection and evaluation of a compressed air energy storage system.

[0022] The fifth aspect of the present application provides a computer program product, including a computer program, which is executed to implement the above-mentioned compressed air energy storage system capacity determination site selection and evaluation method.

[0023] Therefore, the embodiments of the present application have the following beneficial effects:

[0024] The embodiments of the present application can construct a wind, solar and storage system operation model of the target area based on a preset distribution network system and CAES system model; determine the operation constraints and the system total cost objective function corresponding to each device and distribution network system in the CAES system model through the wind, solar and storage system operation model, so as to construct a CAES fixed capacity site selection model according to the system total cost objective function and the operation constraints; select different nodes in the distribution network system according to multiple preset fixed capacity site selection strategies, and configure the CAES system through different nodes, so as to solve the system total cost objective function corresponding to each fixed capacity site selection strategy in multiple fixed capacity site selection strategies according to the CAES fixed capacity site selection model, and evaluate each fixed capacity site selection strategy according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed capacity site selection strategy after a fault occurs in the distribution network system, and determine the target fixed capacity site selection strategy among the multiple fixed capacity site selection strategies according to the load loss economic loss, and calculate the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed capacity site selection strategy, thereby ensuring the stability and reliability of the power operation after connecting to the compressed air energy storage system, and effectively improving the economy of the power system. This solves the problem that the existing technology is difficult to reasonably and effectively determine the capacity and site of energy storage in new power systems.

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

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

[0027] Figure 1 A flowchart of a method for determining the capacity, site selection and evaluation of a compressed air energy storage system provided according to an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a physical model framework of a CAES capacity location selection model based on a distribution network provided for one embodiment of the present application;

[0029] Figure 3 A working schematic diagram of a wind-solar coupled CAES system model provided for one embodiment of the present application;

[0030] Figure 4 A schematic diagram of a time sequence change of an electric load provided for an embodiment of the present application;

[0031] Figure 5 A schematic diagram of a fixed capacity site selection process provided for an embodiment of the present application;

[0032] Figure 6This is an example diagram of a device for determining the capacity, site selection and evaluation of a compressed air energy storage system according to an embodiment of the present application;

[0033] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0034] Among them, 10-compressed air energy storage system capacity determination site selection and evaluation device; 100-first modeling module, 200-second modeling module, 300-evaluation module; 701-memory, 702-processor, 703-communication interface. DETAILED DESCRIPTION

[0035] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0036] The following describes the method for sizing and site selection and evaluation of a compressed air energy storage system according to an embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a method for sizing and site selection and evaluation of a compressed air energy storage system. In this method, a wind-solar-storage system operation model of the target area is constructed based on a preset distribution network system and CAES system model; the operation constraints corresponding to each device and distribution network system in the CAES system model and the system total cost objective function are determined through the wind-solar-storage system operation model, so as to construct a CAES sizing and site selection model according to the system total cost objective function and the operation constraints; different nodes are selected in the distribution network system according to the preset multiple sizing and site selection strategies, and the CAES system is configured through different nodes. , in order to solve the system total cost objective function corresponding to each of the multiple fixed capacity location selection strategies according to the CAES fixed capacity location selection model, and evaluate each fixed capacity location selection strategy according to the system total cost objective function, so as to obtain the load loss economic loss corresponding to each fixed capacity location selection strategy after the distribution network system fails, and determine the target fixed capacity location selection strategy among the multiple fixed capacity location selection strategies according to the load loss economic loss, and calculate the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed capacity location selection strategy, thereby ensuring the stability and reliability of the power operation after the compressed air energy storage system is connected, and effectively improving the economy of the power system. Therefore, the problem that the existing technology is difficult to reasonably and effectively perform fixed capacity location selection for energy storage in new power systems is solved.

[0037] Specifically, Figure 1 A flowchart of a method for determining the capacity, site selection and evaluation of a compressed air energy storage system provided in an embodiment of the present application.

[0038] like Figure 1As shown, the method for determining the capacity of a compressed air energy storage system and selecting a site and evaluating the compressed air energy storage system includes the following steps:

[0039] In step S101, a wind-solar-storage system operation model of a target area is constructed based on a preset distribution network system and CAES system model.

[0040] The embodiment of the present application can first construct a wind-solar-storage system operation model (i.e., a CAES fixed capacity site selection model physical model) of the target area through wind turbines, photovoltaic power generation systems, IEEE33 node distribution networks, and CAES system models, such as Figure 2 shown.

[0041] Specifically, in the embodiments of the present application, wind and photovoltaic power generation can be predicted based on the historical power generation data of the target area, and the wind, photovoltaic and storage system operation model generates electricity according to the historical data of wind speed, light intensity and ambient temperature respectively; secondly, the output upper limit of the wind, photovoltaic and storage system operation model is determined by the uncertain wind and solar energy resources, and the electricity generated by wind and solar energy can be input into the power grid to supply the power load in the distribution network, or stored in the CAES system. The part that is not absorbed is discarded, and the penalty for abandoning wind and photovoltaic power is taken into consideration, thereby generating the cost of abandoned power.

[0042] In addition, the CAES system model can use wind and solar power generation for charging, and can sell electricity to the power grid or purchase electricity from the power grid; the charging and discharging power and gas storage SOC of the CAES system cannot exceed their own upper and lower limits, and the power sent from the wind turbine and photovoltaic panels to the distribution network is not allowed to exceed the capacity of each transmission line; in the embodiment of the present application, the various mathematical expressions of the wind-solar-storage system operation model are as follows:

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050] in, is the wind power generation at time t, in kW; ρ is the density, in kg / m 3 ; R is the radius of the wind wheel, in m; V is the wind speed, in m / s; C pis the wind energy utilization coefficient; λ is the tip speed ratio; β is the blade pitch angle, in degrees; ω r is the angular velocity of the wind wheel, in rad / s; is the photovoltaic power generation, in kW; η is the light source conversion efficiency; S is the photovoltaic panel area, in m 3 ;I t is the light intensity, in kW / m 2 ; is the ambient temperature, in °C; and are the power flowing from the wind turbine and photovoltaic panel to the grid at time t; Formula (6) shows that the power sent from the wind turbine and photovoltaic panel to the grid is not allowed to exceed the capacity T of the transmission line u ; Formula (7) stipulates that wind energy and photovoltaic output cannot exceed wind energy and solar energy resources, where represent the wind energy and solar energy resources at time t respectively.

[0051] Optionally, in one embodiment of the present application, before constructing the wind, solar and storage system operation model of the target area based on the preset distribution network system and CAES system model, it also includes: modeling the electric motor, multi-stage compressor, gas storage tank, multi-stage expander and generator in the CAES system respectively to construct the CAES system model.

[0052] It should be noted that the CAES system model in the embodiment of the present application mainly includes a motor, a multi-stage compressor, a gas storage tank, a multi-stage expander and a generator. Figure 3 shown.

[0053] Specifically, in the charging mode, the embodiment of the present application can use surplus electricity to drive the compressor, and convert part of the unconsumed electricity into high-pressure air stored in the air tank to achieve energy storage; in the discharging mode, the high-pressure air is discharged through the throttle valve used to stabilize the output pressure, and then enters the expander to drive the generator to work.

[0054] In the embodiment of the present application, the mathematical expression of the CAES system model is as follows:

[0055]

[0056]

[0057]

[0058]

[0059] in, represents the charging power (i.e. compression power) of the CAES system at time t, in kW; Ncom is the number of compressor stages; γ and R g are its specific heat capacity and gas constant respectively; is the mass flow rate; T com，out，i and T com，in，i is the inlet and outlet temperature, in °C; T com，out，i represents the outlet temperature of the i-th stage compressor, η ch is the charging efficiency of the CAES system; π com，i is the rated compression ratio of stage i; represents the expansion power (i.e., discharge power) of the CAES system at time t, in kW; N exp is the number of expander stages; is its mass flow rate; T exp，out，i and T exp，in，i is the inlet and outlet temperature in °C; T exp，out，i represents the outlet temperature of the i-th stage expander; η dis is the discharge efficiency of the CAES system; π exp，i It is the rated compression ratio of stage i.

[0060] At present, the traditional CAES system gas tank model is generally modeled on the basis of thermodynamics by calculating the pressure difference after the compression and expansion processes. However, considering that the main function of the CAES system of the embodiment of the present application is the conversion between electric power, the embodiment of the present application can directly use the system capacity change value to establish the gas tank mathematical model, and its mathematical expression is as follows:

[0061]

[0062] Among them, SOC t Indicates the gas storage capacity of the gas tank at time t; is the rated capacity of the CAES system.

[0063] Therefore, the embodiments of the present application provide reliable technical support for the construction of wind-solar-storage system operation model and CAES capacity location model by constructing a CAES system model.

[0064] In step S102, the operation constraints corresponding to each device and distribution network system in the CAES system model and the system total cost objective function are determined through the wind, solar and storage system operation model, so as to construct a CAES capacity selection model according to the system total cost objective function and the operation constraints.

[0065] Furthermore, the embodiments of the present application also need to consider the impact of the grid structure. Configuring the CAES system at different locations will result in a different structure of the entire system. Considering the line loss in the line, configuring the CAES system at different locations in the distribution network will result in different currents in the system, which will affect the final capacity configuration result of the CAES system, and thus cause different system costs of the wind, solar and storage system operation model.

[0066] Therefore, the embodiments of the present application need to consider multiple operating constraints such as line losses and load timing changes, and use minimizing system cost (i.e., the total system cost objective function) as the objective function, so as to establish a fixed-capacity site selection model for the CAES system that takes into account the impact of the grid structure.

[0067] Optionally, in one embodiment of the present application, the operation constraints corresponding to each device and the distribution network system in the CAES system model and the system total cost objective function are determined through the wind, solar and storage system operation model, so as to construct a CAES capacity determination and site selection model according to the system total cost objective function and the operation constraints, including: solving the equipment capacity corresponding to each device in the wind, solar and storage system based on a preset optimization solution strategy, and calculating the equipment investment and operation and maintenance cost, electricity purchase and sales cost and wind and solar abandonment penalty of the CAES system according to the equipment capacity, so as to construct the system total cost objective function corresponding to the CAES system through the equipment investment and operation and maintenance cost, electricity purchase and sales cost and wind and solar abandonment penalty, wherein the equipment capacity includes the installed capacity of photovoltaic and wind turbines, the total power of compressors, the total power of expanders and the capacity of gas storage tanks; determining the line loss constraints for accessing the CAES system at different locations in the distribution network, and calculating the line loss of the CAES system through the line loss constraints. consumption; calculate the compression power of the CAES system, the expansion side power generation of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power and the sum of the wind and solar power abandonment at time t, and determine the electric balance constraint of the CAES system in the operation constraint conditions based on the CAES system discharge power, the CAES system charging power, the wind power generation power, the photovoltaic power generation power, the line loss power, the load value and the sum of the wind and solar power abandonment; obtain the energy storage state variables and the energy release state variables of the CAES system, and establish the coupling constraints of the CAES system in the operation constraint conditions based on the energy storage state variables and the energy release state variables; obtain the lower limit and upper limit of the gas tank capacity of the CAES system, and determine the gas storage capacity constraint of the CAES system in the operation constraint conditions based on the lower limit and upper limit of the gas tank capacity; construct a CAES fixed capacity site selection model based on the line loss constraint, the electric balance constraint, the coupling constraint, the gas storage capacity constraint and the system total cost objective function.

[0068] Those skilled in the art should understand that in the operation of the low-voltage distribution network, it is necessary to pay attention to the changes in the power system flow. There is line loss in the line of the embodiment of the present application, so that the CAES system is configured at different locations, the system structure is different, and the flow when the system is running is different. The change of the flow will affect the line loss, and then cause different system costs. In the embodiment of the present application, the theoretical expression of the line loss is as follows:

[0069]

[0070] Among them, P loss.L It represents the power loss on line L, in kW; I is the effective current of the component, in A; R is the resistance value, in Ω; U is the voltage value, in kV; λ is the power factor; ρ is the resistivity, in Ω·m; l is the length of the line, in m; A is the cross-sectional area, in mm 2 ; P is the load.

[0071] Furthermore, the line loss rate can be used to simplify the calculation of line loss, as shown in the following formula:

[0072] P loss.L =α·P L (14)

[0073] Among them, α is the line loss rate; P L is the power flowing through line L.

[0074] It is understandable that the location of the CAES system is particularly important when considering distribution network line losses. The greater the losses, the larger the capacity of the CAES system configuration, and the higher the system cost.

[0075] Secondly, at any time period, the embodiments of the present application must meet the load demand and ensure the power balance of the CAES system, such as Figure 4 As shown in the figure, the power balance constraint of the CAES fixed capacity site selection model is:

[0076]

[0077] in, It represents the sum of wind and solar power abandoned at time t; represents the load value in the power grid at time t;

[0078] In addition, the charging and discharging of the CAES system can be achieved by compressing and expanding the gas. Subject to the rated power and rated capacity of the CAES system, the mathematical expression of the charging and discharging power limit constraints of the CAES system is as follows:

[0079]

[0080]

[0081] in, Indicates the rated charging or discharging power of the CAES system in kW; is the energy storage state variable of the CAES system, 1 means charging, otherwise 0; It is the energy release state variable of the CAES system, which is 1 during discharge and 0 otherwise.

[0082] Afterwards, the embodiment of the present application also needs to consider the coupling constraints of the CAES system charging and discharging state variables, as shown in the following formula, which is used to ensure that the CAES system does not work in the compression and expansion stages at the same time:

[0083]

[0084] At time t, the gas storage capacity constraint of the CAES system is a constraint condition that reflects the gas storage device in the CAES system. Under normal operating conditions, the gas storage device has a volume capacity limit, and its mathematical expression is as follows:

[0085] η 1 ≤SOC t ≤η 2 (19)

[0086] Among them, η 1 and η 2 The lower and upper limits of the gas tank capacity.

[0087] Combining the above constraints and taking minimizing system cost as the goal, the optimization variable is the capacity of the CAES system, thus constructing the CAES fixed capacity site selection model, as shown in the following formula:

[0088] min C=C I +C e +C loss (20)

[0089] Among them, C is the total cost objective function of the system; C I Investment and maintenance costs for system equipment; C e The cost of purchasing and selling electricity for the system; C loss Punishment for system abandonment of wind and solar power.

[0090] The mathematical expression of the investment and operation and maintenance cost of the above system equipment is:

[0091]

[0092] Where r is the base discount rate; n is the system life; ξ j Q is the proportion of annual equipment operation and maintenance cost to construction cost; j and S jThey represent the planned capacity and unit capacity construction cost of the j-th type of equipment respectively.

[0093] The mathematical expression of the electricity purchase and sales cost of the above system is:

[0094]

[0095] in, and Respectively represent the total amount of electric energy purchased and sold from the CAES system grid, in kWh; c e.in and c e.out They represent the electricity price when purchasing and selling electricity, respectively, in yuan / kWh.

[0096] The mathematical expression of the wind and solar power abandonment penalty for the above system is:

[0097]

[0098] Among them, β w , β PV These are the penalty unit prices for abandoning wind power and abandoning solar power respectively; They are the total amount of wind and solar power abandoned throughout the year respectively.

[0099] Therefore, the embodiments of the present application construct a CAES capacity location selection model by determining the objective function and operation constraints, thereby optimizing the capacity of the CAES system.

[0100] In step S103, different nodes are selected in the distribution network system according to multiple preset fixed-capacity site selection strategies, and the CAES system is configured through different nodes to solve the system total cost objective function corresponding to each of the multiple fixed-capacity site selection strategies according to the CAES fixed-capacity site selection model, and each fixed-capacity site selection strategy is evaluated according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed-capacity site selection strategy after a fault occurs in the distribution network system, and a target fixed-capacity site selection strategy among the multiple fixed-capacity site selection strategies is determined according to the load loss economic loss, and the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed-capacity site selection strategy is calculated.

[0101] Furthermore, the embodiments of the present application can select nodes in the distribution network to configure the CAES system to formulate a node access plan, and compare the system total cost objective function of each plan to obtain at least one of the optimal CAES system capacity (i.e., the target configuration capacity) and the optimal configuration location (i.e., the target configuration location) to establish a CAES fixed capacity site selection model.

[0102] Therefore, the embodiments of the present application can establish and solve a multi-parameter linear programming problem, regard the invariants as parameters, and transform the node capacity optimization configuration problem into a multi-parameter linear programming problem, that is, at which node to configure and how much capacity of the CAES system to configure, such as Figure 5 As shown, the embodiment of the present application can be solved using the Matlab Cplex12.10 solver.

[0103] Optionally, in one embodiment of the present application, the load loss economic loss corresponding to each capacity-fixed site selection strategy after a fault occurs in the distribution network system is obtained, and a target capacity-fixed site selection strategy among multiple capacity-fixed site selection strategies is determined based on the load loss economic loss, including: adding interference to the CAES system, and judging whether the CAES system meets a preset power supply fault condition, and when the CAES system meets the power supply fault condition, calculating the hourly load loss of the CAES system at time t; calculating the load loss economic loss of the CAES system based on the hourly load loss, a preset load loss penalty unit price and load loss duration, so as to determine the target capacity-fixed site selection strategy corresponding to the CAES system through the load loss economic loss.

[0104] Those skilled in the art should understand that, the larger the capacity of the CAES system configuration, the more electricity the CAES system can supply when a fault causes the power grid to be unable to supply power to the distribution network, resulting in a load loss. The less load loss is generated and the shorter the load loss duration, and accordingly, the greater the cost of capacity optimization configuration.

[0105] Therefore, the embodiments of the present application must simultaneously consider the impact of the configuration location on line loss, the impact of the configuration capacity on cost, and the impact of the economic loss of load loss caused by faults, so as to determine the optimal capacity and site selection plan for the CAES system.

[0106] In the actual implementation process, the embodiment of the present application can evaluate different fixed capacity site selection schemes and add certain interference to the CAES system to make the CAES system appear (i.e., meet the power supply fault condition), and the power supply fault condition is as follows:

[0107] (1) The fault causes the power system to be unable to supply power to the distribution network;

[0108] (2) The fault causes the CAES system to be unable to supply power to the distribution network;

[0109] It is understandable that the energy storage system and the power grid simultaneously supplying power to the distribution network is similar to dual power supply. Compared with single power supply, dual power supply has the following advantages:

[0110] (1) Improve the availability and reliability of the power system and reduce equipment downtime;

[0111] (2) Reduce the impact of power grid accidents on system stability and reduce losses caused by failures;

[0112] (3) Enhance the system's anti-interference capability and improve the quality of data transmission.

[0113] Afterwards, the embodiment of the present application uses the economic loss of load loss caused by a CAES system failure as an indicator: the amount of load loss caused by the failure and the loss caused by the duration, and the capacity configuration and access plan with the minimum economic loss is optimal.

[0114] Therefore, the embodiments of the present application can calculate the economic losses caused by the load loss and duration of the CAES system to evaluate and determine the optimal fixed capacity site selection strategy (i.e., the target fixed capacity site selection strategy), thereby improving the operational stability and reliability after connecting to the CAES system.

[0115] Optionally, in one embodiment of the present application, the mathematical expression of the load loss economic loss of the CAES system is:

[0116]

[0117] Among them, C a Indicates economic loss due to load loss; is the time-loss load of the CAES system at time t; c loss represents the load loss penalty unit price; T represents the load loss duration.

[0118] In the specific implementation process, the mathematical expression of the load loss economic loss of the CAES system of the embodiment of the present application is as follows:

[0119]

[0120] Among them, C a Economic losses caused by load loss due to failure; is the load loss at time t; T is the duration of load loss; c loss Penalty unit price for load loss.

[0121] Therefore, the embodiments of the present application effectively improve the quality and reliability of the target capacity location selection strategy corresponding to the CAES system by setting appropriate load loss economic losses.

[0122] In summary, the embodiment of the present application first establishes a fixed capacity site selection optimization model including wind power and photovoltaic power generation systems and CAES systems based on the distribution network system; secondly, assuming that accurate wind power and photovoltaic predictions are unavailable, the output is predicted using historical data, taking into account that accessing the CAES system at different locations will cause changes in the structure of the entire system, and considering that the existence of line losses will cause different currents in the CAES system, changes in currents will affect the final configuration capacity of the CAES system and the cost of the CAES system; thereafter, the embodiment of the present application establishes constraints on each device of the system, and adopts a linear programming method to optimize the capacity configuration of the CAES system and select node access locations to minimize the system cost, thereby determining the capacity configuration and access plan of the CAES system; finally, the access plan of the CAES system is evaluated, with the economic loss of load loss caused by a CAES system failure as an indicator: the amount of load loss caused by the failure and the loss caused by the duration, and the capacity configuration and access plan with the smallest economic loss are the best, thereby being able to improve the economy and reliability of the CAES system under the premise of ensuring the operation of the CAES system.

[0123] According to the compressed air energy storage system sizing site selection and evaluation method proposed in the embodiment of the present application, a wind-solar-storage system operation model of the target area is constructed based on a preset distribution network system and CAES system model; the operation constraints corresponding to each device and distribution network system in the CAES system model and the system total cost objective function are determined through the wind-solar-storage system operation model, so as to construct a CAES sizing site selection model according to the system total cost objective function and the operation constraints; different nodes are selected in the distribution network system according to multiple preset sizing site selection strategies, and the CAES system is configured through different nodes to determine the CAES sizing site selection model according to the CAES sizing site selection strategy. The capacity site selection model solves the system total cost objective function corresponding to each of the multiple fixed capacity site selection strategies, and evaluates each fixed capacity site selection strategy based on the system total cost objective function to obtain the load loss economic loss corresponding to each fixed capacity site selection strategy after a fault occurs in the distribution network system, and determines the target fixed capacity site selection strategy among the multiple fixed capacity site selection strategies based on the load loss economic loss, and calculates the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed capacity site selection strategy, thereby ensuring the stability and reliability of power operation after connecting to the compressed air energy storage system, and effectively improving the economy of the power system.

[0124] Secondly, the compressed air energy storage system capacity determination site selection and evaluation device proposed in accordance with the embodiment of the present application is described with reference to the accompanying drawings.

[0125] Figure 6 It is a block diagram of a device for determining the capacity, site selection and evaluation of a compressed air energy storage system according to an embodiment of the present application.

[0126] like Figure 6As shown, the compressed air energy storage system capacity determination site selection and evaluation device 10 includes: a first modeling module 100, a second modeling module 200 and an evaluation module 300.

[0127] Among them, the first modeling module 100 is used to build a wind-solar-storage system operation model of the target area based on a preset distribution network system and CAES system model.

[0128] The second modeling module 200 is used to determine the operating constraints corresponding to each device and distribution network system in the CAES system model and the system total cost objective function through the wind, solar and storage system operating model, so as to construct a CAES fixed capacity site selection model according to the system total cost objective function and the operating constraints.

[0129] The evaluation module 300 is used to select different nodes in the distribution network system according to multiple preset fixed-capacity site selection strategies, and configure the CAES system through different nodes, so as to solve the system total cost objective function corresponding to each fixed-capacity site selection strategy in the multiple fixed-capacity site selection strategies according to the CAES fixed-capacity site selection model, and evaluate each fixed-capacity site selection strategy according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed-capacity site selection strategy after a fault occurs in the distribution network system, and determine the target fixed-capacity site selection strategy among the multiple fixed-capacity site selection strategies according to the load loss economic loss, and calculate the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed-capacity site selection strategy.

[0130] Optionally, in one embodiment of the present application, the second modeling module 200 includes: a first calculation unit, a first constraint unit, a second constraint unit, a third constraint unit, a fourth constraint unit and a construction unit.

[0131] Among them, the first calculation unit is used to solve the equipment capacity corresponding to each device in the wind, solar and storage system based on a preset optimization solution strategy, and calculate the equipment investment and operation and maintenance cost, electricity purchase and sales cost and wind and solar power abandonment penalty of the CAES system according to the equipment capacity, so as to construct the total system cost objective function corresponding to the CAES system through equipment investment and operation and maintenance cost, electricity purchase and sales cost and wind and solar power abandonment penalty, wherein the equipment capacity includes the installed capacity of photovoltaic and wind turbines, the total power of compressors, the total power of expanders and the capacity of gas storage tanks.

[0132] The first constraint unit is used to determine the line loss constraints of the CAES system connected to different positions of the distribution network, and calculate the line loss of the CAES system through the line loss constraints.

[0133] The second constraint unit is used to calculate the compression power of the CAES system, the expansion side power generation of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power and the sum of the abandoned wind and solar power powers at time t, and determine the electrical balance constraint of the CAES system in the operating constraint conditions based on the CAES system discharge power, the CAES system charging power, the wind power generation power, the photovoltaic power generation power, the line loss power, the load value and the sum of the abandoned wind and solar power powers.

[0134] The third constraint unit is used to obtain the energy storage state variables and energy release state variables of the CAES system, and establish the coupling constraints of the CAES system in the operation constraint conditions according to the energy storage state variables and the energy release state variables.

[0135] The fourth constraint unit is used to obtain the lower limit and the upper limit of the gas storage tank capacity of the CAES system, and determine the gas storage capacity constraint of the CAES system in the operation constraint condition based on the lower limit and the upper limit of the gas storage tank capacity.

[0136] The construction unit is used to construct a CAES fixed capacity site selection model based on line loss constraints, power balance constraints, coupling constraints, gas storage capacity constraints and system total cost objective function.

[0137] Optionally, in one embodiment of the present application, the compressed air energy storage system sizing, site selection and evaluation device 10 of the embodiment of the present application also includes: a third modeling module, which is used to model the motor, multi-stage compressor, gas storage tank, multi-stage expander and generator in the CAES system before building the wind, solar and storage system operation model of the target area based on the preset distribution network system and CAES system model to build a CAES system model.

[0138] Optionally, in one embodiment of the present application, the evaluation module 300 includes: an interference unit and a determination unit.

[0139] The interference unit is used to add interference to the CAES system and determine whether the CAES system meets the preset power supply fault condition, and when the CAES system meets the power supply fault condition, calculate the time-loss load of the CAES system at time t.

[0140] The determination unit is used to calculate the load loss economic loss of the CAES system according to the load loss amount, the preset load loss penalty unit price and the load loss duration, so as to determine the target capacity location selection strategy corresponding to the CAES system through the load loss economic loss.

[0141] Optionally, in one embodiment of the present application, the mathematical expression of the load loss economic loss of the CAES system is:

[0142]

[0143] Among them, Ca Indicates economic loss due to load loss; is the time-loss load of the CAES system at time t; c loss represents the load loss penalty unit price; T represents the load loss duration.

[0144] It should be noted that the aforementioned explanation of the embodiment of the method for determining the capacity, site selection and evaluation of a compressed air energy storage system is also applicable to the device for determining the capacity, site selection and evaluation of a compressed air energy storage system of this embodiment, and will not be repeated here.

[0145] The compressed air energy storage system sizing site selection and evaluation device proposed in the embodiment of the present application includes a first modeling module 100, which is used to construct a wind-solar-storage system operation model of the target area based on a preset distribution network system and CAES system model; a second modeling module 200, which is used to determine the operation constraints corresponding to each device and the distribution network system in the CAES system model and the system total cost objective function through the wind-solar-storage system operation model, so as to construct a CAES sizing site selection model according to the system total cost objective function and the operation constraints; an evaluation module 300, which is used to select different nodes in the distribution network system according to a plurality of preset sizing site selection strategies, and to select different nodes through different nodes. The CAES system is configured to solve the system total cost objective function corresponding to each of the multiple fixed capacity location selection strategies according to the CAES fixed capacity location selection model, and each fixed capacity location selection strategy is evaluated according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed capacity location selection strategy after a fault occurs in the distribution network system, and the target fixed capacity location selection strategy among the multiple fixed capacity location selection strategies is determined according to the load loss economic loss, and the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed capacity location selection strategy is calculated, thereby ensuring the stability and reliability of the power operation after connecting to the compressed air energy storage system, and effectively improving the economy of the power system.

[0146] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0147] A memory 701 , a processor 702 , and a computer program stored in the memory 701 and executable on the processor 702 .

[0148] When the processor 702 executes the program, the method for determining the capacity, site selection and evaluation of the compressed air energy storage system provided in the above embodiment is implemented.

[0149] Furthermore, the electronic device further comprises:

[0150] The communication interface 703 is used for communication between the memory 701 and the processor 702 .

[0151] The memory 701 is used to store computer programs that can be executed on the processor 702 .

[0152] The memory 701 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0153] If the memory 701, the processor 702 and the communication interface 703 are implemented independently, the communication interface 703, the memory 701 and the processor 702 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0154] Optionally, in a specific implementation, if the memory 701, the processor 702 and the communication interface 703 are integrated on a chip, the memory 701, the processor 702 and the communication interface 703 can communicate with each other through an internal interface.

[0155] The processor 702 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0156] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for determining the capacity, site selection and evaluation of a compressed air energy storage system.

[0157] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned compressed air energy storage system capacity determination site selection and evaluation method.

[0158] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0159] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0160] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0161] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0162] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0163] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0164] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0165] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for determining the capacity of a compressed air energy storage system and its evaluation, characterized in that: The following steps are involved: Based on the preset distribution network system and CAES system model, build the wind, solar and storage system operation model of the target area; Determine the operation constraints corresponding to each device and the distribution network system in the CAES system model and the system total cost objective function through the wind-solar-storage system operation model, so as to construct a CAES capacity location selection model according to the system total cost objective function and the operation constraints; Different nodes are selected in the distribution network system according to a plurality of preset fixed-capacity site selection strategies, and a CAES system is configured through the different nodes, so as to solve the system total cost objective function corresponding to each of the plurality of fixed-capacity site selection strategies according to the CAES fixed-capacity site selection model, and each fixed-capacity site selection strategy is evaluated according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed-capacity site selection strategy after a fault occurs in the distribution network system, and a target fixed-capacity site selection strategy among the plurality of fixed-capacity site selection strategies is determined according to the load loss economic loss, and the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed-capacity site selection strategy is calculated.

2. The method according to claim 1, characterized in that: The step of determining the operation constraints corresponding to each device in the CAES system model and the distribution network system and the system total cost objective function through the wind-solar-storage system operation model, so as to construct a CAES capacity location selection model according to the system total cost objective function and the operation constraints, includes: Based on the preset optimization solution strategy, the equipment capacity corresponding to each device in the wind-solar-storage system is solved, and the equipment investment and operation and maintenance cost, the purchase and sale cost of electricity, and the penalty for abandoning wind and solar power of the CAES system are calculated according to the equipment capacity, so as to construct the total system cost objective function corresponding to the CAES system through the equipment investment and operation and maintenance cost, the purchase and sale cost of electricity, and the penalty for abandoning wind and solar power, wherein the equipment capacity includes the installed capacity of photovoltaic and wind turbines, the total power of compressors, the total power of expanders, and the capacity of gas storage tanks; Determine line loss constraints for accessing the CAES system at different locations of a distribution network, and calculate line losses of the CAES system using the line loss constraints; Calculate the CAES system compression power, CAES system expansion side power generation, wind power generation power, photovoltaic power generation power, line loss power and the sum of wind and solar power abandonment at time t, and determine the electrical balance constraint of the CAES system in the operating constraint condition based on the CAES system discharge power, the CAES system charging power, the wind power generation power, the photovoltaic power generation power, the line loss power, the load value and the sum of wind and solar power abandonment; Acquire energy storage state variables and energy release state variables of the CAES system, and establish coupling constraints of the CAES system in the operation constraint conditions according to the energy storage state variables and the energy release state variables; Acquire a lower limit and an upper limit of a gas storage tank capacity of the CAES system, and determine a gas storage capacity constraint of the CAES system in the operation constraint condition based on the lower limit and the upper limit of the gas storage tank capacity; The CAES fixed capacity site selection model is constructed based on the line loss constraint, the electricity balance constraint, the coupling constraint, the gas storage capacity constraint and the system total cost objective function.

3. The method according to claim 2, characterized in that Before constructing the wind-solar-storage system operation model of the target area based on the preset distribution network system and the CAES system model, the method further includes: The electric motor, multi-stage compressor, gas storage tank, multi-stage expander and generator in the CAES system are modeled respectively to construct the CAES system model.

4. The method according to claim 3, characterized in that The obtaining of the load loss economic loss corresponding to each fixed capacity location selection strategy after a fault occurs in the distribution network system, and determining a target fixed capacity location selection strategy among multiple fixed capacity location selection strategies according to the load loss economic loss, includes: Adding interference to the CAES system, and determining whether the CAES system meets a preset power supply fault condition, and if the CAES system meets the power supply fault condition, calculating the time-loss load of the CAES system at time t; The load loss economic loss of the CAES system is calculated according to the load loss amount, the preset load loss penalty unit price and the load loss duration, so as to determine the target capacity location selection strategy corresponding to the CAES system through the load loss economic loss.

5. The method according to claim 4, characterized in that The mathematical expression of the load loss economic loss of the CAES system is: Among them, C a Indicates the economic loss of load loss; represents the time-loss load of the CAES system at time t; C loss represents the load loss penalty unit price; T represents the load loss duration.

6. A device for fixed capacity site selection and evaluation of compressed air energy storage system, characterized in that: include: The first modeling module is used to build a wind-solar-storage system operation model in the target area based on a preset distribution network system and CAES system model; A second modeling module is used to determine the operation constraints corresponding to each device and the distribution network system in the CAES system model and the system total cost objective function through the wind-solar-storage system operation model, so as to construct a CAES fixed capacity site selection model according to the system total cost objective function and the operation constraints; An evaluation module is used to select different nodes in the distribution network system according to a plurality of preset fixed-capacity site selection strategies, and configure the CAES system through the different nodes, so as to solve the system total cost objective function corresponding to each of the plurality of fixed-capacity site selection strategies according to the CAES fixed-capacity site selection model, and evaluate each fixed-capacity site selection strategy according to the system total cost objective function to obtain the load loss economic loss corresponding to each fixed-capacity site selection strategy after a fault occurs in the distribution network system, and determine a target fixed-capacity site selection strategy among the plurality of fixed-capacity site selection strategies according to the load loss economic loss, and calculate the target configuration capacity and / or target configuration position of the CAES system corresponding to the target fixed-capacity site selection strategy.

7. The device according to claim 6, characterized in that The second modeling module comprises: A first calculation unit is used to solve the equipment capacity corresponding to each device in the wind-solar-storage system based on a preset optimization solution strategy, and calculate the equipment investment and operation and maintenance cost, the purchase and sale cost of electricity, and the penalty for abandoning wind and solar power of the CAES system according to the equipment capacity, so as to construct a total system cost objective function corresponding to the CAES system through the equipment investment and operation and maintenance cost, the purchase and sale cost of electricity, and the penalty for abandoning wind and solar power, wherein the equipment capacity includes the installed capacity of photovoltaic and wind turbines, the total power of compressors, the total power of expanders, and the capacity of gas storage tanks; A first constraint unit, used to determine line loss constraints for accessing the CAES system at different locations of a distribution network, and calculate the line loss of the CAES system according to the line loss constraints; The second constraint unit is used to calculate the compression power of the CAES system, the expansion side power generation of the CAES system, the wind power generation power, the photovoltaic power generation power, the line loss power and the sum of the abandoned wind and abandoned solar power at time t, and determine the electric balance constraint of the CAES system in the operation constraint condition based on the CAES system discharge power, the CAES system charging power, the wind power generation power, the photovoltaic power generation power, the line loss power, the load value and the sum of the abandoned wind and abandoned solar power; a third constraint unit, configured to obtain an energy storage state variable and an energy release state variable of the CAES system, and establish a coupling constraint of the CAES system in the operation constraint condition according to the energy storage state variable and the energy release state variable; a fourth constraint unit, configured to obtain a lower limit and an upper limit of a gas storage tank capacity of the CAES system, and determine a gas storage capacity constraint of the CAES system in the operation constraint condition based on the lower limit and the upper limit of the gas storage tank capacity; A construction unit is used to construct the CAES fixed capacity site selection model based on the line loss constraint, the electricity balance constraint, the coupling constraint, the gas storage capacity constraint and the system total cost objective function.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for determining the capacity, site selection, and evaluation of a compressed air energy storage system as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for determining the capacity, site selection and evaluation of a compressed air energy storage system as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the method for determining the capacity, site selection and evaluation of a compressed air energy storage system as described in any one of claims 1 to 5.

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