Compressed air energy storage system comprehensive efficiency evaluation method and device

Abstract

The invention relates to a compressed air energy storage system comprehensive efficiency evaluation method and device, and the method comprises the steps: firstly guaranteeing the multi-dimensional evaluation of the system efficiency through the evaluation indexes, including the conversion efficiency of active power and reactive power, the abandoned power of new energy, and the voltage level of a power distribution network; secondly, constructing an efficiency calculation model, decomposing the efficiency calculation model into power balance, node voltage constraint, transmission power constraint and energy storage system boundary constraint, and ensuring physical consistency through second-order cone constraint; afterwards, proposing a solving method based on linearization processing and a commercial solver, and adopting a multi-objective optimization model to obtain an optimal efficiency quantitative evaluation scheme; and finally, performing multi-scene simulation and empirical test based on actual data, and verifying the accuracy and feasibility of the evaluation scheme. Therefore, the problems that an existing new energy power generation technology has intermittency and volatility, and the stability and economical efficiency of a power system are greatly affected are solved.

Description

Technical Field

[0001] The present application relates to the field of power systems and energy storage technology, and in particular to a method and device for evaluating the comprehensive performance of a compressed air energy storage system. Background Art

[0002] As global demand for renewable energy increases, the proportion of wind and photovoltaic power generation in power systems continues to increase.

[0003] However, existing new energy sources such as wind power and photovoltaic power generation are intermittent and volatile, which poses challenges to the stability and economy of the power system and needs to be urgently addressed.

[0004] As an important energy storage technology, compressed air energy storage system can play an important role in the power system, such as peak load shifting and valley filling. Therefore, it is of great significance to develop a comprehensive performance evaluation method for compressed air energy storage in a high proportion of new energy scenarios. Summary of the invention

[0005] The present application provides a method and device for evaluating the comprehensive performance of a compressed air energy storage system to solve the problems that existing renewable energy power generation technologies are intermittent and volatile, greatly affecting the stability and economy of the power system.

[0006] A first aspect embodiment of the present application provides a method for comprehensive performance evaluation of a compressed air energy storage system, comprising the following steps: constructing an performance calculation model corresponding to a target compressed air energy storage power station; converting the performance calculation model into a linearized solution model of the compressed air energy storage power station, and solving the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station; evaluating the power station operation plan through a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

[0007] Optionally, in one embodiment of the present application, after obtaining the comprehensive performance evaluation result corresponding to the compressed air energy storage power station, it also includes: obtaining the actual wind and solar power generation data and actual power system operation data corresponding to the target compressed air energy storage power station; building a multi-scenario simulation test environment for the target compressed air energy storage power station, and based on the multi-scenario simulation test environment and the power station operation plan, performing simulated operation operations on the target compressed air energy storage power station to obtain simulated operation results; comparing the simulated operation results with the actual wind and solar power generation data and the actual power system operation data to obtain operation comparison results, and optimizing the performance calculation model according to the operation comparison results.

[0008] Optionally, in one embodiment of the present application, constructing an efficiency calculation model corresponding to the target compressed air energy storage power station includes: establishing multiple efficiency evaluation indicators corresponding to the target compressed air energy storage power station, wherein the multiple efficiency evaluation indicators include an active adjustable capacity ratio indicator, a reactive adjustable capacity ratio indicator, a new energy curtailment indicator, a distribution network voltage level indicator, a power loss indicator, and a power supply reliability indicator; obtaining the operating mechanism of the target compressed air energy storage power station to determine the distribution network power balance constraint, node voltage constraint, line transmission power constraint and energy storage system boundary constraint of the target compressed air energy storage power station according to the operating mechanism; constructing the efficiency calculation model based on the distribution network power balance constraint, the node voltage constraint, the line transmission power constraint and the energy storage system boundary constraint, and in combination with a preset second-order cone constraint.

[0009] Optionally, in one embodiment of the present application, the efficiency calculation model is converted into a linearized solution model of the compressed air energy storage power station, and the linearized solution model is solved to obtain a power station operation plan corresponding to the target compressed air energy storage power station, including: determining multiple optimization objectives of the linearized solution model, wherein the multiple optimization objectives include a power purchase cost minimization objective, a new energy abandonment objective, an energy storage operation cost minimization objective, and a network loss minimization objective; determining the weight of each of the multiple optimization objectives to establish an objective function of the linearized solution model based on the weight and the multiple optimization objectives; solving the objective function based on a preset solver to obtain a power station operation plan corresponding to the target compressed air energy storage power station.

[0010] A second aspect of the present application provides a device for comprehensive performance evaluation of a compressed air energy storage system, comprising: a modeling module for constructing an performance calculation model corresponding to a target compressed air energy storage power station; a conversion module for converting the performance calculation model into a linearized solution model of the compressed air energy storage power station, and solving the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station; an evaluation module for evaluating the power station operation plan through a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

[0011] Optionally, in one embodiment of the present application, it also includes: an acquisition module, which is used to obtain the actual wind and solar power generation data and actual power system operation data corresponding to the target compressed air energy storage power station after obtaining the comprehensive performance evaluation result corresponding to the compressed air energy storage power station; a simulation module, which is used to build a multi-scenario simulation test environment for the target compressed air energy storage power station, and based on the multi-scenario simulation test environment and the power station operation plan, perform simulated operation operations on the target compressed air energy storage power station to obtain simulated operation results; an optimization module, which is used to compare the simulated operation results with the actual wind and solar power generation data and the actual power system operation data to obtain operation comparison results, and optimize the performance calculation model according to the operation comparison results.

[0012] Optionally, in one embodiment of the present application, the modeling module includes: an establishment unit, used to establish multiple performance evaluation indicators corresponding to the target compressed air energy storage power station, wherein the multiple performance evaluation indicators include an active adjustable capacity ratio indicator, a reactive adjustable capacity ratio indicator, a new energy abandonment indicator, a distribution network voltage level indicator, a power loss indicator, and a power supply reliability indicator; a first determination unit, used to obtain the operating mechanism of the target compressed air energy storage power station, so as to determine the distribution network power balance constraints, node voltage constraints, line transmission power constraints and energy storage system boundary constraints of the target compressed air energy storage power station according to the operating mechanism; a construction unit, used to construct the performance calculation model based on the distribution network power balance constraints, the node voltage constraints, the line transmission power constraints and the energy storage system boundary constraints, and in combination with preset second-order cone constraints.

[0013] Optionally, in one embodiment of the present application, the conversion module includes: a second determination unit, used to determine multiple optimization objectives of the linearization solution model, wherein the multiple optimization objectives include a power purchase cost minimization objective, a new energy abandonment amount minimization objective, an energy storage operation cost minimization objective, and a network loss minimization objective; a third determination unit, used to determine the weight of each of the multiple optimization objectives, so as to establish an objective function of the linearization solution model based on the weight and the multiple optimization objectives; a solution unit, used to solve the objective function based on a preset solver, so as to obtain a power station operation plan corresponding to the target compressed air energy storage power station.

[0014] 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 evaluating the comprehensive performance of a compressed air energy storage system as described in the above embodiment.

[0015] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for evaluating the comprehensive efficiency of a compressed air energy storage system.

[0016] The fifth aspect of the present application provides a computer program product, including a computer program, which is executed to implement the above-mentioned method for evaluating the comprehensive efficiency of a compressed air energy storage system.

[0017] Therefore, the embodiments of the present application have the following beneficial effects:

[0018] The embodiments of the present application can be achieved by constructing an efficiency calculation model corresponding to the target compressed air energy storage power station; converting the efficiency calculation model into a linearized solution model of the compressed air energy storage power station, and solving the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station; evaluating the power station operation plan through a plurality of pre-constructed efficiency evaluation indicators to obtain a comprehensive efficiency evaluation result corresponding to the compressed air energy storage power station. The present application achieves an accurate evaluation of the comprehensive efficiency of the compressed air energy storage system by establishing efficiency evaluation indicators of compressed air energy storage power stations, constructing an optimized calculation model, and solving it based on linearization processing and commercial solvers. As a result, the problems that the existing new energy power generation technology is intermittent and volatile, which greatly affects the stability and economy of the power system, are solved.

[0019] 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

[0020] 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:

[0021] Figure 1 A flowchart of a method for evaluating the comprehensive performance of a compressed air energy storage system provided according to an embodiment of the present application;

[0022] Figure 2 A logical architecture diagram of a method for evaluating the comprehensive performance of a compressed air energy storage system provided in accordance with an embodiment of the present application;

[0023] Figure 3 A schematic diagram of a grid-connected control model for a compressed air energy storage system provided for one embodiment of the present application;

[0024] Figure 4 A schematic diagram of a grid-connected test of a compressed air energy storage system provided for one embodiment of the present application;

[0025] Figure 5This is an example diagram of a device for evaluating the comprehensive performance of a compressed air energy storage system according to an embodiment of the present application;

[0026] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0027] Among them, 10-compressed air energy storage system comprehensive efficiency evaluation device; 100-modeling module, 200-conversion module, 300-evaluation module; 601-memory, 602-processor, 603-communication interface. DETAILED DESCRIPTION

[0028] 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.

[0029] The following describes the method and device for comprehensive performance evaluation of a compressed air energy storage system of 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 comprehensive performance evaluation of a compressed air energy storage system, in which an performance calculation model corresponding to a target compressed air energy storage power station is constructed; the performance calculation model is converted into a linearized solution model of the compressed air energy storage power station, and the linearized solution model is solved to obtain a power station operation plan corresponding to the target compressed air energy storage power station; the power station operation plan is evaluated by using a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station. The present application achieves an accurate evaluation of the comprehensive performance of a compressed air energy storage system by establishing performance evaluation indicators of a compressed air energy storage power station, constructing an optimized calculation model, and solving it based on linearization processing and a commercial solver. As a result, the problem that the existing new energy power generation technology is intermittent and volatile, which greatly affects the stability and economy of the power system, is solved.

[0030] Specifically, Figure 1 A flowchart of a method for evaluating the comprehensive performance of a compressed air energy storage system provided in an embodiment of the present application.

[0031] like Figure 1 As shown, the method for evaluating the comprehensive performance of the compressed air energy storage system includes the following steps:

[0032] In step S101, an efficiency calculation model corresponding to a target compressed air energy storage power station is constructed.

[0033] The embodiments of the present application can first construct a compressed air energy storage power station performance evaluation index system, such as Figure 2As shown in the figure, the evaluation index system includes the active adjustable capacity ratio, reactive adjustable capacity ratio, renewable energy curtailment amount, distribution network voltage level, power loss and power supply reliability.

[0034] Among them, in terms of the regulation efficiency of energy storage power stations, the adjustable capacity ratio of the energy storage system in participating in the system regulation is evaluated; in terms of the amount of abandoned electricity from new energy, the amount of abandoned electricity caused by the volatility of wind and photovoltaic power generation is evaluated; in terms of the voltage level of the distribution network, the voltage stability of the power grid is evaluated when a high proportion of new energy is connected; in terms of power loss, the loss of the system during power transmission is calculated; in terms of power supply reliability, the operating stability and reliability of the system in the scenario of a high proportion of new energy is evaluated.

[0035] Furthermore, the embodiments of the present application also need to establish an efficiency calculation model for a compressed air energy storage power station. Specifically, the embodiments of the present application can analyze the operation mechanism of the energy storage station in the power system, decompose the efficiency calculation model into the distribution network power balance part, the node voltage constraint part, the line transmission power constraint part and the energy storage system boundary constraint part; at the same time, introduce the second-order cone constraint to ensure the physical consistency between current and power.

[0036] It can be understood that the efficiency calculation model of the embodiment of the present application can fully reflect the operating characteristics of the compressed air energy storage power station by integrating the dynamic interaction process between the energy storage station and the power grid, and provide a scientific basis for efficiency calculation.

[0037] Optionally, in one embodiment of the present application, an efficiency calculation model corresponding to the target compressed air energy storage power station is constructed, including: establishing multiple efficiency evaluation indicators corresponding to the target compressed air energy storage power station, wherein the multiple efficiency evaluation indicators include an active adjustable capacity ratio indicator, a reactive adjustable capacity ratio indicator, a new energy curtailment indicator, a distribution network voltage level indicator, a power loss indicator, and a power supply reliability indicator; obtaining the operating mechanism of the target compressed air energy storage power station to determine the distribution network power balance constraints, node voltage constraints, line transmission power constraints, and energy storage system boundary constraints of the target compressed air energy storage power station according to the operating mechanism; constructing an efficiency calculation model based on the distribution network power balance constraints, node voltage constraints, line transmission power constraints, and energy storage system boundary constraints, and in combination with preset second-order cone constraints.

[0038] Specifically, the embodiment of the present application first establishes a set of performance evaluation index system for compressed air energy storage power station, wherein each evaluation index is as follows:

[0039] 1. Amount of abandoned electricity from new energy sources:

[0040] This indicator is used to evaluate the unused electricity of wind and photovoltaic power generation due to insufficient electricity demand or improper scheduling. The mathematical expression of the abandoned electricity of new energy is:

[0041]

[0042] Among them, Pg PV D (n,t) is the amount of abandoned light at node n at time t; E curtail is the total amount of wasted electricity.

[0043] 2. Active adjustable capacity ratio:

[0044] This indicator measures the ratio of the active power output of the energy storage system to its capacity in peak load regulation or dispatching, thereby evaluating the working efficiency of the energy storage system. The formula for the active power adjustable capacity ratio of the compressed air energy storage system is:

[0045]

[0046] Among them, Pg PV D (n,t) is the active power output of the energy storage system at time t; C CAES is the capacity of the energy storage system; η active It is the total active electrical efficiency of the compressed air energy storage system.

[0047] 3. Reactive adjustable capacity ratio:

[0048] This indicator is used to evaluate the efficiency of the energy storage system when participating in reactive power regulation. It is specifically expressed as the ratio of reactive power output to system capacity. Its mathematical expression is:

[0049]

[0050] Among them, Q CAES-up (t) represents the reactive power output at time t; η reactive It is the total reactive power adjustable capacity ratio of the compressed air energy storage system.

[0051] 4. Distribution network voltage level:

[0052] This indicator is used to monitor the voltage fluctuation in the distribution network to ensure that the system voltage is always within a safe range. The mathematical expression of the distribution network voltage level is:

[0053]

[0054] Where U(n,t) is the node voltage of node n at time t; U min , U max are the upper and lower limits of the grid node voltage.

[0055] Therefore, the embodiments of the present application define the above-mentioned evaluation indicators, so as to comprehensively and accurately evaluate the comprehensive performance of the compressed air energy storage system in a high proportion of new energy scenarios.

[0056] In the actual implementation process, the embodiment of the present application can also analyze the energy conversion process and working mechanism of the compressed air energy storage power station, such as Figure 3 As shown, the efficiency calculation model of the compressed air energy storage station is deconstructed into the power balance part, the energy storage SoC part, and the multi-mode operation state conversion part, as described below:

[0057] Power balance constraint: The energy storage power station participates in both the peak-shaving market and the frequency-shaving market. The actual power levels of the compressor and turbine can be expressed as:

[0058]

[0059] in, and Respectively represent the minimum and maximum active power of the compressor; and They represent the peak load power, frequency modulation power and actual power of the compressor during period t respectively; and They represent the peak-shaving power, frequency-regulating power and actual active output of the turbine generator set during period t respectively; Indicates the call ratio of reactive reserve; and They represent the minimum and maximum active power of the turbine generator set in the power generation mode respectively; is the reactive reserve power in period t; and The minimum and maximum reactive power output of the turbine generator set in phase modulation mode, and is a negative value, corresponding to the reactive power output limit of the generator during phase leading operation; μ c,t , μ g,t and μ sc,t are Boolean quantities, representing compression conditions, power generation conditions and phase modulation conditions respectively.

[0060] It should be noted that equations (7) and (8) are the upper and lower limit constraints of the compressor power; equations (9) and (10) are the upper and lower limit constraints of the power of the turbine generator set under power generation conditions; equation (11) is a supplementary constraint that only considers the positive standby situation; and equation (12) represents the reactive power output range of the turbine generator set under the phase adjustment mode.

[0061] Energy storage SoC constraints: Gas storage SoC and heat storage SoC couple the compression side and the power generation side and are functions of multiple thermodynamic parameters. When describing the gas storage SoC in terms of gas storage quality, the following relationship exists:

[0062]

[0063] Among them, A caes-soc,t SoC is the gas storage mass expressed by the compressed air energy storage system; RM maxIndicates the maximum circulating air mass corresponding to the gas storage working pressure range; and They represent the air mass flow corresponding to the compression condition, power generation condition and phase modulation condition during period t, respectively. and It is described by the charge and discharge function that characterizes the thermodynamic characteristics of the energy storage power station. is a constant.

[0064] The relationship between the internal thermodynamic characteristics of a compressed air energy storage station and the market services it provides can be determined by the SoC of the heat storage tank and the gas storage, specifically expressed as:

[0065]

[0066] Among them, M HTF,t It represents the mass flow rate of heat transfer oil in the high-temperature heat storage tank during period t; and are the maximum and minimum masses of the heat transfer oil in the high temperature tank, respectively; and are the gas storage SoC corresponding to the maximum and minimum gas storage pressures, respectively.

[0067] It should be noted that formula (14) is the upper and lower limit constraints of the quality of the heat transfer oil in the high-temperature heat storage tank; formula (15)-formula (17) are the constraints on the quality of the high-pressure air stored in the gas storage reservoir. Considering that the air quality consumed by the phase adjustment mode is very small, it is not included in formula (15).

[0068] In addition, in order to better participate in the operation of the next-day electricity market, the gas storage SoC must also meet the following constraints:

[0069] |A caes-soc,T -A caes-soc,0 |≤δ·A caes-soc,0 (18)

[0070] Among them, A caes-soc,0 and A caes-soc,T They represent the gas storage SoC at the start and end of the scheduling period respectively; δ represents the allowable SoC deviation percentage.

[0071] Considering the operating constraints of the compressed air energy storage system under the phase-shifting mode: After the phase-shifting mode is introduced, the operating status of the compressor and turbine must meet

[0072]

[0073] Formula (19) shows that the compressed air energy storage station is not allowed to work in compression mode and power generation mode at the same time, and the turbine generator set must work in power generation mode or phase adjustment mode and is not allowed to shut down. At the same time, the compressed air energy storage station can work in compression mode and phase adjustment mode at the same time.

[0074] In step S102, the efficiency calculation model is converted into a linearized solution model of a compressed air energy storage power station, and the linearized solution model is solved to obtain a power station operation plan corresponding to the target compressed air energy storage power station.

[0075] In step S103, the power plant operation plan is evaluated by using a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power plant.

[0076] Afterwards, the embodiments of the present application also need to adopt a multi-objective optimization method to set the weights of objectives such as electricity purchase cost, new energy power abandonment, energy storage operation cost and network loss to obtain the objective function of optimized operation; secondly, a linear solution model of the compressed air energy storage power station is constructed according to the efficiency calculation model, and the original nonlinear optimization model is converted into a linear model. The operation plan of the power station is solved by commercial solvers such as CPLEX, and its various performance indicators are evaluated, so as to evaluate the power station operation plan through multiple pre-constructed performance evaluation indicators to obtain the comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

[0077] Optionally, in one embodiment of the present application, the efficiency calculation model is converted into a linearized solution model of a compressed air energy storage power station, and the linearized solution model is solved to obtain a power station operation plan corresponding to the target compressed air energy storage power station, including: determining multiple optimization objectives of the linearized solution model, wherein the multiple optimization objectives include a power purchase cost minimization objective, a new energy abandonment objective, an energy storage operation cost minimization objective, and a network loss minimization objective; determining the weight of each of the multiple optimization objectives to establish an objective function of the linearized solution model based on the weight and the multiple optimization objectives; solving the objective function based on a preset solver to obtain a power station operation plan corresponding to the target compressed air energy storage power station.

[0078] Specifically, the embodiments of the present application can use a multi-objective optimization method to achieve multiple optimization goals of minimizing electricity purchase costs, minimizing new energy curtailment, minimizing energy storage operating costs, and minimizing network losses, and determine the weight of each of the multiple optimization goals.

[0079] Afterwards, the embodiment of the present application can combine the efficiency calculation model of the compressed air energy storage power station mentioned above to establish a quantitative evaluation model of the multi-mode operation efficiency of the compressed air energy storage station, the specific form of which can be expressed as a mixed integer nonlinear optimization problem, and its mathematical expression is as follows:

[0080]

[0081] The main sources of nonlinearity in the operation optimization model shown in formula (20) are as follows:

[0082] 1. The charge and discharge function terms of the compressor and turbine shown in equations (15) to (17);

[0083] 2. The multiplication of two Boolean quantities in equation (19).

[0084] Afterwards, the embodiments of the present application will process the above nonlinear terms respectively.

[0085] For the absolute value term in the objective function, the present embodiment needs to introduce two auxiliary continuous variables: and And satisfy the following constraints:

[0086]

[0087] in, or One of them must be forced to zero, for which an auxiliary Boolean variable u is introduced t , so the absolute value part Can be replaced by And add the following linear constraints to the original optimization model:

[0088]

[0089] For the charge and discharge function items of the compressor and turbine, the embodiment of the present application can use the incremental method to calculate the nonlinear discharge function of the turbine generator set. Perform piecewise linearization, the specific processing process is as follows:

[0090] Introducing K auxiliary continuous variables and K-1 auxiliary Boolean variables ξ, and use K+1 points to divide the turbine power generation operation range Divided into K segments, that is, and The output power of the turbine generator set can be expressed as follows:

[0091]

[0092] The discharge function can be approximately linearly expressed as follows:

[0093]

[0094] The following additional constraints must be met:

[0095]

[0096] For the operating state constraint shown in formula (19), its equivalent form can be expressed as follows:

[0097]

[0098] At this point, the embodiment of the present application can transform the original nonlinear problem into a multi-objective mixed integer linear optimization problem, and solve the linearized multi-objective mixed integer optimization problem to obtain the comprehensive performance evaluation result of compressed air energy storage.

[0099] Optionally, in one embodiment of the present application, after obtaining the comprehensive performance evaluation results corresponding to the compressed air energy storage power station, it also includes: obtaining the actual wind and solar power generation data and actual power system operation data corresponding to the target compressed air energy storage power station; building a multi-scenario simulation test environment for the target compressed air energy storage power station, and based on the multi-scenario simulation test environment and the power station operation plan, performing simulated operation operations on the target compressed air energy storage power station to obtain simulated operation results; comparing the simulated operation results with the actual wind and solar power generation data and the actual power system operation data to obtain operation comparison results, and optimizing the performance calculation model according to the operation comparison results.

[0100] In addition, the embodiments of the present application can also build a multi-scenario simulation test environment for compressed air energy storage power stations based on actual wind and solar power generation data and power system operation data, such as Figure 4 As shown, the system operation under different renewable energy penetration scenarios is simulated, that is, the efficiency of the power station is simulated under different renewable energy penetration scenarios to obtain simulated operation results; then, the embodiment of the present application can verify the accuracy of the model by comparing the simulated operation results with the actual operation data, and optimize the model parameters; finally, the test results are applied to actual operation, thereby providing data support for the quantitative evaluation of the actual efficiency of the power station, ensuring the feasibility and efficiency improvement of the efficiency evaluation system in actual scenarios.

[0101] According to the comprehensive performance evaluation method of the compressed air energy storage system proposed in the embodiment of the present application, first, the multi-dimensional evaluation of the system performance is ensured through the evaluation indicators including the conversion efficiency of active power and reactive power, the amount of new energy abandoned, and the voltage level of the distribution network; secondly, the performance calculation model is constructed, decomposed into power balance, node voltage constraints, transmission power constraints and energy storage system boundary constraints, and the physical consistency is ensured through the second-order cone constraints; then, a solution method based on linearization processing and commercial solver is proposed, and a multi-objective optimization model is adopted to obtain the optimal performance quantitative evaluation scheme; finally, multi-scenario simulation and empirical testing are carried out based on actual data to verify the accuracy and feasibility of the evaluation scheme, thereby realizing the quantitative evaluation of the performance of the compressed air energy storage system in the scenario of a high proportion of new energy, and evaluating the system stability, energy utilization and economy of compressed air energy storage in different new energy access scenarios, which has broad application prospects.

[0102] Secondly, a device for evaluating the comprehensive performance of a compressed air energy storage system according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0103] Figure 5 It is a block diagram of a device for evaluating the comprehensive performance of a compressed air energy storage system according to an embodiment of the present application.

[0104] like Figure 5 As shown, the compressed air energy storage system comprehensive performance evaluation device 10 includes: a modeling module 100, a conversion module 200 and an evaluation module 300.

[0105] Among them, the modeling module 100 is used to construct an efficiency calculation model corresponding to the target compressed air energy storage power station.

[0106] The conversion module 200 is used to convert the efficiency calculation model into a linear solution model of the compressed air energy storage power station, and solve the linear solution model to obtain the power station operation plan corresponding to the target compressed air energy storage power station.

[0107] The evaluation module 300 is used to evaluate the power station operation plan through a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

[0108] Optionally, in one embodiment of the present application, the compressed air energy storage system comprehensive efficiency evaluation device 10 of the embodiment of the present application further includes: an acquisition module, a simulation module and an optimization module.

[0109] Among them, the acquisition module is used to obtain the actual wind and solar power generation data and actual power system operation data corresponding to the target compressed air energy storage power station after obtaining the comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

[0110] The simulation module is used to build a multi-scenario simulation test environment for the target compressed air energy storage power station, and based on the multi-scenario simulation test environment and the power station operation plan, simulate the operation of the target compressed air energy storage power station to obtain the simulation operation results.

[0111] The optimization module is used to compare the simulation operation results with the actual wind and solar power generation data and the actual power system operation data to obtain the operation comparison results, and optimize the efficiency calculation model according to the operation comparison results.

[0112] Optionally, in one embodiment of the present application, the modeling module 100 includes: an establishing unit, a first determining unit and a constructing unit.

[0113] Among them, a unit is established to establish multiple performance evaluation indicators corresponding to the target compressed air energy storage power station, wherein the multiple performance evaluation indicators include an active adjustable capacity ratio indicator, a reactive adjustable capacity ratio indicator, a new energy power abandonment indicator, a distribution network voltage level indicator, a power loss indicator and a power supply reliability indicator.

[0114] The first determination unit is used to obtain the operating mechanism of the target compressed air energy storage power station to determine the distribution network power balance constraints, node voltage constraints, line transmission power constraints and energy storage system boundary constraints of the target compressed air energy storage power station according to the operating mechanism.

[0115] The construction unit is used to construct an efficiency calculation model based on the power balance constraints of the distribution network, the node voltage constraints, the line transmission power constraints and the boundary constraints of the energy storage system, and combined with the preset second-order cone constraints.

[0116] Optionally, in one embodiment of the present application, the conversion module 200 includes: a second determination unit, a third determination unit and a solving unit.

[0117] Among them, the second determination unit is used to determine multiple optimization objectives of the linearization solution model, wherein the multiple optimization objectives include minimizing the electricity purchase cost, minimizing the amount of new energy abandoned electricity, minimizing the energy storage operation cost and minimizing the network loss.

[0118] The third determination unit is used to determine the weight of each optimization target among the multiple optimization targets, so as to establish the objective function of the linearization solution model based on the weight and the multiple optimization targets.

[0119] The solving unit is used to solve the objective function based on a preset solver to obtain a power station operation plan corresponding to the target compressed air energy storage power station.

[0120] It should be noted that the aforementioned explanation of the embodiment of the method for evaluating the comprehensive performance of a compressed air energy storage system is also applicable to the device for evaluating the comprehensive performance of a compressed air energy storage system of this embodiment, and will not be repeated here.

[0121] The device for evaluating the comprehensive performance of a compressed air energy storage system proposed in accordance with an embodiment of the present application includes a modeling module for constructing an performance calculation model corresponding to a target compressed air energy storage power station; a conversion module for converting the performance calculation model into a linearized solution model of the compressed air energy storage power station, and solving the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station; and an evaluation module for evaluating the power station operation plan through a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station. The present application achieves an accurate evaluation of the comprehensive performance of a compressed air energy storage system by establishing performance evaluation indicators for a compressed air energy storage power station, constructing an optimized calculation model, and solving the problem based on linearization processing and a commercial solver.

[0122] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0123] A memory 601 , a processor 602 , and a computer program stored in the memory 601 and executable on the processor 602 .

[0124] When the processor 602 executes the program, the comprehensive performance evaluation method of the compressed air energy storage system provided in the above embodiment is implemented.

[0125] Furthermore, the electronic device further comprises:

[0126] The communication interface 603 is used for communication between the memory 601 and the processor 602 .

[0127] The memory 601 is used to store computer programs that can be executed on the processor 602 .

[0128] The memory 601 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.

[0129] If the memory 601, the processor 602 and the communication interface 603 are implemented independently, the communication interface 603, the memory 601 and the processor 602 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 6 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.

[0130] Optionally, in a specific implementation, if the memory 601, the processor 602 and the communication interface 603 are integrated on a chip, the memory 601, the processor 602 and the communication interface 603 can communicate with each other through an internal interface.

[0131] The processor 602 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.

[0132] 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 evaluating the comprehensive efficiency of a compressed air energy storage system.

[0133] 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 method for evaluating the comprehensive efficiency of a compressed air energy storage system.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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 evaluating the comprehensive performance of a compressed air energy storage system, characterized in that: The following steps are involved: Construct an efficiency calculation model corresponding to the target compressed air energy storage power station; Converting the efficiency calculation model into a linearized solution model of the compressed air energy storage power station, and solving the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station; The power station operation plan is evaluated by using a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

2. The method according to claim 1, characterized in that After obtaining the comprehensive performance evaluation result corresponding to the compressed air energy storage power station, it also includes: Acquire actual wind and solar power generation data and actual power system operation data corresponding to the target compressed air energy storage power station; Building a multi-scenario simulation test environment for the target compressed air energy storage power station, and based on the multi-scenario simulation test environment and the power station operation plan, performing a simulated operation operation on the target compressed air energy storage power station to obtain a simulated operation result; The simulation operation result is compared with the actual wind and solar power generation data and the actual power system operation data to obtain an operation comparison result, and the efficiency calculation model is optimized according to the operation comparison result.

3. The method according to claim 1, characterized in that The construction of the efficiency calculation model corresponding to the target compressed air energy storage power station includes: Establishing a plurality of performance evaluation indicators corresponding to the target compressed air energy storage power station, wherein the plurality of performance evaluation indicators include an active adjustable capacity ratio indicator, a reactive adjustable capacity ratio indicator, a new energy abandoned power indicator, a distribution network voltage level indicator, a power loss indicator, and a power supply reliability indicator; Acquire the operating mechanism of the target compressed air energy storage power station to determine the distribution network power balance constraint, node voltage constraint, line transmission power constraint and energy storage system boundary constraint of the target compressed air energy storage power station according to the operating mechanism; The efficiency calculation model is constructed based on the power balance constraint of the distribution network, the node voltage constraint, the line transmission power constraint and the boundary constraint of the energy storage system, and in combination with a preset second-order cone constraint.

4. The method according to claim 3, characterized in that The converting the efficiency calculation model into a linearized solution model of the compressed air energy storage power station, and solving the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station, includes: Determining multiple optimization objectives of the linearization solution model, wherein the multiple optimization objectives include a goal of minimizing electricity purchase costs, a goal of minimizing the amount of abandoned electricity from new energy sources, a goal of minimizing energy storage operating costs, and a goal of minimizing network losses; Determining a weight of each of the plurality of optimization objectives to establish an objective function of the linearization solution model based on the weight and the plurality of optimization objectives; The objective function is solved based on a preset solver to obtain a power station operation plan corresponding to the target compressed air energy storage power station.

5. A device for evaluating the comprehensive performance of a compressed air energy storage system, characterized in that: include: A modeling module is used to construct an efficiency calculation model corresponding to the target compressed air energy storage power station; A conversion module, used to convert the efficiency calculation model into a linearized solution model of the compressed air energy storage power station, and solve the linearized solution model to obtain a power station operation plan corresponding to the target compressed air energy storage power station; The evaluation module is used to evaluate the power station operation plan through a plurality of pre-constructed performance evaluation indicators to obtain a comprehensive performance evaluation result corresponding to the compressed air energy storage power station.

6. The device according to claim 5, characterized in that Also includes: An acquisition module, used to acquire actual wind and solar power generation data and actual power system operation data corresponding to the target compressed air energy storage power station after obtaining the comprehensive performance evaluation result corresponding to the compressed air energy storage power station; A simulation module, used to build a multi-scenario simulation test environment for the target compressed air energy storage power station, and based on the multi-scenario simulation test environment and the power station operation plan, perform a simulated operation on the target compressed air energy storage power station to obtain a simulated operation result; The optimization module is used to compare the simulation operation result with the actual wind and solar power generation data and the actual power system operation data to obtain an operation comparison result, and optimize the efficiency calculation model according to the operation comparison result.

7. The device according to claim 5, characterized in that The modeling module includes: An establishing unit, used to establish a plurality of performance evaluation indicators corresponding to the target compressed air energy storage power station, wherein the plurality of performance evaluation indicators include an active adjustable capacity ratio indicator, a reactive adjustable capacity ratio indicator, a new energy abandoned power indicator, a distribution network voltage level indicator, a power loss indicator, and a power supply reliability indicator; A first determination unit is used to obtain an operation mechanism of the target compressed air energy storage power station to determine a distribution network power balance constraint, a node voltage constraint, a line transmission power constraint, and an energy storage system boundary constraint of the target compressed air energy storage power station according to the operation mechanism; A construction unit is used to construct the efficiency calculation model based on the power balance constraint of the distribution network, the node voltage constraint, the line transmission power constraint and the energy storage system boundary constraint, and in combination with a preset second-order cone constraint.

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 evaluating the comprehensive efficiency of a compressed air energy storage system as described in any one of claims 1 to 4.

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 comprehensive performance evaluation method of a compressed air energy storage system as described in any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the method for comprehensive performance evaluation of a compressed air energy storage system as described in any one of claims 1 to 4.

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