Method and system for evaluating reliability of wind and light storage system under multi-element energy storage configuration difference

Abstract

The invention discloses a method and a system for evaluating the reliability of a wind and light storage system under a multi-element energy storage configuration difference, and relates to the technical field of energy storage reliability evaluation, and the method comprises the steps: building a reliability model of the wind and light storage system; a wind power module in the reliability model is obtained by modeling wind speed by adopting a Weibull probability density function model; the photovoltaic module is obtained by modeling output power by using a power conversion formula and an accumulative probability density function of normal distribution; the load module is obtained by modeling a load by adopting a peak load membership function; the energy storage module is obtained by performing simulation modeling on the performance state of each energy storage sub-module by adopting a multi-state model; the constraint conditions comprise power constraint and capacity constraint; and based on the reliability model of the wind and light storage system, carrying out reliability evaluation of a safety and stability dimension, an operation value dimension and an energy storage consumption dimension on the wind and light storage system. According to the invention, the reliability of the wind-solar storage system can be predicted more accurately.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage reliability assessment, and in particular to a method and system for assessing the reliability of a wind-solar-storage system under different multi-energy storage configurations. Background Art

[0002] In wind and solar power generation systems, the application of energy storage technology is an important means to solve its instability. The emergence of various energy storage technologies such as electrochemical energy storage, Carnot battery energy storage and compressed air energy storage has provided new solutions for the reliability of wind and solar power generation. Electrochemical energy storage, especially lithium-ion batteries, has become one of the most commonly used energy storage technologies due to its high energy density and rapid response capability; Carnot battery energy storage uses thermal energy to convert into electrical energy, has a high energy conversion efficiency, and is suitable for large-scale energy storage applications; compressed air energy storage converts electrical energy into compressed air for storage, which is suitable for large-scale and long-term energy storage.

[0003] It can be seen that energy storage technology plays an important role in wind and solar power generation systems, so the research on reliability assessment methods and models is still particularly important. Reliability assessment refers to the use of quantitative and qualitative methods to analyze the performance of the system under specific conditions and evaluate its reliability and stability under different circumstances. For wind, solar and storage systems, reliability assessment not only involves the performance of the energy storage equipment itself, but also includes factors such as the volatility of wind and photovoltaic power generation, changes in load demand, and so on. Therefore, it is particularly necessary to establish a reliability assessment model and indicator system that comprehensively considers multiple energy storage configurations. Summary of the invention

[0004] The purpose of this application is to provide a reliability assessment method and system for a wind-solar-storage system under different multi-energy storage configurations, which can more accurately predict the reliability of the system.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a method for evaluating the reliability of a wind-solar-storage system under different multi-energy storage configurations, including: A reliability model of a wind-solar-storage system is established; the reliability model includes a wind power module, a photovoltaic module, a load module, an energy storage module and multiple constraints; the wind power module is obtained by modeling the wind speed using a Weibull probability density function model; the photovoltaic module is obtained by modeling the output power using a power conversion formula and a cumulative probability density function of a normal distribution; the load module is obtained by modeling the load using a peak load membership function; the energy storage module includes an electrochemical energy storage submodule, a Carnot battery energy storage submodule and a compressed air energy storage submodule; the energy storage module is obtained by simulating and modeling the performance status of each energy storage submodule using a multi-state model; the constraints include power constraints and capacity constraints.

[0006] Based on the reliability model of the wind-solar-storage system, the reliability of the wind-solar-storage system is evaluated in terms of safety and stability, operation value and energy storage and absorption.

[0007] In a second aspect, the present application provides a wind-solar-storage system reliability assessment device under different multi-energy storage configurations, comprising: A model building module is used to establish a reliability model of a wind-solar-storage system; the reliability model includes a wind power module, a photovoltaic module, a load module, an energy storage module and multiple constraints; the wind power module is obtained by modeling the wind speed using a Weibull probability density function model; the photovoltaic module is obtained by modeling the output power using a power conversion formula and a cumulative probability density function of a normal distribution; the load module is obtained by modeling the load using a peak load membership function; the energy storage module includes an electrochemical energy storage submodule, a Carnot battery energy storage submodule and a compressed air energy storage submodule; the energy storage module is obtained by simulating and modeling the performance status of each energy storage submodule using a multi-state model; the constraints include power constraints and capacity constraints.

[0008] The reliability assessment module is used to conduct reliability assessment on the wind-solar-storage system in terms of safety and stability, operation value and energy storage and consumption based on the reliability model of the wind-solar-storage system.

[0009] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides a reliability assessment method and system for a wind-solar-storage system under different multivariate energy storage configurations. The method constructs a reliability model for a wind-solar-storage system. In the model construction, the wind power module simulates the wind speed using the Weibull probability density function model. The photovoltaic module simulates the output power using the power conversion formula and the cumulative probability density function of the normal distribution. The load module simulates the load using the peak load membership function. The energy storage module simulates the performance state of each energy storage submodule using a multi-state model. The constraints of the model include power constraints and capacity constraints. Based on this reliability model, the wind-solar-storage system is evaluated for reliability in three aspects: safety and stability, operating efficiency, and energy storage absorption. The present application can more accurately predict the reliability of a wind-solar-storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0011] Figure 1This is an application environment diagram of a wind-solar-storage system reliability assessment method under different multi-energy storage configurations in one embodiment of the present application.

[0012] Figure 2 A schematic diagram of reliability assessment of a wind-solar-storage system under a multi-energy storage configuration provided in one embodiment of the present application.

[0013] Figure 3 A schematic diagram of the functional modules of a wind-solar-storage system reliability assessment system under different multi-energy storage configurations provided in one embodiment of the present application. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0015] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0016] Embodiment 1 like Figure 1 As shown, this embodiment provides a method for evaluating the reliability of a wind-solar-storage system under different multi-energy storage configurations, including: Step 101: Establish a reliability model of the wind-solar-storage system; the reliability model includes a wind power module, a photovoltaic module, a load module, an energy storage module and multiple constraints; the wind power module is obtained by modeling the wind speed using a Weibull probability density function model; the photovoltaic module is obtained by modeling the output power using a power conversion formula and a cumulative probability density function of a normal distribution; the load module is obtained by modeling the load using a peak load membership function; the energy storage module includes an electrochemical energy storage submodule, a Carnot battery energy storage submodule and a compressed air energy storage submodule; the energy storage module is obtained by simulating and modeling the performance status of each energy storage submodule using a multi-state model; the constraints include power constraints and capacity constraints.

[0017] Step 102: Based on the reliability model of the wind-solar-storage system, reliability evaluation of the wind-solar-storage system is performed in terms of safety and stability, operation value, and energy storage and absorption.

[0018] In this embodiment, when executing step 101, the specific steps may be as follows: like Figure 2As shown in the figure, according to the structure of the wind-solar-storage system, the wind-solar-storage system is divided into four modules: wind power module, photovoltaic module, load module and energy storage module. By constructing the Weibull distribution model of wind speed, the normal distribution model of solar intensity and the peak load membership function of load, the wind power output, photovoltaic output and load forecasting models are constructed in turn, and the multi-state model of multivariate energy storage is constructed in turn according to the SOH decay process of electrochemical energy storage, the capacity decay process of Carnot battery and compressed air energy storage.

[0019] Specifically, the uncertainty of the wind turbine output sequence of the wind power module mainly comes from the inherent intermittent, random and volatile nature of wind speed. In order to model the wind speed, this embodiment adopts the Weibull probability density function model. Assuming that the wind speed of the wind power generation system follows a two-parameter Weibull distribution, its Weibull probability density function can be expressed as shown in formula (1): (1).

[0020] Where c and k are the scale parameter (m / s) and shape parameter of the Weibull probability density function model respectively; v is the random variable wind speed (m / s); is the probability density function of wind speed.

[0021] Then, integrate equation (1) to obtain the probability density function of wind speed: (2).

[0022] In the formula, is the cumulative distribution function (CDF) of wind speed.

[0023] Next, the inverse function of equation (2) is obtained to obtain the wind speed model, and then the output model of the wind turbine is obtained: (3).

[0024] (4).

[0025] (5).

[0026] In the formula, is the output power of the wind turbine at time i, A, B, and C represent the relevant parameters of wind power output, is the rated power of the wind turbine, They respectively represent the rated wind speed, cut-in wind speed and cut-out wind speed of the wind turbine.

[0027] Specifically, the construction of the photovoltaic module is as follows: The output sequence of the photovoltaic module's photovoltaic motor group is related to the light radiation. The power conversion formula can be used to calculate the corresponding output power of the photovoltaic group. Based on the cumulative probability density function of the normal distribution, the probability under each light intensity is calculated and simulated and predicted. , the conversion formula is: (6).

[0028] In the formula, is the power of the photovoltaic unit at time i; is the rated power of the photovoltaic unit; The light radiance given for a standard environment is usually 1kW / m²; It is the specific light radiance, usually 0.15kW / m².

[0029] Specifically, the construction of the load module is as follows: The load module in this embodiment is modeled using the peak load membership function. Assume that the peak load value of the load group is , the load value range is divided into M intervals, and the ratio of each load to the peak load is the set : (7).

[0030] In the formula, It indicates the ratio of the load in the xth interval to the peak load.

[0031] The corresponding probability set in each interval is , as follows: (8).

[0032] In the formula, Represents the probability that the load is in the xth interval.

[0033] Then the output sequence of the load can be obtained by using the sequential Monte Carlo simulation method.

[0034] Specifically, in this embodiment, the construction of the energy storage module is as follows: The reliability model of the energy storage module covers the electrochemical energy storage submodule, the Carnot battery energy storage submodule and the compressed air energy storage submodule, and the multi-state model is used to simulate and model the performance status of these energy storage submodules. In particular, in the field of electrochemical energy storage, from the perspective of capacity, the SOH (State of Health) of the battery compartment can be defined as the ratio of the current rated capacity of the battery compartment to the initial rated capacity. The SOH of the battery compartment can reflect the degradation of the battery compartment, whether gradual or sudden, and it is a way to measure the performance and health of the battery compartment. At the initial moment, the SOH value of the battery compartment is 100%, and when the SOH value of the battery compartment drops to a certain threshold, it indicates that the battery compartment has become a faulty component.

[0035] Specifically, for a storage battery compartment , assuming that it can be divided into different states, using Indicates different battery compartment states. For each distinguished state, it corresponds to a certain battery compartment SOH state range: (9).

[0036] In the formula, is the xth state of electrochemical energy storage, are the upper and lower bounds of the SOH level corresponding to the x-th state of the battery compartment.

[0037] set up During the period, the performance state of the electrochemical energy storage battery compartment is , then the SOH of the electrochemical energy storage battery compartment during this period can be expressed as: (10).

[0038] In the formula, Indicates that the electrochemical energy storage battery compartment is The ratio of the total capacity of the time period to the rated capacity, Indicates that the electrochemical energy storage battery compartment is Performance status of the time period.

[0039] Similarly, for the Carnot battery energy storage submodule and the compressed air energy storage submodule, considering the reliability changes over time due to the loss of life, the energy conversion efficiency gradually decreases with the increase of the number of cycles. According to the change of energy conversion efficiency attenuation, a multi-state model of two types of energy storage is established: (11).

[0040] (12).

[0041] In the formula, They represent the state sets of Carnot battery energy storage and compressed air energy storage respectively; They represent the xth state of Carnot battery energy storage and compressed air energy storage respectively; They represent the state numbers of Carnot battery energy storage and compressed air energy storage respectively.

[0042] set up During this period, Carnot battery energy storage and compressed air energy storage were respectively , The energy conversion efficiency of the two types of energy storage in this period can be expressed as: (13).

[0043] (14).

[0044] In the formula, Represents Carnot battery energy storage and compressed air energy storage respectively. The expected energy conversion efficiency within the time period, are the upper and lower bounds of the energy conversion efficiency level corresponding to the x-th state of the Carnot battery, are the upper and lower bounds of the energy conversion efficiency level corresponding to the x-th state of compressed air, Represents Carnot battery energy storage and compressed air energy storage respectively. Performance status of the time period.

[0045] Among them, in this embodiment, when constructing the reliability model, the mathematical models of the wind power module, photovoltaic module, load module and energy storage module are considered, and the coordinated operation and coordination between these modules are considered to establish the reliability model of the wind-solar-storage system. According to the mathematical models and connection relationships between the modules, the capacity constraints and power constraints of the wind-solar-storage system are established. The specific constraints between the modules are shown in formulas (15)-(24): The power constraint is: (15).

[0046] (16).

[0047] (17). (18).

[0048] (19).

[0049] In the formula, They represent wind power output, photovoltaic output, load sequence and compensation power respectively. Indicates the charge and discharge power, Indicates the upper limit of power transmission, They represent the energy storage charging and discharging power, electrochemical energy storage charging and discharging power, Carnot battery energy storage and compressed air energy storage charging and discharging power respectively. They represent the proportion of electrochemical energy storage and Carnot battery energy storage charge and discharge to the total energy storage charge and discharge. Represent the energy storage capacity of electrochemical energy storage, Carnot battery energy storage and compressed air energy storage, respectively. Electrochemical energy storage The ratio of the total capacity of the time period to the rated capacity, Represents Carnot battery energy storage and compressed air energy storage The energy transfer efficiency of the time period, They represent the ratio of the storage capacity of electrochemical energy storage, Carnot battery energy storage and compressed air energy storage at time i to the total capacity at the current time. represents the i-th moment, Indicates the total simulation time. Indicates the charging and discharging period between two adjacent moments.

[0050] The capacity constraint is: (20).

[0051] (twenty one).

[0052] (twenty two).

[0053] (twenty three).

[0054] (twenty four).

[0055] In the formula, represents the total energy storage capacity, Indicates the upper and lower limits of energy storage capacity, They respectively represent the ratio of electrochemical energy storage and Carnot battery energy storage capacity to the total energy storage capacity.

[0056] In some embodiments, when executing step 102, the specific steps may be as follows: According to different configuration scenarios of multi-energy storage, the reliability differences of different types of energy storage are analyzed. The reliability evaluation method and index system of wind, solar and storage systems are proposed in terms of safety and stability, operation value, and energy storage consumption. Through the analysis of a series of indicators, the reliability of the system can be predicted more accurately, providing a scientific basis for the reliable and stable operation of the wind, solar and storage systems.

[0057] Specifically, the safety and stability dimensions include expected power shortage (LOLE), expected energy shortage (EENS), and load shedding probability (PLC): (25).

[0058] (26).

[0059] (27).

[0060] (28).

[0061] In the formula, Indicates the amount of power shortage for the load. Indicates that the system exceeds the upper limit of operation.

[0062] Specifically, the operational value dimensions include the power shortage probability (LOLP), power utilization rate (PU), and output power fluctuation (OPF) of the wind, solar and storage combined system: (29).

[0063] (30).

[0064] (31).

[0065] Energy storage consumption dimensions include energy storage consumption margin (ESCM), energy storage non-recharge rate (NRR), and energy storage non-discharge rate (NDR): (32).

[0066] (33).

[0067] (34).

[0068] Finally, based on the reliability assessment results of the wind, solar and storage systems in the three dimensions of safety and stability, operational value, and energy storage and absorption, the reliability of the wind, solar and storage systems is accurately assessed.

[0069] Embodiment 2 like Figure 3 As shown, this embodiment provides a wind-solar-storage system reliability assessment device under different multi-energy storage configurations, including: The model building module 301 is used to establish a reliability model of the wind-solar-storage system; the reliability model includes a wind power module, a photovoltaic module, a load module, an energy storage module and multiple constraints; the wind power module is obtained by modeling the wind speed using a Weibull probability density function model; the photovoltaic module is obtained by modeling the output power using a power conversion formula and a cumulative probability density function of a normal distribution; the load module is obtained by modeling the load using a peak load membership function; the energy storage module includes an electrochemical energy storage submodule, a Carnot battery energy storage submodule and a compressed air energy storage submodule; the energy storage module is obtained by simulating and modeling the performance status of each energy storage submodule using a multi-state model; the constraints include power constraints and capacity constraints.

[0070] The reliability assessment module 302 is used to perform reliability assessment on the wind-solar-storage system in terms of safety and stability, operation value and energy storage and consumption based on the reliability model of the wind-solar-storage system.

[0071] In summary, this application has the following technical effects: (1) This application divides the wind-solar-storage system into wind power module, photovoltaic module, load module and energy storage module under the consideration of multi-energy storage access, and constructs a reliability model of the wind-solar-storage system under the consideration of large-scale energy storage configuration differences. For the differences in multi-energy storage configurations, analyzing the reliability of their access to the wind-solar system has certain reference value, filling the gap in this research field.

[0072] (2) This application takes into account the capacity decay process of the electrochemical energy storage system and the expected decay process of the energy conversion efficiency of the Carnot battery and the compressed air energy storage system. Sampling detection and fitting of relevant data quantify the relationship between the performance decay and the number of cycles of the three types of energy storage systems, and constructs a multi-state model of multivariate energy storage, which makes the calculation results more accurate and flexible.

[0073] (3) This application constructs a reliability assessment index system for wind, solar and storage systems, and proposes nine types of assessment indicators for wind, solar and storage systems under different energy storage configurations from the three dimensions of safety and stability, operational value, and energy storage absorption. It studies the reliability assessment method for wind, solar and storage systems under multi-energy storage access, which can more accurately predict the reliability of the system and provide a scientific basis for the operation of wind, solar and storage systems.

[0074] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A reliability assessment method for a wind-solar-storage system under different multi-energy storage configurations, characterized in that: The reliability evaluation method comprises: Establish a reliability model of a wind-solar-storage system; the reliability model includes a wind power module, a photovoltaic module, a load module, an energy storage module and multiple constraints; the wind power module is obtained by modeling the wind speed using a Weibull probability density function model; the photovoltaic module is obtained by modeling the output power using a power conversion formula and a cumulative probability density function of a normal distribution; the load module is obtained by modeling the load using a peak load membership function; the energy storage module includes an electrochemical energy storage submodule, a Carnot battery energy storage submodule and a compressed air energy storage submodule; the energy storage module is obtained by simulating and modeling the performance status of each energy storage submodule using a multi-state model; the constraints include power constraints and capacity constraints; Based on the reliability model of the wind-solar-storage system, the reliability of the wind-solar-storage system is evaluated in terms of safety and stability, operation value and energy storage and absorption.

2. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 1 is characterized in that: The formula expression of the wind power module is: ； Where v is the random variable wind speed, is the output power of the wind turbine at time i, A, B, and C represent the relevant parameters of wind power output, is the rated power of the wind turbine, They respectively represent the rated wind speed, cut-in wind speed and cut-out wind speed of the wind turbine.

3. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 2 is characterized in that: The construction of the photovoltaic module specifically includes: According to the formula , construct photovoltaic modules; In the formula, is the power of the photovoltaic unit at time i; is the rated power of the photovoltaic unit; The illumination radiance given for the standard environment; is the specific light radiance.

4. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 3 is characterized in that: The construction of the load module specifically includes: According to the formula and formula , build load module; in, It indicates the ratio of the load in the xth interval to the peak load. Represents the probability that the load is in the xth interval.

5. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 4 is characterized in that: The formula expression of the electrochemical energy storage submodule in the energy storage module is: ； In the formula, Indicates that the electrochemical energy storage battery compartment is The ratio of the total capacity of the time period to the rated capacity, Indicates that the electrochemical energy storage battery compartment is Performance status of the time period.

6. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 5 is characterized in that: The formula expression of the Carnot battery energy storage submodule in the energy storage module is: ； ； in, represents the state set of Carnot battery energy storage, represents the xth state of Carnot battery energy storage, The number of states representing the energy storage of the Carnot battery, Indicates that Kano battery storage The expected energy conversion efficiency within the time period, are the upper and lower bounds of the energy conversion efficiency level corresponding to the x-th state of the Carnot battery, Indicates that Kano battery storage Performance status of the time period.

7. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 6 is characterized in that: The formula expression of the compressed air energy storage submodule in the energy storage module is: ； ； In the formula, represents the state set of compressed air energy storage, represents the xth state of compressed air energy storage; The number of states representing compressed air energy storage, Compressed air storage The expected energy conversion efficiency within the time period, are the upper and lower bounds of the energy conversion efficiency level corresponding to the x-th state of compressed air, Compressed air storage Performance status of the time period.

8. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 7 is characterized in that: The power constraint in the constraint condition is specifically: ； ； ； ； ； In the formula, They represent wind power output, photovoltaic output, load sequence and compensation power respectively. Indicates the charge and discharge power, Indicates the upper limit of power transmission, They represent the energy storage charging and discharging power, electrochemical energy storage charging and discharging power, Carnot battery energy storage and compressed air energy storage charging and discharging power respectively. They represent the proportion of electrochemical energy storage and Carnot battery energy storage charge and discharge to the total energy storage charge and discharge. Represent the energy storage capacity of electrochemical energy storage, Carnot battery energy storage and compressed air energy storage, respectively. Electrochemical energy storage The ratio of the total capacity of the time period to the rated capacity, Represents Carnot battery energy storage and compressed air energy storage The energy transfer efficiency of the time period, They represent the ratio of the storage capacity of electrochemical energy storage, Carnot battery energy storage and compressed air energy storage at time i to the total capacity at the current time. represents the i-th moment, Indicates the total simulation time. Indicates the charging and discharging period between two adjacent moments; The capacity constraint in the constraint condition is specifically: ； ； ； ； ； In the formula, represents the total energy storage capacity, Indicates the upper and lower limits of energy storage capacity, They respectively represent the ratio of electrochemical energy storage and Carnot battery energy storage capacity to the total energy storage capacity.

9. The reliability assessment method of a wind-solar-storage system under different multi-energy storage configurations according to claim 8 is characterized in that: Based on the reliability model of the wind-solar-storage system, the reliability of the wind-solar-storage system is evaluated in terms of safety and stability, operation value, and energy storage and consumption, including: According to the formula , , and , conduct reliability assessment on the wind-solar-storage system in terms of safety and stability; According to the formula , and , conduct reliability evaluation of the wind-solar-storage system in terms of operational value; According to the formula , and , conduct reliability assessment of the wind-solar-storage system in terms of energy storage and absorption; in, Indicates the amount of power shortage for the load. Indicates that the system exceeds the upper limit of operation.

10. A reliability assessment system for wind-solar-storage systems under different multi-energy storage configurations, characterized in that: include: A model building module is used to establish a reliability model of a wind-solar-storage system; the reliability model includes a wind power module, a photovoltaic module, a load module, an energy storage module and multiple constraints; the wind power module is obtained by modeling the wind speed using a Weibull probability density function model; the photovoltaic module is obtained by modeling the output power using a power conversion formula and a cumulative probability density function of a normal distribution; the load module is obtained by modeling the load using a peak load membership function; the energy storage module includes an electrochemical energy storage submodule, a Carnot battery energy storage submodule and a compressed air energy storage submodule; the energy storage module is obtained by simulating and modeling the performance state of each energy storage submodule using a multi-state model; the constraints include power constraints and capacity constraints; The reliability assessment module is used to conduct reliability assessment on the wind-solar-storage system in terms of safety and stability, operation value and energy storage and consumption based on the reliability model of the wind-solar-storage system.

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