Electric energy storage credible capacity evaluation method considering power supply and demand factors

Abstract

The invention discloses an electric energy storage credible capacity evaluation method considering power supply and demand factors, and relates to the technical field of power dispatching, and the method comprises the steps: collecting electric energy storage equipment operation data and power supply operation data; based on the electric energy storage equipment operation data and the electric power supply operation data, constructing a new energy and hydropower dispatching model for evaluating the balance of the electric power system, and calculating the electric power adequacy, the electric quantity adequacy and the electric power supply tension duration; based on the electric power adequacy and the electric power adequacy distribution characteristics, calculating an electric power adequacy correction coefficient; calculating a capacity service duration correction coefficient based on the average value of the total duration of the power supply shortage period; the credible capacity of the electric energy storage is calculated by integrating the electric quantity adequacy correction coefficient, the capacity service duration correction coefficient and the equipment reliability correction coefficient, and the credible capacity of the electric energy storage can be evaluated more comprehensively by introducing the electric quantity adequacy correction coefficient, the capacity service duration correction coefficient and the equipment reliability correction coefficient.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power dispatching, and in particular to a method for evaluating the credible capacity of electric energy storage taking into account factors of power supply and demand. Background Art

[0002] Trusted capacity is an important basic data reported by market players in the capacity market. Market operators are responsible for evaluating the trusted capacity of different types of market members. On this basis, market operators organize market members to declare capacity prices, and clear the winning capacity of various market members according to their grid capacity needs. Trusted capacity is essentially the effective power generation output of different types of power sources after considering various types of influencing factors. The trustworthy capacity transactions in the capacity market are essentially to meet the capacity requirements during grid operation. The factors affecting the power generation output of different types of power sources are different, resulting in different methods for evaluating their trusted capacity. As an emerging market player, the current trusted capacity evaluation of electric energy storage refers to conventional power supply evaluation methods, focusing on the impact of equipment reliability. In fact, as an electric energy storage device, the main influencing factors of electric energy storage power generation output are the overall power supply and demand of the grid and the requirements for the duration of capacity service provision. The specific situation is as follows:

[0003] The power supply margin has a great impact on the capacity service of electric energy storage. Electric energy storage does not have the ability to store electric energy for a long time, that is, electric energy storage can only store and release electric energy on a single operating day. If electric energy storage is required to release electric energy and provide capacity services, then the operating day must have a certain power supply margin, that is, the electric energy storage is allowed to charge during the period of surplus power supply, as a basic condition for discharging during the period of tight power supply that requires capacity services;

[0004] The capacity service market demand has a great impact on the capacity service capability of electric energy storage. Limited by its own storage capacity, electric energy storage needs to meet the discharge limit requirements according to the discharge time of its maximum exchange power.

[0005] The above two factors show that the reliable capacity of electric energy storage is not only related to the reliability of its own equipment, but also to the supply and demand of electricity. The current reliable capacity assessment method only considers the reliability of equipment, which will cause the evaluation result of the reliable capacity of electric energy storage to be too high, and there are two specific problems:

[0006] When the overall power supply of the power grid is tight, there will be no charging opportunity for energy storage and it will not be able to provide capacity services, resulting in unavailability of capacity services;

[0007] If the grid requires capacity services for a longer period of time, the duration of capacity services that electric energy storage can provide will not meet operational requirements, or the capacity services provided will be lower than its credible capacity level. Summary of the invention

[0008] In view of the problems existing in the existing power grid, the present invention is proposed.

[0009] Therefore, the problem to be solved by the present invention is how to improve the accuracy of the evaluation results of the reliable capacity of electric energy storage.

[0010] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0011] In a first aspect, an embodiment of the present invention provides a method for evaluating the trusted capacity of an electric energy storage device taking into account power supply and demand factors, which includes collecting operation data of an electric energy storage device and power supply operation data;

[0012] Based on the operation data of electric energy storage equipment and power supply, a new energy and hydropower dispatching model for evaluating the balance of the power system is constructed;

[0013] Based on the new energy and hydropower dispatch model of power system balance, calculate the power surplus, power surplus and power supply shortage duration;

[0014] Based on the power surplus and power surplus distribution characteristics, calculate the power surplus correction coefficient;

[0015] Calculate the capacity service duration correction factor based on the average total duration during the power supply shortage period;

[0016] The reliable capacity of the electric energy storage is calculated by combining the power surplus correction factor, capacity service time correction factor and equipment reliability correction factor.

[0017] As a preferred solution of the method for evaluating the reliable capacity of electric energy storage considering the power supply and demand factors of the present invention, the operating data of the electric energy storage device includes the exchange power, storage capacity and fault data of the same type of equipment, and the basic power supply data includes the daily power load, new energy power generation, conventional power supply start and stop status and power generation capacity of each operation day.

[0018] As a preferred solution of the method for evaluating the reliable capacity of electric energy storage considering the power supply and demand factors of the present invention, wherein: the construction of a new energy and hydropower dispatching model for evaluating the balance of the power system based on the operation data of the electric energy storage device and the power supply operation data includes constructing a new energy and hydropower dispatching model with the goal of maximizing the balance of the remaining power generation demand, which is expressed as:

[0019]

[0020]

[0021] in, are the remaining power generation demand in period t of the operating day and the average remaining power generation demand in each period of the operating day, NT and ΔT are the number of optimized periods and time intervals, respectively. are the power generation output of hydropower h and new energy power station n during operation day d and time period t, NH and NN are the number of hydropower stations and new energy power stations respectively. is the power load demand during period t of the operating day, They are the maximum and minimum power generation limits of hydropower h operation day d respectively.

[0022] As a preferred solution of the method for evaluating the reliable capacity of electric energy storage considering the power supply and demand factors of the present invention, the new energy and hydropower dispatching model based on the balance of the power system calculates the power surplus, power surplus and power supply shortage duration, including calculating the power surplus of the operating day, that is, the ratio of the thermal power supply capacity to the power corresponding to the remaining power generation demand, which can be expressed as:

[0023]

[0024] In the formula, NG represents the number of thermal power units, is the maximum power output of thermal power unit g on operating day d, then Represents the thermal power supply capacity on the operating day, Represents the amount of electricity corresponding to the remaining power generation demand, Represents the power reserve on the operating day;

[0025] The power surplus on the operating day is calculated as the ratio of the maximum power generation output of thermal power to the maximum remaining power generation demand, which can be expressed as:

[0026]

[0027] In the formula, represents the maximum remaining generation demand, Represents the power adequacy on the operating day;

[0028] The calculation of the duration of power supply shortage on the operating day, that is, the ratio of the maximum power generation output of thermal power to the maximum remaining power generation demand, can be expressed as:

[0029]

[0030] In the formula, ε P Represents the threshold for judging the power supply shortage. If the judgment condition shown in the formula is met, the period is the power supply shortage period of the operation day. The total duration of the power supply shortage period throughout the day is counted and recorded as NTS d .

[0031] As a preferred solution of the method for evaluating the reliable capacity of electric energy storage considering the power supply and demand factors of the present invention, wherein: the calculation of the power surplus correction coefficient based on the power surplus and the power surplus distribution characteristics includes analyzing the power surplus and the power surplus distribution characteristics in the historical operation conditions, evaluating the impact of the power surplus on the electric energy storage capacity service, and calculating the power surplus correction coefficient. The operating days that need to provide capacity services in the historical operating days can use the power surplus as a judgment condition, that is:

[0032]

[0033] In the formula, ε DP is the judgment threshold of capacity service demand. If the power surplus on a certain operation day meets the above formula, all historical operation days are counted, and the total number of operation days requiring capacity service is recorded as NDR;

[0034] If there is a capacity service operation day, its power margin exceeds the judgment threshold, which can be expressed as:

[0035]

[0036] In the formula, ε DE Represents the power surplus judgment threshold. All historical operating days are counted, and the total number of operating days that meet the judgment conditions shown in the above formula is NDSR;

[0037] The power margin correction coefficient is defined as the ratio of the total number of operating days that meet the power margin judgment conditions to the total number of operating days that require capacity service, that is:

[0038]

[0039] In the formula, Represents the correction factor of the energy storage capacity surplus.

[0040] As a preferred solution of the method for evaluating the reliable capacity of electric energy storage considering the power supply and demand factors of the present invention, wherein: the calculation of the capacity service time correction coefficient based on the average total time of the power supply shortage period includes statistically calculating the total time of the power supply shortage period during the operation day that meets the judgment condition shown in the formula

[0041] The average value is the service time requirement of the electric energy storage capacity, which can be expressed as:

[0042]

[0043] In the formula, Representative satisfaction The execution date of the judgment condition shown, Represents the average value of all data on days that meet the conditions, and NTRN represents the service time requirement of electric energy storage capacity;

[0044] Comparing the service time requirement of electric energy storage capacity and the discharge time of electric energy storage, it is expressed as: |

[0045] NTRN>NTSD

[0046] In the formula, NTSD represents the discharge time of the energy storage, that is, the ratio of the storage capacity to the maximum exchange power, expressed as:

[0047]

[0048] In the formula, are the storage capacity and maximum exchange power of the electric energy storage s respectively;

[0049] The capacity service duration correction coefficient is a piecewise function. If the formula is satisfied,

[0050]

[0051] It is corrected according to the service time requirement of the energy storage capacity and the discharge time of the energy storage, otherwise the correction coefficient is 0, expressed as:

[0052]

[0053] In the formula, Represents the correction factor of the service time of the electric energy storage capacity.

[0054] As a preferred solution of the method for evaluating the reliable capacity of electric energy storage considering the power supply and demand factors of the present invention, wherein: the comprehensive power margin correction coefficient, the capacity service time correction coefficient and the equipment reliability correction coefficient, the calculation of the reliable capacity of the electric energy storage includes calculating the equipment reliability correction coefficient, and the equipment reliability correction coefficient is its failure rate, which is expressed as:

[0055]

[0056] In the formula, Represents the reliability correction factor of the electric energy storage equipment, α s is the failure rate of electric energy storage;

[0057] The power margin correction coefficient, capacity service time correction coefficient, and equipment reliability correction coefficient are added together to obtain a comprehensive correction coefficient, and then the reliable capacity of the electric energy storage is calculated, which is expressed as:

[0058]

[0059] Where P s Dmax , They represent the maximum exchange power and reliable capacity of the electric energy storage s respectively.

[0060] In a second aspect, an embodiment of the present invention provides an electric energy storage trusted capacity assessment system based on consideration of power supply and demand factors, which includes a data acquisition module for collecting operation data of the electric energy storage device and basic data of power supply;

[0061] Analysis module, used to count and analyze power supply and demand data and build new energy and hydropower dispatch models;

[0062] The evaluation module is used to calculate the power margin correction factor, the equipment reliability correction factor, and evaluate the reliable capacity of the electric energy storage device.

[0063] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as described in the first aspect of the present invention are implemented.

[0064] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as described in the first aspect of the present invention are implemented.

[0065] The beneficial effects of the present invention are as follows: by introducing a power surplus correction coefficient, a capacity service duration correction coefficient and an equipment reliability correction coefficient, the present invention can more comprehensively evaluate the reliable capacity of electric energy storage, and by analyzing the historical operation data of the power grid, calculating the power surplus, power surplus and power supply tension duration of each operating day, it can more accurately reflect the actual operation of the power grid, thereby improving the evaluation accuracy of the reliable capacity of electric energy storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0067] Figure 1 A flow chart of a reliable capacity assessment method for electric energy storage considering power supply and demand factors;

[0068] Figure 2 It is a module diagram of the reliable capacity assessment system of electric energy storage considering the power supply and demand factors; DETAILED DESCRIPTION

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0071] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0072] Example 1

[0073] Reference Figure 1-2 , which is the first embodiment of the present invention, and provides a method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors, including:

[0074] S1: Obtaining basic data

[0075] The purpose of this step is to obtain the basic data required for the evaluation.

[0076] Preferably, the required basic data includes electric energy storage operation data and power supply operation data. The specific data items and sources are:

[0077] The operation data of the energy storage system, including the maximum exchange power of the energy storage system, the maximum / minimum storage capacity and the failure data of the same type of equipment, are all derived from the design parameters of the energy storage system;

[0078] Power supply operation data, including daily power load, new energy power generation, conventional power supply on and off status and power generation capacity, all come from the power dispatching and control system.

[0079] S2: Construct a new energy and hydropower dispatch model for evaluating the balance of the power system

[0080] The purpose of implementing this step is to analyze the power supply situation on each operating day, statistically calculate the power surplus, power surplus and the duration of power supply tension, and on this basis evaluate the overall operation situation.

[0081] Preferably, a new energy and hydropower dispatching model with the goal of maximizing the balance of remaining power generation demand is constructed and solved. The regulation capacity of new energy power generation output is relatively poor, while the regulation capacity of hydropower power generation output is relatively strong. Constructing a new energy and hydropower dispatching model with the goal of maximizing the balance of remaining power generation demand and giving priority to the power generation output of new energy and hydropower can maximize the advantages of the strong regulation capacity of hydropower and reduce the impact of new energy power generation output on power supply. The model uses the variance of remaining power generation demand as the evaluation index of the balance of remaining power generation demand, and the optimization goal can be expressed as the minimum variance of remaining power generation demand; the constraints include power balance constraints and hydropower generation characteristics constraints, which can be expressed as:

[0082]

[0083]

[0084] In the formula, are the remaining power generation demand in period t of the operating day and the average remaining power generation demand in each period of the operating day, NT and ΔT are the number of optimized periods and time intervals, respectively. are the power generation output of hydropower h and new energy power station n during operation day d and time period t, NH and NN are the number of hydropower stations and new energy power stations respectively. is the power load demand during period t of the operating day, They are the maximum and minimum power generation limits of hydropower h operation day d respectively.

[0085] This model is essentially a convex quadratic programming problem, which can be solved by using the interior point method or calling commercial software packages such as Cplex to obtain the remaining power generation demand in each period of the operating day.

[0086] S3: A new energy and hydropower dispatching model based on the balance of the power system, calculating the power surplus, power surplus and power supply shortage duration

[0087] Preferably, the power adequacy of the operating day is evaluated, that is, the ratio of the thermal power supply capacity to the power corresponding to the remaining power generation demand, which can be expressed as:

[0088]

[0089] In the formula, NG represents the number of thermal power units. is the maximum power output of thermal power unit g on operating day d, then Represents the thermal power supply capacity on the operating day, Represents the amount of electricity corresponding to the remaining power generation demand, Represents the battery level on the operating day.

[0090] Preferably, the power adequacy on the operating day is evaluated, that is, the ratio of the maximum power generation output of thermal power to the maximum remaining power generation demand, which can be expressed as:

[0091]

[0092] In the formula, represents the maximum remaining generation demand, Represents the power surplus on the operating day.

[0093] Preferably, the duration of power supply shortage on the operating day is evaluated, that is, the sum of the time periods during which the difference between the ratio of the maximum power generation output of thermal power to the remaining power generation demand and the power surplus does not meet the threshold. The judgment condition can be expressed as:

[0094] In the formula, ε P Represents the threshold for judging power supply shortage.

[0095] If the judgment conditions shown in the formula are met, then this period is the power supply shortage period of the operation day. The total duration of the power supply shortage period throughout the day is counted and recorded as NTS d .

[0096] S4: Calculate the power surplus correction coefficient based on the power surplus and power surplus distribution characteristics

[0097] The purpose of this step is to evaluate the impact of power surplus on the capacity service of electric energy storage and calculate its power surplus correction coefficient by analyzing the power surplus and power surplus distribution characteristics in historical operation conditions. Limited by its own operating characteristics, electric energy storage can only store and release power on a single operating day. If the time is too long, its operating losses will increase significantly. Therefore, when and only when the power surplus of the power grid is low and market members are required to provide capacity services, and when the power surplus is high and there is surplus power, electric energy storage can provide capacity services by charging during the period of surplus power and discharging during the period of power shortage.

[0098] Preferably, the operating days that need to provide capacity services in the historical operating days can use the power surplus as a judgment condition, that is:

[0099]

[0100] In the formula, ε DP It is the threshold for judging capacity service demand.

[0101] If the power surplus on a certain operation day meets the above formula, there is a demand for capacity service on that operation day. All historical operation days are counted, and the total number of operation days that require capacity service is recorded as NDR.

[0102] Preferably, when there is an operating day for capacity service, the power surplus exceeds the judgment threshold, which indicates that there is a period of surplus power supply on the operating day, and the power storage can be charged and then discharged during the period of tight power supply to provide capacity service. The above judgment criteria can be expressed as:

[0103]

[0104] In the formula, ε DE Represents the threshold value for judging the power surplus. The judgment condition shown in the formula indicates that the electric energy storage can provide capacity service only when and only when the power surplus on that operating day is lower than the judgment condition and there is a demand for capacity service, and the power surplus exceeds the judgment condition and there is a period of surplus power supply for charging the power storage. The total number of operating days that meet the judgment condition shown in the formula is the NDSR after statistics are collected on all historical operating days.

[0105] Preferably, the electric energy storage power surplus correction coefficient is defined as the ratio of the total number of operating days that meet the power surplus judgment condition to the total number of operating days that require capacity service, that is:

[0106]

[0107] In the formula, Represents the correction factor of the energy storage capacity surplus.

[0108] S5: Calculate the capacity service duration correction coefficient based on the average total duration of the power supply shortage period

[0109] The purpose of this step is to take into account the capacity service duration requirements and to correct the energy storage capacity service. Due to the storage capacity limit of the energy storage itself, even if it is fully charged, if the capacity service duration exceeds its discharge duration, the energy storage must reduce the discharge power to meet the time requirements. For this reason, it is necessary to introduce a capacity service duration correction factor.

[0110] Preferably, the statistics satisfy the formula

[0111] The judgment condition shown is the total duration of the power supply shortage period during the operation day, and its average is the service time requirement of the electric energy storage capacity, which can be expressed as:

[0112]

[0113] In the formula, Representative satisfaction The execution date of the judgment condition shown, It represents the average value of all data on days that meet the operating conditions, and NTRN represents the service time requirement of electric energy storage capacity.

[0114] Preferably, the service time requirement of the energy storage capacity and the discharge time of the energy storage are compared. If the service time requirement of the energy storage capacity exceeds the discharge time of the energy storage, the reliable capacity will be corrected according to the service time requirement of the energy storage capacity, otherwise no correction is required. The above judgment conditions can be expressed as:

[0115] NTRN>NTSD

[0116] In the formula, NTSD represents the discharge time of the energy storage, that is, the ratio of the storage capacity to the maximum exchange power, which can be expressed as:

[0117] In the formula, are the storage capacity of the electric energy storage s and the maximum exchange power respectively.

[0118] Preferably, the electric energy storage capacity service time correction coefficient is a piecewise function. If the formula is satisfied, it is corrected according to the electric energy storage capacity service time requirement and the electric energy storage discharge time. Otherwise, the correction coefficient is 0, which can be expressed as:

[0119] In the formula, Represents the correction factor of the service time of the electric energy storage capacity.

[0120] S6: Evaluate the reliability correction factor of electric energy storage equipment

[0121] The purpose of implementing this step is to analyze the failure rate of the electric energy storage equipment and evaluate the reliability correction factor of the electric energy storage equipment.

[0122] Preferably, the reliability correction factor of the electric energy storage device is its failure rate, which can be expressed as:

[0123]

[0124] In the formula, Represents the reliability correction factor of the electric energy storage equipment, α s is the failure rate of the electric energy storage.

[0125] Step 6: Calculate the reliable capacity of the electric energy storage by combining the power surplus correction factor, capacity service time correction factor and equipment reliability correction factor

[0126] The purpose of implementing this step is to comprehensively consider factors such as the energy storage capacity surplus, capacity service time, equipment failure, etc., and evaluate its reliable capacity.

[0127] Calculate the equipment reliability correction factor, which is its failure rate and is expressed as:

[0128]

[0129] In the formula, Represents the reliability correction factor of the electric energy storage equipment, α s The failure rate of electric energy storage

[0130] Preferably, since the three influencing factors of power surplus, capacity service time and equipment failure are three types of factors that do not affect each other, it is necessary to add the power surplus correction coefficient, the capacity service time correction coefficient and the equipment reliability correction coefficient to obtain a comprehensive correction coefficient, and then calculate the reliable capacity of the electric energy storage, which can be expressed as:

[0131]

[0132] Where P s Dmax , They represent the maximum exchange power and reliable capacity of the electric energy storage s respectively.

[0133] Furthermore, this embodiment also provides an electric energy storage reliable capacity assessment system taking into account power supply and demand factors, including:

[0134] Data acquisition module, used to collect operation data of electric energy storage equipment and basic data of power supply;

[0135] Analysis module, used to count and analyze power supply and demand data and build new energy and hydropower dispatch models;

[0136] The evaluation module is used to calculate the power margin correction factor, the equipment reliability correction factor, and evaluate the reliable capacity of the electric energy storage device.

[0137] This embodiment also provides a computer device, which is applicable to the case of a method for evaluating the trusted capacity of electric energy storage considering power supply and demand factors, and includes a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to implement the method for evaluating the trusted capacity of electric energy storage considering power supply and demand factors as proposed in the above embodiment.

[0138] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0139] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as proposed in the above embodiment is implemented.

[0140] In summary, the present invention can more comprehensively evaluate the reliable capacity of electric energy storage by introducing the power surplus correction coefficient, the capacity service time correction coefficient and the equipment reliability correction coefficient. By analyzing the historical operation data of the power grid and calculating the power surplus, power surplus and power supply tension duration of each operation day, the actual operation of the power grid can be more accurately reflected, thereby improving the evaluation accuracy of the reliable capacity of electric energy storage.

[0141] Example 2

[0142] The second embodiment of the present invention provides a method for evaluating the reliable capacity of electric energy storage taking into account power supply and demand factors. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0143] In order to verify the effectiveness of the proposed method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors, the following experiment was conducted. The experimental objects include system A and system B, where system A is a traditional reliable capacity evaluation system for electric energy storage, and system B is an electric energy storage reliable capacity evaluation system considering power supply and demand factors using the present invention.

[0144] Data collection: Both System A and System B collect the same energy storage equipment operation data and power supply operation data. The data includes energy storage exchange power, storage capacity, failure data of the same type of equipment, and daily power load, new energy power generation, conventional power supply start and stop status and power generation capacity.

[0145] Model construction: The traditional evaluation method is used for system A, without considering the power supply and demand situation, and the trusted capacity is evaluated directly based on the equipment reliability.

[0146] Based on the collected data, a new energy and hydropower dispatching model for system B is constructed to evaluate the balance of the power system, and to calculate the power surplus, power surplus and duration of power supply tension.

[0147] Correction factor calculation: System A calculates the trusted capacity directly based on the equipment reliability.

[0148] System B calculates the power surplus correction coefficient based on the power surplus and power surplus distribution characteristics; calculates the capacity service duration correction coefficient based on the average total duration of the power supply tension period; and calculates the equipment reliability correction coefficient at the same time.

[0149] Trusted capacity calculation:

[0150] System A directly derives the trusted capacity.

[0151] System B calculates the credible capacity of the electric energy storage by combining the power surplus correction factor, capacity service time correction factor and equipment reliability correction factor.

[0152] Data Records:

[0153] During the experiment, the reliable capacity data of different systems were recorded on multiple operating days to ensure that the data were representative and repeatable.

[0154]

[0155] Table 1

[0156] From the data in Table 1, it can be seen that by comparing the trusted capacity data of system A and system B on different operating days, it can be clearly seen that after the trusted capacity evaluation method of electric energy storage considering power supply and demand factors is adopted, the trusted capacity of system B is significantly higher than that of system A under all test conditions. This is mainly reflected in the following aspects:

[0157] Impact of power adequacy correction coefficient: System B analyzes historical operation conditions and evaluates the impact of power adequacy on the capacity service of electric energy storage. The calculated power adequacy correction coefficients are all greater than 1. This means that after considering the power supply and demand, the system can more reasonably evaluate the available power of electric energy storage, thereby improving the credible capacity.

[0158] Function of the capacity service duration correction coefficient: During periods of tight power supply, system B calculates the capacity service duration correction coefficient to ensure that the system can provide sufficient capacity services during these periods. Experimental data shows that the capacity service duration correction coefficient of system B is greater than 1 on all operating days, further improving the system's reliable capacity.

[0159] Application of comprehensive correction coefficient: System B comprehensively considers the power surplus correction coefficient, capacity service time correction coefficient and equipment reliability correction coefficient, which makes its assessed reliable capacity more accurate and reliable. In contrast, System A only considers equipment reliability and ignores power supply and demand factors, resulting in a low reliable capacity assessment result.

[0160] Practical application effect: In practical applications, the B system can better adapt to changes in power supply and demand and provide more efficient electric energy storage services. When the power supply is sufficient, the B system can make full use of the power surplus and provide higher reliable capacity; when the power supply is tight, the B system can also ensure the necessary capacity service by adjusting the correction coefficient.

[0161] In summary, the energy storage reliable capacity assessment method that takes into account power supply and demand factors adopted by system B significantly improves the reliable capacity of the energy storage device and enhances the adaptability and reliability of the system. This shows that the present invention has significant innovation and advantages in practical applications.

[0162] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors, characterized by: include, Collecting data on the operation of electric energy storage equipment and power supply; Based on the operation data of electric energy storage equipment and power supply, a new energy and hydropower dispatching model for evaluating the balance of the power system is constructed; Based on the new energy and hydropower dispatch model of power system balance, calculate the power surplus, power surplus and power supply shortage duration; Based on the power surplus and power surplus distribution characteristics, calculate the power surplus correction coefficient; Calculate the capacity service duration correction factor based on the average total duration during the power supply shortage period; The reliable capacity of the electric energy storage is calculated by combining the power surplus correction factor, capacity service time correction factor and equipment reliability correction factor.

2. The method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as claimed in claim 1, characterized in that: The electric energy storage equipment operation data includes the electric energy storage exchange power, storage capacity and fault data of the same type of equipment, and the basic power supply data includes the daily power load, new energy power generation, conventional power supply start and stop status and power generation capacity.

3. The method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as claimed in claim 2, characterized in that: The construction of a new energy and hydropower dispatching model for evaluating the balance of the power system based on the operation data of the electric energy storage device and the operation data of the power supply includes constructing a new energy and hydropower dispatching model with the goal of maximizing the balance of the remaining power generation demand, which is expressed as: in, are the remaining power generation demand in period t of the operating day and the average remaining power generation demand in each period of the operating day, NT and ΔT are the number of optimized periods and time intervals, respectively. are the power generation output of hydropower h and new energy power station n during operation day d and time period t, NH and NN are the number of hydropower stations and new energy power stations respectively. is the power load demand during period t of the operating day, They are the maximum and minimum power generation limits of hydropower h operation day d respectively.

4. The method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as claimed in claim 3, characterized in that: The new energy and hydropower dispatching model based on the balance of the power system calculates the power surplus, power surplus and power supply shortage duration, including the calculation of the power surplus on the operating day, that is, the ratio of the thermal power supply capacity to the power corresponding to the remaining power generation demand, which can be expressed as: In the formula, NG represents the number of thermal power units, is the maximum power output of thermal power unit g on operating day d, then Represents the thermal power supply capacity on the operating day, Represents the amount of electricity corresponding to the remaining power generation demand, Represents the power reserve on the operating day; The power surplus on the operating day is calculated as the ratio of the maximum power generation output of thermal power to the maximum remaining power generation demand, which can be expressed as: In the formula, represents the maximum remaining generation demand, Represents the power adequacy on the operating day; The calculation of the duration of power supply shortage on the operating day, that is, the ratio of the maximum power generation output of thermal power to the maximum remaining power generation demand, can be expressed as: NG In the formula, ε P Represents the threshold for judging the power supply shortage. If the judgment condition shown in the formula is met, the period is the power supply shortage period of the operation day. The total duration of the power supply shortage period throughout the day is counted and recorded as NTS d .

5. The method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as claimed in claim 4, characterized in that: The calculation of the power surplus correction coefficient based on the power surplus and power surplus distribution characteristics includes analyzing the power surplus and power surplus distribution characteristics in the historical operation conditions, evaluating the impact of power surplus on the electric energy storage capacity service, and calculating the power surplus correction coefficient. The power surplus can be used as a judgment condition for the operation day that needs to provide capacity service in the historical operation day, that is: In the formula, ε DP is the judgment threshold of capacity service demand. If the power surplus on a certain operation day meets the above formula, all historical operation days are counted, and the total number of operation days requiring capacity service is recorded as NDR; If there is a capacity service operation day, its power margin exceeds the judgment threshold, which can be expressed as: In the formula, ε DE Represents the power surplus judgment threshold. All historical operating days are counted, and the total number of operating days that meet the judgment conditions shown in the above formula is NDSR; The power margin correction coefficient is defined as the ratio of the total number of operating days that meet the power margin judgment conditions to the total number of operating days that require capacity service, that is: In the formula, Represents the correction factor of the energy storage capacity surplus.

6. The method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as claimed in claim 5, characterized in that: The calculation of the capacity service duration correction coefficient based on the total duration average of the power supply shortage period includes the following statistical formula: The judgment condition shown is the total duration of the power supply shortage period during the operation day, and its average is the service time requirement of the electric energy storage capacity, which can be expressed as: In the formula, Representative satisfaction The execution date of the judgment condition shown, Represents the average value of all data on days that meet the conditions, and NTRN represents the service time requirement of electric energy storage capacity; Comparing the service time requirement of electric energy storage capacity and the discharge time of electric energy storage, it is expressed as: | NTRN>NTSD In the formula, NTSD represents the discharge time of the energy storage, that is, the ratio of the storage capacity to the maximum exchange power, expressed as: In the formula, are the storage capacity and maximum exchange power of the electric energy storage s respectively; The capacity service duration correction coefficient is a piecewise function. If the formula is satisfied, It is corrected according to the service time requirement of the energy storage capacity and the discharge time of the energy storage, otherwise the correction coefficient is 0, expressed as: In the formula, Represents the correction factor of the service time of the electric energy storage capacity.

7. The method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as claimed in claim 6, characterized in that: The comprehensive power margin correction coefficient, capacity service time correction coefficient and equipment reliability correction coefficient, the calculation of the reliable capacity of the electric energy storage includes the calculation of the equipment reliability correction coefficient, and the equipment reliability correction coefficient is its failure rate, which is expressed as: In the formula, Represents the reliability correction factor of the electric energy storage equipment, α s is the failure rate of electric energy storage; The power margin correction coefficient, capacity service time correction coefficient, and equipment reliability correction coefficient are added together to obtain a comprehensive correction coefficient, and then the reliable capacity of the electric energy storage is calculated, which is expressed as: In the formula, They represent the maximum exchange power and reliable capacity of the electric energy storage s respectively.

8. A system for evaluating the reliable capacity of electric energy storage based on consideration of power supply and demand factors, based on the method for evaluating the reliable capacity of electric energy storage based on consideration of power supply and demand factors as claimed in any one of claims 1 to 7, characterized in that: Also includes, Data acquisition module, used to collect operation data of electric energy storage equipment and basic data of power supply; Analysis module, used to count and analyze power supply and demand data and build new energy and hydropower dispatch models; The evaluation module is used to calculate the power margin correction factor, the equipment reliability correction factor, and evaluate the reliable capacity of the electric energy storage device.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the reliable capacity of electric energy storage considering power supply and demand factors as described in any one of claims 1 to 7 are implemented.

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