User side energy storage capacity configuration method

Abstract

The invention discloses a user side energy storage capacity configuration method, which belongs to the field of electric power, and comprises the following steps of: establishing a charging capacity function in a valley value electricity price time period and a discharging capacity function in a peak value electricity price time period; the method comprises the following steps: calculating allowable charging amounts and allowable discharging amounts under different configuration amounts based on a real-time load curve, taking a smaller value in the allowable charging amounts and the allowable discharging amounts as charging and discharging amounts under the configuration amounts, and calculating charging and discharging times of a user in a time period under the configuration amounts according to load data of the user in previous years and the charging and discharging amounts under the configuration amounts; and fitting the relationship between the configuration quantity and the charging and discharging times to form an objective function, finding the maximum charging and discharging times of the objective function through a genetic algorithm, and taking the configuration quantity corresponding to the maximum charging and discharging times as the optimal configuration quantity. According to the user side energy storage capacity configuration method, the fluctuation of the user side load is reflected more truly, the more accurate optimal distribution and storage capacity is obtained, and the economic benefits of industrial and commercial energy storage investment are guaranteed.

Description

Technical Field

[0001] The present invention belongs to the electric power field, and in particular relates to a method for configuring energy storage capacity at a user side. Background Art

[0002] In recent years, with the rapid development of social economy and the continuous improvement of people's living standards, the frequency of peak loads in the power system has continued to increase, and the load of power users has shown a large peak-to-valley difference. Battery energy storage (hereinafter referred to as "energy storage") can achieve the temporal and spatial translation of electric energy with its flexible throughput capacity of electric power, and has the potential to cope with load fluctuations. At the same time, in recent years, the state has successively issued a series of policies such as "Guiding Opinions on Promoting the Development of Energy Storage Industry and Technology" and "Implementation Rules for Grid-connected Operation Management and Auxiliary Service Management of Electrochemical Energy Storage Power Stations in the Southern Region", actively encouraging the development of user-side energy storage. It can be foreseen that the main direction of the energy storage market in the future will extend to the user side. User-side energy storage directly acts on users. Without changing the user's electricity consumption behavior, it can directly enjoy the dividends of the electricity price system reform, and benefit from arbitrage through "low storage and high release", realizing user demand side management and load peak shaving and valley filling, and can also provide users with uninterrupted power supply in the event of a power outage, improving power supply reliability. In the future, with the deepening of the power system reform and the entry of power users into the power market, the development prospects of user-side energy storage will be very broad.

[0003] The existing storage capacity calculation scheme is relatively simple, only considering the average load of the enterprise during the peak period and the average load during the valley period within a year, so as to obtain the size of the storage capacity. For example, the invention patent application with application publication number CN112001598A discloses a method for evaluating energy storage configuration for different users based on energy storage selection, including based on battery energy storage market indicators, verifying energy storage technology and performance index parameters, constructing a battery energy storage selection evaluation model based on interval analytic hierarchy process, and evaluating energy storage batteries; selecting energy storage batteries, and establishing an energy storage full life cycle configuration model based on the time-of-use electricity price mechanism, energy storage battery technology and performance parameters; selecting different users' annual average load curves for energy storage configuration, and calculating the corresponding user energy storage evaluation index parameters.

[0004] This method can reflect the average load of the user in a year. However, since this method only calculates the average power load of the user in the same period of a year, it is difficult to reflect the load volatility, and the load conditions of enterprises in the same period of time on different working days are different. Therefore, it is difficult to characterize the load conditions of the user in the year with only the average load, and it is difficult to obtain the optimal storage capacity of the user. Summary of the invention

[0005] The purpose of the present invention is to provide a method for configuring energy storage capacity on the user side, so as to solve the problem that it is difficult to obtain the optimal energy storage capacity due to fluctuations in user power load in the existing energy storage capacity calculation scheme.

[0006] In order to achieve the above object, the technical solution of the present invention is as follows: The present invention relates to a method for configuring energy storage capacity at a user side, which comprises the following steps: S1. Collect the peak electricity price time period, valley electricity price time period and the user's real-time load curve in the user's area; S2. Establishing a charging function in the valley electricity price period and a discharging function in the peak electricity price period; S3. Set the configuration amount of energy storage configured by the user, substitute the configuration amount and real-time load curve into the charging amount function and the discharging amount function, calculate the allowable charging amount and the allowable discharging amount, take the smaller value of the allowable charging amount and the allowable discharging amount as the charge and discharge amount under the configuration amount, and calculate the number of charge and discharge times of the user in a period under the configuration amount according to the charge and discharge amount under the configuration amount; S4. Repeat S3 to obtain multiple sets of configuration amounts and the data of charge and discharge times under the corresponding configuration amounts, and obtain the relationship between the configuration amount and the charge and discharge times by fitting to form an objective function; S5. Find the maximum number of charge and discharge times of the objective function through a genetic algorithm, and take the configuration amount corresponding to the maximum number of charge and discharge times as the optimal configuration amount.

[0007] Preferably, the expression of the charging capacity function in the valley electricity price time period established in S2 is: (1), Among them, Q 充 is the allowed charging amount, t3 and t4 represent the starting time and ending time of the valley electricity price period, respectively. t Real-time load curve for users; (2), Among them, P max is the maximum capacity allowed for the user during this period, P N The transmission power of the energy storage configured for the user.

[0008] Preferably, the expression of the discharge capacity function in the peak electricity price time period established in S2 is: (3), Among them, Q 放 To allow the discharge amount, t1 and t2 represent the start time and end time of the peak electricity price period, respectively. t Real-time load curve for users; (4), Among them, P N The transmission power of the energy storage configured for the user.

[0009] Preferably, the calculation formula for calculating the number of charge and discharge times of the user in a period under the configured amount in S3 is: (5), Among them, n k is the number of charge and discharge times, n represents the nth charge and discharge, Q n is the charge of the nth charge-discharge cycle, (6), Among them, P N The transmission power of the energy storage configured for the user.

[0010] Preferably, the S4 is combined with formula (5) and formula (6) to obtain a relationship between the configuration amount and the number of charge and discharge times.

[0011] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects: The user-side energy storage capacity configuration method involved in the present invention establishes a charging amount function in a valley electricity price time period and a discharging amount function in a peak electricity price time period; calculates the allowable charging amount and the allowable discharging amount under different configuration amounts based on a real-time load curve, takes the smaller value of the allowable charging amount and the allowable discharging amount as the charging and discharging amount under the configuration amount, calculates the number of charging and discharging times of the user under the configuration amount in a year based on the user's load data in previous years and the charging and discharging amount under the configuration amount, fits the relationship between the configuration amount and the number of charging and discharging times, forms an objective function, finds the maximum number of charging and discharging times of the objective function through a genetic algorithm, and takes the configuration amount corresponding to the maximum number of charging and discharging times as the optimal configuration amount, so as to more truly reflect the volatility of the user-side load, obtain a more accurate optimal storage capacity, and ensure the economic benefits of industrial and commercial energy storage investment. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] FIG1 is a flow chart of a method for configuring energy storage capacity on the user side according to the present invention. DETAILED DESCRIPTION

[0013] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with examples. The following examples are used to illustrate the present invention but are not used to limit the scope of the present invention.

[0014] See attached Figure 1 As shown, the present invention relates to a method for configuring energy storage capacity on the user side, comprising the following steps: S1. Collect the peak electricity price time period (t1, t2), valley electricity price time period (t3, t4) and the user's real-time load curve P t .

[0015] S2. Establishing a charging function in the valley electricity price period and a discharging function in the peak electricity price period; The expression of the charging capacity function during the valley electricity price period is: (1), Among them, Q 充 is the allowed charging amount, t3 and t4 represent the starting time and ending time of the valley electricity price period, respectively. t Real-time load curve for users; (2), Among them, P max is the maximum capacity allowed for the user during this period, P N The transmission power of the energy storage configured for the user; The expression of the discharge capacity function during the peak electricity price period is: (3), Among them, Q 放 To allow the discharge amount, t1 and t2 represent the start time and end time of the peak electricity price period, respectively. t Real-time load curve for users; (4), Among them, P N The transmission power of the energy storage configured by the user. The configuration amount can be calculated by the transmission power size P of the energy storage configured. N 2 times, that is, the configuration amount is 2P N .

[0016] S3. Set the configuration amount of energy storage configured by the user, substitute the configuration amount and real-time load curve into the charging amount function and the discharging amount function, calculate the allowable charging amount and the allowable discharging amount, and take the smaller value of the allowable charging amount and the allowable discharging amount as the charge and discharge amount Q under the configuration amount, that is, Q=min(Q 充 , Q 放 ), calculate the number of charge and discharge times of the user within one year under the configuration amount according to the user's load data in previous years and the charge and discharge amount under the configuration amount; The user's load data in previous years refers to the user's load situation in each time period, which is a collection of the amount of electricity used by the user at each moment in a certain time period. Generally, one time period is one year.

[0017] The calculation formula for the number of charge and discharge times of the user in the next time period under the configuration amount is: (5), Among them, n kis the number of charge and discharge times, n represents the nth charge and discharge, Q n is the charge of the nth charge-discharge cycle, (6), Among them, P N The transmission power of the energy storage configured for the user.

[0018] S4. Repeat S3 to obtain multiple sets of configuration amounts and the data of charge and discharge times under the corresponding configuration amounts. Combine equation (5) and equation (6) to obtain the relationship between the configuration amount and the charge and discharge times by fitting to form an objective function. The objective function can be expressed as: ; S5. Find the maximum charge and discharge times of the objective function through a genetic algorithm, and take the configuration amount corresponding to the maximum charge and discharge times as the optimal configuration amount. The genetic algorithm is a conventional solution in this field and does not belong to the content to be protected by the present invention. The steps of the genetic algorithm are:

[0019] S5.1. Generate the initial population: Randomly generate several storage capacities as the initial population P(0). Each storage capacity is an individual, and each individual is a candidate for a solution. Random numbers can be used to generate the initial population.

[0020] S5.2. Individual evaluation: In the tth iteration, the number of charge and discharge times at various storage capacities in the population P(t) is calculated as the evaluation indicator for each individual.

[0021] S5.3. Select excellent individuals: select individuals according to a certain selection probability based on the individual's maximum charge and discharge times. The purpose of the selection operation is to directly pass on the optimized individuals to the next generation or to generate new individuals through pairing and crossover and then pass them on to the next generation.

[0022] S5.4. Crossover and mutation operations: Crossover operation refers to exchanging genes of selected parent individuals to generate new offspring individuals; mutation operation refers to randomly mutating certain genes of an individual to generate new offspring individuals.

[0023] S5.5. Form a new generation of population: merge the parent generation and the offspring to form a new population P(t+1), and discard some individuals to control the population size. Usually a certain number of excellent individuals are retained as parents to ensure the convergence of the algorithm.

[0024] The present invention is described in detail above in conjunction with the embodiments, but the contents described are only preferred embodiments of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of application of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for configuring energy storage capacity on the user side, characterized in that: It includes the following steps: S1. Collect the peak electricity price time period, valley electricity price time period and the user's real-time load curve in the user's area; S2. Establishing a charging function in the valley electricity price period and a discharging function in the peak electricity price period; S3. Set the configuration amount of energy storage configured by the user, substitute the configuration amount and real-time load curve into the charging amount function and the discharging amount function, calculate the allowable charging amount and the allowable discharging amount, take the smaller value of the allowable charging amount and the allowable discharging amount as the charge and discharge amount under the configuration amount, and calculate the number of charge and discharge times of the user in a period under the configuration amount according to the charge and discharge amount under the configuration amount; S4. Repeat S3 to obtain multiple sets of configuration amounts and the data of charge and discharge times under the corresponding configuration amounts, and obtain the relationship between the configuration amount and the charge and discharge times by fitting to form an objective function; S5. Find the maximum number of charge and discharge times of the objective function through a genetic algorithm, and take the configuration amount corresponding to the maximum number of charge and discharge times as the optimal configuration amount.

2. The method for configuring energy storage capacity on the user side according to claim 1, characterized in that: The expression of the charging capacity function in the valley electricity price period established in S2 is: （1）， Among them, Q 充 is the allowed charging amount, t3 and t4 represent the starting time and ending time of the valley electricity price period, respectively. t Real-time load curve for users; （2）， Among them, P max is the maximum capacity allowed for the user during this period, P N The transmission power of the energy storage configured for the user.

3. The method for configuring energy storage capacity on the user side according to claim 1, characterized in that: The expression of the discharge capacity function in the peak electricity price time period established in S2 is: （3）， Among them, Q 放 To allow the discharge amount, t1 and t2 represent the start time and end time of the peak electricity price period, respectively. t Real-time load curve for users; （4）， Among them, P N The transmission power of the energy storage configured for the user.

4. The method for configuring the energy storage capacity on the user side according to claim 1, characterized in that: The calculation formula for calculating the number of charge and discharge times of the user in the next time period of the configured amount in S3 is: （5）， Among them, n k is the number of charge and discharge times, n represents the nth charge and discharge, Q n is the charge of the nth charge-discharge cycle, （6）， Among them, P N The transmission power of the energy storage configured for the user.

5. The method for configuring the energy storage capacity on the user side according to claim 4, characterized in that: The S4 described above combines equation (5) and equation (6) to obtain an expression for the relationship between the configuration amount and the number of charge and discharge times.

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