Energy storage configuration method, system, device and medium considering full life cycle benefits

Abstract

The present invention provides a method, system, device and medium for energy storage configuration considering the whole life cycle benefit. The method is to perform an analysis on the effective utilization of energy storage for the obtained annual power consumption dataset of energy storage users to generate an effective daily energy storage value sequence. After arranging it in ascending order of the effective daily energy storage value, the effective day corresponding to the median of the sequence is obtained as the typical day. And a whole life cycle benefit model of energy storage is constructed according to the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the obtained annual demand response data participated by the energy storage and the annual power outage loss reduction data of the energy storage, and the optimal capacity configuration strategy including the optimal configuration capacity and the optimal energy storage charge and discharge power is obtained by solving the whole life cycle benefit model of energy storage. On the basis of improving the accuracy of typical day screening, the present invention effectively balances the investment cost and application value of the energy storage system, thereby improving the rationality of energy storage capacity configuration and the utilization rate of the energy storage system.

Description

Technical Field

[0001] The present invention relates to the technical field of electrochemical energy storage, and in particular, to a method, system, device and medium for energy storage configuration considering the whole life cycle benefit. Background Art

[0002] Electrochemical energy storage is a new type of energy storage system, which can "store electricity" during the period when the grid electricity price is low and "discharge electricity" when the grid electricity price is high, and reduce the user's electricity cost through the operation mode of "peak shaving and valley filling". The capacity configuration of the energy storage system is crucial for its application effect: if the selected energy storage capacity is too large, although the charge and discharge capacity can be effectively improved, its investment is high, and due to the imbalance of the daily electricity load, there will be too much redundancy and low utilization rate; if the selected energy storage capacity is too small, although a high utilization rate can be achieved, the charge and discharge amount each time is small, and the overall investment value is reduced.

[0003] The existing energy storage capacity configuration methods usually determine the typical day based on the daily electricity average value found from the annual electricity load, and then configure according to the peak and valley loads corresponding to a certain peak-valley time period within the typical day. Although this method can guide the energy storage capacity configuration to a certain extent, it still has relatively large application defects: 1) Although the energy storage is "valley charging and peak discharging", the actual daily electricity also includes the electricity during the flat period. Without considering the influence of the electricity during the flat period, it is inevitable that the selected typical day based on the electricity average value is not accurate and reliable enough; 2) When specifically configuring, the whole life cycle benefit problem of the energy storage system is not comprehensively considered, resulting in difficulty in balancing the investment cost and application value of the energy storage system. Therefore, there is an urgent need to provide an energy storage capacity configuration method that can ensure reliable screening of typical days and effectively balance the investment cost and application value. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for energy storage configuration considering the whole life cycle benefit. By analyzing the effective utilization value of energy storage for the annual electricity consumption dataset to screen the typical days, and constructing an energy storage whole life cycle benefit model based on the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the data of the energy storage participating in the demand side response throughout the year and the data of the energy storage reducing power outage losses throughout the year to obtain the optimal capacity configuration strategy, it can effectively balance the investment cost and application value of the energy storage system on the basis of improving the accuracy of typical day screening, and further improve the rationality of energy storage capacity configuration and the utilization rate of the energy storage system.

[0005] In order to achieve the above purpose, it is necessary to provide a method, system, computer device and storage medium for energy storage configuration considering the whole life cycle benefit in view of the above technical problems.

[0006] In a first aspect, an embodiment of the present invention provides a method for energy storage configuration considering the benefits of the entire life cycle. The method includes the following steps:

[0007] Obtain the annual electricity consumption dataset of the energy storage user, and conduct an analysis of the effective utilization of energy storage on the annual electricity consumption dataset to generate a corresponding sequence of daily effective energy storage values;

[0008] Arrange the sequence of daily effective energy storage values in ascending order according to the daily effective energy storage values, and obtain the median of the sorted sequence of daily effective energy storage values. Use the effective day corresponding to the median as the typical day;

[0009] Construct an energy storage full life cycle benefit model based on the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the obtained data on the energy storage's annual participation in demand response and the energy storage's annual reduction in power outage losses;

[0010] Solve the energy storage full life cycle benefit model to obtain an optimal capacity configuration strategy; the optimal capacity configuration strategy includes the optimal configuration capacity and the optimal energy storage charge and discharge power.

[0011] Further, the step of conducting an analysis of the effective utilization of energy storage on the annual electricity consumption dataset to generate a corresponding sequence of daily effective energy storage values includes:

[0012] Obtain the daily basic load electricity consumption of the energy storage user, and based on the daily basic load electricity consumption, conduct effective data screening on the annual electricity consumption dataset to generate a corresponding annual energy storage effective day set;

[0013] Arrange the electricity consumption corresponding to all the effective days of energy storage in the annual energy storage effective day set in chronological order of dates to obtain a corresponding annual sequence of effective day electricity consumption;

[0014] Generate a corresponding sequence of daily effective energy storage values based on the total discharge amount and the total charge amount corresponding to the electricity consumption of each effective day in the annual sequence of effective day electricity consumption.

[0015] Further, the step of obtaining the daily basic load electricity consumption of the energy storage user and conducting effective data screening on the annual electricity consumption dataset based on the daily basic load electricity consumption to generate a corresponding annual energy storage effective day set includes:

[0016] Obtain the non-production load powers and their corresponding load factors of the energy storage user, and based on all the non-production load powers and their corresponding load factors, obtain the daily basic load electricity consumption;

[0017] Obtain the electricity data information in the annual electricity consumption dataset where the daily electricity consumption is greater than the daily basic load electricity consumption, and based on the electricity data information, generate the annual energy storage effective day set.

[0018] Further, the energy storage charge and discharge data includes charging duration, electricity load during the charging period, electricity price during the charging period, discharging duration, electricity load during the discharging period, and electricity price during the discharging period; the energy storage annual demand response data includes the number of responses, the duration of each response, and the corresponding response power; the energy storage annual power outage loss reduction data includes the number of times the energy storage reduces power outage losses through power supply, the duration of each power supply, and the corresponding power supply power;

[0019] The steps of constructing an energy storage full - life - cycle benefit model based on the energy storage charge and discharge data of each energy storage cycle within a typical day, as well as the obtained energy storage annual demand response data and energy storage annual power outage loss reduction data, include:

[0020] Based on the charging duration and discharging duration in each energy storage charge and discharge data, obtain the energy storage charge and discharge design time, and construct an energy storage investment cost model according to the energy storage charge and discharge design time, the unit power cost of the energy storage converter, and the unit capacity cost of the energy storage;

[0021] Based on the linear relationship between the energy storage operation and maintenance cost and the energy storage capacity, construct an energy storage annual operation and maintenance cost model;

[0022] Construct an energy storage peak - shaving and valley - filling revenue model according to the electricity load during the charging period, the electricity price during the charging period, the electricity load during the discharging period, and the electricity price during the discharging period in each energy storage charge and discharge data;

[0023] Construct corresponding energy storage demand response revenue models and energy storage power outage loss reduction models respectively according to the energy storage annual demand response data and the energy storage annual power outage loss reduction data;

[0024] Integrate the energy storage peak - shaving and valley - filling revenue model, the energy storage demand response revenue model, and the energy storage power outage loss reduction model to obtain an energy storage annual revenue model;

[0025] Perform full - life - cycle net present value calculation according to the energy storage annual revenue model, the energy storage annual operation and maintenance cost model, and the energy storage investment cost model to obtain the energy storage full - life - cycle benefit model.

[0026] Further, the energy storage investment cost model is expressed as:

[0027]

[0028] In the formula,

[0029]

[0030]

[0031] Wherein, represents the initial investment cost of the energy storage system; , and respectively represent the unit power cost of the energy storage converter, the unit capacity cost of the energy storage, and the unit capacity cost of the energy storage project construction; and respectively represent the energy storage power and the energy storage capacity; represents the designed charge-discharge time of the energy storage; and respectively represent the charging duration during the charging period and the discharging duration during the discharging period within the i-th energy storage cycle, ; N represents the total number of energy storage cycles within a typical day.

[0032] Furthermore, the annual income model of the energy storage is expressed as:

[0033]

[0034] In the formula,

[0035]

[0036]

[0037]

[0038]

[0039]

[0040] Among them, represents the annual income of the energy storage; , and respectively represent the peak shaving and valley filling income of the energy storage, the demand response income of the energy storage, and the reduction of power outage losses of the energy storage; and respectively represent the charging amount and the discharging amount during the i-th energy storage cycle; and respectively represent the charging duration and the electrical load during the charging period within the i-th energy storage cycle; and respectively represent the discharging duration and the electrical load during the discharging period within the i-th energy storage cycle; represents the energy storage capacity; and respectively represent the installed capacity of the transformer and the maximum load factor; and respectively represent the electricity price during the discharging period and the electricity price during the charging period within the i-th energy storage cycle; represents the number of responses; and respectively represent the The response duration and response power of the secondary participation in the response; Indicates the subsidy for unit electricity quantity of the response; Indicates the number of times of power outage loss reduction by energy storage power supply; and respectively represent the th power supply duration and power supply power of power outage reduction by energy storage power supply; Indicates the unit electricity quantity loss coefficient.

[0041] Furthermore, the energy storage full - life - cycle benefit model is expressed as:

[0042]

[0043] wherein, Represents the energy storage full - life - cycle benefit; Represents the annual income of the energy storage; Represents the operation years of the energy storage; Represents the capacity decay coefficient of the energy storage with the increase of operation years; and respectively represent the annual operation and maintenance cost of the energy storage system and the initial investment cost of the energy storage system; Represents the total operation years of the energy storage; Represents the annual net income discount rate of the energy storage.

[0044] On the second aspect, the embodiment of the present invention provides an energy storage configuration system considering the full - life - cycle benefit, and the system includes:

[0045] A data processing module, configured to obtain the annual power consumption data set of the energy storage user, and perform an analysis on the effective utilization of the energy storage for the annual power consumption data set to generate a corresponding effective daily energy storage value sequence;

[0046] A typical day screening module, configured to sort the effective daily energy storage value sequence in ascending order according to the effective daily energy storage value, and obtain the median of the sorted effective daily energy storage value sequence, and use the effective day corresponding to the median as the typical day;

[0047] An optimization model construction module, configured to construct an energy storage full - life - cycle benefit model according to the energy storage charge - discharge data of each energy storage cycle period in the typical day, as well as the obtained annual demand - side response data of the energy storage and the annual power outage loss reduction data of the energy storage;

[0048] A configuration strategy acquisition module, configured to solve the energy storage full - life - cycle benefit model to obtain an optimal capacity configuration strategy; the optimal capacity configuration strategy includes an optimal configuration capacity and an optimal energy storage charge - discharge power.

[0049] In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0050] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0051] The above application provides a method, system, device, and medium for energy storage configuration considering the full life cycle benefits. Through the method, an annual power consumption dataset of energy storage users is obtained, and an effective daily energy storage value sequence is generated by analyzing the effective utilization of the annual power consumption dataset. The effective daily energy storage value sequence is sorted in ascending order of the effective daily energy storage value, and the median of the sorted effective daily energy storage value sequence is obtained. The effective day corresponding to the median is used as the typical day. Then, according to the energy storage charge and discharge data of each energy storage cycle within the typical day, as well as the obtained energy storage's annual participation in demand response data and the energy storage's annual reduction in power outage loss data, an energy storage full life cycle benefit model is constructed, and the energy storage full life cycle benefit model is solved to obtain a technical solution for the optimal capacity configuration strategy including the optimal configuration capacity and the optimal energy storage charge and discharge power. Compared with the prior art, the energy storage configuration method considering the full life cycle benefits can not only effectively improve the accuracy of typical day screening by analyzing the effective utilization value of the annual power consumption dataset to screen the typical day, but also effectively balance the investment cost and application value of the energy storage system by constructing an energy storage full life cycle benefit model based on the energy storage charge and discharge data of each energy storage cycle within the typical day, as well as the energy storage's annual participation in demand response data and the energy storage's annual reduction in power outage loss data to obtain the optimal capacity configuration strategy, thereby improving the rationality of energy storage capacity configuration and the utilization rate of the energy storage system. Description of the Drawings

[0052] Figure 1 is a schematic flowchart of the energy storage configuration method considering the full life cycle benefits in an embodiment of the present invention;

[0053] Figure 2 is a schematic structural diagram of the energy storage configuration system considering the full life cycle benefits in an embodiment of the present invention;

[0054] Figure 3 is an internal structure diagram of the computer device in an embodiment of the present invention. Detailed Embodiments

[0055] In order to make the objectives, technical solutions, and beneficial effects of this application clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Obviously, the following described embodiments are part of the embodiments of the present invention and are only used to illustrate the present invention, but not to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0056] The energy storage configuration method considering the full life cycle benefits provided by the present invention can be understood as a method proposed based on the current application status that the typical day screening in the existing energy storage capacity configuration method is not accurate and reliable enough, and the investment cost and application value of the energy storage system are not considered, resulting in the inability to ensure the best energy storage utilization rate. By analyzing the effective utilization value of energy storage for the annual electricity consumption dataset to screen typical days, and based on the durations of different valley price time periods and peak price time periods within a typical day and the corresponding load curves, the energy storage charging amount and energy storage discharging amount of each energy storage cycle are statistically calculated. Combining the obtained data of the energy storage participating in the demand-side response throughout the year and the data of the energy storage reducing power outage losses throughout the year to construct an energy storage full life cycle benefit model for obtaining the optimal capacity configuration strategy, this energy storage capacity configuration optimization method is not only applicable to electrochemical energy storage, but other types of energy storage technologies and systems can also refer to it.

[0057] In one embodiment, as Figure 1 shown, a method for configuring energy storage considering the full life cycle benefits is provided, including the following steps:

[0058] S11. Obtain the annual electricity consumption dataset of the energy storage user, and conduct an analysis of the effective utilization of energy storage for the annual electricity consumption dataset to generate a corresponding sequence of effective daily energy storage values; among them, the energy storage user can be understood as an enterprise user that reduces the electricity cost by configuring an energy storage system, and the corresponding annual electricity consumption dataset can be understood as the annual electricity consumption data of the energy storage user obtained on a daily basis. In the actual production process, the daily electricity consumption of the energy storage user includes basic load electricity consumption and / or production load electricity consumption: the basic load electricity consumption can be understood as the electricity consumption corresponding to the load when the enterprise does not start production or the production equipment is under maintenance, including the basic electricity generated by the office load, equipment standby load, etc.; the production load electricity consumption can be understood as the electricity consumption corresponding to the equipment load during the enterprise's production and manufacturing, including the production electricity generated by motors, air compressors, production line equipment, etc.; generally, the production load electricity consumption is greater than the basic load electricity consumption.

[0059] The effective daily energy storage value sequence in this embodiment can be understood as being based on the daily basic load electricity consumption of the energy storage user, screening out the effective daily electricity consumption data with energy storage utilization in the annual electricity consumption dataset, and taking the difference between the electricity consumption during peak price periods and the electricity consumption during valley price periods in the effective daily electricity consumption data as the energy storage value sequence generated by the effective daily energy storage value. Specifically, the steps of performing an analysis on the annual electricity consumption dataset for effective energy storage utilization and generating the corresponding effective daily energy storage value sequence include:

[0060] Obtain the daily basic load electricity consumption of the energy storage user, and based on the daily basic load electricity consumption, perform effective data screening on the annual electricity consumption dataset to generate the corresponding annual effective energy storage day set; among them, the annual effective energy storage day set can be understood as screening out the daily electricity consumption data with effective energy storage utilization in the annual electricity consumption dataset based on the daily basic load electricity consumption, and using it as the basic analysis data for determining typical days in the future and adding it to the annual effective energy storage day set for use. Specifically, the steps of obtaining the daily basic load electricity consumption of the energy storage user, and based on the daily basic load electricity consumption, performing effective data screening on the annual electricity consumption dataset to generate the corresponding annual effective energy storage day set include:

[0061] Obtain the non-production load powers and corresponding load coefficients of the energy storage user, and based on all the non-production load powers and corresponding load coefficients, obtain the daily basic load electricity consumption; among them, the non-production load powers and the load coefficients corresponding to each non-production load specifically involved in the energy storage user vary depending on the actual application scenario and are not specifically limited here. Correspondingly, the daily basic load electricity consumption is expressed as:

[0062]

[0063] Among them, represents the daily basic load electricity consumption of the energy storage user; and respectively represent the power and load coefficient corresponding to the jth non-production load involved in the energy storage user; represents the total number of non-production loads involved in the energy storage user.

[0064] Obtain the power data information of the daily power consumption in the annual power consumption dataset that is greater than the daily basic load power consumption, and generate the annual effective energy storage day set according to the power data information; among them, the power data information can be understood as including the dates and corresponding power consumption data of all days with daily power consumption greater than the daily basic load power consumption (there is production load power consumption); that is, based on the daily basic load power consumption, compare the daily power consumption of each day in the annual power consumption dataset with it. If the daily power consumption is less than the daily basic load power consumption, that day is an ineffective utilization day. If the daily power consumption is greater than the daily basic load power consumption, that day is counted as an effective utilization day, and the total daily power consumption corresponding to all effective utilization days is summarized to generate the required annual effective energy storage day set as the basis for determining subsequent typical days.

[0065] Sort the power consumption corresponding to all effective energy storage days in the annual effective energy storage day set according to the chronological order of dates to obtain the corresponding annual effective day power sequence; that is, the annual effective day power sequence can be understood as a sequence formed by arranging the power consumption corresponding to the effective utilization days in the annual effective energy storage day set in the natural order of dates, which can be expressed as:

[0066]

[0067] In the formula, represents the annual effective day power sequence; represents the power consumption of the k-th effective utilization day in the annual effective day power sequence (excluding ineffective utilization days); represents the total number of effective utilization days in

[0068] Generate the corresponding effective day energy storage value sequence according to the total discharge amount and total charge amount corresponding to the power consumption of each effective day in the annual effective day power sequence; among them, the effective day energy storage value sequence can be understood as first identifying all peak price periods (energy storage discharge), flat price periods (energy storage neither charges nor discharges), and valley price periods (energy storage charging) corresponding to the effective day power consumption based on the energy storage operation mode of the energy storage user, splitting and counting the daily power consumption according to each period to obtain the power consumption situation in different periods, and then generating a sequence based on the difference between the discharge weight in the peak price period and the total charge amount in the valley price period of the effective day power consumption. In practical applications, the process of obtaining the effective day energy storage value sequence is as follows:

[0069] Assume that there are multiple peak-valley price difference periods in a day in the area where the energy storage user is located, and the deployed energy storage system can execute a multi-charge and multi-discharge operation mode. One day of each effective day can be divided into multiple periods, which are expressed as:

[0070]

[0071] Among them, represents the total time within an effective day, that is, 24 hours; and respectively represent the i-th charging duration (energy storage charging period duration) and discharging duration (energy storage discharging period duration) within the valid day; represents the flat price period duration within the valid day (the period when the energy storage neither charges nor discharges); N represents the total number of charging times within the valid day (total number of charge-discharge cycles), which can be determined according to the maximum number of charging / discharging times allowed for the energy storage system in the actual region.

[0072] Correspondingly, the total electricity within the valid day can be obtained by summing the electricity in different time periods, expressed as:

[0073]

[0074] where, represents the total electricity of the k-th valid utilization day; and respectively represent the charging amount in the i-th valley price period and the discharging amount in the i-th peak price period within the k-th valid utilization day; represents the total electricity in the flat price period within the k-th valid utilization day.

[0075] Considering that the difference between the total electricity in the peak price periods and the total electricity in the valley price periods of each valid utilization day can reflect the value of energy storage for "peak shaving and valley filling", subtract the total electricity in all valley price periods (daily charging total) from the total electricity in all peak price periods (daily discharging total) of each valid utilization day to obtain the corresponding daily energy storage value:

[0076]

[0077] where, represents the energy storage value of the k-th valid utilization day.

[0078] Based on the above energy storage value of each valid utilization day, an effective day energy storage value sequence can be generated, expressed as:

[0079]

[0080] where, represents the effective day energy storage value sequence; represents the energy storage value of the k-th valid utilization day in the effective day energy storage value sequence.

[0081] S12. Arrange the effective - day energy - storage value sequence in ascending order of the effective - day energy - storage value, and obtain the median of the sorted effective - day energy - storage value sequence. Take the effective day corresponding to the median as the typical day. Here, the typical day can be understood as follows: considering that a small energy - storage value indicates that the difference in electricity consumption between the peak period and the valley period on that day is not significant, and the potential for peak shaving and valley filling is small, so the configured energy - storage capacity should be small; while a large energy - storage value indicates that the difference in electricity consumption between the peak period and the valley period on that day is large, and the potential for peak shaving and valley filling is large, so the configured energy - storage capacity should be large. Preferably, it is the date corresponding to the median of the sequence obtained by rearranging the effective - day energy - storage value sequence from small to large according to the energy - storage value. The median of the effective - day energy - storage value sequence can represent the typical peak - valley electricity difference throughout the year, with a moderate corresponding energy - storage capacity and good representativeness.

[0082] The typical - day screening method provided in this embodiment can start from the perspective of the annual energy - storage usage, ensure that the energy - storage peak - shaving and valley - filling function is maximally exerted, effectively balance the investment cost and application value of the energy - storage system, and thus ensure that the energy - storage configuration generates a high application value.

[0083] S13. According to the energy - storage charge - discharge data of each energy - storage cycle period within the typical day, as well as the obtained annual energy - storage participation in demand - side response data and the annual energy - storage power - outage loss reduction data, construct an energy - storage full - life - cycle benefit model. Here, each energy - storage cycle period within the typical day can be understood as corresponding to each peak - valley electricity - price period in the area where the energy - storage user is located: if there is one peak - valley price - difference period in a day in the area where the energy - storage user is located, then there is one energy - storage cycle period (including one charging and one discharging) corresponding to the typical day; if there are two peak - valley periods in a day in the area where the energy - storage user is located, then there are two energy - storage cycle periods corresponding to the typical day. Correspondingly, the energy - storage charge - discharge data can include data such as the charging duration, the electricity load during the charging period, the electricity price during the charging period, the discharging duration, the electricity load during the discharging period, and the electricity price during the discharging period of each energy - storage cycle period, all of which can be obtained based on the real - data analysis of the typical day and are convenient for subsequent analysis of the initial investment cost of the energy - storage and the benefits obtained from smoothing the grid load fluctuation through peak shaving and valley filling during the operation of the energy - storage.

[0084] The data of the energy storage participating in the demand-side response throughout the year in this embodiment can be understood as the relevant data of the energy storage system participating in the grid demand-side response in a year including typical days. Preferably, it includes the number of responses (the total number of times the energy storage system participates in the demand-side response in a year), the duration of each response (the duration of each demand-side response), and the corresponding response power (the power participating in the demand-side response). The data of the energy storage reducing power outage losses throughout the year can be understood as the relevant data of the energy storage system reducing the losses caused by power supply interruption to users due to insufficient or interrupted grid power supply in a year including typical days. Preferably, it includes the number of times the energy storage power supply reduces power outage losses (the total number of times the energy storage system reduces power outage losses in a year), the duration of each power supply (the duration of each power outage reduction), and the corresponding power supply power (the operating power of the energy storage system when reducing power outage losses), etc. It should be noted that the data of the energy storage participating in the demand-side response throughout the year can be used for subsequent analysis of the benefits of the energy storage system through participating in power transactions such as the demand-side response of the grid, and the data of the energy storage reducing power outage losses throughout the year can be used for subsequent analysis of the power shortage losses that can be reduced by providing power support when the grid power supply is insufficient or interrupted. For specific details, see the relevant description of the energy storage annual benefit model construction below, and it will not be elaborated here.

[0085] The full-life cycle benefit model of the energy storage in this embodiment can be understood as an energy storage capacity configuration optimization model constructed by analyzing the full-life cycle benefits of the energy storage system from aspects such as the initial investment cost, operation and maintenance cost, peak-valley price difference benefit, demand-side response benefit, and power supply support loss reduction of the energy storage system. Specifically, the steps of constructing the full-life cycle benefit model of the energy storage according to the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the obtained data of the energy storage participating in the demand-side response throughout the year and the data of the energy storage reducing power outage losses throughout the year, include:

[0086] According to the charging duration and discharging duration in each energy storage charge and discharge data, obtain the energy storage charge and discharge design time, and construct an energy storage investment cost model according to the energy storage charge and discharge design time, the unit power cost of the energy storage converter, and the unit capacity cost of the energy storage; among them, the energy storage charge and discharge design time can be understood as the optimal energy storage charge and discharge duration that can ensure that the power configuration of the energy storage system can fully charge or discharge in each charge and discharge time period. Considering that if this time is set too large, the energy storage power will be small, and there may be a situation where the energy storage system cannot be fully charged during the valley electricity period. On the contrary, if this time is set too small, the energy storage power will be large. Although it can ensure that the energy storage is fully charged, it will inevitably cause waste of power configuration. To ensure the rationality of the power configuration of the energy storage system, in this embodiment, the energy storage charge and discharge design time is preferably set to the minimum value of the charging duration and discharging duration of all energy storage cycle periods within the typical day, which can be expressed as:

[0087]

[0088] Wherein, Indicates the energy storage charge and discharge design time; and respectively represent the charging duration during the charging period and the discharging duration during the discharging period within the i-th energy storage cycle; ; N represents the total number of energy storage cycles within a typical day.

[0089] The energy storage investment cost model can be understood as a mathematical expression for the initial construction investment cost of an energy storage system established based on the consideration that energy storage investment is positively correlated with energy storage capacity and the power of the energy storage converter; specifically, the energy storage investment cost model is expressed as:

[0090]

[0091] In the formula,

[0092]

[0093] Among them, represents the initial investment cost of the energy storage system; , and respectively represent the unit power cost of the energy storage converter, the unit capacity cost of the energy storage, and the unit capacity cost of the energy storage project construction; and respectively represent the energy storage power and the energy storage capacity, and the energy storage capacity is an unknown value and needs to be analyzed and determined in combination with subsequent methods; represents the energy storage charge and discharge design time.

[0094] Based on the linear relationship between the energy storage operation and maintenance cost and the energy storage capacity, an annual energy storage operation and maintenance cost model is constructed; among them, the annual energy storage operation and maintenance cost model can be understood as a mathematical expression for the annual operation and maintenance cost of an energy storage system established based on the consideration that the annual energy storage operation and maintenance cost is positively correlated with the initial investment (energy storage capacity) of the energy storage, and is preferably expressed as:

[0095]

[0096] Among them, represents the annual operation and maintenance cost of the energy storage system; represents the charging constant for the operation and maintenance cost, which can be set according to actual application requirements; represents the correction coefficient expression of the charging constant for the operation and maintenance cost that is positively correlated with the operation years m of the energy storage system, that is, this correction coefficient becomes larger as time goes by, and this expression can be obtained through research and analysis of the operation and maintenance costs of energy storage systems in the market, and is not specifically limited here.

[0097] Construct a peak shaving and valley filling revenue model for energy storage based on the charging period electricity load, charging period electricity price, discharging period electricity load, and discharging period electricity price in each energy storage charge and discharge data; among them, the peak shaving and valley filling revenue model for energy storage can be understood as a mathematical expression of the peak-valley spread revenue obtained based on the analysis of the electricity cost reduction that can be achieved by charging the energy storage at a lower electricity price during the daily low-price period and discharging it at a higher electricity price, specifically expressed as:

[0098]

[0099] In the formula,

[0100]

[0101]

[0102] Among them, represents the peak shaving and valley filling revenue of the energy storage; and respectively represent the charging amount and discharging amount in the i-th energy storage cycle, and the charging amount is determined by the energy storage capacity and the chargeable electricity amount during the charging period, and the discharging amount is determined by the charged electricity amount of the energy storage and the electricity consumption amount during this period; and respectively represent the charging duration and electricity load during the charging period in the i-th energy storage cycle; and respectively represent the discharging duration and electricity load during the discharging period in the i-th energy storage cycle; represents the energy storage capacity; and respectively represent the installed capacity of the transformer and the maximum load factor, and the maximum load factor can be understood as a coefficient set to ensure the safe operation of the transformer and meet the demand management requirements, and the specific value can be set according to the actual application requirements; and respectively represent the electricity price during the discharging period and the electricity price during the charging period in the i-th energy storage cycle; N represents the total number of energy storage cycles in a typical day.

[0103] Construct a corresponding energy storage demand response revenue model and an energy storage power outage loss reduction model respectively according to the annual energy storage participation in demand side response data and the annual energy storage power outage loss reduction data; among them, the energy storage demand response revenue model can be understood as a mathematical expression obtained based on the analysis of the revenue obtained by the energy storage participating in power grid demand side response and other power transactions throughout the year, considering that after configuring the energy storage system, energy storage users (enterprises) can adjust their electricity loads at any time, and according to the load fluctuations of the regional power grid, reducing or increasing the load will obtain relevant subsidy revenues, expressed as:

[0104]

[0105] Among them, represents the energy storage demand response benefit; represents the number of responses; and respectively represent the response duration and response power of the th participation in the response; represents the subsidy for unit electricity quantity of the response.

[0106] The energy storage power outage loss reduction model can be understood as that the configuration of the energy storage system will reduce the risk of power supply interruption for users. When the power grid power supply is insufficient or interrupted, the energy storage system can supply power to reduce the loss of insufficient power supply. Based on the mathematical expression of the power supply loss that can be avoided by the energy storage system providing power support for the power grid throughout the year, it is expressed as:

[0107]

[0108] Among them, represents the reduction of power outage loss by energy storage; represents the number of times of power outage loss reduction by energy storage power supply; and respectively represent the power supply duration and power supply power of the th energy storage power supply for reducing power outage; represents the unit electricity quantity loss coefficient.

[0109] Integrate the energy storage peak shaving and valley filling benefit model, the energy storage demand response benefit model and the energy storage power outage loss reduction model to obtain the annual energy storage benefit model; among them, the annual energy storage benefit model can be understood as the mathematical expression obtained by summarizing the annual energy storage peak shaving and valley filling benefit, energy storage demand response benefit and energy storage power outage loss reduction of the energy storage system, and is expressed as:

[0110]

[0111] Among them, represents the annual energy storage benefit; , and respectively represent the energy storage peak shaving and valley filling benefit, energy storage demand response benefit and energy storage power outage loss reduction.

[0112] In this embodiment, by comprehensively analyzing the configuration benefits of the energy storage system from aspects such as peak-valley price difference benefits, demand-side response benefits and power supply support loss reduction, the reliability of the energy storage operation value evaluation can be effectively guaranteed, and thus a reliable guarantee can be provided for the subsequent accurate and effective evaluation of the whole life cycle benefits of the energy storage.

[0113] Based on the annual energy storage revenue model, the annual operation and maintenance cost model of energy storage, and the energy storage investment cost model, the net present value of the whole life cycle is calculated to obtain the whole life cycle benefit model of energy storage; among them, the whole life cycle benefit model of energy storage can be understood as fully considering the characteristics that the smaller the capacity configuration of the energy storage system, the smaller the investment and the higher the utilization rate, but its charge and discharge capacity is limited, while the larger the capacity configuration of the energy storage system, the larger the investment, the larger its charge and discharge capacity, but the utilization rate will decrease. In order to reasonably configure the energy storage capacity, an optimization model of energy storage capacity S is preferably formed with the net present value of the whole life cycle as the calculation target. Specifically, the whole life cycle benefit model of energy storage is expressed as:

[0114]

[0115] Among them, represents the whole life cycle benefit of energy storage; represents the annual revenue of energy storage; represents the number of operating years of energy storage; represents the capacity attenuation coefficient of energy storage with the increase of operating years; and respectively represent the annual operation and maintenance cost of the energy storage system and the initial investment cost of the energy storage system, which can be obtained by conducting research and analysis on energy storage systems in the market and combining relevant specification documents of equipment suppliers, etc., and are not specifically limited here; represents the total operating years of energy storage; represents the annual net revenue discount rate of energy storage.

[0116] In this embodiment, by conducting a net present value revenue analysis on the energy storage system from aspects such as the initial investment cost, operation and maintenance cost, peak-valley price difference revenue, demand response revenue, and reduction of losses in power supply support of the energy storage system, the operation value of the energy storage system is effectively evaluated, and thus a knowable analysis basis is provided for obtaining the energy storage capacity that can balance the investment cost and application value of the energy storage system at the same time.

[0117] S14. Solve the whole life cycle benefit model of energy storage to obtain the optimal capacity configuration strategy; the optimal capacity configuration strategy includes the optimal configuration capacity and the optimal charge and discharge power of energy storage; the specific process of solving the whole life cycle benefit model of energy storage is as follows:

[0118] First, according to the energy storage charge and discharge design time determine the upper limit of the energy storage capacity configuration to obtain the maximum configuration capacity ;

[0119] Then, based on the obtained maximum configuration capacity to obtain the value range of the configuration capacity After that, for the configuration capacity Traverse the values within this value range to obtain the corresponding evaluation values of the full life cycle benefits of energy storage, and use the configuration capacity corresponding to the maximum evaluation value of the full life cycle benefits of energy storage as the optimal configuration capacity ;

[0120] Finally, based on the obtained optimal configuration capacity , the optimal charging and discharging power of the energy storage can be obtained as follows:

[0121]

[0122] In the formula, and respectively represent the optimal charging and discharging power of the energy storage and the corresponding optimal configuration capacity.

[0123] To facilitate the understanding of the implementation technology of the energy storage configuration method considering the full life cycle benefits proposed in this application, the following takes the process of obtaining the optimal capacity configuration strategy of energy storage based on the typical daily data of a certain enterprise in a year as an example for detailed description:

[0124] It is assumed that through the above-mentioned median of the effective daily energy storage value sequence, a typical day of a certain enterprise in a year has been determined, and the peak-valley periods, electricity prices, and electricity consumption during this typical day are shown in Table 1 below:

[0125] Table 1 Information Table of Peak-Valley Periods and Electricity Prices during a Typical Day

[0126]

[0127] As shown in Table 1, there are two peak-valley periods in the typical day of a certain enterprise, that is, the operation mode of the energy storage configured by the enterprise is "two charges and two discharges", then based on the data in Table 1, the designed charging and discharging time of the energy storage can be obtained as .

[0128] It is assumed that through market research, the unit power cost of the energy storage converter is determined to be 200 yuan / kW, the unit capacity cost of the energy storage is 600 yuan / kWh, and the unit capacity cost of the energy storage project construction is 180 yuan / kWh, then the energy storage investment cost model can be obtained as:

[0129] .

[0130] It is assumed that the charging constant of the energy storage system operation and maintenance cost is 50 yuan / kWh, and the expression of the correction coefficient of the charging constant of the operation and maintenance cost is expressed as , then

[0131] the annual operation and maintenance cost model of the energy storage can be obtained as:

[0132] 。

[0133] Suppose the transformer capacity of a certain energy storage user is 1250 kVA, and the maximum load factor of the transformer is taken as 0.8. Based on the data shown in Table 1, according to the charging and discharging amount calculation formulas of the energy storage cycle period, it can be obtained that the chargeable amount at the first valley power time is 7000 kWh, the first peak power consumption is 1800 kWh, the chargeable amount at the second valley power time is 800 kWh, and the second peak power consumption is 3500 kWh; at the same time, it is assumed that the number of times the energy storage user enterprise participates in demand-side response per year is 5, and the electricity quantity participated in demand-side response each time is taken as the energy storage system capacity ,The subsidy for unit electricity quantity of demand-side response is 4 yuan / kWh, and the number of power outages of the enterprise caused by insufficient power supply from the power grid within one year of the energy storage user enterprise is 2, and the reduced power loss each time is taken as the energy storage system capacity ,The unit power loss coefficient B is 20 yuan / kWh; substitute the above data into the corresponding energy storage peak shaving and valley filling income model, energy storage demand response income model and energy storage reduced power outage loss model respectively, and then accumulate the obtained energy storage peak shaving and valley filling income, energy storage demand response income and energy storage reduced power outage loss to obtain the annual income of the energy storage.

[0134] In addition, it is assumed that the total operating years of the energy storage is 8, the discount rate of the annual net income of the energy storage is 0.06, and the capacity attenuation coefficient of the energy storage with the increase of the operating years is set based on the market research results as

[0135] ,Substitute the annual income of the energy storage, the annual operation and maintenance cost of the energy storage system and the initial investment cost of the energy storage system obtained through the above steps into the corresponding energy storage full life cycle benefit model, and then based on the maximum configuration capacity calculation formula, the value range of the configuration capacity can be obtained as After that, taking the energy storage capacity as the optimization variable and maximizing the energy storage full life cycle benefit as the optimization goal for optimization and solution, traverse the value of the energy storage capacity S from 0 to 2000 kWh, and when S is 1800, The maximum is 2,593,965 yuan, then the optimal configuration capacity can be determined to be 1800 kW, and the corresponding optimal energy storage charge and discharge power is 900 kW.

[0136] In the embodiments of the present application, by obtaining the annual power consumption dataset of energy storage users, analyzing the effective utilization of energy storage for the annual power consumption dataset to generate a corresponding sequence of effective daily energy storage values, arranging the sequence of effective daily energy storage values in ascending order of the effective daily energy storage value, and obtaining the median of the sorted sequence of effective daily energy storage values, the effective day corresponding to the median is used as the typical day. Then, according to the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the obtained data of the energy storage participating in demand-side response throughout the year and the data of the energy storage reducing power outage losses throughout the year, an energy storage full-life cycle benefit model is constructed, and the energy storage full-life cycle benefit model is solved to obtain a solution for the optimal capacity configuration strategy including the optimal configuration capacity and the optimal energy storage charge and discharge power, effectively solving the application defects in the existing energy storage capacity configuration methods that the screening of typical days is not accurate and reliable enough, and the investment cost and application value of the energy storage system are not considered, resulting in the inability to ensure the best energy storage utilization rate. It can not only effectively improve the accuracy of typical day screening by analyzing the effective utilization value of energy storage for the annual power consumption dataset to screen typical days, but also effectively balance the investment cost and application value of the energy storage system by analyzing the energy storage full-life cycle benefit based on the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the data of the energy storage participating in demand-side response throughout the year and the data of the energy storage reducing power outage losses throughout the year to obtain the optimal capacity configuration strategy, thereby improving the rationality of energy storage capacity configuration and the utilization rate of the energy storage system.

[0137] It should be noted that although the steps in the above flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders.

[0138] In one embodiment, as Figure 2 shown, a system for energy storage configuration considering the full-life cycle benefit is provided, and the system includes:

[0139] A data processing module 1, configured to obtain the annual power consumption dataset of energy storage users, and analyze the effective utilization of energy storage for the annual power consumption dataset to generate a corresponding sequence of effective daily energy storage values;

[0140] A typical day screening module 2, configured to arrange the sequence of effective daily energy storage values in ascending order of the effective daily energy storage value, and obtain the median of the sorted sequence of effective daily energy storage values, and use the effective day corresponding to the median as the typical day;

[0141] An optimization model construction module 3, configured to construct an energy storage full-life cycle benefit model according to the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the obtained data of the energy storage participating in demand-side response throughout the year and the data of the energy storage reducing power outage losses throughout the year;

[0142] A configuration strategy acquisition module 4 is used to solve the energy storage full - life - cycle benefit model to obtain an optimal capacity configuration strategy; the optimal capacity configuration strategy includes an optimal configuration capacity and an optimal energy storage charge - discharge power.

[0143] For the specific limitations of the energy storage configuration system considering the full - life - cycle benefit, reference can be made to the limitations of the energy storage configuration method considering the full - life - cycle benefit in the above text, and the corresponding technical effects can also be equivalently obtained, which will not be elaborated here. Each module in the above - mentioned energy storage configuration system considering the full - life - cycle benefit can be implemented in whole or in part by software, hardware, and their combinations. The above - mentioned modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above - mentioned modules.

[0144] Figure 3 The internal structure diagram of a computer device in an embodiment is shown. The computer device can specifically be a terminal or a server. As Figure 3 shown, the computer device includes a processor, a memory, a network interface, a display, a camera, and an input device connected through a system bus. Among them, 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 network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program, when executed by the processor, implements the energy storage configuration method considering the full - life - cycle benefit. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad set on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0145] Those of ordinary skill in the art can understand that Figure 3 the structure shown in

[0146] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computing device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0146] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above - mentioned method are implemented.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0148] In summary, an energy storage configuration method and system considering the full life cycle benefits provided by the embodiments of the present invention. The energy storage configuration method considering the full life cycle benefits realizes obtaining the annual power consumption data set of energy storage users, performing energy storage effective utilization analysis on the annual power consumption data set to generate a corresponding effective daily energy storage value sequence, arranging the effective daily energy storage value sequence in ascending order of the effective daily energy storage value, and obtaining the median of the sorted effective daily energy storage value sequence. The effective day corresponding to the median is used as the typical day. Then, according to the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the obtained annual energy storage participation in demand response data and annual energy storage reduction of power outage loss data, an energy storage full life cycle benefit model is constructed, and the energy storage full life cycle benefit model is solved to obtain a technical solution of an optimal capacity configuration strategy including the optimal configuration capacity and the optimal energy storage charge and discharge power. This method can not only effectively improve the accuracy of typical day screening by analyzing the effective utilization value of energy storage in the annual power consumption data set to screen the typical day, but also effectively balance the investment cost and application value of the energy storage system by analyzing the energy storage full life cycle benefits based on the energy storage charge and discharge data of each energy storage cycle period within the typical day, as well as the annual energy storage participation in demand response data and annual energy storage reduction of power outage loss data to obtain the optimal capacity configuration strategy, thereby improving the rationality of energy storage capacity configuration and the utilization rate of the energy storage system.

[0149] Each embodiment in this specification is described in a progressive manner. For the parts that are the same or similar in each embodiment, they can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered as the scope recorded in this specification.

[0150] The above-described embodiments only represent several preferred embodiments of the present application. The description is relatively specific and detailed, but it cannot be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and substitutions can be made, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the protection scope of the claims.

Claims

1. A method for energy storage configuration considering the full life cycle benefits, characterized in that: The method comprises the following steps: Obtain an annual electricity consumption data set of energy storage users, and perform energy storage effective utilization analysis on the annual electricity consumption data set to generate a corresponding effective daily energy storage value sequence; the effective daily energy storage value sequence is based on the daily basic load electricity consumption of the energy storage user, and the effective daily electricity consumption data with energy storage utilization in the annual electricity consumption data is screened out, and the difference between the electricity in the peak price time period and the electricity in the valley price time period in the effective daily electricity consumption data is used as the energy storage value sequence generated by the effective daily energy storage value; Arrange the effective daily energy storage value sequence in ascending order according to the effective daily energy storage value, obtain the median of the sorted effective daily energy storage value sequence, and take the effective day corresponding to the median as a typical day; Based on the energy storage charging and discharging data of each energy storage cycle in the typical day, as well as the acquired data on energy storage's participation in demand-side response throughout the year and energy storage's reduction in power outage losses throughout the year, a full life cycle benefit model for energy storage is constructed; the full life cycle benefit model for energy storage is an energy storage capacity configuration optimization model constructed by analyzing the full life cycle benefits of the energy storage system from the perspectives of the initial investment cost, operation and maintenance cost, peak-valley price difference benefits, demand-side response benefits, and power supply support loss reduction of the energy storage system; Solving the energy storage life cycle benefit model to obtain an optimal capacity configuration strategy; the optimal capacity configuration strategy includes an optimal configuration capacity and an optimal energy storage charging and discharging power; The energy storage life cycle benefit model is expressed as: In the formula, in, Indicates the benefits of energy storage throughout its life cycle; represents the annual revenue of energy storage; Indicates the year of energy storage operation; It represents the capacity decay coefficient of energy storage as the operating years increase; and They represent the annual operation and maintenance cost of the energy storage system and the initial investment cost of the energy storage system respectively; Indicates the total operating years of the energy storage; represents the annual net benefit discount rate of energy storage; represents the annual revenue of energy storage; , and They represent the benefits of energy storage for peak load reduction, energy storage for demand response, and energy storage for reducing power outage losses. and Respectively represent the charging and discharging amounts of the i-th energy storage cycle; and They respectively represent the charging time and power load of the charging period in the i-th energy storage cycle; and They respectively represent the discharge duration and power load of the discharge period in the i-th energy storage cycle; Indicates energy storage capacity; and Respectively represent the transformer's installed capacity and maximum load factor; and They respectively represent the electricity price during the discharge period and the electricity price during the charging period of the i-th energy storage cycle.

2. The energy storage configuration method considering the full life cycle benefits as claimed in claim 1, characterized in that: The step of performing energy storage effective utilization analysis on the annual electricity consumption data set to generate a corresponding effective daily energy storage value sequence comprises: Obtaining the daily basic load power consumption of the energy storage user, and screening the annual power consumption data set for valid data according to the daily basic load power consumption, to generate a corresponding annual energy storage valid day set; According to the date sequence, the power consumption corresponding to all the energy storage effective days in the annual energy storage effective day set is sorted to obtain the corresponding annual effective day power sequence; According to the total discharge amount and the total charge amount corresponding to each effective daily electricity quantity in the annual effective daily electricity quantity sequence, a corresponding effective daily energy storage value sequence is generated.

3. The energy storage configuration method considering the full life cycle benefits as claimed in claim 2 is characterized in that: The step of obtaining the daily basic load power consumption of the energy storage user, and filtering the annual power consumption data set for effective data according to the daily basic load power consumption to generate the corresponding annual energy storage effective day set includes: Obtaining the power of each non-production load and the corresponding load factor of the energy storage user, and obtaining the daily basic load power consumption according to all the non-production load powers and the corresponding load factors; The power data information of the daily power consumption in the annual power consumption data set that is greater than the daily basic load power consumption is obtained, and the annual energy storage effective day set is generated according to the power data information.

4. The energy storage configuration method considering the full life cycle benefits as claimed in claim 1, characterized in that: The energy storage charging and discharging data include charging time, power load during the charging period, electricity price during the charging period, discharging time, power load during the discharging period and electricity price during the discharging period; the energy storage participation in demand-side response data throughout the year include the number of responses, the duration of each response and the corresponding response power; the energy storage power outage loss reduction data throughout the year include the number of power outage losses reduced by energy storage power supply, the duration of each power supply and the corresponding power supply power; The step of constructing the energy storage life cycle benefit model based on the energy storage charging and discharging data of each energy storage cycle in the typical day, as well as the acquired energy storage participation in demand-side response data throughout the year and energy storage reduction in power outage loss data throughout the year includes: According to the charging time and discharging time in each energy storage charging and discharging data, the energy storage charging and discharging design time is obtained, and according to the energy storage charging and discharging design time, the unit power cost of the energy storage converter and the unit capacity cost of the energy storage, an energy storage investment cost model is constructed; Based on the linear relationship between energy storage operation and maintenance cost and energy storage capacity, an energy storage annual operation and maintenance cost model is constructed; According to the charging period power load, charging period electricity price, discharging period power load and discharging period electricity price in each energy storage charging and discharging data, a peak-shaving and valley-filling profit model for energy storage is constructed; According to the data of energy storage participating in demand-side response throughout the year and the data of energy storage reducing power outage losses throughout the year, respectively, a corresponding energy storage demand response benefit model and energy storage power outage loss reduction model are constructed; The energy storage peak-shaving and valley-filling profit model, the energy storage demand response profit model and the energy storage power outage loss reduction model are integrated to obtain an energy storage annual profit model; The energy storage full life cycle net present value is calculated based on the energy storage annual revenue model, the energy storage annual operation and maintenance cost model and the energy storage investment cost model to obtain the energy storage full life cycle benefit model.

5. The energy storage configuration method considering the full life cycle benefits as claimed in claim 4, characterized in that: The energy storage investment cost model is expressed as: In the formula, in, Represents the initial investment cost of the energy storage system; , and They represent the unit power cost of energy storage converter, the unit capacity cost of energy storage and the unit capacity cost of energy storage project construction respectively; and Respectively represent energy storage power and energy storage capacity; Indicates the design time of energy storage charging and discharging; and They represent the charging duration of the charging period and the discharging duration of the discharging period in the i-th energy storage cycle, respectively. ; N represents the total number of energy storage cycles in a typical day.

6. The energy storage configuration method considering the full life cycle benefits as claimed in claim 4, characterized in that: The energy storage demand response benefit model is expressed as: in, represents the energy storage demand response benefit; Indicates the number of responses; and Respectively represent Response duration and response power of the participant response; Indicates the response unit electricity subsidy; The energy storage model for reducing power outage losses is expressed as: in, It means that energy storage reduces power outage losses; It means that energy storage power supply reduces the number of power outage losses; and Respectively represent Secondary energy storage power supply reduces the power outage duration and power supply; Indicates the unit power loss coefficient.

7. An energy storage configuration system considering the benefits of the entire life cycle, characterized in that: The system comprises: A data processing module is used to obtain an annual electricity consumption data set of an energy storage user, and perform an energy storage effective utilization analysis on the annual electricity consumption data set to generate a corresponding effective daily energy storage value sequence; the effective daily energy storage value sequence is based on the daily basic load electricity consumption of the energy storage user, and the effective daily electricity consumption data with energy storage utilization in the annual electricity consumption data is screened out, and the difference between the electricity in the peak price time period and the electricity in the valley price time period in the effective daily electricity consumption data is used as the energy storage value sequence generated by the effective daily energy storage value; A typical day screening module is used to sort the effective day energy storage value sequence in ascending order according to the effective day energy storage value, and obtain the median of the sorted effective day energy storage value sequence, and take the effective day corresponding to the median as a typical day; An optimization model building module is used to build an energy storage full life cycle benefit model based on the energy storage charging and discharging data of each energy storage cycle in the typical day, as well as the acquired energy storage participation in demand side response data throughout the year and the energy storage reduction in power outage loss data throughout the year; the energy storage full life cycle benefit model is an energy storage capacity configuration optimization model constructed by analyzing the energy storage system's full life cycle benefits from the initial investment cost, operation and maintenance cost, peak-valley price difference benefits, demand side response benefits and power supply support loss reduction of the energy storage system; A configuration strategy acquisition module is used to solve the energy storage life cycle benefit model to obtain an optimal capacity configuration strategy; the optimal capacity configuration strategy includes an optimal configuration capacity and an optimal energy storage charging and discharging power; The energy storage life cycle benefit model is expressed as: In the formula, in, Indicates the benefits of energy storage throughout its life cycle; represents the annual revenue of energy storage; Indicates the year of energy storage operation; It represents the capacity decay coefficient of energy storage as the operating years increase; and They represent the annual operation and maintenance cost of the energy storage system and the initial investment cost of the energy storage system respectively; Indicates the total operating years of the energy storage; represents the annual net benefit discount rate of energy storage; represents the annual revenue of energy storage; , and They represent the benefits of energy storage for peak load reduction, energy storage for demand response, and energy storage for reducing power outage losses. and Respectively represent the charging and discharging amounts of the i-th energy storage cycle; and They respectively represent the charging time and power load of the charging period in the i-th energy storage cycle; and They respectively represent the discharge duration and power load of the discharge period in the i-th energy storage cycle; Indicates energy storage capacity; and Respectively represent the transformer's installed capacity and maximum load factor; and They respectively represent the electricity price during the discharge period and the electricity price during the charging period of the i-th energy storage cycle.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. 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 according to any one of claims 1 to 5 are implemented.

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