User-side energy storage system operation evaluation method, device, equipment and medium

Abstract

This application relates to a method, apparatus, equipment, and medium for evaluating the operation of a user-side energy storage system. The method includes: acquiring revenue-related parameters of the user-side energy storage system, including: the load of the user-side energy storage system and the user-side metering system within a preset historical period, the actual retail electricity price within the preset historical period, and the basic technical parameters of the energy storage system; determining the ideal revenue that the energy storage system brings to the user based on the revenue-related parameters; and determining the actual operating status of the energy storage system within the preset historical period based on the actual and ideal revenue of the energy storage system. This method can improve the accuracy of evaluating the actual operating status of the energy storage system.

Description

Technical Field

[0001] This application relates to the fields of power systems and energy storage technology, and in particular to a method, apparatus, equipment and medium for evaluating the operation of a user-side energy storage system. Background Technology

[0002] In the fields of power systems and energy storage technology, the reference price linkage mechanism is being gradually promoted. Its time-of-use pricing is no longer a fixed peak-valley-flat price set by the government, but rather a high-dimensional time-varying price series formed monthly based on the coupling relationship between the medium- and long-term wholesale market and the spot market's quantity and price, exhibiting hourly heterogeneity while maintaining market uniformity. Under this mechanism, the retail electricity side cannot adjust price parameters, and users face high-frequency price signals that are entirely determined by market supply and demand and updated monthly.

[0003] User-side energy storage systems can reduce electricity costs through "charging during off-peak hours and discharging during peak hours," and can also aggregate participation in virtual power plants to obtain ancillary service revenue. However, the energy storage revenue calculation and energy storage operation evaluation technologies in related fields are mostly based on fixed electricity prices, which cannot effectively cope with the high-frequency dynamic characteristics of the reference price linkage package mechanism, resulting in low accuracy in assessing the actual operating status of energy storage systems. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, equipment, and medium for evaluating the operation of user-side energy storage systems that can improve the accuracy of evaluating the actual operating status of energy storage systems, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides an operational evaluation method for a user-side energy storage system, including:

[0006] Obtain revenue-related parameters of the user-side energy storage system, including: the load of the user-side energy storage system and the user-side gate meter during a preset historical period, the actual retail electricity price during the preset historical period, and the basic technical parameters of the energy storage system.

[0007] The ideal benefits that the energy storage system brings to the user are determined based on the aforementioned benefit-related parameters;

[0008] Based on the actual and ideal benefits of the energy storage system during the preset historical period, the actual operating status of the energy storage system during the preset historical period is determined.

[0009] The basic technical parameters include at least one of maximum charge / discharge power, rated capacity, and minimum allowable capacity, as well as charge / discharge efficiency. Determining the ideal benefit to the user from the energy storage system based on the benefit-related parameters includes: determining the user's original load based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load characterizes the user's original load without the energy storage system; calculating the ideal equivalent power exchanged between the energy storage system and the grid within the preset historical period, based on the basic technical parameters, the actual retail electricity price, and the user's original load, with the goal of maximizing the net charge / discharge benefit of the energy storage system; determining the ideal electricity cost for the user based on the actual retail electricity price, the user's original load, and the ideal equivalent power; and determining the ideal benefit based on the benchmark electricity cost within the preset historical period and the ideal electricity cost.

[0010] In one embodiment, the step of calculating the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period, based on the basic technical parameters, the actual retail electricity price, and the user's original load, with the objective of maximizing the net revenue from charging and discharging of the energy storage system, includes: calculating the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period, based on the actual retail electricity price and the charging and discharging efficiency, with the objective function being the objective function; wherein the constraints of the objective function include at least one of the following: satisfying the maximum charging and discharging power; satisfying the rated capacity; satisfying the minimum allowable capacity; and the sum of the user's original load and the ideal equivalent power being less than or equal to a preset maximum value of the original load.

[0011] In one embodiment, determining the actual operating status of the energy storage system within the preset historical period based on the actual revenue and the ideal revenue of the energy storage system within the preset historical period includes: determining the actual revenue achievement rate based on the ratio of the actual revenue to the ideal revenue; determining that the energy storage system is operating abnormally if the actual revenue achievement rate is less than or equal to a preset threshold; and determining that the energy storage system is operating normally if the actual revenue achievement rate is greater than the preset threshold.

[0012] In one embodiment, the method further includes: determining the predicted retail electricity price for a preset historical period based on a pre-built day-ahead electricity price prediction model; determining the predicted revenue brought to users by the energy storage system based on the predicted retail electricity price and the revenue-related parameters; and determining the actual operating status of the energy storage system within the preset historical period based on the actual revenue and the ideal revenue of the energy storage system, including: determining the actual revenue achievement rate of the energy storage system based on the ratio of the actual revenue to the ideal revenue; determining the predicted revenue achievement rate of the energy storage system based on the ratio of the predicted revenue to the ideal revenue; and determining the actual operating status of the energy storage system and the prediction deviation of the day-ahead electricity price prediction model within the preset historical period based on the actual revenue achievement rate and the predicted revenue achievement rate.

[0013] In one embodiment, determining the predicted revenue for the user from the energy storage system based on the predicted retail electricity price and the revenue-related parameters includes: determining the user's original load based on the load and the charging / discharging efficiency in the basic technical parameters; the user's original load characterizes the user's original load without the energy storage system; calculating the predicted equivalent power exchanged between the energy storage system and the grid within the preset historical period, based on the basic technical parameters, the predicted retail electricity price, and the user's original load, with the goal of maximizing the net charging / discharging revenue of the energy storage system; determining the predicted electricity cost for the user based on the actual retail electricity price, the user's original load, and the predicted equivalent power; and determining the predicted revenue based on the benchmark electricity cost within the preset historical period and the predicted electricity cost.

[0014] In one embodiment, determining the actual operating status of the energy storage system and the prediction deviation of the day-ahead electricity price prediction model within a preset historical period based on the actual revenue achievement rate and the predicted revenue achievement rate includes: determining that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements when both the actual revenue achievement rate and the predicted revenue achievement rate are less than or equal to a preset threshold; determining that the energy storage system is operating normally and the prediction deviation meets the requirements when both the actual revenue achievement rate and the predicted revenue achievement rate are greater than the preset threshold, and determining the source of revenue loss based on the relationship between the actual revenue achievement rate and the predicted revenue achievement rate; determining that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model meets the requirements when the actual revenue achievement rate is less than or equal to the preset threshold and the predicted revenue achievement rate is greater than the preset threshold; and determining that the energy storage system is operating normally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements when the actual revenue achievement rate is greater than the preset threshold and the predicted revenue achievement rate is less than or equal to the preset threshold.

[0015] In one embodiment, the basic technical parameters include the charging and discharging efficiency of the energy storage system; the method for determining the actual revenue includes: determining the user's original load based on the load and the charging and discharging efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load without an energy storage system; determining the benchmark electricity price for the preset historical period based on the user's original load and the actual retail electricity price; determining the actual electricity cost incurred by the user with an energy storage system based on the actual retail electricity price and the load of the user-side meter during the preset historical period; and determining the actual revenue based on the benchmark electricity cost and the actual electricity cost.

[0016] Secondly, this application also provides an operation evaluation device for a user-side energy storage system, comprising:

[0017] The acquisition module is used to acquire revenue-related parameters of the user-side energy storage system. The revenue-related parameters include: the load of the user-side energy storage system and the user-side gate meter in a preset historical period, the actual retail electricity price in the preset historical period, and the basic technical parameters of the energy storage system.

[0018] The first determining module is used to determine the ideal benefit that the energy storage system brings to the user based on the benefit-related parameters.

[0019] The second determining module is used to determine the actual operating status of the energy storage system within the preset historical period based on the actual benefit and the ideal benefit of the energy storage system within the preset historical period.

[0020] The basic technical parameters include at least one of maximum charge / discharge power, rated capacity, and minimum allowable capacity, as well as charge / discharge efficiency; the first determining module is specifically used for:

[0021] The user's original load is determined based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system.

[0022] Based on the basic technical parameters, the actual retail electricity price, and the user's original load, with the goal of maximizing the net revenue from charging and discharging the energy storage system, the ideal equivalent power exchanged between the energy storage system and the grid during the preset historical period is calculated.

[0023] The ideal electricity cost for the user is determined based on the actual retail electricity price, the user's original load, and the ideal equivalent power.

[0024] The ideal revenue is determined based on the benchmark electricity price and the ideal electricity price within a preset historical period.

[0025] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the operation evaluation method for the user-side energy storage system provided in the first aspect of this application.

[0026] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the operation evaluation method for the user-side energy storage system provided in the first aspect of this application.

[0027] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the operation evaluation method for the user-side energy storage system provided in the first aspect of this application.

[0028] The aforementioned user-side energy storage system operation evaluation method, device, computer equipment, computer-readable storage medium, and computer program product acquire revenue-related parameters of the user-side energy storage system. These revenue-related parameters include: the load of the user-side energy storage system and the user-side gate meter during a preset historical period, the actual retail electricity price during the preset historical period, and the basic technical parameters of the energy storage system. Based on the revenue-related parameters, the ideal revenue that the energy storage system brings to the user is determined. Based on the actual and ideal revenue of the energy storage system during the preset historical period, the actual operating status of the energy storage system during the preset historical period is determined. As can be seen, the embodiments of this application determine the ideal benefit that the energy storage system brings to the user based on the benefit-related parameters, that is, the theoretical optimal benefit that energy storage brings to the user under theoretical conditions. The benefit-related parameters are actual values ​​and include the actual retail electricity price, so that the ideal benefit can truly reflect the theoretical optimal benefit that the energy storage system brings to the user under the actual retail electricity price. Therefore, by evaluating the actual operation of the energy storage system based on the actual benefit and the ideal benefit, a quantitative comparison relationship between the actual benefit and the ideal benefit can be established, the gap between the actual operation and the theoretical optimal can be clarified, and the existence of operational anomalies in the energy storage system can be more accurately assessed, thereby improving the evaluation accuracy of the actual operation of the energy storage system under the reference price linkage package. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is an application environment diagram of an operation evaluation method for a user-side energy storage system in one embodiment.

[0031] Figure 2 This is a flowchart illustrating an operational evaluation method for a user-side energy storage system in one embodiment.

[0032] Figure 3 This is a flowchart illustrating step 202 in one embodiment;

[0033] Figure 4 This is a flowchart illustrating step 203 in one embodiment;

[0034] Figure 5 This is a schematic diagram of the process for determining the predicted revenue in one embodiment;

[0035] Figure 6 This is a flowchart illustrating the operation evaluation method for a user-side energy storage system in another embodiment;

[0036] Figure 7 This is an example of an operational curve for a typical day without energy storage during winter.

[0037] Figure 8 A bar chart comparing monthly retail electricity costs for different strategies in an example;

[0038] Figure 9 A bar chart comparing the monthly retail revenue of various strategies in an example;

[0039] Figure 10 An example of an optimized operation curve for an energy storage system based on an ideal retail electricity price on a typical winter day;

[0040] Figure 11 An example of an optimized operating curve for an energy storage system based on predicted retail electricity prices on a typical winter day;

[0041] Figure 12 This is a structural block diagram of an operation evaluation device for a user-side energy storage system in one embodiment;

[0042] Figure 13 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0044] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0045] In related technologies, there is a lack of quantitative comparison and evaluation methods between actual operating results and theoretical optimality. Most focus is on revenue forecasting during the planning stage of energy storage based on fixed electricity prices. For already operational energy storage systems, there is a lack of a complete evaluation system that goes from collecting actual operating data, back-calculating the user's original load, constructing a theoretically optimal strategy considering monthly dynamically updated high-frequency price sequences, to calculating the revenue achievement rate. Users cannot intuitively understand the gap between the actual operating results of the energy storage system and the theoretically feasible optimality, and they cannot independently distinguish the contribution of "day-ahead electricity price forecast deviation" and "real-time control execution deviation" to revenue loss, making it difficult to diagnose the quality of control strategies or the operating status of equipment.

[0046] Therefore, there is an urgent need for a user-side energy storage revenue calculation and energy storage operation evaluation method that can adapt to the characteristics of reference price linkage packages (high-frequency monthly updates and hourly heterogeneous prices), accurately consider demand constraints and charging and discharging efficiency, and quantify the actual operating effects and predicted operating schemes.

[0047] Therefore, this application proposes an operation evaluation method for user-side energy storage systems, which can be applied to a reference price linkage package mechanism. It can accurately quantify the gap between the actual operation effect of the energy storage system and the theoretically feasible optimal solution, which will be described in detail below.

[0048] The operation evaluation method for user-side energy storage systems provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0049] In one exemplary embodiment, such as Figure 2As shown, an operational evaluation method for a user-side energy storage system is provided, which can be applied to... Figure 1 Taking the server in the example, the explanation includes the following steps 201 to 203. Wherein:

[0050] Step 201: Obtain the revenue-related parameters of the user-side energy storage system. The revenue-related parameters include: the load of the user-side energy storage system and the user-side gate meter in a preset historical period, the actual retail electricity price in the preset historical period, and the basic technical parameters of the energy storage system.

[0051] Among these, revenue-related parameters refer to parameters related to the revenue of the energy storage system. The revenue of an energy storage system can be understood as the electricity cost savings it brings to users. An energy storage system is an adjustable charging and discharging system installed on the user's side to save users on electricity costs.

[0052] For example, the load of the energy storage system is obtained by collecting the load data from the system's meters within a preset historical period (e.g., last month), and the load of the user is obtained by collecting the load data from the user's meter within the same preset historical period. The load within the preset historical period is a load time series (i.e., the load at each moment). The actual retail electricity price at each moment within the preset historical period, as well as the basic technical parameters of the energy storage system, are obtained. These parameters include at least one of the maximum charging / discharging power, rated capacity, and minimum allowable capacity, and the charging / discharging efficiency. The actual revenue-related parameters are thus obtained and used to calculate the revenue (electricity cost savings) that the energy storage system brings to the user.

[0053] Optionally, the load curves of the energy storage system's meters for the previous month or day, the load curves of the electricity user's meter for the previous month or day, the retail electricity price curves for the previous month or day, and the basic technical parameters of the energy storage system can be obtained. The basic technical parameters include rated capacity, minimum allowable capacity, maximum charging and discharging power, and charging and discharging efficiency.

[0054] Step 202: Determine the ideal benefits that the energy storage system brings to the user based on the relevant benefit parameters.

[0055] For example, firstly, based on the load and basic technical parameters, the user's original load without an energy storage system is determined. Then, based on the user's original load and actual retail electricity price within a preset historical period, the base electricity cost that the user needs to pay to the grid without an energy storage system is determined. And based on the basic technical parameters, actual retail electricity price, and user's original load, the ideal electricity cost that the user needs to pay with an energy storage system (i.e., the minimum electricity cost, the theoretically optimal value) is determined. Finally, based on the base electricity cost and ideal electricity cost within the preset historical period, the electricity cost theoretically saved for the user by the energy storage system is determined, which is the ideal benefit brought to the user by the energy storage system (the theoretically optimal (maximum) benefit considering energy storage).

[0056] The example also includes: determining the actual electricity cost (i.e., the actual value) that the user needs to pay when there is an energy storage system, based on the actual retail electricity price and the load of the user-side gate meter in a preset historical period; and determining the actual electricity cost saved by the energy storage system for the user based on the benchmark electricity price and the actual electricity price in the preset historical period, which is the actual benefit brought to the user by the energy storage system (actual benefit when considering energy storage).

[0057] Step 203: Based on the actual and ideal benefits of the energy storage system within the preset historical period, determine the actual operating status of the energy storage system within the preset historical period.

[0058] For example, after obtaining the actual and ideal benefits within a preset historical period, the actual and ideal benefits are compared and the comparison results are quantified. Based on the comparison results, the actual operating effect of the energy storage system within the preset historical period is judged.

[0059] Optionally, if the actual revenue equals the ideal revenue, the actual operating state of the energy storage system is determined to be normal (no revenue loss or minimal revenue loss); if the actual revenue is less than the ideal revenue, the actual operating state of the energy storage system is determined to be abnormal (revenue loss exists or the revenue loss is too great).

[0060] In the aforementioned method for evaluating the operation of a user-side energy storage system, revenue-related parameters of the user-side energy storage system are obtained. These parameters include: the load of the user-side energy storage system and the user-side metering system within a preset historical period, the actual retail electricity price within the preset historical period, and the basic technical parameters of the energy storage system. Based on these revenue-related parameters, the ideal revenue brought to the user by the energy storage system is determined. Based on the actual and ideal revenue of the energy storage system within the preset historical period, the actual operating status of the energy storage system within the preset historical period is determined. It is evident that this embodiment determines the ideal revenue brought to the user by the energy storage system based on revenue-related parameters, which is the theoretically optimal revenue brought to the user by energy storage under theoretical conditions. Since the revenue-related parameters are actual values ​​and include the actual retail electricity price, the ideal revenue can truly reflect the theoretically optimal revenue brought to the user by the energy storage system under the actual retail electricity price. Therefore, evaluating the actual operation of the energy storage system based on actual and ideal revenue can establish a quantitative comparison relationship between actual and ideal revenue, clarify the gap between actual operation and theoretical optimality, and thus more accurately assess whether there are operational anomalies in the energy storage system, thereby improving the evaluation accuracy of the actual operation of the energy storage system under the reference price linkage package.

[0061] In one exemplary embodiment, such as Figure 3 As shown, step 202 includes steps 301 to 304. Wherein:

[0062] Step 301: Determine the user's original load based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system.

[0063] For example, based on the load curve of the energy storage system and the user's load curve within a preset historical period, and considering the charging and discharging efficiency, the original user load curve without considering energy storage is derived by reverse calculation using the following formula:

[0064]

[0065] Where t represents time t within a preset historical time period. The user's original load at time t, Let t be the load of the energy storage system. The load of the user-side gateway table at time t within a preset historical time period. For charge and discharge efficiency; This indicates the power drawn from the grid during energy storage charging. This indicates the power sent to the grid side during energy storage discharge.

[0066] The base electricity charge for a user within a preset historical period can also be calculated using the following formula, based on the user's original load curve and actual retail electricity price curve, without energy storage:

[0067]

[0068] in, The base electricity rate is T, where T is the total number of hours within a preset historical period. Let t be the actual retail electricity price at time t.

[0069] Step 302: Based on basic technical parameters, actual retail electricity price and user's original load, with the goal of maximizing the net revenue of energy storage system charging and discharging, calculate the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period.

[0070] The ideal equivalent power within a preset historical period can be understood as the optimal equivalent power time series exchanged between the energy storage system and the grid at the grid connection point, i.e., the ideal equivalent power of the energy storage system on the grid side. Equivalent power refers to the power after considering charging and discharging efficiency. The ideal equivalent power is used to characterize the impact of the charging and discharging behavior of the energy storage system on the grid power supply under the theoretically optimal charging and discharging strategy.

[0071] For example, a mixed-integer linear programming model based on actual retail electricity prices is constructed beforehand, using a preset historical period as the optimization cycle. The model aims to minimize electricity costs (maximize the net revenue from energy storage charging and discharging), and is constrained by charging and discharging efficiency loss, SOC continuity constraints, grid-side power demand constraints, and peak-valley price difference thresholds. The ideal equivalent power of the energy storage system is used as the decision variable. After obtaining the basic technical parameters, actual retail electricity prices, user loads, and the pre-constructed mixed-integer linear programming model, the basic technical parameters, actual retail electricity prices, and user loads are input into the mixed-integer linear programming model. With the goal of minimizing electricity costs, the model is solved based on the model constraints to obtain the ideal equivalent power of the energy storage system within the preset historical period, i.e., the ideal equivalent power time series. This series represents the theoretically optimal charging and discharging strategy of the energy storage system within the preset historical period, and is used for subsequent calculations of ideal electricity costs.

[0072] Step 303: Determine the ideal electricity cost for the user based on the actual retail electricity price, the user's original load, and the ideal equivalent power.

[0073] For example, the ideal electricity cost (i.e., the theoretically optimal electricity cost) that a user needs to spend within a preset historical period is calculated using the following formula:

[0074]

[0075] in, For ideal electricity rates, Let t be the ideal equivalent power of the energy storage system on the grid side.

[0076] Step 304: Determine the ideal revenue based on the benchmark electricity price and ideal electricity price within the preset historical time period.

[0077] For example, the ideal benefit to users from an energy storage system is determined based on the difference between the benchmark electricity price and the ideal electricity price, for instance, by calculating the ideal benefit using the following formula. :

[0078]

[0079] Therefore, this embodiment first considers the charging and discharging efficiency to calculate the user's original load, and determines the ideal benefit based on the user's original load, which can ensure the reliability of the ideal benefit.

[0080] In an exemplary embodiment, step 302 includes: based on the actual retail electricity price and charging / discharging efficiency, and with the objective function of maximizing the net charging / discharging revenue of the energy storage system, calculating the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period; wherein the constraints of the objective function include at least one of the following: satisfying the maximum charging / discharging power; satisfying the rated capacity; satisfying the minimum allowable capacity; and the sum of the user's original load and the ideal equivalent power is less than or equal to the preset maximum value of the original load.

[0081] For example, substituting the actual retail electricity price and charging / discharging efficiency into the objective function of the mixed-integer linear programming model, the objective function is to minimize electricity costs (maximize the net revenue from charging and discharging of the energy storage system):

[0082]

[0083]

[0084] in, Let t represent the equivalent power of the energy storage system to the grid side at time t. Let be the amount of charge stored in the energy storage system at time t. Let t be the amount of discharge released by the energy storage system at time t.

[0085] The constraints of the mixed-integer linear programming model include:

[0086] Power upper limit constraint based on maximum charge and discharge power:

[0087]

[0088] in, These are the absolute values ​​of the charging power and the discharging power of the energy storage system at time t, respectively.

[0089] Charge-discharge mutual exclusion constraint:

[0090]

[0091] in, Let be the binary variables of the charging state and the binary variables of the discharging state at time t, respectively. , .

[0092] Auxiliary variables , Satisfying the Big M method linearization constraints:

[0093]

[0094] set up The remaining energy storage capacity at the end of time t, and the initial capacity. With termination capacity All are set to minimum allowable capacity Satisfying SOC continuity constraints and based on rated capacity Upper and lower bound constraints:

[0095]

[0096] The total power of the user is the sum of the user's original load and the equivalent power of the energy storage system on the grid side, satisfying the power demand constraint on the grid side:

[0097]

[0098]

[0099] in, Let t be the total power of the user. The maximum original load of users within a preset historical period can be set in advance according to needs.

[0100] Electricity price difference threshold constraint: Only when the peak-valley electricity price difference exceeds a set threshold. Arbitrage across time periods is allowed:

[0101]

[0102] in, These are the actual retail electricity prices at time j and time i, respectively.

[0103] A mixed-integer linear programming solver is used to solve the objective function based on the above constraints, obtaining the optimal charging and discharging amounts of the energy storage system at each time point within a preset time period. This allows for the calculation of the ideal equivalent power sequence of the energy storage system on the grid side. This is used for calculating the ideal electricity cost later.

[0104] Optionally, before optimization, the actual operating data of the energy storage system (i.e., the data obtained above) is used to determine whether it exceeds the boundary conditions based on the basic technical parameters. If so, the basic technical parameters are adjusted; otherwise, the basic technical parameters are kept unchanged.

[0105] It should be noted that, on the one hand, energy storage charging not only incurs electricity costs based on real-time prices but also increases the instantaneous power drawn from the grid, potentially leading to an increase in peak demand and thus demand-based electricity charges; conversely, discharging can reduce peak demand. Many related methods employ simplified peak-valley arbitrage models based on fixed time periods, focusing only on electricity costs and neglecting the coupling effect of demand-based electricity charges under hourly heterogeneous price sequences. This results in an inability to accurately quantify the dynamic impact of energy storage strategies on demand-based electricity charges in scenarios with high-frequency fluctuations in reference prices, leading to significant deviations in revenue assessment. This embodiment, however, uses joint modeling of grid-side power constraints and demand ceilings to accurately quantify the net impact of the increase in demand-based electricity charges caused by energy storage charging and the reduction in demand caused by discharging. This solves the problem of measurement deviations caused by related methods focusing only on electricity costs while ignoring changes in demand-based electricity charges. Therefore, this embodiment can accurately quantify the dynamic impact of energy storage strategies on demand-based electricity charges, improving the accuracy of revenue calculation.

[0106] On the other hand, since the hourly price difference of the reference price linkage package is slight, the bidirectional energy loss caused by the charging and discharging efficiency of the energy storage system directly affects the economic assessment of arbitrage opportunities. Related technologies either ignore the impact of efficiency or only use fixed coefficients for rough conversion, making it difficult to adapt to the fine-grained, high-frequency electricity price settlement requirements, and easily leading to calculation errors in revenue-sharing scenarios. However, this application's embodiment introduces charging and discharging efficiency into the energy balance equation and equivalent power calculation, accurately establishing the conversion relationship between grid-side electricity and energy storage-side electricity, thus solving the problem of calculation errors caused by improper efficiency modeling in revenue-sharing settlement scenarios. Therefore, this embodiment can ensure the accuracy of the ideal equivalent power in revenue-sharing settlement scenarios, thereby ensuring the accuracy of electricity cost calculation.

[0107] In an exemplary embodiment, step 203 includes: determining the actual benefit achievement rate based on the ratio of actual benefit to ideal benefit; determining that the energy storage system is operating abnormally if the actual benefit achievement rate is less than or equal to a preset threshold; and determining that the energy storage system is operating normally if the actual benefit achievement rate is greater than the preset threshold.

[0108] For example, the actual profit achievement rate is calculated using the following formula. :

[0109]

[0110] in, The threshold is close to zero. When the absolute value of the ideal return is less than this threshold, the return achievement rate is defined as 0 to avoid division by zero errors. For actual benefits.

[0111] If the actual return achievement rate is less than or equal to a preset threshold, such as 60%, the energy storage system is determined to be operating in an abnormal state (loss) within the preset historical period, and the actual operating effect is not up to standard. If the actual return achievement rate is greater than the preset threshold, such as 60%, the energy storage system is determined to be operating in a normal state (no loss) within the preset historical period, and the actual operating effect is up to standard. Furthermore, when the actual return is negative, a negative achievement rate reflects that the system is operating in a loss-making state (not only does it not save money for users, but it also increases electricity bills).

[0112] Optionally, after obtaining the actual benefit, ideal benefit, actual benefit achievement rate, and the charge / discharge strategy curve of the energy storage system, these can be output in the form of visual charts for users to view.

[0113] Therefore, by constructing an actual benefit achievement rate index in this embodiment, users can intuitively diagnose the gap between the actual operating effect of the energy storage system and the theoretically feasible optimal result, providing a quantitative basis for control strategy optimization and equipment status assessment.

[0114] The above describes the assessment of the actual operating status of an energy storage system over a past period based on actual and ideal returns. To further determine the source of revenue loss (whether it is caused by electricity price forecasts or by deviations in the control execution of the energy storage system), the predicted returns are determined, and the actual operating status is assessed based on actual, predicted, and ideal returns, the following is a detailed explanation.

[0115] In one exemplary embodiment, the method further includes: determining the predicted retail electricity price for a preset historical period based on a pre-built day-ahead electricity price prediction model; and determining the predicted revenue that the energy storage system will bring to the user based on the predicted retail electricity price and revenue-related parameters.

[0116] like Figure 4 As shown, step 203 includes steps 401 to 403:

[0117] Step 401: Determine the actual benefit achievement rate of the energy storage system based on the ratio of actual benefit to ideal benefit.

[0118] Step 402: Determine the predicted return achievement rate of the energy storage system based on the ratio of predicted return to ideal return.

[0119] Step 403: Based on the actual revenue achievement rate and the predicted revenue achievement rate, determine the actual operating status of the energy storage system within the preset historical period and the prediction deviation of the day-ahead electricity price prediction model.

[0120] Among them, the day-ahead electricity price forecasting model is a mathematical model used to predict the retail electricity price at each time of the next day. Its inputs usually include historical electricity price data, weather information, etc., and the output is the predicted retail electricity price sequence at each time.

[0121] For example, firstly, a predicted retail electricity price sequence for a preset historical period is determined based on a day-ahead electricity price forecasting model (or it can be predicted in advance before the start of the month). Then, the predicted revenue brought to users by the energy storage system is determined based on the predicted retail electricity price sequence and revenue-related parameters. The actual revenue achievement rate is calculated using formula (16), and the predicted revenue achievement rate is calculated using the following formula. :

[0122]

[0123] in, To predict returns, For ideal returns.

[0124] Finally, based on the actual revenue achievement rate and the predicted revenue achievement rate, it is determined whether the actual operating status of the energy storage system within the preset historical period and the prediction deviation of the day-ahead electricity price prediction model meet the requirements.

[0125] Therefore, by introducing predicted revenue and outputting it in the form of visual charts, it is possible to evaluate the contribution of day-ahead forecasting bias and control execution bias to revenue loss.

[0126] In one exemplary embodiment, such as Figure 5 As shown, the method for determining the predicted return specifically includes steps 501 to 504. Wherein:

[0127] Step 501: Determine the user's original load based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system.

[0128] For example, the user's original load is calculated using formula (1).

[0129] Step 502: Based on basic technical parameters, predicted retail electricity prices and original user loads, with the goal of maximizing the net revenue of the energy storage system's charging and discharging, calculate the predicted equivalent power exchanged between the energy storage system and the grid within a preset historical period.

[0130] The predicted equivalent power within the preset historical period can be understood as the time series of predicted equivalent power exchanged between the energy storage system and the grid at the grid connection point, i.e., the predicted equivalent power of the energy storage system on the grid side. Equivalent power refers to the power after considering charging and discharging efficiency. The predicted equivalent power is used to characterize the expected impact of the energy storage system's charging and discharging behavior on the grid's power supply under the prediction strategy (based on the predicted retail electricity price, obtained by solving a mixed-integer linear programming model to obtain the charging and discharging power series).

[0131] For example, the actual retail electricity price in the objective function (5) Replace with predicted retail electricity prices The objective function is then obtained as follows:

[0132]

[0133] Substituting the predicted retail electricity price sequence into the objective function (18), and combining it with equations (6) to (15), the objective function (18) is solved with the goal of minimizing electricity expenditure, to obtain the predicted equivalent power sequence of the energy storage system on the grid side. This is used for subsequent calculations of predicted electricity costs.

[0134] That is, solving the day-ahead forecasting strategy At that time, only the electricity price in the objective function of the mixed-integer linear programming model is changed from the actual retail electricity price. Replace with predicted electricity price The constraints characterizing the physical feasible domain and boundary of an energy storage system include charge and discharge efficiency. Rated capacity Rated power , upper limit of demand and arbitrage threshold All parameters remain constant, ensuring that the only source of difference in the evaluation of revenue achievement is the accuracy of electricity price forecasts, rather than changes in physical parameters or constraint parameters.

[0135] Step 503: Determine the predicted electricity cost for the user based on the actual retail electricity price, the user's original load, and the predicted equivalent power.

[0136] For example, the predicted electricity cost (i.e., the predicted optimal electricity cost) that a user needs to spend within a preset historical period is calculated using the following formula:

[0137]

[0138] in, To predict electricity costs, Let t be the predicted equivalent power of the energy storage system on the grid side.

[0139] In other words, the forecasting strategy is recalculated under the actual retail electricity price to obtain the predicted optimal electricity price, which is used to independently evaluate the quality of day-ahead decisions.

[0140] Step 504: Determine the projected revenue based on the benchmark electricity price and projected electricity price within the preset historical period.

[0141] For example, the predicted revenue that the energy storage system will bring to the user is determined based on the difference between the benchmark electricity price and the predicted electricity price, for example, by calculating the predicted revenue using the following formula. :

[0142]

[0143] Therefore, this embodiment first considers the charging and discharging efficiency to calculate the user's original load, and determines the predicted revenue based on the user's original load, which can ensure the reliability of the predicted revenue.

[0144] In an exemplary embodiment, step 403 includes: if both the actual revenue achievement rate and the predicted revenue achievement rate are less than or equal to a preset threshold, determining that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements; if both the actual revenue achievement rate and the predicted revenue achievement rate are greater than the preset threshold, determining that the energy storage system is operating normally and the prediction deviation meets the requirements, and determining the source of revenue loss based on the relationship between the actual revenue achievement rate and the predicted revenue achievement rate; if the actual revenue achievement rate is less than or equal to the preset threshold and the predicted revenue achievement rate is greater than the preset threshold, determining that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model meets the requirements; if the actual revenue achievement rate is greater than the preset threshold and the predicted revenue achievement rate is less than or equal to the preset threshold, determining that the energy storage system is operating normally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements.

[0145] For example, if both the actual revenue achievement rate and the predicted revenue achievement rate are lower than a preset threshold (e.g., 60%), it means that neither the prediction nor the actual result has reached the theoretical optimal level. This indicates that the control execution or equipment status is abnormal, and a comprehensive investigation of the hardware and control links, as well as the day-ahead electricity price prediction model, can be conducted.

[0146] If both the actual and predicted revenue achievement rates are greater than 60%, it indicates potential prediction and / or execution biases, suggesting room for improvement in the day-ahead electricity price forecasting model and / or control execution. Therefore, the source of revenue loss is determined based on the relationship between the actual and predicted rates of return. Specifically, if the actual revenue achievement rate is greater than or equal to the predicted rate of return, the revenue loss is determined to originate from the day-ahead electricity price forecasting model, which can be improved. If the actual revenue achievement rate is less than the predicted rate of return, the revenue loss is determined to originate from the control execution of the energy storage system, which can be improved by addressing the system's control execution and health status. These improvements aim to increase the revenue generated by the energy storage system.

[0147] That is, by comparing the predicted return achievement rate Achievement rate with actual returns Independent diagnostic prediction bias and execution bias: if If so, the day-ahead electricity price forecasting model needs improvement; and If all values ​​are below the preset threshold, the control execution or device status is determined to be abnormal.

[0148] Therefore, this embodiment defines two types of indicators, namely the predicted revenue achievement rate and the actual revenue achievement rate, to achieve an independent quantitative evaluation of the day-ahead decision quality and the real-time control effect. This enables users to clearly distinguish the sources of revenue loss, and this refined diagnostic capability significantly improves the targeting of energy storage operation optimization.

[0149] In an exemplary embodiment, the method for determining actual revenue includes: determining the user's original load based on the load and the charging / discharging efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load without an energy storage system; determining the benchmark electricity price for a preset historical period based on the user's original load and the actual retail electricity price; determining the actual electricity cost incurred by the user with an energy storage system based on the actual retail electricity price and the load of the user-side meter in the preset historical period; and determining the actual revenue based on the benchmark electricity price and the actual electricity cost.

[0150] For example, firstly, the user's original load is calculated using formula (1). The sequence is used to calculate the user's base electricity charge in the absence of energy storage using formula (2). Then, the actual electricity cost to the user in the case of an energy storage system is calculated using the following formula:

[0151]

[0152] in, This is the actual electricity cost.

[0153] Finally, based on the difference between the benchmark electricity price and the actual electricity price, the actual benefit brought to the user by the energy storage system is determined, for example, by calculating the actual benefit using the following formula. :

[0154]

[0155] Therefore, this embodiment first considers the charging and discharging efficiency to calculate the user's original load, and determines the actual benefit based on the user's original load, which can ensure the reliability of the actual benefit.

[0156] The following detailed embodiment describes the operation evaluation method of the user-side energy storage system according to this application, such as... Figure 6 As shown, the method specifically includes the following steps:

[0157] Step 601: Obtain the revenue-related parameters of the user-side energy storage system. The revenue-related parameters include: the load of the user-side energy storage system and the user-side gate meter in a preset historical period, the actual retail electricity price in the preset historical period, and the basic technical parameters of the energy storage system.

[0158] Step 602: Determine the user's original load based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system.

[0159] Step 603: Determine the base electricity charge for the preset historical period based on the user's original load and actual retail electricity price;

[0160] Step 604: Determine the actual electricity cost paid by the user when there is an energy storage system, based on the actual retail electricity price and the load of the user-side meter in the preset historical period.

[0161] Step 605: Determine the actual revenue based on the benchmark electricity price and the actual electricity price;

[0162] Step 606: Based on the actual retail electricity price and charging and discharging efficiency, with the objective function of maximizing the net charging and discharging revenue of the energy storage system, and based on the constraints, calculate the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period.

[0163] Step 607: Determine the ideal electricity cost for the user based on the actual retail electricity price, the user's original load, and the ideal equivalent power.

[0164] Step 608: Determine the ideal revenue based on the benchmark electricity price and ideal electricity price within the preset historical time period;

[0165] Step 609: Determine the predicted retail electricity price for a preset historical period based on the pre-built day-ahead electricity price prediction model;

[0166] Step 610: Based on basic technical parameters, predicted retail electricity prices and user loads, with the goal of maximizing the net revenue from charging and discharging of the energy storage system, and based on constraints, calculate the predicted equivalent power exchanged between the energy storage system and the grid within a preset historical period.

[0167] Step 611: Determine the predicted electricity cost for the user based on the actual retail electricity price, the user's original load, and the predicted equivalent power.

[0168] Step 612: Determine the projected revenue based on the benchmark electricity price and projected electricity price within the preset historical period;

[0169] Step 613: Determine the actual return achievement rate of the energy storage system based on the ratio of actual return to ideal return, and determine the predicted return achievement rate of the energy storage system based on the ratio of predicted return to ideal return.

[0170] Step 614: Based on the actual revenue achievement rate and the predicted revenue achievement rate, determine the actual operating status of the energy storage system within the preset historical period and the prediction deviation of the day-ahead electricity price prediction model.

[0171] The method of this application is described below with an exemplary specific embodiment:

[0172] This embodiment is applied to a factory whose total electricity consumption in 2025 is approximately 100 million kWh, with a maximum monthly demand of 22 MW (occurring during peak hours on June 18, 2025). An energy storage system is configured with a rated power of 5 MW, a rated capacity of 18 MWh, a minimum allowable capacity of 0.9 MWh (5% of rated capacity), a charge / discharge efficiency of 93%, and a peak-valley arbitrage price difference threshold of 0.15 yuan / kWh. The energy storage system is connected to the factory's 35 kV substation via a 10 kV busbar, and the metering point is located downstream of the outgoing circuit breaker in the high-voltage distribution room. The user adopts a reference price-linked package, with time-of-use pricing published monthly by the trading center, forming an hourly price sequence.

[0173] The evaluation method in this embodiment includes five processing steps, which are executed sequentially to form a closed-loop evaluation system:

[0174] S1: Obtain revenue-related parameters of the user-side energy storage system;

[0175] Operational data from January 1, 2025 to December 31, 2025 was obtained from the on-site data acquisition system, specifically including the load curve of the energy storage system meters for the previous month. The load curve of the electricity user access meter for one month Retail time-of-use electricity price curve for last month (The price is composed of the time-sharing reference price published by the trading center, plus the capped floating price, the monthly market operating cost allocation, and the fixed price, forming 720 to 744 independent hourly prices each month), as well as the basic technical parameters of the energy storage system (rated capacity). Minimum allowable capacity Maximum charging and discharging power Charge and discharge efficiency ).

[0176] S2: Construct a baseline scenario without energy storage and calculate the baseline electricity cost;

[0177] Based on the load curves of the energy storage system meters and the gate meter, the user's original load curve without considering energy storage can be derived using the following formula. :

[0178]

[0179] Based on the original load curve and the actual retail electricity price (time-of-use price) curve, the user's base electricity fee under the condition of no energy storage is calculated according to formula (2).

[0180] like Figure 7 As shown in the figure, this is the operating curve for a typical winter day (January 1st) without energy storage. The upper part displays the original user load curve. and actual retail electricity price curve The peak and valley distribution is shown, and the corresponding electricity cost distribution is displayed at the bottom.

[0181] S3: Determine the operating boundary and calculate the actual revenue;

[0182] Based on actual operating data of the energy storage system in 2025, the maximum charging power was 4.8MW, the maximum discharging power was 4.9MW, and the SOC operating range was 12% to 95%. This was maintained after verification that the basic technical parameters were not exceeded. As an optimization calculation parameter, the actual peak-valley arbitrage revenue of the energy storage system is calculated according to formula (22). :

[0183] Calculations show that the total actual retail revenue for the entire year of 2025... The initial investment was 2,855,426 yuan. After the investment was split between the investor and the user at an 8:2 ratio, the user received 571,085 yuan. Figure 8 As shown in the figure, this is a bar chart comparing monthly retail electricity costs for each strategy. The bars without energy storage represent the base electricity cost. Model prediction and model ideal The bars represent the actual electricity costs after implementing energy storage; the difference between the two represents the electricity cost savings brought about by energy storage. For example... Figure 9 As shown in the figure, this is a bar chart comparing the monthly retail revenue of each strategy, which intuitively shows the difference between the model's prediction and the model's ideal revenue.

[0184] S4: Establish an optimization model and solve for the ideal return;

[0185] A mixed-integer linear programming model based on actual retail electricity prices is constructed with a daily optimization period. The objective function is to minimize daily electricity cost.

[0186]

[0187]

[0188] The constraints include:

[0189]

[0190] Charge-discharge mutual exclusion constraint:

[0191]

[0192]

[0193]

[0194] SOC continuity constraints and capacity upper and lower limits constraints:

[0195]

[0196]

[0197] Grid-side power demand constraints:

[0198]

[0199]

[0200] in .

[0201] Electricity price difference threshold constraint: Only when the peak-valley electricity price difference exceeds a set threshold. Arbitrage across time periods is allowed:

[0202]

[0203] The optimal daily charge / discharge power sequence and the grid-side power of energy storage are obtained by using a mixed-integer linear programming solver. .like Figure 10 As shown in the figure, this figure is the optimized operation curve of the energy storage system based on the ideal retail electricity price on a typical winter day (January 1). The upper sub-figure shows the correspondence between the optimized energy storage charging and discharging power and the time-of-use electricity price curve, and the lower sub-figure shows the SOC curve. It can be seen that the initial and final capacity are both 0.9MWh and the system operates within the boundary throughout the day. The optimization strategy charges during the off-peak hours and discharges during the peak hours while meeting the demand constraint.

[0204] Substitute the ideal energy storage grid-side power sequence obtained from daily optimization into formula (35) to calculate the theoretically optimal electricity cost:

[0205]

[0206] Calculate the ideal return according to formula (36):

[0207]

[0208] Calculations show that the theoretically optimal total retail revenue for the entire year of 2025... The total revenue is 3,756,818 yuan, corresponding to a user revenue of 751,364 yuan. The theoretical revenue of the day-ahead forecasting strategy is obtained by recalculating the revenue under the actual electricity price. Yuan. For example... Figure 11 As shown, this figure represents the optimized operation curve of the energy storage system based on the predicted retail electricity price on a typical winter day (January 1st). Figure 10 The comparison shows that the timing of charging and discharging differs from the SOC curve due to deviations in the predicted electricity price. This difference ultimately manifests as a gap between the predicted and ideal returns.

[0209] S5: Evaluation of Profitability and Output of Results

[0210] According to formulas (16) and (17), the actual revenue achievement rate and the predicted revenue achievement rate are both 76.0%, indicating that there is room for improvement in the day-ahead electricity price prediction model (prediction deviation of about 24%), while the real-time control execution has no significant deviation. At this time, if... If the day-ahead electricity price forecasting model is deemed to need improvement, then the control execution or equipment status is deemed abnormal. The actual revenue, forecast strategy revenue, theoretical optimal revenue, achievement rate of the two types of revenue, and daily optimization strategy curves are output in the form of visual charts to form a monthly revenue evaluation report.

[0211] In summary, this application addresses the shortcomings of related technologies, such as neglecting the impact of demand charges, providing coarse modeling of charging and discharging efficiency, and lacking comparative evaluation between actual operation and theoretical optimality. It constructs a benchmark electricity cost in a scenario without energy storage through reverse engineering, and establishes a theoretically optimal strategy model considering charging and discharging efficiency based on mixed-integer linear programming. This enables a quantitative comparative evaluation between actual operating results and theoretical optimality. By distinguishing between prediction deviation and execution deviation, it provides independent diagnostic basis for prediction model optimization and control strategy improvement. It can accurately quantify the gap between the actual operating results of an energy storage system and the theoretically feasible optimality, providing scientific support for energy storage investment decisions and operational optimization, and has significant engineering practical value.

[0212] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0213] Based on the same inventive concept, this application also provides an operation evaluation device for a user-side energy storage system to implement the operation evaluation method for the user-side energy storage system described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the operation evaluation device for a user-side energy storage system provided below can be found in the limitations of the operation evaluation method for user-side energy storage systems described above, and will not be repeated here.

[0214] In one exemplary embodiment, such as Figure 12 As shown, an operation evaluation device for a user-side energy storage system is provided, comprising: an acquisition module 1201, a first determination module 1202, and a second determination module 1203, wherein:

[0215] The acquisition module 1201 is used to acquire the revenue-related parameters of the user-side energy storage system. The revenue-related parameters include: the load of the user-side energy storage system and the user-side gate meter in a preset historical period, the actual retail electricity price in the preset historical period, and the basic technical parameters of the energy storage system.

[0216] The first determining module 1202 is used to determine the ideal benefits that the energy storage system brings to the user based on the benefit-related parameters.

[0217] The second determining module 1203 is used to determine the actual operating status of the energy storage system within a preset historical period based on the actual and ideal benefits of the energy storage system within the preset historical period.

[0218] In one embodiment, the basic technical parameters include at least one of maximum charging / discharging power, rated capacity, and minimum allowable capacity, as well as charging / discharging efficiency; the first determining module 1202 is specifically used to: determine the user's original load based on the load and the charging / discharging efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system; based on the basic technical parameters, the actual retail electricity price, and the user's original load, calculate the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period with the goal of maximizing the net charging / discharging revenue of the energy storage system; determine the ideal electricity cost paid by the user based on the actual retail electricity price, the user's original load, and the ideal equivalent power; and determine the ideal revenue based on the benchmark electricity cost and the ideal electricity cost within the preset historical period.

[0219] In one embodiment, the first determining module 1202 is specifically used to: calculate the ideal equivalent power exchanged between the energy storage system and the grid within a preset historical period, based on the actual retail electricity price and charging / discharging efficiency, with the objective function being to maximize the net charging / discharging revenue of the energy storage system; wherein the constraints of the objective function include at least one of the following: satisfying the maximum charging / discharging power; satisfying the rated capacity; satisfying the minimum allowable capacity; and the sum of the user's original load and the ideal equivalent power is less than or equal to the preset maximum value of the original load.

[0220] In one embodiment, the second determining module 1203 is specifically used to: determine the actual return achievement rate based on the ratio of actual return to ideal return; determine that the energy storage system is operating abnormally if the actual return achievement rate is less than or equal to a preset threshold; and determine that the energy storage system is operating normally if the actual return achievement rate is greater than the preset threshold.

[0221] In one embodiment, the apparatus further includes: a third determining module, configured to determine the predicted retail electricity price within a preset historical period based on a pre-built day-ahead electricity price prediction model; a fourth determining module, configured to: determine the predicted revenue brought to users by the energy storage system based on the predicted retail electricity price and revenue-related parameters; and a second determining module 1203, specifically configured to: determine the actual revenue achievement rate of the energy storage system based on the ratio of actual revenue to ideal revenue; determine the predicted revenue achievement rate of the energy storage system based on the ratio of predicted revenue to ideal revenue; and determine the actual operating status of the energy storage system and the prediction deviation of the day-ahead electricity price prediction model within the preset historical period based on the actual revenue achievement rate and the predicted revenue achievement rate.

[0222] In one embodiment, the fourth determining module is specifically used to: determine the user's original load based on the load and the charging and discharging efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system; based on the basic technical parameters, the predicted retail electricity price, and the user's original load, and with the goal of maximizing the net charging and discharging revenue of the energy storage system, calculate the predicted equivalent power exchanged between the energy storage system and the grid within a preset historical period; determine the user's predicted electricity cost based on the actual retail electricity price, the user's original load, and the predicted equivalent power; and determine the predicted revenue based on the benchmark electricity cost and the predicted electricity cost within the preset historical period.

[0223] In one embodiment, the second determining module 1203 is specifically configured to: determine that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements when both the actual revenue achievement rate and the predicted revenue achievement rate are less than or equal to a preset threshold; determine that the energy storage system is operating normally and the prediction deviation meets the requirements when both the actual revenue achievement rate and the predicted revenue achievement rate are greater than the preset threshold, and determine the source of revenue loss based on the relationship between the actual revenue achievement rate and the predicted revenue achievement rate; determine that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model meets the requirements when the actual revenue achievement rate is less than or equal to the preset threshold and the predicted revenue achievement rate is greater than the preset threshold; and determine that the energy storage system is operating normally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements when the actual revenue achievement rate is greater than the preset threshold and the predicted revenue achievement rate is less than or equal to the preset threshold.

[0224] In one embodiment, the basic technical parameters include the charging and discharging efficiency of the energy storage system; the device further includes: a fifth determining module, used to determine the user's original load based on the load and the charging and discharging efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load without an energy storage system; a sixth determining module, used to determine the benchmark electricity price within a preset historical period based on the user's original load and the actual retail electricity price; a seventh determining module, used to determine the actual electricity price paid by the user with an energy storage system based on the actual retail electricity price and the load of the user-side meter within the preset historical period; and an eighth determining module, used to determine the actual revenue based on the benchmark electricity price and the actual electricity price.

[0225] Each module in the aforementioned user-side energy storage system operation evaluation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0226] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 13As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores operational evaluation data for the user-side energy storage system. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an operational evaluation method for a user-side energy storage system.

[0227] Those skilled in the art will understand that Figure 13 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0228] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement an operational evaluation method for a user-side energy storage system.

[0229] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements an operational evaluation method for a user-side energy storage system.

[0230] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements an operational evaluation method for a user-side energy storage system.

[0231] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0232] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0233] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for operation evaluation of a user-side energy storage system, characterized in that, The method includes: Obtain revenue-related parameters of the user-side energy storage system, including: the load of the user-side energy storage system and the user-side gate meter during a preset historical period, the actual retail electricity price during the preset historical period, and the basic technical parameters of the energy storage system. The ideal benefits that the energy storage system brings to the user are determined based on the aforementioned benefit-related parameters; Based on the actual and ideal benefits of the energy storage system during the preset historical period, the actual operating status of the energy storage system during the preset historical period is determined. The basic technical parameters include at least one of maximum charge / discharge power, rated capacity, and minimum allowable capacity, as well as charge / discharge efficiency; determining the ideal benefit to the user from the energy storage system based on the benefit-related parameters includes: The user's original load is determined based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system. Based on the basic technical parameters, the actual retail electricity price, and the user's original load, with the goal of maximizing the net revenue of the energy storage system's charging and discharging, the ideal equivalent power exchanged between the energy storage system and the grid during the preset historical period is calculated. The ideal electricity cost for the user is determined based on the actual retail electricity price, the user's original load, and the ideal equivalent power. The ideal revenue is determined based on the benchmark electricity price and the ideal electricity price within a preset historical period.

2. The method of claim 1, wherein, Based on the basic technical parameters, the actual retail electricity price, and the user's original load, and with the goal of maximizing the net revenue from charging and discharging the energy storage system, the ideal equivalent power exchanged between the energy storage system and the grid within the preset historical period is calculated, including: Based on the actual retail electricity price and the charging and discharging efficiency, and with the objective function of maximizing the net charging and discharging revenue of the energy storage system, the ideal equivalent power exchanged between the energy storage system and the grid during the preset historical period is calculated. The constraints of the objective function include at least one of the following: The maximum charge / discharge power is satisfied; The rated capacity is met; The minimum allowable capacity must be met; The sum of the user's original load and the ideal equivalent power is less than or equal to the preset maximum value of the original load.

3. The method according to claim 1, characterized in that, The step of determining the actual operating status of the energy storage system within the preset historical period based on the actual and ideal returns of the energy storage system includes: The actual return achievement rate is determined based on the ratio of the actual return to the ideal return. If the actual return achievement rate is less than or equal to a preset threshold, the energy storage system is determined to be operating abnormally. If the actual return achievement rate is greater than a preset threshold, the energy storage system is determined to be operating normally.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: The predicted retail electricity price for a preset historical period is determined based on a pre-built day-ahead electricity price prediction model. The predicted revenue that the energy storage system will bring to users is determined based on the predicted retail electricity price and the revenue-related parameters. The step of determining the actual operating status of the energy storage system within the preset historical period based on the actual and ideal returns of the energy storage system includes: The actual return achievement rate of the energy storage system is determined based on the ratio of the actual return to the ideal return. The predicted return achievement rate of the energy storage system is determined based on the ratio of the predicted return to the ideal return. Based on the actual revenue achievement rate and the predicted revenue achievement rate, the actual operating status of the energy storage system within a preset historical period and the prediction deviation of the day-ahead electricity price prediction model are determined.

5. The method according to claim 4, characterized in that, The step of determining the predicted revenue that the energy storage system will bring to users based on the predicted retail electricity price and the revenue-related parameters includes: The user's original load is determined based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system. Based on the basic technical parameters, the predicted retail electricity price, and the user's original load, with the goal of maximizing the net revenue from charging and discharging the energy storage system, the predicted equivalent power exchanged between the energy storage system and the grid during the preset historical period is calculated. The predicted electricity cost to the user is determined based on the actual retail electricity price, the user's original load, and the predicted equivalent power. The predicted revenue is determined based on the benchmark electricity price within a preset historical period and the predicted electricity price.

6. The method according to claim 4, characterized in that, The step of determining the actual operating status of the energy storage system and the prediction deviation of the day-ahead electricity price prediction model within a preset historical period based on the actual revenue achievement rate and the predicted revenue achievement rate includes: If both the actual revenue achievement rate and the predicted revenue achievement rate are less than or equal to a preset threshold, it is determined that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements. If both the actual revenue achievement rate and the predicted revenue achievement rate are greater than a preset threshold, it is determined that the energy storage system is operating normally and the prediction deviation meets the requirements, and the source of revenue loss is determined based on the relationship between the actual revenue achievement rate and the predicted revenue achievement rate. If the actual revenue achievement rate is less than or equal to a preset threshold, and the predicted revenue achievement rate is greater than a preset threshold, it is determined that the energy storage system is operating abnormally and the prediction deviation of the day-ahead electricity price prediction model meets the requirements. If the actual revenue achievement rate is greater than a preset threshold and the predicted revenue achievement rate is less than or equal to a preset threshold, it is determined that the energy storage system is operating normally and the prediction deviation of the day-ahead electricity price prediction model does not meet the requirements.

7. The method according to any one of claims 1-3, characterized in that, The basic technical parameters include the charging and discharging efficiency of the energy storage system; the method for determining the actual benefit includes: The user's original load is determined based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system. The base electricity price for the preset historical period is determined based on the user's original load and the actual retail electricity price. Based on the actual retail electricity price and the load of the user-side gate meter in a preset historical period, determine the actual electricity cost paid by the user when there is an energy storage system. The actual revenue is determined based on the benchmark electricity price and the actual electricity price.

8. An operation evaluation device for a user-side energy storage system, characterized in that, The device includes: The acquisition module is used to acquire revenue-related parameters of the user-side energy storage system. The revenue-related parameters include: the load of the user-side energy storage system and the user-side gate meter in a preset historical period, the actual retail electricity price in the preset historical period, and the basic technical parameters of the energy storage system. The first determining module is used to determine the ideal benefit that the energy storage system brings to the user based on the benefit-related parameters. The second determining module is used to determine the actual operating status of the energy storage system within the preset historical period based on the actual benefit and the ideal benefit of the energy storage system within the preset historical period. The basic technical parameters include at least one of maximum charge / discharge power, rated capacity, and minimum allowable capacity, as well as charge / discharge efficiency; the first determining module is specifically used for: The user's original load is determined based on the load and the charge / discharge efficiency in the basic technical parameters; the user's original load is used to characterize the user's original load in the absence of an energy storage system. Based on the basic technical parameters, the actual retail electricity price, and the user's original load, with the goal of maximizing the net revenue of the energy storage system's charging and discharging, the ideal equivalent power exchanged between the energy storage system and the grid during the preset historical period is calculated. The ideal electricity cost for the user is determined based on the actual retail electricity price, the user's original load, and the ideal equivalent power. The ideal revenue is determined based on the benchmark electricity price and the ideal electricity price within a preset historical period.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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