Energy storage full life cycle soh staged utilization value improvement method and system

Abstract

The application provides a kind of energy storage full life cycle SOH phased utilization value evaluation and promotion method and system, the method includes: the target model of the optimal economy of battery energy storage system in full life cycle, and the lowest cost of grid side and user side is established;The cost parameters of battery energy storage system, grid frequency modulation data, frequency modulation negotiation result and user side power demand prediction information are input into the target model, the optimal configuration scheme is obtained by adjusting the price coefficient of battery energy storage system participating in the first stage and the second stage service unit price, and the rated power and rated capacity of battery energy storage system in the first stage and the second stage are configured according to the optimal configuration scheme.The application comprehensively considers the applicability of battery energy storage system in each stage and scene in full life cycle, and configures the rated power and rated capacity in different stages, to realize the maximum utilization and promotion of the value of battery energy storage system in full life cycle.

Description

Technical Field

[0001] This invention relates to the field of energy storage technology, and in particular to a method and system for enhancing the value of SOH (Solar Energy Storage) utilization in stages throughout its entire life cycle. Background Technology

[0002] The assessment of the benefits and risks of battery energy storage systems in specific scenarios is one of the criteria that energy storage vendors need to consider. Battery energy storage systems can participate in different application scenarios of the power system, such as grid-side frequency regulation, peak shaving and valley filling on the user side, and energy ancillary services.

[0003] Different scenarios have different requirements for the technical reliability of battery energy storage systems. When participating in different application scenarios, the reliability, resilience and applicability of battery energy storage systems to the current state of health (SOH) need to be considered. In order to improve the service life and economic benefits of battery energy storage systems, it is necessary to evaluate the utilization value of battery energy storage systems throughout their entire life cycle, thereby improving their economic benefits. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a method and system for enhancing the value of SOH (Solar Energy Storage) utilization in stages throughout its entire life cycle, so as to overcome the above problems or at least partially solve them.

[0005] A first aspect of this invention discloses a method for enhancing the value of SOH (Solar Energy Storage) throughout its entire lifecycle, the method comprising:

[0006] A target model is established to optimize the energy storage economy of the battery energy storage system throughout its entire life cycle and minimize the costs on both the grid side and the user side. The life cycle of the battery energy storage system is divided into two stages: the first stage for grid-side frequency regulation and the second stage for participating in user-side energy optimization scheduling in a shared energy storage mode.

[0007] Input the cost parameters of the battery energy storage system, grid frequency regulation data, frequency regulation negotiation results, and user-side electricity demand forecast information into the target model;

[0008] The target model is solved by combining mixed integer linear programming algorithm to obtain the optimal configuration scheme. The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The optimal configuration scheme includes: the rated power and rated capacity of the battery energy storage system in the first stage and the second stage respectively, the energy storage revenue and service unit price of the battery energy storage system participating in grid-side frequency regulation in the first stage, the energy storage revenue and service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second stage, and the costs on the grid side and the user side.

[0009] According to the optimal configuration scheme, the rated power and rated capacity of the battery energy storage system are configured in the first stage and the second stage, respectively.

[0010] Optionally, the target model for establishing the battery energy storage system with optimal energy storage economics throughout its entire life cycle and minimum costs on both the grid and user sides includes:

[0011] An objective function is established, which aims to optimize the energy storage economy of the battery energy storage system throughout its entire life cycle and minimize the costs on both the grid side and the user side.

[0012] A first constraint condition is determined, which is used for grid-side frequency regulation, and the regional control error command for grid-side frequency regulation satisfies the maximum allowable error of the grid region.

[0013] A second constraint is determined, which is used for user-side energy optimization scheduling. The total power provided to the user satisfies the power balance between the user's load demand power. The total power provided to the user includes the renewable energy power provided by the user, the power purchased by the user from the grid, and the power discharged by the battery energy storage system.

[0014] A third constraint condition is determined, which is used to limit the power range of charging and discharging and to calculate the rated power of the battery energy storage system;

[0015] A fourth constraint condition is determined, which is used to constrain the state of charge and capacity of the battery energy storage system, as well as to calculate the rated capacity.

[0016] The optimal configuration scheme is obtained by solving the target model using a mixed-integer linear programming algorithm, including:

[0017] Using the first, second, third, and fourth constraints as constraints, and combining them with a mixed-integer linear programming algorithm, the target model is solved to obtain the optimal configuration scheme.

[0018] Optionally, the objective function includes: an outer function that optimizes the energy storage economy of the battery energy storage system throughout its entire life cycle, and an inner function that minimizes costs on both the grid side and the user side; the objective function is expressed as:

[0019]

[0020] in, For the outer function, For the inner function, , These are typical scenarios of the first stage. and typical scenarios in the second stage Each of their respective operating days , These refer to the service life of the battery energy storage system in the first stage and the second stage, respectively. , Typical scenario of the first stage and typical scenarios in the second stage Their respective totals The benefit of the battery energy storage system participating in grid-side frequency regulation in the first stage, The environmental benefits of the battery energy storage system participating in grid-side frequency regulation in the first stage. This refers to the penalty cost incurred when the battery energy storage system fails to meet actual demand during grid-side frequency regulation in the first phase. The benefits of the battery energy storage system participating in user-side energy optimization scheduling in the second phase, The environmental benefits of the battery energy storage system participating in user-side energy optimization scheduling in the second phase. The cost parameters of the battery energy storage system are as follows: The cost for users to purchase electricity from the grid.

[0021] Optionally, the optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The specific adjustment process includes:

[0022] The initial service unit price for the battery energy storage system to participate in power-side frequency regulation in the first stage and the initial service unit price for the battery energy storage system to participate in user-side energy optimization scheduling in the second stage are preset.

[0023] Using the first, second, third, and fourth constraints as constraints, and combining them with a mixed-integer linear programming algorithm to solve the target model, the optimal configuration scheme is obtained, including:

[0024] Using the first, second, third, and fourth constraints as constraints, the service unit price coefficients of the battery energy storage system participating in power-side frequency regulation in the first stage and the service unit price coefficients of the battery energy storage system participating in user-side energy optimization scheduling in the second stage are adjusted respectively. When the objective function simultaneously satisfies the objectives of achieving optimal energy storage economy of the battery energy storage system throughout its entire life cycle and minimizing costs on both the grid side and the user side, the optimal configuration scheme is obtained.

[0025] Optionally, obtaining the optimal configuration scheme includes solving for the rated power and rated capacity of the battery energy storage system in the first stage and the second stage, including:

[0026] Based on the first constraint and the grid frequency regulation data, the frequency regulation charging power and frequency regulation discharging power of the battery energy storage system participating in grid-side frequency regulation in the first stage are calculated.

[0027] Based on the second constraint and the user-side power demand prediction information, the scheduled charging power and scheduled discharging power of the battery energy storage system participating in user-side energy optimization scheduling in the second stage are calculated.

[0028] Based on the third constraint, the frequency-modulated charging power, and the frequency-modulated discharging power, the rated power of the battery energy storage system in the first stage is calculated; based on the third constraint, the scheduled charging power, and the scheduled discharging power, the rated power of the battery energy storage system in the second stage is calculated.

[0029] Based on the fourth constraint, the frequency-modulated charging power, and the frequency-modulated discharging power, the rated capacity of the battery energy storage system in the first stage is calculated; based on the fourth constraint, the scheduled charging power, and the scheduled discharging power, the rated capacity of the battery energy storage system in the second stage is calculated.

[0030] Optionally, participating in user-side energy optimization scheduling in a shared energy storage mode includes:

[0031] Calculate the operating unit price of the user-configured energy storage system and the service unit price of the battery energy storage system participating in the user-side energy optimization scheduling in the second stage;

[0032] The system outputs a prompt to the user indicating the relationship between the operating unit price of the user-configured energy storage and the service unit price of the battery energy storage system participating in the user-side energy optimization scheduling in the second stage, so that the user can choose a power supply method with a lower unit price.

[0033] Optionally, the method further includes: dividing the entire life cycle of the battery energy storage system into stages based on the State of Health (SOH) of the battery energy storage system, specifically including:

[0034] Establish a capacity decay model for the battery energy storage system in the first and second stages to predict the real-time changes in the SOH of the battery energy storage system;

[0035] The battery energy storage system is divided into two phases: the first phase is when the State of Harmony (SOH) is between 80% and 100%, in which it participates in grid-side frequency regulation; the second phase is when the SOH is between 50% and 80%, in which it participates in user-side energy optimization scheduling in a shared energy storage mode.

[0036] A second aspect of this invention discloses a phased utilization value enhancement system for SOH (Solar Energy Storage) throughout its entire lifecycle, the system comprising:

[0037] A module is established to create a target model for optimizing the energy storage economy of a battery energy storage system throughout its entire life cycle and minimizing costs on both the grid and user sides. The life cycle of the battery energy storage system is divided into two phases: a first phase for grid-side frequency regulation and a second phase for participating in user-side energy optimization scheduling in a shared energy storage mode.

[0038] The input module is used to input the cost parameters of the battery energy storage system, grid frequency regulation data, frequency regulation negotiation results, and user-side electricity demand forecast information into the target model;

[0039] The solution module is used to solve the target model by combining a mixed integer linear programming algorithm to obtain the optimal configuration scheme. The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The optimal configuration scheme includes: the rated power and rated capacity of the battery energy storage system in the first stage and the second stage respectively, the energy storage revenue and service unit price of the battery energy storage system participating in grid-side frequency regulation in the first stage, the energy storage revenue and service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second stage, and the costs on the grid side and the user side.

[0040] The configuration module is used to configure the rated power and rated capacity of the battery energy storage system in the first stage and the second stage according to the optimal configuration scheme.

[0041] The embodiments of the present invention have the following advantages:

[0042] In this embodiment of the invention, the lifecycle of the battery energy storage system is divided into two stages based on the different ranges of State of Health (SOH). The first stage, with higher reliability, is used for grid-side frequency regulation, while the second stage, with lower reliability, participates in user energy optimization scheduling through shared energy storage. This fully considers the applicability of the current SOH and application scenarios, enabling the battery energy storage system to be used throughout its entire lifecycle. By adjusting the price coefficient of the service unit price for battery energy storage in the first and second stages, the optimal configuration scheme is obtained, simultaneously satisfying the optimal energy storage economy and grid-side costs, and minimizing costs on both the grid and user sides. Based on this optimal configuration scheme, the rated power and rated capacity of the battery energy storage system in both stages are configured, thereby maximizing and enhancing the value of the battery energy storage system throughout its entire lifecycle. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of a method for enhancing the value of SOH (Solar Energy Storage) throughout its entire life cycle, provided by an embodiment of the present invention.

[0045] Figure 2 This is a schematic diagram of a phased utilization value enhancement system for energy storage throughout its entire life cycle (SOH) provided in an embodiment of the present invention. Detailed Implementation

[0046] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] To fully consider the applicability of the current State of Health (SOH) and application scenarios of battery energy storage systems, and to maximize and enhance the value of battery energy storage systems throughout their entire lifecycle, the applicant proposes the following technical concept: Based on different SOHs throughout the lifecycle of the battery energy storage system, its entire lifecycle is divided into a first stage and a second stage to participate in different demand-side scheduling. Furthermore, by constructing a target model for optimal energy storage economics and demand-side costs, the rated capacity and rated power of the energy storage system are configured, and the economic benefits of different stages are analyzed.

[0048] Specifically, the battery energy storage system in the first stage of SOH participates in grid-side frequency regulation. Then, the battery energy storage system in the second stage, after being decommissioned from the first stage, participates in user-side energy optimization scheduling in a shared energy storage (SES) mode. An "outer-inner" layer objective model is established, aiming to achieve optimal energy storage economics and minimum demand-side costs. By adjusting the service unit price coefficients for the battery energy storage system participating in the first and second stages, the optimal energy storage economics and minimum grid-side and user-side costs throughout the entire lifecycle of the battery energy storage system are simultaneously achieved. This yields the optimal configuration scheme that maximizes the value of the battery energy storage system. Based on this optimal configuration scheme, the energy storage capacity and power of the battery energy storage system in the first and second stages are configured. Finally, a capacity decay model of the battery energy storage system is established to calculate the lifespan of the two stages and accurately predict the real-time changes in the SOH.

[0049] This invention provides a method for enhancing the value of SOH (Solar Energy Storage) across its entire lifecycle, such as... Figure 1 As shown, Figure 1 A flowchart illustrating the steps of a method for enhancing the value of SOH (Solar Energy Storage) throughout its entire lifecycle, as provided in this embodiment of the invention, includes the following steps:

[0050] Step S201: Establish a target model for the battery energy storage system to achieve optimal energy storage economy throughout its entire life cycle and minimize costs on both the grid side and the user side. The life cycle of the battery energy storage system is divided into two stages: a first stage for grid-side frequency regulation and a second stage for participating in user-side energy optimization scheduling in a shared energy storage mode.

[0051] The reliability of battery energy storage systems changes with the State of Health (SOH). Battery energy storage systems exhibit high reliability between 80% and 100% SOH, and lower reliability between 50% and 80% SOH. Therefore, the first stage is defined as the SOH range of 80%-100%, and the second stage as the SOH range of 50%-80%. Due to frequent power fluctuations on the grid side, higher technical reliability is required for battery energy storage systems. However, user-side power is more stable, and its reliability requirements are lower. Therefore, the first stage of the battery energy storage system is used for grid-side frequency regulation, while the second stage participates in user-side energy optimization scheduling through shared energy storage. This fully utilizes the applicability of the current SOH and application scenarios of the battery energy storage system, enabling its use throughout its entire lifecycle. A target model for the battery energy storage system throughout its entire lifecycle is established, including target models for both the first and second stages.

[0052] In one feasible implementation, the objective model for establishing the battery energy storage system with optimal energy storage economics throughout its entire life cycle and minimum costs on both the grid side and the user side includes the following steps:

[0053] A1: Establish an objective function, which aims to achieve optimal energy storage economics for the battery energy storage system throughout its entire lifecycle, while minimizing costs on both the grid and user sides. Therefore, the objective function comprises: an outer function optimizing energy storage economics throughout the battery energy storage system's lifecycle, and an inner function minimizing costs on both the grid and user sides; the objective function is expressed as:

[0054]

[0055] in, For the outer function, For the inner function, , These are typical scenarios of the first stage. and typical scenarios in the second stage Each of their respective operating days , These refer to the service life of the battery energy storage system in the first stage and the second stage, respectively. , Typical scenario of the first stage and typical scenarios in the second stage Their respective totals The benefit of the battery energy storage system participating in grid-side frequency regulation in the first stage, The environmental benefits of the battery energy storage system participating in grid-side frequency regulation in the first stage. This refers to the penalty cost incurred when the battery energy storage system fails to meet actual demand during grid-side frequency regulation in the first phase. The benefits of the battery energy storage system participating in user-side energy optimization scheduling in the second phase, The environmental benefits of the battery energy storage system participating in user-side energy optimization scheduling in the second phase. The cost parameters of the battery energy storage system are as follows: The cost for users to purchase electricity from the grid.

[0056] Specifically, the process of establishing the objective function is as follows:

[0057] First, establish the relevant functions for the battery energy storage system's participation in grid-side frequency regulation during the first phase. As the upper and lower frequency regulation reserve capacity for grid-side frequency regulation scheduling, the battery energy storage system's basic frequency regulation requirements must meet the specified dead zone within the regulation range. or In grid frequency regulation, "up-regulation" refers to the energy storage provider releasing a certain amount of power to the grid side when the system frequency is 49.967Hz lower than the actual requirement. "Down-regulation" refers to the battery storage system charging from the grid side when the system frequency is 50.033Hz higher than the actual requirement. The relevant function for the battery storage system's participation in grid frequency regulation in the first phase is expressed as follows:

[0058]

[0059]

[0060]

[0061]

[0062] in, and This refers to the power of the battery energy storage system participating in grid-side up- and down-frequency regulation during the first phase. The frequency regulation benefits of battery energy storage systems participating in grid-side frequency regulation in the first phase. The environmental benefits of battery energy storage systems participating in grid-side frequency regulation in the first phase. and For battery energy storage systems The charging and discharging power that is constantly involved in frequency modulation. Rated power configured for battery energy storage systems For the initial scheduling time, This represents the total number of scheduling periods within one cycle of the battery energy storage system. and For battery energy storage systems in Initial up and down frequency modulation service unit price at any time For conventional coal-fired units Total emissions of various pollutants For conventional units The unit cost of each pollutant This refers to the total amount of emissions.

[0063] Furthermore, if the battery energy storage system fails to meet the actual demand on the demand side during the first phase of grid-side frequency regulation, it should be subject to a certain penalty, the penalty cost function of which is expressed as:

[0064]

[0065] in, Unit price for frequency regulation mismatch penalty; This refers to the deviation between the required reserve power and the actual power consumed / supplied.

[0066] Secondly, a function is established to enable the battery energy storage system to participate in user-side energy optimization scheduling in the second phase. After acquiring user-side electricity consumption information, charging and discharging auxiliary services are provided to users through the dispatch center. At this time, the electricity cost for each user includes the cost of purchasing electricity from the grid and the service fee for leasing shared energy storage. Therefore, the benefit of the battery energy storage system participating in user energy optimization scheduling in the second phase is expressed as:

[0067]

[0068]

[0069] in, The benefits that battery energy storage systems gain from participating in user-side energy optimization scheduling in the second phase. The environmental benefits gained by battery energy storage systems participating in user-side energy optimization scheduling in the second phase. The total number of time periods during which the battery energy storage system participates in energy optimization for each user within a scheduling cycle in the second phase. For the total user, and The real-time charging and discharging unit price for users leasing shared energy storage. This is an adjustment factor for the unit price of shared energy storage services. and Hewei shared energy storage for users Perform charging and discharging power, For shared energy storage The power supplied to each user during a given time period.

[0070] The cost for users to purchase electricity from the grid is:

[0071]

[0072] in, Regional electricity price; For users Purchase electricity from the grid.

[0073] Finally, by integrating the relevant functions of the two stages, we obtain the objective function of the battery energy storage system throughout its entire life cycle. This means we obtain the outer function that optimizes the energy storage economy of the battery energy storage system and the inner function that minimizes costs on both the grid side and the user side.

[0074] A2: Determine the first constraint condition, which is used for grid-side frequency regulation. The area control error (ACE) command for grid-side frequency regulation satisfies the maximum allowable error of the grid area. For example, the first constraint can be expressed as:

[0075]

[0076] in, To mitigate real-time regional control error power command fluctuations. The maximum allowable ACE power deviation for the power grid area. The real-time power of the battery energy storage system is specifically expressed as follows:

[0077]

[0078] The frequency deviation should satisfy the following formula:

[0079]

[0080] in, This is the frequency deviation coefficient. If We can obtain:

[0081]

[0082] A3: Determine the second constraint condition, which is used for user-side energy optimization scheduling. The total power provided to the user satisfies the power balance between the user's load demand power. The total power provided to the user includes the renewable energy power provided by the user, the power purchased by the user from the grid, and the power discharged by the battery energy storage system.

[0083] Since each user has its own renewable energy output power and load demand, and the real-time matching degree between the former and the latter is not high, shared energy storage is introduced. The main constraints at this stage include power balance constraints; for example, the second constraint can be expressed as:

[0084]

[0085]

[0086] in, and For users New energy output power, For users Load demand, and For shared energy storage Total charge and discharge amount at any given moment.

[0087] A4: Determine the third constraint, which is used to limit the power range and calculate the rated power of the battery energy storage system during charging and discharging. For example, the third constraint can be expressed as:

[0088]

[0089]

[0090] in, and The maximum power charge and discharge power of the battery energy storage system in the first and second stages are respectively. and These are the rated power of the battery energy storage system in the first and second stages, respectively. and These represent the conversion efficiency of the battery energy storage system during the first stage of charging and discharging, respectively. and These represent the conversion efficiency of the battery energy storage system during the second stage of charging and discharging.

[0091] A5: Determine the fourth constraint, which is used to constrain the state of charge and capacity of the battery energy storage system, as well as to calculate the rated capacity. For example, the fourth constraint can be expressed as:

[0092]

[0093]

[0094] in, For battery energy storage systems in Battery status at any time. and These represent the upper and lower bounds of the battery energy storage system's capacity in the first stage. and These represent the upper and lower limits of the battery energy storage system's capacity in the second stage. and These represent the minimum and maximum states of charge of the battery energy storage system in the first stage, respectively. and These represent the minimum and maximum states of charge of the battery energy storage system in the second stage, respectively. and These are the State of Charge (SOC) of the battery energy storage system at the initial moment and at the beginning of the next scheduling cycle, respectively.

[0095] In this embodiment, the lifecycle of the battery energy storage system is divided into two stages based on the different ranges of State of Health (SOH). The first stage, which has higher reliability, is used for grid-side frequency regulation, while the second stage, which has lower reliability, participates in user energy optimization scheduling through shared energy storage. This fully considers the applicability of the current SOH and application scenarios, enabling the battery energy storage system to be used throughout its entire lifecycle. By establishing a target model that optimizes the energy storage economy of the battery energy storage system throughout its entire lifecycle and minimizes the costs on both the grid and user sides, the rated power and rated capacity of the battery energy storage system can be solved subsequently.

[0096] Step S102: Input the cost parameters of the battery energy storage system, grid frequency regulation data, frequency regulation negotiation results, and user-side electricity demand forecast information into the target model.

[0097] In this embodiment, the cost parameters of the battery energy storage system The data includes initial construction costs, operation and maintenance costs, replacement costs, and residual value. Grid frequency regulation data includes real-time regional control error power output, grid frequency regulation error coefficients, and frequency dead zone range. Frequency regulation negotiation results include penalty costs incurred when the battery energy storage system fails to meet grid-side demand during dispatch. User-side electricity demand forecasting information includes real-time renewable energy output and load demand in the region. By inputting the above information into the target model, and solving the model while ensuring optimal energy storage economics and minimum demand-side costs for the battery energy storage system, the optimal configuration scheme is obtained.

[0098] Step S103: Solve the target model using a mixed-integer linear programming algorithm to obtain the optimal configuration scheme. The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The optimal configuration scheme includes: the rated power and rated capacity of the battery energy storage system in the first stage and the second stage, the energy storage revenue and service unit price of the battery energy storage system participating in grid-side frequency regulation in the first stage, the energy storage revenue and service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second stage, and the costs on the grid side and the user side.

[0099] In this embodiment, by adjusting the price coefficient of the service unit price for the battery energy storage system participating in the first and second phases, the optimal configuration scheme is obtained, simultaneously satisfying the optimal energy storage economics of the battery energy storage system throughout its entire life cycle and the lowest costs on both the grid and user sides. Therefore, this optimal configuration scheme can reflect the economic benefits of the battery energy storage system to the greatest extent. The rated power and rated capacity of the battery energy storage system in the optimal configuration scheme for the first and second phases refer to the rated power and rated capacity configured for the battery energy storage system when participating in grid-side frequency regulation in the first phase and participating in user-side energy optimization scheduling with a shared energy storage mode in the second phase. The energy storage benefits from participating in grid-side frequency regulation in the first phase include grid-side frequency regulation benefits and energy storage-equivalent environmental benefits. The energy storage benefits from participating in user-side energy optimization scheduling in the second phase include energy storage benefits from participating in optimization scheduling and energy storage-equivalent environmental benefits.

[0100] In one feasible implementation, the optimal configuration scheme is obtained by solving the target model using a mixed-integer linear programming algorithm, including: using the first constraint, the second constraint, the third constraint, and the fourth constraint as constraints, the optimal configuration scheme is obtained by solving the target model using a mixed-integer linear programming algorithm.

[0101] In this embodiment, the first, second, third, and fourth constraints are used as constraints. The Big M method is used to transform the nonlinear constraints of the target model into a mixed-integer linear programming problem, and then the optimal configuration scheme is obtained by solving the problem.

[0102] In one feasible implementation, the optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first and second phases. The specific adjustment process includes:

[0103] The initial service unit price for the battery energy storage system to participate in power-side frequency regulation in the first stage and the initial service unit price for the battery energy storage system to participate in user-side energy optimization scheduling in the second stage are preset.

[0104] Using the first, second, third, and fourth constraints as constraints, and combining them with a mixed-integer linear programming algorithm to solve the target model, the optimal configuration scheme is obtained, including:

[0105] Using the first, second, third, and fourth constraints as constraints, the service unit price coefficients of the battery energy storage system participating in power-side frequency regulation in the first stage and the service unit price coefficients of the battery energy storage system participating in user-side energy optimization scheduling in the second stage are adjusted respectively. When the objective function simultaneously satisfies the objectives of achieving optimal energy storage economy of the battery energy storage system throughout its entire life cycle and minimizing costs on both the grid side and the user side, the optimal configuration scheme is obtained.

[0106] In this embodiment, to ensure the target model simultaneously achieves optimal energy storage economics and minimizes both grid-side and user-side costs, the price coefficients for the service unit price participating in grid-side frequency regulation in the first stage and the service unit price participating in user-side energy optimization scheduling in the second stage are continuously adjusted. The optimal configuration scheme is obtained when the target model simultaneously achieves optimal energy storage economics and minimizes both grid-side and user-side demand costs. The final service unit price for each stage is obtained by multiplying the initial service unit price of each stage by its respective price coefficient; that is, the initial service unit price of the first stage multiplied by its first-stage price coefficient yields the service unit price of the first stage, and the initial service unit price of the second stage multiplied by its second-stage price coefficient yields the service unit price of the second stage.

[0107] In one feasible implementation, obtaining the optimal configuration scheme includes solving for the rated power and rated capacity of the battery energy storage system in the first stage and the second stage, respectively, including:

[0108] Based on the first constraint and the grid frequency regulation data, the frequency regulation charging power and frequency regulation discharging power of the battery energy storage system participating in grid-side frequency regulation in the first stage are calculated.

[0109] Based on the second constraint and the user-side power demand prediction information, the scheduled charging power and scheduled discharging power of the battery energy storage system participating in user-side energy optimization scheduling in the second stage are calculated.

[0110] Based on the third constraint, the frequency-modulated charging power, and the frequency-modulated discharging power, the rated power of the battery energy storage system in the first stage is calculated; based on the third constraint, the scheduled charging power, and the scheduled discharging power, the rated power of the battery energy storage system in the second stage is calculated.

[0111] Based on the fourth constraint, the frequency-modulated charging power, and the frequency-modulated discharging power, the rated capacity of the battery energy storage system in the first stage is calculated; based on the fourth constraint, the scheduled charging power, and the scheduled discharging power, the rated capacity of the battery energy storage system in the second stage is calculated.

[0112] In this embodiment, the frequency-modulated charging power and frequency-modulated discharging power refer to the actual charging power and discharging power of the battery energy storage system participating in user-side frequency regulation in the first stage; the scheduled charging power and scheduled discharging power refer to the actual charging power and discharging power of the user participating in user-side energy optimization scheduling in the second stage.

[0113] Step S104: Configure the rated power and rated capacity of the battery energy storage system in the first stage and the second stage according to the optimal configuration scheme.

[0114] In this embodiment, the rated power and capacity of the first-stage battery energy storage system participating in grid-side frequency regulation are set according to the optimal configuration scheme, as are the rated power and capacity of the second-stage battery energy storage system for shared energy storage. Subsequently, the system participates in energy dispatch according to the set rated power and capacity. Since this optimal configuration scheme is obtained under the conditions of optimal energy storage economy and minimum costs on both the user side and the grid side, the battery energy storage system configured based on this optimal scheme maximizes the value of the battery energy storage system throughout its entire lifecycle.

[0115] In one feasible implementation, the participation in user-side energy optimization scheduling in a shared energy storage mode includes:

[0116] Calculate the operating unit price of the user-configured energy storage system and the service unit price of the battery energy storage system participating in the user-side energy optimization scheduling in the second stage;

[0117] The system outputs a prompt to the user indicating the relationship between the operating unit price of the user-configured energy storage and the service unit price of the battery energy storage system participating in the user-side energy optimization scheduling in the second stage, so that the user can choose a power supply method with a lower unit price.

[0118] In this embodiment, energy storage is introduced to match the load demand on the user side with the total power supply. To minimize the cost on the user side, the operating unit price of the user's own energy storage is compared with the service unit price of the battery energy storage system participating in the user-side energy optimization scheduling in the second stage and the shared energy storage mode. The user chooses the power supply method with the better economic efficiency.

[0119] In one embodiment, the entire lifecycle of the battery energy storage system is divided into stages based on the State of Health (SOH) of the battery energy storage system, specifically including:

[0120] Establish a capacity decay model for the battery energy storage system in the first and second stages to predict the real-time changes in the SOH of the battery energy storage system;

[0121] The battery energy storage system is divided into two phases: the first phase is when the State of Harmony (SOH) is between 80% and 100%, in which it participates in grid-side frequency regulation; the second phase is when the SOH is between 50% and 80%, in which it participates in user-side energy optimization scheduling in a shared energy storage mode.

[0122] Establishing a capacity decay model for battery energy storage systems includes:

[0123] Phase 1:

[0124] The degradation rate of the new battery is mainly related to the real-time depth of discharge. Real-time discharge quantity Rated capacity of battery energy storage system Related to this, the specific expression is as follows:

[0125]

[0126] in, To fix the depth of discharge The number of battery energy storage system cycles under these conditions and Fit coefficients.

[0127] The lifespan of a battery energy storage system is expressed as follows:

[0128]

[0129] The expression for the number of battery replacement cycles is as follows:

[0130]

[0131] in, This refers to the total project duration for Phase 1.

[0132] Phase Two:

[0133] The specific expression for the capacity decay model of the second-stage battery energy storage system is as follows:

[0134]

[0135] in, For the capacity retention rate of the second-stage battery energy storage system, with the number of cycles... The increase leads to a decrease.

[0136] The lifespan expression for the second-stage battery energy storage system is as follows:

[0137]

[0138] in, and This refers to the initial and final cycle counts of the second-stage battery energy storage system. For the scene The equivalent number of cycles that the second-stage battery energy storage system participates in shared energy storage within a single day.

[0139] The expression for the number of battery energy storage system replacements in the second stage is as follows:

[0140]

[0141] in, This refers to the total project duration for the second phase.

[0142] In this embodiment, the entire lifecycle of the battery energy storage system is divided into two stages based on the different State of Health (SOH) values. By establishing capacity decay models for the battery energy storage system in both stages, the lifespan of each stage can be accurately calculated, thereby accurately predicting the real-time changes in the SOH. During use, the applicability of the current SOH of the battery energy storage system can be matched with the application scenarios, thus maximizing the value utilization of the battery energy storage system at different stages.

[0143] Figure 2This is a schematic diagram of a phased utilization value enhancement system for energy storage throughout its entire life cycle (SOH) according to an embodiment of the present invention. Figure 2 As shown, the system includes:

[0144] Module 21 is established to establish a target model for the battery energy storage system to achieve optimal energy storage economy and the lowest cost on both the grid side and the user side throughout its entire life cycle. The life cycle of the battery energy storage system is divided into two stages: a first stage for grid-side frequency regulation and a second stage for participating in user-side energy optimization scheduling in a shared energy storage mode.

[0145] Input module 22 is used to input the cost parameters of the battery energy storage system, grid frequency regulation data, frequency regulation negotiation results, and user-side electricity demand forecast information into the target model;

[0146] Solution module 23 is used to solve the target model by combining a mixed integer linear programming algorithm to obtain the optimal configuration scheme. The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The optimal configuration scheme includes: the rated power and rated capacity of the battery energy storage system in the first stage and the second stage, the energy storage revenue and service unit price of the battery energy storage system participating in grid-side frequency regulation in the first stage, the energy storage revenue and service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second stage, and the costs on the grid side and the user side.

[0147] Configuration module 24 is used to configure the rated power and rated capacity of the battery energy storage system in the first stage and the second stage according to the optimal configuration scheme.

[0148] Optionally, the establishment module includes:

[0149] The function establishment module is used to establish the objective function, which aims to optimize the energy storage economy of the battery energy storage system throughout its entire life cycle and minimize the costs on both the grid side and the user side.

[0150] The first constraint determination module is used to determine the first constraint condition, which is used for grid-side frequency regulation. The ACE command of grid-side frequency regulation satisfies the maximum allowable error of the grid area.

[0151] The second constraint determination module is used to determine the second constraint condition, which is used for user-side energy optimization scheduling. The total power provided to the user satisfies the power balance between the user's load demand power. The total power provided to the user includes the renewable energy power provided by the user, the power purchased by the user from the grid, and the power discharged by the battery energy storage system.

[0152] The third constraint determination module is used to determine the third constraint condition, which is used to limit the power range of charging and discharging and calculate the rated power of the battery energy storage system.

[0153] The fourth constraint determination module is used to determine the fourth constraint condition, which is used to constrain the state of charge and capacity of the battery energy storage system, as well as to calculate the rated capacity.

[0154] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0155] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0156] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0157] The above provides a detailed description of the method and system for enhancing the value of SOH (Solar Energy Storage) throughout its entire life cycle, as provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for enhancing the value of SOH (Solar Energy Storage) throughout its entire lifecycle, characterized in that: The method includes: A target model is established to optimize the energy storage economy of the battery energy storage system throughout its entire life cycle and minimize the costs on both the grid side and the user side. The life cycle of the battery energy storage system is divided into two stages: the first stage for grid-side frequency regulation and the second stage for participating in user-side energy optimization scheduling in a shared energy storage mode. Input the cost parameters of the battery energy storage system, grid frequency regulation data, frequency regulation negotiation results, and user-side electricity demand forecast information into the target model; The target model is solved by combining mixed integer linear programming algorithm to obtain the optimal configuration scheme. The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The optimal configuration scheme includes: the rated power and rated capacity of the battery energy storage system in the first stage and the second stage respectively, the energy storage revenue and service unit price of the battery energy storage system participating in grid-side frequency regulation in the first stage, the energy storage revenue and service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second stage, and the costs on the grid side and the user side. According to the optimal configuration scheme, the rated power and rated capacity of the battery energy storage system are configured in the first stage and the second stage, respectively.

2. The method according to claim 1, characterized in that, The target model for establishing a battery energy storage system that achieves optimal energy storage economics throughout its entire lifecycle and minimizes costs on both the grid and user sides includes: An objective function is established, which aims to optimize the energy storage economy of the battery energy storage system throughout its entire life cycle and minimize the costs on both the grid side and the user side. A first constraint condition is determined, which is used for grid-side frequency regulation, and the regional control error command for grid-side frequency regulation satisfies the maximum allowable error of the grid region. A second constraint is determined, which is used for user-side energy optimization scheduling. The total power provided to the user satisfies the power balance between the user's load demand power. The total power provided to the user includes the renewable energy power provided by the user, the power purchased by the user from the grid, and the power discharged by the battery energy storage system. A third constraint condition is determined, which is used to limit the power range of charging and discharging and to calculate the rated power of the battery energy storage system; A fourth constraint condition is determined, which is used to constrain the state of charge and capacity of the battery energy storage system, as well as to calculate the rated capacity. The optimal configuration scheme is obtained by solving the target model using a mixed-integer linear programming algorithm, including: Using the first, second, third, and fourth constraints as constraints, and combining them with a mixed-integer linear programming algorithm, the target model is solved to obtain the optimal configuration scheme.

3. The method according to claim 2, characterized in that, The objective function includes: an outer function that optimizes the energy storage economy of the battery energy storage system throughout its entire life cycle, and an inner function that minimizes costs on both the grid side and the user side; the objective function is expressed as: in, For the outer function, For the inner function, , These are typical scenarios of the first stage. and typical scenarios in the second stage Each of their respective operating days , These refer to the service life of the battery energy storage system in the first stage and the second stage, respectively. , Typical scenario of the first stage and typical scenarios in the second stage Their respective totals The benefit of the battery energy storage system participating in grid-side frequency regulation in the first stage, The environmental benefits of the battery energy storage system participating in grid-side frequency regulation in the first stage. This refers to the penalty cost incurred when the battery energy storage system fails to meet actual demand during grid-side frequency regulation in the first phase. The benefits of the battery energy storage system participating in user-side energy optimization scheduling in the second phase, The environmental benefits of the battery energy storage system participating in user-side energy optimization scheduling in the second phase. The cost parameters of the battery energy storage system are as follows: The cost for users to purchase electricity from the grid.

4. The method according to claim 2, characterized in that, The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first and second phases. The specific adjustment process includes: The initial service unit price for the battery energy storage system to participate in the first and second phases is preset in advance; Using the first, second, third, and fourth constraints as constraints, and combining them with a mixed-integer linear programming algorithm to solve the target model, the optimal configuration scheme is obtained, including: Using the first, second, third, and fourth constraints as constraints, the service unit price coefficients of the battery energy storage system participating in power-side frequency regulation in the first stage and the service unit price coefficients of the battery energy storage system participating in user-side energy optimization scheduling in the second stage are adjusted respectively. When the target model simultaneously satisfies the goal of achieving optimal energy storage economy of the battery energy storage system throughout its entire life cycle and minimizing costs on both the grid side and the user side, the optimal configuration scheme is obtained.

5. The method according to claim 4, characterized in that, The process of obtaining the optimal configuration scheme includes solving for the rated power and rated capacity of the battery energy storage system in the first stage and the second stage, including: Based on the first constraint and the grid frequency regulation data, the frequency regulation charging power and frequency regulation discharging power of the battery energy storage system participating in grid-side frequency regulation in the first stage are calculated. Based on the second constraint and the user-side power demand prediction information, the scheduled charging power and scheduled discharging power of the battery energy storage system participating in user-side energy optimization scheduling in the second stage are calculated. Based on the third constraint, the frequency-modulated charging power, and the frequency-modulated discharging power, the rated power of the battery energy storage system in the first stage is calculated; based on the third constraint, the scheduled charging power, and the scheduled discharging power, the rated power of the battery energy storage system in the second stage is calculated. Based on the fourth constraint, the frequency-modulated charging power, and the frequency-modulated discharging power, the rated capacity of the battery energy storage system in the first stage is calculated; based on the fourth constraint, the scheduled charging power, and the scheduled discharging power, the rated capacity of the battery energy storage system in the second stage is calculated.

6. The method according to claim 1, characterized in that, The participation in user-side energy optimization scheduling in the shared energy storage mode includes: Calculate the operating unit price of the user-configured energy storage system and the service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second phase, respectively. The system outputs a prompt to the user indicating the relationship between the operating unit price of the user-configured energy storage and the service unit price of the battery energy storage system participating in the user-side energy optimization scheduling in the second stage, so that the user can choose a power supply method with a lower unit price.

7. The method according to claim 1, characterized in that, The method further includes: dividing the entire life cycle of the battery energy storage system into stages based on the State of Health (SOH) of the battery energy storage system, specifically including: Establish a capacity decay model for the battery energy storage system in the first and second stages to predict the real-time changes in the SOH of the battery energy storage system; The battery energy storage system is divided into two phases: the first phase is when the State of Harmony (SOH) is between 80% and 100%, in which it participates in grid-side frequency regulation; the second phase is when the SOH is between 50% and 80%, in which it participates in user-side energy optimization scheduling in a shared energy storage mode.

8. A phased value enhancement system for SOH (Solar Energy Storage) throughout its entire lifecycle, characterized in that, The system includes: A module is established to create a target model for optimizing the energy storage economy of a battery energy storage system throughout its entire life cycle and minimizing costs on both the grid and user sides. The life cycle of the battery energy storage system is divided into two phases: a first phase for grid-side frequency regulation and a second phase for participating in user-side energy optimization scheduling in a shared energy storage mode. The input module is used to input the cost parameters of the battery energy storage system, grid frequency regulation data, frequency regulation negotiation results, and user-side electricity demand forecast information into the target model; The solution module is used to solve the target model by combining a mixed integer linear programming algorithm to obtain the optimal configuration scheme. The optimal configuration scheme is obtained by adjusting the price coefficient of the service unit price of the battery energy storage system participating in the first stage and the second stage. The optimal configuration scheme includes: the rated power and rated capacity of the battery energy storage system in the first stage and the second stage respectively, the energy storage revenue and service unit price of the battery energy storage system participating in grid-side frequency regulation in the first stage, the energy storage revenue and service unit price of the battery energy storage system participating in user-side energy optimization scheduling in the second stage, and the costs on the grid side and the user side. The configuration module is used to configure the rated power and rated capacity of the battery energy storage system in the first stage and the second stage according to the optimal configuration scheme.

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