A multi-objective optimization configuration method and system for network-forming energy storage

Abstract

The application discloses a multi-target optimization configuration method and system for network-constructed energy storage, and the method comprises the following steps: acquiring basic operation data, frequency boundary values, static device parameters and an initial capacity power configuration scheme set of a target power system; acquiring the power system frequency, the frequency change rate and the quasi-steady frequency deviation of the power system after the network-constructed energy storage device under each initial scheme is configured according to the basic operation data and the static device parameters; selecting a candidate capacity power configuration scheme from the initial scheme set according to the frequency parameters and the frequency boundary values; performing operation optimization on each candidate scheme to obtain network-constructed energy storage effect data; and obtaining a target capacity power configuration scheme according to the effect data, the candidate scheme and an optimization algorithm, so that the new energy consumption capacity and the frequency support capacity of a high-proportion new energy power system are improved.

Description

Technical Field

[0001] This invention relates to the field of new power system energy storage planning technology, and in particular to a multi-objective optimization configuration method and system for grid-type energy storage. Background Technology

[0002] With the advancement of the "dual carbon" target, the power system is accelerating its transformation into a new type of power system dominated by new energy sources, with the installed capacity of new energy sources such as wind power and photovoltaics continuously increasing. However, the output of new energy sources is characterized by fluctuations, randomness, and intermittency. Large-scale grid connection can easily lead to problems such as difficulties in active power balance, limited absorption of new energy sources, and decreased system operational stability. At the same time, new energy units are mainly connected to the grid through power electronic equipment, lacking the natural inertia and damping support capabilities of traditional thermal power. As the operating capacity of thermal power decreases, the equivalent inertia level of the system declines, and frequency security issues such as increased frequency variation rate and lower frequency minimum point become more prominent.

[0003] Energy storage technology, characterized by its fast response, flexible adjustment, and convenient deployment, is a crucial means to enhance the absorption capacity of new energy sources and the regulation capacity of the system. Compared to traditional grid-connected energy storage, grid-based energy storage can simulate the external characteristics of synchronous machines through grid control or virtual synchronization control, providing frequency response and inertia support for the system, making it more suitable for the active support needs of high-proportion new energy systems. However, existing energy storage capacity configuration methods often focus on economic efficiency, new energy absorption, peak shaving and valley filling, or ancillary service revenue, and frequency security constraints are often simplified to reserve capacity constraints or frequency regulation capacity constraints, failing to fully reflect the comprehensive role of grid-based energy storage in new energy absorption, frequency support, and inertia support. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention discloses a multi-objective optimization configuration method and system for grid-type energy storage, which is used to improve the renewable energy absorption capacity and frequency support capacity of high-proportion renewable energy power systems.

[0005] To achieve the above objectives, this invention discloses a multi-objective optimization configuration method for grid-type energy storage, comprising: Acquire the basic operating data, frequency boundary values, static equipment parameters, and initial capacity and power configuration scheme set of the target power system and the energy storage device to be configured; wherein, the initial capacity and power configuration scheme set includes several initial capacity and power configuration schemes; Based on the basic operating data and the static equipment parameters, obtain the power system frequency, power system frequency change rate and quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system according to each set of the initial capacity power configuration scheme; Based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation, and the frequency boundary value, several sets of candidate capacity and power configuration schemes corresponding to the energy storage device to be configured are selected from the initial capacity and power configuration scheme set. For any set of candidate capacity and power configuration schemes, the operation of the energy storage device to be configured and the target power system is optimized to obtain the grid-based energy storage effect data of the energy storage device to be configured under the candidate capacity and power configuration scheme. Based on the grid-connected energy storage effect data, several sets of candidate capacity and power configuration schemes, and a preset scheme optimization algorithm, the target capacity and power configuration scheme of the energy storage device to be configured is obtained.

[0006] This invention discloses a multi-objective optimization configuration method for grid-based energy storage. It acquires basic operational data, frequency boundary values, and an initial capacity and power configuration scheme set. Based on each initial scheme, it obtains the power system frequency, frequency change rate, and quasi-steady-state frequency deviation. By acquiring these parameters, the impact of grid-based energy storage on the system's dynamic frequency response is incorporated into the capacity configuration constraint and evaluation process, overcoming the limitation of existing technologies that rely solely on static reserve capacity constraints and cannot accurately reflect the dynamic frequency process. Simultaneously, candidate schemes are selected based on these dynamic frequency parameters and frequency boundary values. Operational optimization of these candidate schemes yields multi-dimensional grid-based energy storage effect data, improving the accuracy of operational analysis. Finally, based on the effect data and optimization algorithms, a target capacity and power configuration scheme is obtained. This achieves multi-objective collaborative optimization of grid-based energy storage power and capacity, significantly improving the comprehensive applicability of the configuration scheme in terms of both new energy consumption and system frequency security.

[0007] As a preferred example, the acquisition of the target power system's basic operating data, frequency boundary values, and the static equipment parameters and initial capacity power configuration scheme set of the energy storage device to be configured includes: The frequency boundary values, typical operating data, and power generation operating data of each power source in the target power system are acquired to obtain the basic operating data of the target power system based on the typical operating data and the power generation operating data. The typical operating data includes a typical daily load curve, a renewable energy curtailment power curve without energy storage devices, a renewable energy available power curve without energy storage devices, and a disturbance power value under typical frequency disturbance scenarios. The power sources include thermal power units and renewable energy power stations. When the power source is the thermal power unit, the power generation operation data includes rated capacity, minimum active power output, maximum active power output, ramp rate, minimum start-stop duration, inertial time constant, thermal power frequency response delay time, and thermal power frequency response ramp time. When the power source is the new energy power station, the power generation operation data includes the rated capacity and a typical daily power output curve; The static equipment parameters, multiple initial rated energy storage power, and multiple initial rated energy storage capacity of the energy storage device to be configured are obtained, so as to obtain the initial capacity power configuration scheme set corresponding to the energy storage device to be configured based on the initial rated energy storage power and the initial rated energy storage capacity; wherein, the initial capacity power configuration scheme set includes multiple different initial capacity power configuration schemes; each initial capacity power configuration scheme includes an initial rated energy storage power and an initial rated energy storage capacity.

[0008] The above scheme clarifies that the basic operating data includes typical daily load curves, curtailed power and available power without energy storage, and typical disturbance power values; thermal power unit data includes rated capacity, ramp rate, start-stop duration, inertia time constant, frequency response delay, and ramp time; new energy data includes rated capacity and typical daily power output curves; the initial scheme set consists of multiple initial energy storage rated power and capacity combinations, so as to ensure that subsequent frequency dynamic response calculations and joint operation optimizations have a complete data foundation by systematically defining the composition of input data. This solves the problem in existing technologies where incomplete parameters make it impossible to accurately characterize the dynamic response characteristics of grid-type energy storage and thermal power synergy, and improves the feasibility and accuracy of the configuration method.

[0009] As a preferred example, the static equipment parameters include energy storage frequency response delay time, energy storage frequency response ramp-up time, virtual inertia constant, energy storage rated power, and equivalent inertia constant; the frequency boundary value includes the system rated frequency; the step of obtaining the power system frequency, power system frequency change rate, and quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system based on the basic operating data and the equipment parameters includes: For any set of initial capacity power configuration schemes, obtain the initial rated energy storage power in the initial capacity power configuration scheme; Based on the thermal power frequency response delay time, the thermal power frequency response ramp-up time, the energy storage frequency response delay time, and the energy storage frequency response ramp-up time, the equivalent total frequency regulation capacity between the thermal power unit and the energy storage device to be configured is obtained. Based on the disturbance power value, the inertial time constant, the rated capacity of the thermal power unit, the rated capacity of the new energy power station, the initial energy storage rated power in the initial capacity power configuration scheme, and the energy storage rated power, the system equivalent inertial constant when the energy storage device to be configured is connected to the target power system is obtained; Based on the system equivalent inertia constant, the disturbance power value, and the synchronous machine rotor motion data corresponding to the target power system, the maximum frequency change rate when the energy storage device to be configured is connected to the target power system is obtained, which is used as the power system frequency change rate. The minimum frequency deviation is obtained based on the equivalent total frequency regulation capacity, the disturbance power value, and the maximum frequency change rate. The power system frequency is then obtained based on the minimum frequency deviation and the system rated frequency. Based on the equivalent total frequency regulation capacity and the disturbance power value, the quasi-steady-state frequency deviation is calculated and used as the quasi-steady-state frequency deviation of the target power system.

[0010] The above scheme combines the differentiated frequency responses of thermal power and grid-connected energy storage into a total frequency regulation capacity, and quantifies three key frequency dynamic indicators based on the synchronous machine rotor motion equation. This enables an accurate pre-assessment of the system frequency security after grid-connected energy storage is connected. Compared with existing technologies that only use standby capacity constraints, this scheme can accurately reflect the rapid response characteristics of energy storage and the improvement effect of virtual inertia support on frequency change rate, minimum point and steady-state deviation, providing a quantitative basis for subsequent frequency security-based scheme selection.

[0011] As a preferred example, the step of selecting several candidate capacity-power configuration schemes corresponding to the energy storage device to be configured from the initial capacity-power configuration scheme set based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation, and the frequency boundary value includes: Obtain the upper limit of the rate of change of frequency, the lower limit of frequency, and the upper limit of the quasi-steady-state frequency deviation of the target power system from the frequency boundary values; Based on the power system frequency change rate, the power system frequency, the quasi-steady-state frequency deviation, the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation, several candidate capacity power configuration schemes corresponding to the energy storage device to be configured are selected from the initial capacity power configuration scheme set.

[0012] The above scheme obtains the upper limit of frequency change rate, the lower limit of frequency, and the upper limit of quasi-steady-state frequency deviation from the frequency boundary values, so that the frequency security assessment has clear qualification standards. Then, based on the calculated relationship between the power system frequency change rate, frequency, quasi-steady-state deviation and these limits, candidate schemes are selected. This provides an operable condition for systematically eliminating capacity schemes that do not meet frequency security requirements, ensuring that all candidate schemes can meet the basic requirements of power grid operation regulations for frequency security, and improving the engineering feasibility of the final configuration scheme.

[0013] As a preferred example, the step of selecting several candidate capacity power configuration schemes corresponding to the energy storage device to be configured from the initial capacity power configuration scheme set based on the power system frequency change rate, the power system frequency, the quasi-steady-state frequency deviation, the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation includes: For any of the aforementioned initial capacity power configuration schemes: When the power system frequency change rate of the initial capacity power configuration scheme is less than or equal to the upper limit of the frequency change rate, the power system frequency is greater than or equal to the lower limit of the frequency, and the quasi-steady-state frequency deviation is less than or equal to the upper limit of the quasi-steady-state frequency deviation, the initial capacity power configuration scheme shall be regarded as a candidate capacity power configuration scheme.

[0014] The above scheme selects a candidate scheme only if its power system frequency change rate is less than or equal to the upper limit of the frequency change rate, the power system frequency is greater than or equal to the lower limit of the frequency, and the quasi-steady-state frequency deviation is less than or equal to the upper limit of the quasi-steady-state frequency deviation. This ensures that the candidate scheme set only includes configurations that can keep the system frequency safe under typical disturbances.

[0015] As a preferred example, for any set of candidate capacity power configuration schemes, the operation optimization of the energy storage device to be configured and the target power system is performed to obtain the grid-connected energy storage effect data of the energy storage device to be configured under the candidate capacity power configuration scheme, including: Based on the typical daily load curve, typical daily power output curve, and renewable energy curtailment power curve of the target power system, obtain the joint operation optimization model when the energy storage equipment to be configured is connected to the target power system; The operating constraints of the target power system are obtained. For any set of candidate capacity power configuration schemes, based on the operating constraints and the initial rated power and initial rated capacity of energy storage in the candidate capacity power configuration scheme, with the goal of maximizing the data output by the joint operation optimization model, the thermal power output plan, actual wind power consumption power and energy storage charging and discharging power corresponding to the candidate capacity power configuration scheme are obtained. Based on the thermal power output plan, the actual wind power absorption capacity, and the energy storage charging and discharging power, the renewable energy absorption rate, frequency support data, and inertia support data of the energy storage device to be configured when it is connected to the target power system according to the candidate capacity power configuration scheme are obtained, so as to serve as the grid-connected energy storage effect data corresponding to the candidate capacity power configuration scheme.

[0016] The above scheme optimizes the operation of energy storage through time-series joint operation, and coordinates the charging and discharging of energy storage, the absorption of new energy sources and the output of thermal power while taking into account system operation constraints. It achieves a refined evaluation of the comprehensive performance of each candidate capacity scheme under typical operating scenarios. Compared with the estimation based solely on static power balance in existing technologies, it can reflect the impact of the actual dispatching capacity of energy storage on absorption and frequency support, and significantly improves the authenticity and reliability of the effect data.

[0017] As a preferred example, the step of obtaining the renewable energy absorption rate, frequency support data, and inertia support data of the energy storage device to be configured when connected to the target power system according to the candidate capacity power configuration scheme, based on the thermal power output plan, the actual wind power absorption capacity, and the energy storage charging and discharging power, as the grid-connected energy storage effect data corresponding to the candidate capacity power configuration scheme, includes: Based on the energy storage charging and discharging power and the new energy curtailment power curve of the target power system, obtain the energy storage curtailment absorption power corresponding to the candidate capacity power configuration scheme; Based on the renewable energy curtailment power curve, renewable energy available power, and the renewable energy absorption power of the energy storage curtailment, the renewable energy absorption rate corresponding to the candidate capacity power configuration scheme is obtained; Based on the power system frequency change rate, power system frequency, and quasi-steady-state frequency deviation corresponding to the candidate capacity power configuration scheme, the frequency support data corresponding to the candidate capacity power configuration scheme is obtained. Based on the initial rated energy storage power, the inertial time constant of the thermal power unit, the rated capacity of the thermal power unit, and the rated capacity of the new energy power station in the candidate capacity power configuration scheme, the inertial support constant corresponding to the candidate capacity power configuration scheme is obtained. The inertia support constant is compared with the preset upper limit value of the inertia support constant to obtain the inertia support data corresponding to the candidate capacity power configuration scheme.

[0018] The above scheme obtains the power absorbed by energy storage for curtailment based on the energy storage charging and discharging power curve and the power curtailment without energy storage; then calculates the renewable energy absorption rate; calculates frequency support data based on the obtained frequency dynamic indicators; and calculates the inertia support constant based on the rated power of energy storage, the inertia and capacity of thermal power, and the capacity of renewable energy, and compares it with the preset upper limit to obtain inertia support data, thus quantifying the technical effects in three dimensions. For example, the renewable energy absorption rate directly reflects the energy storage's ability to absorb curtailment; the frequency support data integrates the improvement degree of the maximum frequency change rate, the lowest point, and the quasi-steady-state deviation; and the inertia support data evaluates the suppression effect of the virtual inertia of energy storage on the initial frequency change rate by comparing the system's equivalent inertia constant with the reference upper limit. In summary, it comprehensively reflects the active support capability of grid-type energy storage and overcomes the shortcomings of the single evaluation dimension of existing technologies.

[0019] As a preferred example, the step of obtaining the target capacity power configuration scheme for the energy storage device to be configured based on the grid-connected energy storage effect data, several sets of candidate capacity power configuration schemes, and a preset scheme optimization algorithm includes: For any set of candidate capacity and power configuration schemes, the comprehensive evaluation target value corresponding to the candidate capacity and power configuration scheme is obtained by weighted summation based on the new energy absorption rate, frequency support data and inertia support data corresponding to the candidate capacity and power configuration scheme. From a group of candidate capacity and power configuration schemes, the candidate capacity and power configuration scheme with the largest comprehensive evaluation target value is selected as the real-time optimal configuration scheme. Obtain the historical optimal configuration scheme and historical comprehensive evaluation target value of the energy storage device to be configured, so that if the comprehensive evaluation target value is greater than the historical comprehensive evaluation target value, the real-time optimal configuration scheme is taken as the historical optimal configuration scheme; Based on the historical global optimal scheme, the initial energy storage rated power and initial energy storage rated capacity in each group of candidate capacity power configuration schemes are updated by a preset optimization algorithm to obtain the updated candidate capacity power configuration scheme set. The updated candidate capacity and power configuration scheme set is used as the initial capacity and power configuration scheme set to repeatedly perform the scheme update operation until the preset maximum number of iterations is reached. The initial rated power and initial rated capacity of the energy storage in the historical optimal configuration scheme when the maximum number of iterations is reached are used as the target capacity power configuration scheme for the energy storage device to be configured.

[0020] The above scheme establishes a comprehensive evaluation target value as the optimization guide and adopts a group iterative optimization algorithm to efficiently search for a multi-objective optimal solution that takes into account renewable energy consumption, frequency security, inertia support and cost in the feasible region. The above iterative mechanism can retain historical optimal solutions, prevent the target value from degrading due to algorithm exploration, and ensure that the final output rated power and rated capacity of energy storage can maximize the comprehensive operation performance of the high-proportion new power system.

[0021] On the other hand, the present invention discloses a multi-objective optimization configuration system for grid-type energy storage, including an initial configuration module, a safety constraint module, a configuration screening module, an effect evaluation module, and a configuration optimization module; The initial configuration module is used to acquire the basic operating data, frequency boundary values, static equipment parameters, and initial capacity and power configuration scheme set of the target power system and the energy storage device to be configured; wherein, the initial capacity and power configuration scheme set includes several initial capacity and power configuration schemes; The safety constraint module is used to obtain, based on the basic operating data and the static equipment parameters, the power system frequency, the power system frequency change rate, and the quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system according to each set of initial capacity power configuration schemes; The configuration filtering module is used to select several sets of candidate capacity power configuration schemes corresponding to the energy storage device to be configured from the initial capacity power configuration scheme set based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation and the frequency boundary value. The effect evaluation module is used to optimize the operation of the energy storage device to be configured and the target power system for any set of candidate capacity power configuration schemes, and obtain the grid-based energy storage effect data of the energy storage device to be configured under the candidate capacity power configuration scheme. The configuration optimization module is used to take several groups of candidate capacity and power configuration schemes as the initial capacity and power configuration scheme set, and repeatedly execute the scheme update operation according to the grid energy storage effect data and the initial capacity and power configuration scheme set until the preset end condition of the scheme update operation is reached, so as to obtain the target capacity and power configuration scheme corresponding to the energy storage device to be configured.

[0022] This invention discloses a multi-objective optimization configuration system for grid-based energy storage. It acquires basic operational data, frequency boundary values, and an initial set of capacity and power configuration schemes. Based on each initial scheme, it obtains the power system frequency, frequency change rate, and quasi-steady-state frequency deviation. By acquiring these parameters, the system incorporates the impact of grid-based energy storage on the dynamic frequency response of the system into the constraint and evaluation process of capacity configuration, overcoming the deficiency of existing technologies that rely solely on static reserve capacity constraints and cannot accurately reflect the dynamic frequency process. Simultaneously, it selects candidate schemes based on these dynamic frequency parameters and frequency boundary values. Operational optimization of these candidate schemes yields multi-dimensional grid-based energy storage effect data, improving the accuracy of operational analysis. Finally, based on the effect data and optimization algorithms, it obtains the target capacity and power configuration scheme, achieving multi-objective collaborative optimization of grid-based energy storage power and capacity. This significantly improves the comprehensive applicability of the configuration scheme in terms of both renewable energy consumption and system frequency security.

[0023] As a preferred example, the initial configuration module includes a power acquisition unit and a device acquisition unit; The power acquisition unit is used to acquire the frequency boundary values, typical operating data, and power generation operating data of each power source in the target power system, so as to obtain the basic operating data of the target power system based on the typical operating data and the power generation operating data. The typical operating data includes a typical daily load curve, a renewable energy curtailment power curve without energy storage access, renewable energy available power without energy storage access, and disturbance power values ​​under typical frequency disturbance scenarios. The power sources include thermal power units and renewable energy power stations. When the power source is a thermal power unit, the power generation operating data includes rated capacity, minimum active power output, maximum active power output, ramp rate, minimum start / stop duration, inertial time constant, thermal power frequency response delay time, and thermal power frequency response ramp time. When the power source is a renewable energy power station, the power generation operating data includes rated capacity and a typical daily output curve. The device acquisition unit is used to acquire the static device parameters, multiple initial rated energy storage power, and multiple initial rated energy storage capacity corresponding to the energy storage device to be configured, so as to obtain the initial capacity power configuration scheme set corresponding to the energy storage device to be configured based on the initial rated energy storage power and the initial rated energy storage capacity; wherein, the initial capacity power configuration scheme set includes multiple different initial capacity power configuration schemes; each initial capacity power configuration scheme includes an initial rated energy storage power and an initial rated energy storage capacity.

[0024] The above scheme clarifies that the basic operating data includes typical daily load curves, curtailed power and available power without energy storage, and typical disturbance power values; thermal power unit data includes rated capacity, ramp rate, start-stop duration, inertia time constant, frequency response delay, and ramp time; new energy data includes rated capacity and typical daily power output curves; the initial scheme set consists of multiple initial energy storage rated power and capacity combinations, so as to ensure that subsequent frequency dynamic response calculations and joint operation optimizations have a complete data foundation by systematically defining the composition of input data. This solves the problem in existing technologies where incomplete parameters make it impossible to accurately characterize the dynamic response characteristics of grid-type energy storage and thermal power synergy, and improves the feasibility and accuracy of the configuration method. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart illustrating a multi-objective optimization configuration method for grid-type energy storage provided in an embodiment of the present invention. Figure 2 This is a structural topology diagram of a power system provided in an embodiment of the present invention; Figure 3 This is a typical load curve and wind power output curve provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a multi-objective optimization configuration system for grid-type energy storage provided in an embodiment of the present invention. Detailed Implementation

[0027] 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, and 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.

[0028] See Figure 1 To enhance the renewable energy absorption capacity and frequency support capacity of high-proportion renewable energy power systems, an embodiment of the present invention provides a multi-objective optimization configuration method for grid-type energy storage, comprising: Step 101: Obtain the basic operating data, frequency boundary values, static equipment parameters, and initial capacity power configuration scheme set of the target power system and the energy storage device to be configured; wherein, the initial capacity power configuration scheme set includes several initial capacity power configuration schemes; Step 102: Based on the basic operating data and the static equipment parameters, obtain the power system frequency, power system frequency change rate, and quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system according to each initial capacity power configuration scheme; Step 103: Based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation, and the frequency boundary value, select several sets of candidate capacity power configuration schemes corresponding to the energy storage device to be configured from the initial capacity power configuration scheme set; Step 104: For any set of candidate capacity power configuration schemes, perform operation optimization on the energy storage device to be configured and the target power system to obtain the grid-connected energy storage effect data of the energy storage device to be configured under the candidate capacity power configuration scheme; Step 105: Based on the grid-connected energy storage effect data, several sets of candidate capacity power configuration schemes, and a preset scheme optimization algorithm, obtain the target capacity power configuration scheme for the energy storage device to be configured.

[0029] In this embodiment, the basic operating data, frequency boundary values, and static equipment parameters of the energy storage device to be configured in the target power system are first obtained. The basic operating data includes: a typical daily load curve, i.e., the system load value recorded at hourly or minute intervals for each time period within a day, such as recording the system load value at 15-minute intervals for each time period within each day; a renewable energy curtailment power curve without energy storage, i.e., the renewable energy power that cannot be absorbed by the system in each time period without energy storage; the renewable energy available power without energy storage, i.e., the maximum power that renewable energy power plants can theoretically generate in each time period; and the disturbance power value under typical frequency disturbance scenarios, which in this embodiment is taken as two percent of the system load power in the corresponding time period. The frequency boundary values ​​include: the system rated frequency; the maximum allowable frequency change rate of the system; the minimum allowable frequency of the system; and the maximum allowable quasi-steady-state frequency deviation of the system.

[0030] The static equipment parameters include: the inertial time constant, rated capacity, frequency response delay time, and frequency response ramp-up time of thermal power units; the rated capacity and typical daily power output curve of new energy power stations; and the virtual inertial constant, frequency response delay time, frequency response ramp-up time, charge / discharge efficiency, upper and lower limits of state of charge, unit cost, and cost normalization reference value of energy storage devices. Multiple initial rated power and multiple initial rated capacity of energy storage are obtained to generate an initial capacity power configuration scheme set. This embodiment uses a particle swarm optimization algorithm to randomly generate multiple sets of initial capacity power configuration schemes. Each scheme contains one initial rated power and one initial rated capacity of energy storage, and satisfies the configuration time relationship (rated capacity equals rated power multiplied by configuration time; in this embodiment, the configuration time is 2 hours).

[0031] For any initial capacity power configuration scheme in the initial capacity power configuration scheme set, the initial rated energy storage power in the scheme is first obtained. Then, based on the obtained thermal power frequency response delay time, thermal power frequency response ramp-up time, energy storage frequency response delay time, and energy storage frequency response ramp-up time, the joint frequency response of the thermal power unit and grid-connected energy storage is equivalent to a linear ramp-up process. Through this equivalence, the total frequency regulation capacity that the thermal power unit and energy storage equipment can provide together is obtained, where the frequency regulation capacity provided by energy storage is proportional to the initial rated energy storage power in the scheme. Next, based on the disturbance power value, the inertial time constant and rated capacity of the thermal power unit, the rated capacity of the new energy power station, the initial rated energy storage power in the initial scheme, and the virtual inertia constant of energy storage, the equivalent inertia constant of the system is calculated. This equivalent inertia constant reflects the comprehensive contribution of the thermal power unit, new energy power station, and energy storage equipment to the inertia of system frequency change. Based on the synchronous machine rotor motion equation, at the initial moment of the disturbance, the system frequency deviation has not yet formed, and the frequency response power has not yet been fully released. At this point, the maximum frequency change rate can be determined from the system's equivalent inertia constant and the disturbance power value; this value is the power system frequency change rate. Subsequently, based on the equivalent total frequency regulation capacity, the disturbance power value, and the aforementioned maximum frequency change rate, the frequency minimum deviation is calculated. Subtracting this frequency minimum deviation from the system's rated frequency yields the disturbed power system frequency (i.e., the frequency minimum). Finally, when the system enters a quasi-steady state, the frequency change rate approaches zero, and the total frequency regulation power reaches its maximum value. At this point, based on the equivalent total frequency regulation capacity, the disturbance power value, and the system load damping coefficient, the quasi-steady-state frequency deviation is calculated; this value is taken as the quasi-steady-state frequency deviation of the target power system.

[0032] Secondly, the upper limit of the rate of change of frequency, the lower limit of frequency, and the upper limit of quasi-steady-state frequency deviation are extracted from the obtained frequency boundary values. For each initial capacity power configuration scheme, the obtained power system frequency change rate, power system frequency, and quasi-steady-state frequency deviation are compared with the above three limits. The judgment rule is as follows: if the power system frequency change rate of the scheme is less than or equal to the upper limit of the rate of change of frequency, the power system frequency is greater than or equal to the lower limit of frequency, and the quasi-steady-state frequency deviation is less than or equal to the upper limit of quasi-steady-state frequency deviation, then the scheme is determined to meet the system frequency security requirements and is selected as a candidate capacity power configuration scheme; otherwise, if any of the above three conditions are not met, the scheme is discarded. After traversing all schemes in the initial capacity power configuration scheme set, several candidate capacity power configuration schemes that meet the system frequency security constraints are obtained.

[0033] For any set of candidate capacity and power configuration schemes, their rated energy storage power and rated capacity are substituted into the joint operation optimization model. The optimization objective of this model is to maximize the comprehensive operational effect, which is composed of the weighted sum of three indicators: new energy absorption rate, frequency support capability, and inertia support capability. The optimization process needs to satisfy a series of operational constraints, including: power balance constraints (the sum of thermal power output, wind power absorption power, and energy storage charging and discharging power equals the load power); wind power output constraints (actual absorption power does not exceed available power); upper and lower limits of thermal power unit output constraints, ramp rate constraints, and minimum start-stop duration constraints; energy storage charging and discharging power constraints (not exceeding the rated power of the scheme); recursive constraints on energy storage state of charge (calculating the current state of charge based on the state of charge, charging and discharging efficiency, and rated capacity of the previous period); upper and lower limits of energy storage state of charge constraints (in this embodiment, 5% to 95%); and state of charge balance constraints at the beginning and end of the scheduling cycle (both at 50% of the rated capacity).

[0034] After solving the above joint operation optimization problem, the optimal thermal power output plan, actual wind power absorption capacity, and energy storage charging and discharging power under the candidate scheme are obtained. The grid-connected energy storage effect data are calculated based on the optimization results. Specifically, the renewable energy absorption rate is calculated as follows: the power absorbed by energy storage (taking the smaller value between the actual charging power of energy storage and the power of abandoned electricity without energy storage) is added to the actual renewable energy absorption power without energy storage to obtain the actual absorption power after energy storage is connected. This ratio is then used as the renewable energy absorption rate. Frequency support capability is calculated by weighting the obtained power system frequency change rate, power system frequency, and quasi-steady-state frequency deviation with reference values ​​in the frequency boundary values, according to preset weights. Inertia support capability is calculated as follows: first, based on the system equivalent inertia constant for each time period (considering the contributions of thermal power units, renewable energy plants, and rated power of energy storage), its average value within a scheduling cycle is calculated. Then, this average value is compared with a preset upper limit reference for the inertia constant to obtain the inertia support capability. The new energy absorption rate, frequency support capability, and inertia support capability obtained from the above calculations are used as the grid-based energy storage effect data corresponding to the candidate capacity power configuration scheme.

[0035] For each candidate capacity and power configuration scheme, the energy storage cost normalization index is first obtained according to the energy storage cost calculation formula (energy storage rated power multiplied by unit cost, then divided by the cost normalization reference value). Then, the scheme's new energy absorption rate, frequency support capability, inertia support capability, and energy storage cost normalization index (take 1 minus the index) are weighted and summed to obtain the comprehensive evaluation target value. The scheme with the largest comprehensive evaluation target value is selected from the current candidate scheme set as the real-time optimal scheme. At the same time, a historical global optimal scheme is maintained, recording the scheme with the largest comprehensive evaluation target value that has appeared throughout the iteration process. The real-time optimal scheme is compared with the historical global optimal scheme: if the comprehensive evaluation target value of the real-time optimal scheme is greater than the historical global optimal value, the historical global optimal scheme is updated as the current real-time optimal scheme. According to the preset particle swarm optimization algorithm, based on the energy storage rated power and rated capacity of all current candidate schemes, combined with the individual historical optimal position of each scheme and the global optimal position of the entire group, the energy storage rated power and rated capacity of each scheme are updated according to the velocity update rule and the position update rule.

[0036] The updated next-generation scheme set is used as the initial capacity and power configuration scheme set. The above steps are repeated until the preset maximum number of iterations is reached. After the iteration terminates, the rated power and rated capacity of the energy storage in the historical globally optimal scheme at the maximum number of iterations are output as the target capacity and power configuration scheme for the energy storage device to be configured.

[0037] The above implementation method acquires basic operating data, frequency boundary values, and an initial capacity and power configuration scheme set. Based on each initial scheme, it acquires the power system frequency, frequency change rate, and quasi-steady-state frequency deviation. By acquiring these power system frequency, frequency change rate, and quasi-steady-state frequency deviation, the impact of grid-based energy storage on the system's dynamic frequency response is incorporated into the capacity configuration constraint and evaluation process. This overcomes the shortcomings of existing technologies that rely solely on static reserve capacity constraints, which cannot accurately reflect the dynamic frequency process. Simultaneously, candidate schemes are selected based on these dynamic frequency parameters and frequency boundary values. Operational optimization of the candidate schemes yields multi-dimensional grid-based energy storage effect data, improving the accuracy of operational analysis. Finally, based on the effect data and optimization algorithms, the target capacity and power configuration scheme is obtained. This achieves multi-objective collaborative optimization of grid-based energy storage power and capacity, significantly improving the comprehensive applicability of the configuration scheme in terms of both new energy consumption and system frequency security.

[0038] In this embodiment, in order to verify as Figure 1 The technical effects of the method shown are as follows: Figure 2 The power system shown is configured with energy storage. Specifically, as... Figure 2The system parameters of the power system are shown in Tables 1, 2 and 3; its base capacity is 100MVA, and the initial state of charge of energy storage is taken as 50% of the rated capacity.

[0039] Table 1 Thermal Power Parameter Settings Table 2 Main parameter settings for grid-type energy storage Table 3 Frequency Response Parameter Settings According to such Figure 2 The power system shown and the power system parameters shown in Tables 1 to 3 are used to verify the effectiveness of the energy storage configuration method described in this embodiment. A grid-type energy storage is connected at node 10 of the target power system to configure the rated power and rated capacity of the grid-type energy storage at that node.

[0040] In this embodiment, step 101 includes: Step 1011: Obtain the frequency boundary values, typical operating data, and power generation operating data of each power source in the target power system, so as to obtain the basic operating data of the target power system based on the typical operating data and the power generation operating data; wherein, the typical operating data includes the typical daily load curve, the renewable energy curtailment power curve when no energy storage equipment is connected, the renewable energy available power when no energy storage equipment is connected, and the disturbance power value under typical frequency disturbance scenarios; the power sources include thermal power units and renewable energy power stations; Step 1012: When the power source is the thermal power unit, the power generation operation data includes rated capacity, minimum active power output, maximum active power output, ramp rate, minimum start-stop duration, inertial time constant, thermal power frequency response delay time, and thermal power frequency response ramp time. Step 1013: When the power source is the new energy power output station, the power generation operation data includes the rated capacity and a typical daily power output curve; Step 1014: Obtain the static equipment parameters, multiple initial rated energy storage power, and multiple initial rated energy storage capacity corresponding to the energy storage device to be configured, so as to obtain the initial capacity power configuration scheme set corresponding to the energy storage device to be configured based on the initial rated energy storage power and the initial rated energy storage capacity; wherein, the initial capacity power configuration scheme set includes multiple different initial capacity power configuration schemes; each initial capacity power configuration scheme includes an initial rated energy storage power and an initial rated energy storage capacity.

[0041] In this embodiment, the frequency boundary values ​​of the target power system are first obtained. According to Table 3, the rated frequency of the system is 50Hz; the maximum allowable frequency change rate of the system is 1.0Hz / s; the minimum allowable frequency of the system is 49.5Hz; and the maximum allowable quasi-steady-state frequency deviation of the system is 0.2Hz. Simultaneously, typical operating data are obtained, including: typical daily load curves, with 15-minute time intervals Δt, covering dispatching periods T=96; the renewable energy curtailment power curve when no energy storage devices are connected; the available renewable energy power when no energy storage devices are connected; and the disturbance power value under typical frequency disturbance scenarios, which in this embodiment is 2% of the system load power for that period. Then, the power generation operation data of each power source in the target power system are obtained.

[0042] The power source includes thermal power units and new energy power stations (this embodiment takes a wind farm as an example). When the power source is a thermal power unit, the power generation operation data includes the rated capacity (unit pu, base capacity 100MVA); The minimum and maximum active power output, ramp rate (pu / h), minimum start-stop duration (h), inertial time constant (unit s), and thermal power frequency response delay time are taken as 1.5s according to Table 3; the thermal power frequency response ramp time is taken as 8.0s according to Table 3.

[0043] In this embodiment, there are a total of 7 thermal power units, and their detailed parameters are shown in Table 1. When the power source is a new energy power station (wind farm), the power generation operation data includes rated capacity (unit: pu) and typical daily power generation curve (i.e., available power at each time period). The installed capacity and typical daily power generation curve of the wind farm in this embodiment are shown below. Figure 3 As shown; specifically, obtain the static equipment parameters of the energy storage device to be configured. According to Tables 2 and 3, these include: energy storage frequency response delay time, taken as 0.3s; energy storage frequency response ramp-up time, taken as 1.5s; virtual inertia constant, with a maximum of 15.0s; the selectable range of rated power and rated capacity of energy storage: according to Table 2, the energy storage capacity configuration range is 100~2000MWh, and the configuration duration is 2h; energy storage charging efficiency and discharging efficiency are both taken as 95%; the lower and upper limits of energy storage state of charge are taken as 5% and 95% respectively; the unit cost of energy storage is taken as 2 yuan / W; and the normalized reference value of energy storage cost is taken as 2 billion yuan.

[0044] Multiple initial rated power and multiple initial rated capacity of energy storage are obtained to generate a set of initial capacity-power configuration schemes. This embodiment uses a particle swarm optimization algorithm with a population size of 20 to randomly generate 20 sets of initial capacity-power configuration schemes. Each scheme contains one initial rated power and one initial rated capacity (satisfying that the initial rated capacity = 2 times the initial rated power). These initial schemes constitute the initial capacity power configuration scheme set.

[0045] The above implementation method clarifies that the basic operating data includes typical daily load curves, abandoned power and available power without energy storage, and typical disturbance power values; thermal power unit data includes rated capacity, ramp rate, start-stop duration, inertial time constant, frequency response delay, and ramp time; new energy data includes rated capacity and typical daily power output curves; the initial scheme set consists of multiple initial energy storage rated power and capacity combinations, so as to ensure that the subsequent frequency dynamic response calculation and joint operation optimization have a complete data foundation by systematically defining the composition of input data. This solves the problem in the existing technology that the dynamic response characteristics of grid-type energy storage and thermal power are not accurately characterized due to incomplete parameters, and improves the feasibility and accuracy of the configuration method.

[0046] In this embodiment, the static equipment parameters include energy storage frequency response delay time, energy storage frequency response ramp-up time, virtual inertia constant, rated energy storage power, and equivalent inertia constant; the frequency boundary value includes the system rated frequency; step 102 includes: Step 1021: For any set of initial capacity power configuration schemes, obtain the initial rated energy storage power in the initial capacity power configuration scheme; Step 1022: Based on the thermal power frequency response delay time, the thermal power frequency response ramp-up time, the energy storage frequency response delay time, and the energy storage frequency response ramp-up time, obtain the equivalent total frequency regulation capacity between the thermal power unit and the energy storage device to be configured. Step 1023: Based on the disturbance power value, the inertial time constant, the rated capacity of the thermal power unit, the rated capacity of the new energy power station, the initial energy storage rated power in the initial capacity power configuration scheme, and the energy storage rated power, obtain the system equivalent inertial constant when the energy storage device to be configured is connected to the target power system. Step 1024: Based on the system equivalent inertia constant, the disturbance power value, and the synchronous machine rotor motion data corresponding to the target power system, obtain the maximum frequency change rate when the energy storage device to be configured is connected to the target power system, and use it as the power system frequency change rate; Step 1025: Based on the equivalent total frequency regulation capacity, the disturbance power value, and the maximum frequency change rate, obtain the frequency minimum point deviation, and based on the frequency minimum point deviation and the system rated frequency, obtain the power system frequency; Step 1026: Calculate the quasi-steady-state frequency deviation based on the equivalent total frequency regulation capacity and the disturbance power value, and use it as the quasi-steady-state frequency deviation of the target power system.

[0047] In this embodiment, based on the dynamic form of the synchronous machine rotor motion equation, and considering the simultaneous inclusion of the frequency response power of the thermal power unit and the frequency response power of the grid-type energy storage in the system frequency dynamic process, a system frequency disturbance response model is established: In the formula, This represents the system frequency deviation after the disturbance during time period t; This represents the system frequency dynamic response coefficient during time period t; This represents the system load damping coefficient during time period t. This represents the frequency response power provided jointly by the thermal power units and grid-type energy storage during time period t. Indicates the dynamic response time after the disturbance; the The system disturbance power is represented in the time period t. The system disturbance power can be determined based on the system load power in the time period t, such as taking two percent of the system load power in the corresponding time period as the system disturbance power.

[0048] The frequency response power provided by the thermal power units and grid-type energy storage is: The frequency response power expression for grid-type energy storage is as follows: In the formula, This represents the frequency response power of the thermal power unit during the t-th time period; This represents the frequency response power of the grid-type energy storage system during time period t. This represents the primary frequency regulation capacity reserved for grid-type energy storage in time period t; Indicates the frequency response delay time of grid-type energy storage; This indicates the frequency response ramp-up time for grid-type energy storage.

[0049] To simplify the calculation of the lowest frequency point, the combined frequency response of the thermal power unit and grid-type energy storage is equivalent to a linear ramping process: In the formula, This represents the total frequency regulation capacity provided by thermal power units and grid-type energy storage during time period t; This represents the frequency regulation capacity that the thermal power unit can provide during the t-th time period; This represents the frequency regulation capacity that grid-type energy storage can provide within time period t; This represents the equivalent response time of the thermal power unit and the grid-type energy storage frequency regulation during the t-th time period; Indicates the frequency regulation response time of thermal power units; This indicates the frequency regulation response time of grid-type energy storage.

[0050] According to the system frequency disturbance response model, at the initial moment of the disturbance, the system frequency deviation has not yet formed, and the frequency response power has not yet been fully released. Therefore, the maximum frequency change rate during time period t is: In the formula, the minimum frequency point occurs at the moment when the frequency decrease rate is zero. Based on the above joint frequency response process, the deviation of the minimum frequency point in time period t can be expressed as: Therefore, the lowest frequency point after the disturbance in time period t is: In the formula, This represents the deviation of the lowest frequency point after the disturbance within time period t; This represents the system's rated frequency, as shown in Table 3, where the system's rated frequency is 50Hz.

[0051] Once the system enters a quasi-steady state, the rate of frequency change approaches zero, and the total frequency modulation power reaches its maximum value. Therefore, the quasi-steady-state frequency deviation during time period t is... for: Based on the maximum rate of change of frequency, the minimum frequency point, and the quasi-steady-state frequency deviation, the following frequency security constraints are constructed for the system: Therefore, by establishing a system frequency disturbance response model in which thermal power units and grid-type energy storage jointly participate in the frequency response, and by constraining the maximum frequency change rate, the minimum frequency point, and the quasi-steady-state frequency deviation, it can be ensured that each grid-type energy storage capacity configuration scheme meets the system frequency safety requirements under typical disturbance scenarios. The proposed frequency support capability index is used to further compare the advantages and disadvantages of frequency dynamic performance among feasible schemes that meet the safety boundary.

[0052] The above implementation method combines the differentiated frequency responses of thermal power and grid-connected energy storage into a total frequency regulation capacity, and quantifies three key frequency dynamic indicators based on the synchronous machine rotor motion equation. This enables an accurate pre-assessment of the system frequency security after grid-connected energy storage is connected. Compared with the existing technology that only uses standby capacity constraints, this method can accurately reflect the rapid response characteristics of energy storage and the improvement effect of virtual inertia support on the frequency change rate, minimum point, and steady-state deviation, providing a quantitative basis for subsequent frequency security-based scheme selection.

[0053] In this embodiment, step 103 includes: Step 1031: Obtain the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation of the target power system from the frequency boundary values; Step 1032: Based on the power system frequency change rate, the power system frequency, the quasi-steady-state frequency deviation, the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation, select several candidate capacity power configuration schemes corresponding to the energy storage device to be configured from the initial capacity power configuration scheme set; wherein, for any set of the initial capacity power configuration schemes: When the power system frequency change rate of the initial capacity power configuration scheme is less than or equal to the upper limit of the frequency change rate, the power system frequency is greater than or equal to the lower limit of the frequency, and the quasi-steady-state frequency deviation is less than or equal to the upper limit of the quasi-steady-state frequency deviation, the initial capacity power configuration scheme shall be regarded as a candidate capacity power configuration scheme.

[0054] In this embodiment, the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation of the target power system are extracted from the acquired frequency boundary values.

[0055] In this embodiment, according to the settings in Table 3, the maximum allowed frequency change rate of the system is 1.0 Hz / s, that is, the upper limit of the frequency change rate is 1.0 Hz / s; the minimum allowed frequency of the system is 49.5 Hz, that is, the lower limit of the frequency is 49.5 Hz; and the maximum allowed quasi-steady-state frequency deviation of the system is 0.2 Hz, that is, the upper limit of the quasi-steady-state frequency deviation is 0.2 Hz.

[0056] For any initial capacity power configuration scheme in the initial capacity power configuration scheme set, obtain the power system frequency change rate, power system frequency, and quasi-steady-state frequency deviation corresponding to the scheme.

[0057] The three frequency dynamic parameters of the above scheme are compared with the three limits obtained respectively: it is determined whether the power system frequency change rate is less than or equal to the upper limit of the frequency change rate (1.0 Hz / s); it is determined whether the power system frequency is greater than or equal to the lower limit of the frequency (49.5 Hz); it is determined whether the quasi-steady-state frequency deviation is less than or equal to the upper limit of the quasi-steady-state frequency deviation (0.2 Hz).

[0058] If all three conditions are met, the initial capacity power configuration scheme is deemed to satisfy the system frequency security requirements and is selected as a candidate capacity power configuration scheme. Conversely, if any one of the three conditions is not met, the initial capacity power configuration scheme is discarded and not included in the subsequent candidate scheme set. After traversing all schemes in the initial capacity power configuration scheme set, several candidate capacity power configuration schemes that satisfy the system frequency security constraints are obtained and used for subsequent operation optimization steps.

[0059] The above implementation method obtains the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation from the frequency boundary values, thus providing a clear qualification standard for frequency security assessment. Then, based on the calculated relationship between the power system frequency change rate, frequency, quasi-steady-state deviation, and these limits, candidate schemes are selected. This provides an operational condition for systematically eliminating capacity schemes that do not meet frequency security requirements, ensuring that all candidate schemes meet the basic requirements of power grid operation regulations for frequency security, and improving the engineering feasibility of the final configuration scheme. Specifically, for a set of initial schemes, a scheme is selected as a candidate scheme only if its power system frequency change rate is less than or equal to the upper limit of the frequency change rate, its power system frequency is greater than or equal to the lower limit of the frequency, and its quasi-steady-state frequency deviation is less than or equal to the upper limit of the quasi-steady-state frequency deviation. This ensures that the candidate scheme set only includes configurations that can maintain the frequency security of the system under typical disturbances.

[0060] In this embodiment, step 104 includes: Step 1041: Based on the typical daily load curve, typical daily power output curve, and renewable energy curtailment power curve of the target power system, obtain the joint operation optimization model when the energy storage equipment to be configured is connected to the target power system; Step 1042: Obtain the operating constraints of the target power system. For any set of candidate capacity power configuration schemes, based on the operating constraints and the initial rated power and initial rated capacity of energy storage in the candidate capacity power configuration scheme, with the goal of maximizing the data output by the joint operation optimization model, obtain the thermal power output plan, actual wind power consumption power and energy storage charging and discharging power corresponding to the candidate capacity power configuration scheme. Step 1043: Based on the thermal power output plan, the actual wind power absorption capacity, and the energy storage charging and discharging power, obtain the renewable energy absorption rate, frequency support data, and inertia support data when the energy storage device to be configured is connected to the target power system according to the candidate capacity power configuration scheme, as the grid-connected energy storage effect data corresponding to the candidate capacity power configuration scheme; wherein, based on the energy storage charging and discharging power and the renewable energy curtailment power curve of the target power system, obtain the energy storage curtailment absorption power corresponding to the candidate capacity power configuration scheme; based on the renewable energy curtailment power curve, the available renewable energy power, and the energy storage curtailment absorption power, obtain the... The renewable energy absorption rate corresponding to the candidate capacity power configuration scheme; the frequency support data corresponding to the candidate capacity power configuration scheme are obtained based on the power system frequency change rate, power system frequency, and quasi-steady-state frequency deviation corresponding to the candidate capacity power configuration scheme; the inertia support constant corresponding to the candidate capacity power configuration scheme is obtained based on the initial energy storage rated power, the inertia time constant of the thermal power unit, the rated capacity of the thermal power unit, and the rated capacity of the renewable energy power station in the candidate capacity power configuration scheme; the inertia support constant is compared with the preset upper limit value of the inertia support constant to obtain the inertia support data corresponding to the candidate capacity power configuration scheme.

[0061] In this embodiment, the operational characteristics and corresponding technical evaluation indicators of the grid-based energy storage participating in active support services such as power regulation, frequency response, and inertia support are as follows: The operational characteristics of grid-based energy storage participating in power regulation are as follows: In scenarios with a high proportion of renewable energy access, renewable energy output is volatile and uncertain. When renewable energy output is high, system load is low, or transmission channels are limited, renewable energy curtailment may occur. In this case, grid-based energy storage absorbs excess renewable energy through charging, reducing renewable energy curtailment. When renewable energy output is low or system load is high, grid-based energy storage releases electrical energy back to the system through discharging, supporting system power balance, thereby realizing the time-based transfer and utilization of renewable energy and improving the renewable energy absorption level.

[0062] The power regulation effect of grid-based energy storage can be expressed as the regulation of the system's net load by the energy storage charging and discharging power. The power regulation power of grid-based energy storage in time period t is defined as: In the formula, This represents the power regulation capacity of grid-connected energy storage in time period t; Indicates the energy storage discharge power; This indicates the energy storage charging power. When... When, it indicates that the stored energy is discharging into the system; when When, it indicates that the energy storage absorbs electrical energy from the system.

[0063] To reflect the role of energy storage in absorbing the curtailment of renewable energy, the charging power of energy storage used to absorb curtailed renewable energy in time period t is defined as: In the formula, This represents the charging power of energy storage used to absorb abandoned renewable energy during time period t. This represents the amount of renewable energy curtailed during time period t when no energy storage is connected.

[0064] Based on the above power regulation relationship, the actual renewable energy consumption power in time period t after energy storage is connected can be expressed as: In the formula, This represents the actual renewable energy consumption power in time period t after grid-connected energy storage is connected. This represents the actual renewable energy consumption power in time period t when no energy storage is connected. This indicates the new energy power absorbed by energy storage through charging.

[0065] Therefore, the renewable energy absorption rate index corresponding to grid-based energy storage participating in power regulation can be expressed as: In the formula, Indicates the rate of new energy consumption; This represents the available power of new energy sources in time period t; This indicates the actual power of renewable energy consumption when no energy storage is connected. This indicates the amount of renewable energy that is abandoned when no energy storage is connected. This represents the new energy power absorbed by energy storage through charging; T represents the number of time periods within the dispatch cycle. Indicates the scheduling time interval.

[0066] Therefore, it can be seen that when grid-based energy storage participates in power regulation, its charging power is achieved through... It directly affects the renewable energy absorption rate. The more fully the energy storage is charged during periods of renewable energy curtailment, the better. The larger the value, the smaller the amount of abandoned renewable energy, and the higher the renewable energy consumption rate index. The higher.

[0067] The operational characteristics of grid-based energy storage in frequency support are as follows: In scenarios with a high proportion of renewable energy integration, when the system experiences power disturbances such as sudden load increases, unit tripping, or a sharp drop in renewable energy output, the system's active power becomes unbalanced, causing the system frequency to deviate from its rated value. Grid-based energy storage, relying on the rapid active power regulation capability of power electronic converters, can quickly respond to system frequency changes during disturbances, providing active power support to the system, thereby improving the system's dynamic frequency characteristics. The frequency support effect is mainly reflected in three aspects: first, reducing the system's maximum rate of frequency change; second, increasing the system's minimum frequency; and third, reducing the quasi-steady-state frequency deviation. Therefore, frequency support capability indicators are established as follows: In the formula, Indicates the first Frequency support capability indicators for each capacity configuration scheme; Indicates the first The maximum absolute frequency change rate of each capacity configuration scheme within the scheduling period; This indicates the maximum allowable rate of frequency change of the system; This represents a reference value for the rate of change of frequency. Indicates the first The lowest frequency of each capacity configuration scheme within the scheduling cycle; Indicates the lowest frequency allowed by the system; This represents the reference value for the lowest frequency point; Indicates the first The maximum quasi-steady-state frequency deviation of each capacity configuration scheme within the scheduling period; This indicates the maximum permissible quasi-steady-state frequency deviation of the system; This represents the reference value for the quasi-steady-state frequency deviation. , , These represent the weighting coefficients corresponding to the maximum rate of frequency change, the lowest frequency point, and the quasi-steady-state frequency deviation, respectively.

[0068] Therefore, when grid-based energy storage participates in frequency support, the smaller the maximum frequency change rate, the higher the minimum frequency point, and the smaller the quasi-steady-state frequency deviation, the greater the frequency support capability index, indicating a stronger system frequency support capability. The operational characteristics of grid-based energy storage participating in inertia support are as follows: In scenarios with a high proportion of renewable energy access, renewable energy units are connected to the grid through power electronic equipment, reducing the proportion of thermal power in the system and leading to a decrease in the system's equivalent inertia level. Grid-based energy storage can simulate the inertia characteristics of a synchronous machine through grid control or virtual synchronization control, rapidly adjusting active power output when the system frequency is disturbed, improving the system's equivalent inertia level, thereby enhancing the system's ability to resist rapid frequency changes. Its inertia support power expression is: In the formula, Rated power of energy storage; This represents the virtual inertia constant provided by the grid-type energy storage during time period t.

[0069] Therefore, the inertia support capability of grid-based energy storage is mainly reflected in its effect on improving the system's equivalent inertia constant. Establishing the system's equivalent inertia constant index: In the formula, Let represent the equivalent inertial constant of the system at time t; Let represent the inertial constant of the i-th thermal power plant; This represents the rated capacity of the i-th thermal power plant; This represents the rated capacity of the j-th renewable energy power station; Indicates the rated power of grid-type energy storage; Indicates the number of thermal power plants; This indicates the number of new energy power stations.

[0070] Furthermore, the inertia support capability index can be expressed as: In the formula, This represents the inertia support capability index; T represents the number of scheduling periods. This represents the normalized upper limit of the system's equivalent inertia constant. Therefore, when grid-type energy storage participates in inertia support, its virtual inertia support capability is... Directly affects the system's equivalent inertial constant The stronger the virtual inertia support capability provided by grid-based energy storage, the larger the system's equivalent inertia constant and the higher the inertia support capability index. The higher the value, the stronger the system's ability to withstand the initial stage of frequency disturbances.

[0071] The above implementation method, through time-series joint operation optimization, coordinates the charging and discharging of energy storage, the absorption of new energy sources, and the output of thermal power while taking into account system operation constraints. This achieves a refined evaluation of the comprehensive performance of each candidate capacity scheme under typical operating scenarios. Compared to existing technologies that rely solely on static power balance estimations, this method reflects the impact of actual energy storage dispatch capabilities on absorption and frequency support, significantly improving the authenticity and reliability of the performance data. Specifically, it obtains the energy storage power absorption capacity based on the energy storage charging and discharging power curves and the power curtailment without energy storage; then calculates the new energy absorption rate; and finally calculates the frequency based on the obtained dynamic frequency indicators. The system provides support data for energy storage, thermal power inertia and capacity, and renewable energy capacity. Inertia support constants are calculated and compared with preset upper limits to obtain inertia support data, quantifying the technical effects across three dimensions. For example, renewable energy absorption rate directly reflects the energy storage's ability to absorb curtailed electricity; frequency support data integrates the improvement of maximum frequency change rate, minimum point, and quasi-steady-state deviation; and inertia support data evaluates the suppression effect of the virtual inertia of energy storage on the initial frequency change rate by comparing the system's equivalent inertia constant with the reference upper limit. In summary, this comprehensively reflects the active support capability of grid-based energy storage, overcoming the shortcomings of existing technologies with their single evaluation dimension.

[0072] In this embodiment, step 105 includes: Step 1051: For any set of candidate capacity and power configuration schemes, perform a weighted summation based on the new energy absorption rate, frequency support data, and inertia support data corresponding to the candidate capacity and power configuration scheme to obtain the comprehensive evaluation target value corresponding to the candidate capacity and power configuration scheme. Step 1052: Select the candidate capacity and power configuration scheme with the largest comprehensive evaluation target value from several groups of candidate capacity and power configuration schemes as the real-time optimal configuration scheme; Step 1053: Obtain the historical optimal configuration scheme and historical comprehensive evaluation target value of the energy storage device to be configured, so that if the comprehensive evaluation target value is greater than the historical comprehensive evaluation target value, the real-time optimal configuration scheme is taken as the historical optimal configuration scheme; Step 1054: Based on the historical global optimal scheme, update the initial energy storage rated power and initial energy storage rated capacity in each group of candidate capacity power configuration schemes using a preset optimization algorithm to obtain the updated candidate capacity power configuration scheme set; Step 1055: Use the updated candidate capacity and power configuration scheme set as the initial capacity and power configuration scheme set, and repeat the scheme update operation until the preset maximum number of iterations is reached; Step 1056: Take the initial rated power and initial rated capacity of the energy storage in the historical optimal configuration scheme when the maximum number of iterations is reached as the target capacity power configuration scheme corresponding to the energy storage device to be configured.

[0073] In this embodiment, the rated power and rated capacity of energy storage are used as particle position variables. A particle swarm optimization algorithm is employed to generate a grid-type energy storage capacity configuration scheme. Considering system frequency security constraints and operational constraints, the grid-type energy storage is jointly optimized with thermal power and wind power, including: Let the m-th particle in the particle swarm represent a grid-type energy storage capacity configuration scheme, and its particle position can be represented as: In the formula, Indicates the position of the m-th particle; This represents the rated power of the grid-type energy storage in the m-th capacity configuration scheme; This represents the rated capacity of the grid-type energy storage in the m-th capacity configuration scheme.

[0074] For each capacity configuration scheme, a joint operation optimization model for grid-connected energy storage, thermal power, and wind power is established based on typical daily load curves and wind power output curves. The objective of the joint operation optimization is to improve the absorption of new energy sources and ensure system frequency security; its objective function can be expressed as: In the formula, This represents the overall operational effect of the m-th capacity configuration scheme; This represents the renewable energy consumption rate corresponding to the m-th capacity configuration scheme; This represents the frequency support capability index corresponding to the m-th capacity configuration scheme. This represents the inertia support capability index corresponding to the m-th capacity configuration scheme. , , These represent the weighting coefficients for different technical evaluation indicators.

[0075] Power balance constraints must be met during joint operation optimization: In the formula, This represents the active power output of the i-th thermal power plant during time period t. This represents the actual wind power absorbed during time period t; This represents the energy storage discharge power during time period t; This represents the energy storage charging power during time period t. Represents the system load power in time period t; the This represents the number of thermal power units; among which, the operating constraints for wind power are: In the formula, This represents the available wind power during time period t.

[0076] The operating constraints for thermal power plants are: ; In the formula, and Let represent the minimum and maximum active power output of the i-th thermal power plant, respectively. This represents the operating status of the i-th thermal power plant during time period t.

[0077] The operational constraints of grid-based energy storage are: In the formula, The rated power of the energy storage; and These represent the state of charge of the energy storage in time period t and time period t-1, respectively. Indicates energy storage charging efficiency; Indicates the energy storage discharge efficiency; Indicates the scheduling time interval; This represents the rated capacity of the grid-type energy storage in the m-th capacity configuration scheme; and These represent the lower and upper limits of the energy storage's state of charge, respectively. This represents the state of charge of grid-connected energy storage in the m-th capacity configuration scheme at the beginning of the scheduling cycle; Indicates the state of charge at the end of the scheduling cycle; This indicates the initial state of charge of the energy storage.

[0078] To prioritize energy storage for renewable energy consumption, the charging and discharging operation of energy storage is guided based on the distribution of wind curtailment in scenarios without energy storage access. When wind curtailment occurs in time period t in scenarios without energy storage, energy storage is guided to charge first to absorb surplus wind power; when wind curtailment is low and the system load is high, energy storage is guided to discharge to support system power balance, thereby realizing the time-shifted utilization of renewable energy.

[0079] At the same time, joint operation optimization must also meet the system frequency security constraints established above: Among them, the Represents the maximum rate of frequency change within time period t; the Indicates the maximum rate of change of frequency; the This represents the lower limit of the lowest frequency point. After completing the joint operation optimization of each capacity configuration scheme in this embodiment, the calculation results of thermal power output, wind power absorption power and energy storage charging and discharging power corresponding to the scheme are obtained, which provide a calculation basis for subsequent technical evaluation of capacity configuration schemes and particle swarm iteration updates.

[0080] In this embodiment, the comprehensive evaluation target value is calculated based on the joint optimization results, and the optimal grid-type energy storage capacity configuration scheme at node 10 is determined. The renewable energy absorption rate index for the m-th capacity configuration scheme is obtained based on the joint optimization calculation results. Frequency support capability indicators and inertia support capability index The frequency support capability index is calculated using the established frequency disturbance response model.

[0081] Meanwhile, to avoid the energy storage rated power and capacity being too large, thus making the scheme uneconomical, an energy storage configuration cost index is introduced. The energy storage capacity configuration cost of the m-th capacity configuration scheme can be expressed as: In the formula, This represents the configuration cost of the m-th capacity configuration scheme; Indicates the unit cost of energy storage; This represents the rated energy storage power of the m-th capacity configuration scheme.

[0082] The energy storage cost is normalized to obtain the energy storage cost normalization index: In the formula, This represents the normalized energy storage cost index for the m-th capacity configuration scheme; This represents a normalized reference value for energy storage costs.

[0083] Based on the indicators of renewable energy absorption rate, frequency support capability, inertia support capability, and energy storage cost, a comprehensive evaluation target value for the m-th capacity configuration scheme is constructed: In the formula, Let represent the comprehensive evaluation target value of the m-th capacity configuration scheme, and A larger value indicates a better overall performance of the capacity configuration scheme. , , , These represent the weighting coefficients for new energy absorption rate, frequency support capability, inertia support capability, and energy storage cost, respectively, with values ​​of 0.5, 0.2, 0.2, and 0.1.

[0084] During the particle swarm optimization iteration process, the individual optimal position and the swarm optimal position of each particle are updated based on the comprehensive evaluation target value of each capacity configuration scheme. When the current comprehensive evaluation target value of the m-th particle is greater than its historical best comprehensive evaluation target value, the individual optimal position of that particle is updated; when the comprehensive evaluation target value of the capacity configuration scheme is greater than the historical best comprehensive evaluation target value of the swarm, the global optimal position of the particle swarm is updated. The particle velocity and position update formulas are: In the formula, the particle swarm size is taken as 20; the maximum number of iterations q is taken as 20; and Let represent the position and velocity of the m-th particle in the q-th iteration, respectively; This represents the optimal position of the m-th particle. This represents the global optimal position of the particle swarm; This represents the inertia weight, which is set to 0.7. and These represent the individual learning factor and the group learning factor, respectively, both set to 1.6; and The random number is within the interval [0, 1]; This represents the position of the m-th particle after the (q+1)-th iteration; This represents the velocity of the m-th particle after the (q+1)-th iteration.

[0085] When the maximum number of iterations is reached, the particle swarm optimization iteration is stopped, and the rated power and rated capacity of the energy storage corresponding to the globally optimal particle are taken as the optimal capacity configuration scheme for grid-type energy storage. In the formula, This represents the optimal grid-type energy storage capacity configuration scheme; Indicates the optimal rated power of energy storage; This indicates the optimal rated energy storage capacity.

[0086] Therefore, through this embodiment, the optimal rated power and rated capacity of the grid-type energy storage at node 10 of the example system can be obtained as 377.37MW / 754.74MWh, and the comparison results of various capacity configuration schemes can be further obtained. The comparison results of some schemes are shown in Table 4.

[0087] Table 4 Comparison Results of Some Schemes As shown in Table 4, after integrating grid-based energy storage, all capacity configurations improved the renewable energy absorption rate, frequency support capability, and inertia support capability compared to before the integration. Specifically, before the integration, the renewable energy absorption rate was 0.67720, the frequency support capability was 0.2580, and the inertia support capability was 0.83934. Under the optimal configuration, with a rated energy storage power of 377.37MW and a rated capacity of 754.74MWh, the renewable energy absorption rate increased to 0.70494, the frequency support capability increased to 0.50638, and the inertia support capability increased to 0.95623. This demonstrates that grid-based energy storage effectively improves the system's renewable energy absorption level and frequency security support capability.

[0088] The above implementation method establishes a comprehensive evaluation target value as the optimization guide and adopts a group iterative optimization algorithm to efficiently search for a multi-objective optimal solution that takes into account renewable energy consumption, frequency security, inertia support and cost in the feasible region. The above iterative mechanism can retain historical optimal solutions, prevent the target value from degrading due to algorithm exploration, and ensure that the final output rated power and rated capacity of energy storage can maximize the comprehensive operation performance of the high-proportion renewable energy power system.

[0089] On the other hand, refer to Figure 4 This embodiment also provides a multi-objective optimization configuration system for grid-type energy storage, including an initial configuration module 401, a safety constraint module 402, a configuration screening module 403, an effect evaluation module 404, and a configuration optimization module 405.

[0090] The initial configuration module 401 is used to acquire the basic operating data, frequency boundary values, static equipment parameters, and initial capacity and power configuration scheme set of the target power system and the energy storage device to be configured; wherein, the initial capacity and power configuration scheme set includes several initial capacity and power configuration schemes. The safety constraint module 402 is used to obtain, based on the basic operating data and the static equipment parameters, the power system frequency, the power system frequency change rate, and the quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system according to each set of the initial capacity power configuration scheme; The configuration filtering module 403 is used to select several sets of candidate capacity power configuration schemes corresponding to the energy storage device to be configured from the initial capacity power configuration scheme set according to the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation and the frequency boundary value. The effect evaluation module 404 is used to optimize the operation of the energy storage device to be configured and the target power system for any set of candidate capacity power configuration schemes, and obtain the grid-based energy storage effect data of the energy storage device to be configured under the candidate capacity power configuration scheme. The configuration optimization module 405 is used to take several groups of candidate capacity and power configuration schemes as the initial capacity and power configuration scheme set, and repeatedly execute the scheme update operation according to the grid energy storage effect data and the initial capacity and power configuration scheme set until the preset end condition of the scheme update operation is reached, so as to obtain the target capacity and power configuration scheme corresponding to the energy storage device to be configured.

[0091] As a preferred example, the initial configuration module 401 includes a power acquisition unit and a device acquisition unit; The power acquisition unit is used to acquire the frequency boundary values, typical operating data, and power generation operating data of each power source in the target power system, so as to obtain the basic operating data of the target power system based on the typical operating data and the power generation operating data. The typical operating data includes a typical daily load curve, a renewable energy curtailment power curve without energy storage access, renewable energy available power without energy storage access, and disturbance power values ​​under typical frequency disturbance scenarios. The power sources include thermal power units and renewable energy power stations. When the power source is a thermal power unit, the power generation operating data includes rated capacity, minimum active power output, maximum active power output, ramp rate, minimum start / stop duration, inertial time constant, thermal power frequency response delay time, and thermal power frequency response ramp time. When the power source is a renewable energy power station, the power generation operating data includes rated capacity and a typical daily output curve. The device acquisition unit is used to acquire the static device parameters, multiple initial rated energy storage power, and multiple initial rated energy storage capacity corresponding to the energy storage device to be configured, so as to obtain the initial capacity power configuration scheme set corresponding to the energy storage device to be configured based on the initial rated energy storage power and the initial rated energy storage capacity; wherein, the initial capacity power configuration scheme set includes multiple different initial capacity power configuration schemes; each initial capacity power configuration scheme includes an initial rated energy storage power and an initial rated energy storage capacity.

[0092] This embodiment provides a multi-objective optimization configuration method and system for grid-based energy storage. Starting from the operational characteristics of grid-based energy storage participating in active support services such as renewable energy consumption, frequency response, and inertia support, it establishes renewable energy consumption rate indicators, frequency support capability indicators, and inertia support capability indicators. This avoids the problem of traditional energy storage capacity configuration using only economic or single operational indicators as evaluation criteria, and more comprehensively reflects the comprehensive support role of grid-based energy storage in high-proportion renewable energy power systems, providing a quantitative evaluation basis for subsequent energy storage capacity configuration.

[0093] Secondly, this embodiment comprehensively considers the dynamic response characteristics of thermal power and grid-based energy storage after frequency disturbances, establishes a system frequency disturbance response model, and constructs frequency safety constraints based on the maximum frequency change rate, the lowest frequency point, and the quasi-steady-state frequency deviation. This can incorporate the rapid frequency response capability and virtual inertia support capability of grid-based energy storage into the capacity configuration process, avoiding the problem that static reserve capacity constraints alone cannot reflect the dynamic frequency process, thereby improving the adaptability of energy storage capacity configuration schemes to system frequency safety requirements.

[0094] This embodiment uses the rated power and rated capacity of energy storage as particle position variables, and adopts the particle swarm optimization algorithm to generate candidate capacity configuration schemes for grid-type energy storage. Under frequency security constraints and operational constraints, grid-type energy storage is jointly optimized with thermal power and wind power. This can coordinate the relationship between energy storage charging and discharging, new energy consumption and conventional unit output, so that the energy storage configuration not only meets the capacity configuration requirements, but also adapts to the system scheduling requirements under typical operating scenarios, thereby improving the engineering feasibility of the capacity configuration results.

[0095] This embodiment calculates the renewable energy absorption rate, frequency support capability, inertia support capability, and energy storage capacity configuration cost of each candidate capacity configuration scheme based on the joint optimization results, and constructs a comprehensive evaluation target value to determine the optimal capacity configuration scheme. This can improve the renewable energy absorption level, enhance the frequency dynamic support capability, and improve the inertia support capability, while avoiding the problem of unreasonable configuration caused by excessive rated power and rated capacity of energy storage, thereby obtaining a grid-type energy storage capacity configuration scheme that takes into account both technical performance and configuration rationality.

[0096] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A multi-objective optimization configuration method for grid-type energy storage, characterized in that, include: Acquire the basic operating data, frequency boundary values, static equipment parameters, and initial capacity and power configuration scheme set of the target power system and the energy storage device to be configured; wherein, the initial capacity and power configuration scheme set includes several initial capacity and power configuration schemes; Based on the basic operating data and the static equipment parameters, obtain the power system frequency, power system frequency change rate and quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system according to each set of the initial capacity power configuration scheme; Based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation, and the frequency boundary value, several sets of candidate capacity and power configuration schemes corresponding to the energy storage device to be configured are selected from the initial capacity and power configuration scheme set. For any set of candidate capacity and power configuration schemes, the operation of the energy storage device to be configured and the target power system is optimized to obtain the grid-based energy storage effect data of the energy storage device to be configured under the candidate capacity and power configuration scheme. Based on the grid-connected energy storage effect data, several sets of candidate capacity and power configuration schemes, and a preset scheme optimization algorithm, the target capacity and power configuration scheme of the energy storage device to be configured is obtained.

2. The multi-objective optimization configuration method for grid-type energy storage according to claim 1, characterized in that, The acquisition of basic operating data of the target power system, frequency boundary values, and static equipment parameters and initial capacity and power configuration schemes of the energy storage devices to be configured includes: The frequency boundary values, typical operating data, and power generation operating data of each power source in the target power system are acquired to obtain the basic operating data of the target power system based on the typical operating data and the power generation operating data. The typical operating data includes a typical daily load curve, a renewable energy curtailment power curve without energy storage devices, a renewable energy available power curve without energy storage devices, and a disturbance power value under typical frequency disturbance scenarios. The power sources include thermal power units and renewable energy power stations. When the power source is the thermal power unit, the power generation operation data includes rated capacity, minimum active power output, maximum active power output, ramp rate, minimum start-stop duration, inertial time constant, thermal power frequency response delay time, and thermal power frequency response ramp time. When the power source is the new energy power station, the power generation operation data includes the rated capacity and a typical daily power output curve; The static equipment parameters, multiple initial rated energy storage power, and multiple initial rated energy storage capacity of the energy storage device to be configured are obtained, so as to obtain the initial capacity power configuration scheme set corresponding to the energy storage device to be configured based on the initial rated energy storage power and the initial rated energy storage capacity; wherein, the initial capacity power configuration scheme set includes multiple different initial capacity power configuration schemes; each initial capacity power configuration scheme includes an initial rated energy storage power and an initial rated energy storage capacity.

3. A multi-objective optimization configuration method for grid-type energy storage according to claim 2, characterized in that, The static equipment parameters include energy storage frequency response delay time, energy storage frequency response ramp-up time, virtual inertia constant, rated energy storage power, and equivalent inertia constant; the frequency boundary values ​​include the system rated frequency; obtaining the power system frequency, power system frequency change rate, and quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system based on the basic operating data and the equipment parameters includes: For any set of initial capacity power configuration schemes, obtain the initial rated energy storage power in the initial capacity power configuration scheme; Based on the thermal power frequency response delay time, the thermal power frequency response ramp-up time, the energy storage frequency response delay time, and the energy storage frequency response ramp-up time, the equivalent total frequency regulation capacity between the thermal power unit and the energy storage device to be configured is obtained. Based on the disturbance power value, the inertial time constant, the rated capacity of the thermal power unit, the rated capacity of the new energy power station, the initial energy storage rated power in the initial capacity power configuration scheme, and the energy storage rated power, the system equivalent inertial constant when the energy storage device to be configured is connected to the target power system is obtained; Based on the system equivalent inertia constant, the disturbance power value, and the synchronous machine rotor motion data corresponding to the target power system, the maximum frequency change rate when the energy storage device to be configured is connected to the target power system is obtained, which is used as the power system frequency change rate. The minimum frequency deviation is obtained based on the equivalent total frequency regulation capacity, the disturbance power value, and the maximum frequency change rate. The power system frequency is then obtained based on the minimum frequency deviation and the system rated frequency. Based on the equivalent total frequency regulation capacity and the disturbance power value, the quasi-steady-state frequency deviation is calculated and used as the quasi-steady-state frequency deviation of the target power system.

4. A multi-objective optimization configuration method for grid-type energy storage according to claim 3, characterized in that, The step of selecting several candidate capacity-power configuration schemes corresponding to the energy storage device to be configured from the initial capacity-power configuration scheme set based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation, and the frequency boundary value includes: Obtain the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation of the target power system from the frequency boundary values; Based on the power system frequency change rate, the power system frequency, the quasi-steady-state frequency deviation, the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation, several candidate capacity power configuration schemes corresponding to the energy storage device to be configured are selected from the initial capacity power configuration scheme set.

5. A multi-objective optimization configuration method for grid-type energy storage according to claim 4, characterized in that, The step of selecting several candidate capacity and power configuration schemes corresponding to the energy storage device to be configured from the initial capacity and power configuration scheme set based on the power system frequency change rate, the power system frequency, the quasi-steady-state frequency deviation, the upper limit of the frequency change rate, the lower limit of the frequency, and the upper limit of the quasi-steady-state frequency deviation includes: For any of the aforementioned initial capacity power configuration schemes: When the power system frequency change rate of the initial capacity power configuration scheme is less than or equal to the upper limit of the frequency change rate, the power system frequency is greater than or equal to the lower limit of the frequency, and the quasi-steady-state frequency deviation is less than or equal to the upper limit of the quasi-steady-state frequency deviation, the initial capacity power configuration scheme shall be regarded as a candidate capacity power configuration scheme.

6. A multi-objective optimization configuration method for grid-type energy storage according to claim 1, characterized in that, For any set of candidate capacity and power configuration schemes, the operation optimization of the energy storage device to be configured and the target power system is performed to obtain the grid-connected energy storage effect data of the energy storage device to be configured under the candidate capacity and power configuration scheme, including: Based on the typical daily load curve, typical daily power output curve, and renewable energy curtailment power curve of the target power system, obtain the joint operation optimization model when the energy storage equipment to be configured is connected to the target power system; The operating constraints of the target power system are obtained. For any set of candidate capacity power configuration schemes, based on the operating constraints and the initial rated power and initial rated capacity of energy storage in the candidate capacity power configuration scheme, with the goal of maximizing the data output by the joint operation optimization model, the thermal power output plan, actual wind power consumption power and energy storage charging and discharging power corresponding to the candidate capacity power configuration scheme are obtained. Based on the thermal power output plan, the actual wind power absorption capacity, and the energy storage charging and discharging power, the renewable energy absorption rate, frequency support data, and inertia support data of the energy storage device to be configured when it is connected to the target power system according to the candidate capacity power configuration scheme are obtained, so as to serve as the grid-connected energy storage effect data corresponding to the candidate capacity power configuration scheme.

7. A multi-objective optimization configuration method for grid-type energy storage according to claim 6, characterized in that, The step of obtaining the renewable energy absorption rate, frequency support data, and inertia support data of the energy storage device to be configured when connected to the target power system according to the candidate capacity power configuration scheme, based on the thermal power output plan, the actual wind power absorption capacity, and the energy storage charging and discharging power, as the grid-connected energy storage effect data corresponding to the candidate capacity power configuration scheme, includes: Based on the energy storage charging and discharging power and the new energy curtailment power curve of the target power system, obtain the energy storage curtailment absorption power corresponding to the candidate capacity power configuration scheme; Based on the renewable energy curtailment power curve, renewable energy available power, and the renewable energy absorption power of the energy storage curtailment, the renewable energy absorption rate corresponding to the candidate capacity power configuration scheme is obtained; Based on the power system frequency change rate, power system frequency, and quasi-steady-state frequency deviation corresponding to the candidate capacity power configuration scheme, the frequency support data corresponding to the candidate capacity power configuration scheme is obtained. Based on the initial rated energy storage power, the inertial time constant of the thermal power unit, the rated capacity of the thermal power unit, and the rated capacity of the new energy power station in the candidate capacity power configuration scheme, the inertial support constant corresponding to the candidate capacity power configuration scheme is obtained. The inertia support constant is compared with the preset upper limit value of the inertia support constant to obtain the inertia support data corresponding to the candidate capacity power configuration scheme.

8. A multi-objective optimization configuration method for grid-type energy storage according to claim 1, characterized in that, The step of obtaining the target capacity power configuration scheme for the energy storage device to be configured based on the grid-connected energy storage effect data, several sets of candidate capacity power configuration schemes, and a preset scheme optimization algorithm includes: For any set of candidate capacity and power configuration schemes, the comprehensive evaluation target value corresponding to the candidate capacity and power configuration scheme is obtained by weighted summation based on the new energy absorption rate, frequency support data and inertia support data corresponding to the candidate capacity and power configuration scheme. From a group of candidate capacity and power configuration schemes, the candidate capacity and power configuration scheme with the largest comprehensive evaluation target value is selected as the real-time optimal configuration scheme. Obtain the historical optimal configuration scheme and historical comprehensive evaluation target value of the energy storage device to be configured, so that if the comprehensive evaluation target value is greater than the historical comprehensive evaluation target value, the real-time optimal configuration scheme is taken as the historical optimal configuration scheme; Based on the historical global optimal scheme, the initial energy storage rated power and initial energy storage rated capacity in each group of candidate capacity power configuration schemes are updated by a preset optimization algorithm to obtain the updated candidate capacity power configuration scheme set. The updated candidate capacity and power configuration scheme set is used as the initial capacity and power configuration scheme set to repeatedly perform the scheme update operation until the preset maximum number of iterations is reached. The initial rated power and initial rated capacity of the energy storage in the historical optimal configuration scheme when the maximum number of iterations is reached are used as the target capacity power configuration scheme for the energy storage device to be configured.

9. A multi-objective optimization configuration system for grid-type energy storage, characterized in that, It includes an initial configuration module, a security constraint module, a configuration filtering module, an effect evaluation module, and a configuration optimization module; The initial configuration module is used to acquire the basic operating data, frequency boundary values, static equipment parameters, and initial capacity and power configuration scheme set of the target power system and the energy storage device to be configured; wherein, the initial capacity and power configuration scheme set includes several initial capacity and power configuration schemes; The safety constraint module is used to obtain, based on the basic operating data and the static equipment parameters, the power system frequency, the power system frequency change rate, and the quasi-steady-state frequency deviation when the energy storage device to be configured is connected to the target power system according to each set of initial capacity power configuration schemes; The configuration filtering module is used to select several sets of candidate capacity power configuration schemes corresponding to the energy storage device to be configured from the initial capacity power configuration scheme set based on the power system frequency, the power system frequency change rate, the quasi-steady-state frequency deviation and the frequency boundary value. The effect evaluation module is used to optimize the operation of the energy storage device to be configured and the target power system for any set of candidate capacity power configuration schemes, and obtain the grid-based energy storage effect data of the energy storage device to be configured under the candidate capacity power configuration scheme. The configuration optimization module is used to take several groups of candidate capacity and power configuration schemes as the initial capacity and power configuration scheme set, and repeatedly execute the scheme update operation according to the grid energy storage effect data and the initial capacity and power configuration scheme set until the preset end condition of the scheme update operation is reached, so as to obtain the target capacity and power configuration scheme corresponding to the energy storage device to be configured.

10. A multi-objective optimization configuration system for grid-type energy storage according to claim 9, characterized in that, The initial configuration module includes a power acquisition unit and a device acquisition unit; The power acquisition unit is used to acquire the frequency boundary values, typical operating data, and power generation operating data of each power source in the target power system, so as to obtain the basic operating data of the target power system based on the typical operating data and the power generation operating data. The typical operating data includes a typical daily load curve, a renewable energy curtailment power curve without energy storage access, renewable energy available power without energy storage access, and disturbance power values ​​under typical frequency disturbance scenarios. The power sources include thermal power units and renewable energy power stations. When the power source is a thermal power unit, the power generation operating data includes rated capacity, minimum active power output, maximum active power output, ramp rate, minimum start / stop duration, inertial time constant, thermal power frequency response delay time, and thermal power frequency response ramp time. When the power source is a renewable energy power station, the power generation operating data includes rated capacity and a typical daily output curve. The device acquisition unit is used to acquire the static device parameters, multiple initial rated energy storage power, and multiple initial rated energy storage capacity corresponding to the energy storage device to be configured, so as to obtain the initial capacity power configuration scheme set corresponding to the energy storage device to be configured based on the initial rated energy storage power and the initial rated energy storage capacity; wherein, the initial capacity power configuration scheme set includes multiple different initial capacity power configuration schemes; each initial capacity power configuration scheme includes an initial rated energy storage power and an initial rated energy storage capacity.

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