Electrochemical energy storage robust configuration method, system and equipment for supporting new energy base delivery and storage medium
By constructing an energy storage optimization configuration model and a nested column constraint generation algorithm, the configuration of the energy storage system is optimized, which solves the problem of low power transmission efficiency from new energy bases, achieves a balance between power supply reliability and economy, and adapts to the uncertainty of new energy output.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- YUNNAN POWER GRID CO LTD
- Filing Date
- 2026-01-21
- Publication Date
- 2026-05-08
AI Technical Summary
In existing technologies, the power transmission efficiency of new energy bases is affected by the intermittency and fluctuation of wind and solar power output, and there is a lack of flexible adjustment of resource optimization, which makes it difficult to balance power supply reliability and economy.
An energy storage optimization configuration model is constructed. By combining the parameters of energy storage equipment, the status of new energy power generation and the operating status of conventional power sources, an objective function and constraints are established. The nested column constraint generation algorithm is used to solve the problem, optimize the configuration of energy storage power and capacity, and consider the system operating cost, energy storage investment cost, carbon emissions and wind and solar curtailment penalty costs. Through a multi-scenario operating cost model and time uncertainty budget, robust configuration of the energy storage system is achieved.
Under extreme uncertainty, the reliability and economy of DC power transmission from new energy bases have been optimized, ensuring the economy and stability of the system throughout its entire life cycle and meeting the power output needs of new energy in different scenarios.
Smart Images
Figure CN122000969A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power system planning and operation technology, and in particular to a robust configuration method, system, equipment and storage medium for electrochemical energy storage that supports the transmission of new energy bases. Background Technology
[0002] Large-scale wind and solar power generation bases primarily use ultra-high-voltage direct current (UHVDC) to deliver clean electricity to load centers. However, the intermittent and fluctuating nature of renewable energy output severely impacts power transmission efficiency.
[0003] In existing technologies, some literature has conducted research on the selection and optimization of power collection lines for large-scale wind power projects in the Shagohuang area, addressing the unique climatic and geological conditions, thus saving planning costs and improving operational reliability. Other literature proposes an improved named entity recognition algorithm that constructs a knowledge graph ontology layer based on the analysis of large-scale new energy base projects, improving the efficiency of engineering data collection and analysis as well as power transmission efficiency. However, the above methods mainly focus on the configuration of the base and transmission planning, lacking flexibility in optimizing resource allocation. Summary of the Invention
[0004] In view of the above-mentioned problems, the present invention provides a robust configuration method, system, equipment and storage medium for electrochemical energy storage to support the transmission of new energy bases.
[0005] Therefore, the technical problem solved by this invention is: how to provide an optimized configuration method for electrochemical energy storage systems that is both economical and ensures power supply reliability for large-scale new energy DC transmission bases, taking into account the extreme uncertainty of wind and solar power output.
[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a robust configuration method for electrochemical energy storage to support the transmission of energy from new energy bases, comprising: Based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, an objective function is constructed, and an energy storage optimization configuration model considering system operating costs and energy storage investment costs is established. Considering the DC channel capacity, the operating characteristics of energy storage equipment, and the uncertainty of new energy output, constraints are established for the energy storage optimization configuration model; The optimal configuration scheme of energy storage power and capacity is obtained by solving the energy storage optimization configuration model based on the nested column constraint generation algorithm.
[0007] As a preferred scheme for a robust configuration method of electrochemical energy storage to support the transmission of new energy from bases, wherein: The establishment of an energy storage optimization configuration model that considers system operating costs and energy storage investment costs, based on the objective function constructed from energy storage device configuration parameters, new energy power generation state variables, and conventional power supply operating state variables, includes: Based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, an objective function is constructed with the goal of minimizing the total system cost. The total system cost includes system operating costs and energy storage investment costs.
[0008] As a preferred scheme for a robust configuration method of electrochemical energy storage to support the transmission of new energy from bases, wherein: The method for constructing an objective function based on energy storage device configuration parameters, new energy power generation state variables, and conventional power supply operation state variables, and establishing an energy storage optimization configuration model that considers system operating costs and energy storage investment costs, also includes: The system operating cost is calculated through a multi-scenario operating cost model, which is generated based on clustering of typical daily operating scenarios and takes into account seasonal characteristics and weather types, covering system operating costs, carbon emission costs, and wind and solar curtailment penalty costs. Energy storage investment costs are calculated based on the total life cycle cost.
[0009] As a preferred scheme for a robust configuration method of electrochemical energy storage to support the transmission of new energy from bases, wherein: The constraints for establishing the energy storage optimization configuration model, taking into account DC channel capacity, energy storage device operating characteristics, and uncertainties in new energy output, include: Establish DC channel capacity constraints to limit the transmitted power from exceeding the transmission limit. Establish operational constraints for new energy bases to maintain system power balance. System power balance is related to conventional power output, actual new energy output, energy storage charging and discharging power, and DC power transmission.
[0010] As a preferred scheme for a robust configuration method of electrochemical energy storage to support the transmission of new energy from bases, wherein: The constraints for establishing the energy storage optimization configuration model, taking into account DC channel capacity, energy storage device operating characteristics, and uncertainties in new energy output, also include: Establish operational constraints for energy storage devices to limit the range of charging and discharging power and the range of stored energy states, and ensure that charging and discharging states are mutually exclusive; Establish constraints on the uncertainty of new energy output, and model the output fluctuations by using a bounded set of uncertainties based on time uncertainty budgeting to control the degree of accumulation of uncertainty in the time dimension.
[0011] As a preferred scheme for a robust configuration method of electrochemical energy storage to support the transmission of new energy from bases, wherein: The nested column constraint generation algorithm is used to solve the energy storage optimization configuration model to obtain the optimal configuration scheme of energy storage power and capacity, including: The energy storage optimization configuration model is decomposed into a two-stage optimization problem, including the main problem of determining the energy storage configuration scheme and the sub-problem of simulating the worst operating scenario under a given configuration; The main problem and sub-problems are solved iteratively based on a nested column constraint generation algorithm.
[0012] As a preferred scheme for a robust configuration method of electrochemical energy storage to support the transmission of new energy from bases, wherein: The nested column constraint generation algorithm is used to solve the energy storage optimization configuration model to obtain the optimal configuration scheme of energy storage power and capacity, including: The iterative solution process includes: Initialize the energy storage configuration scheme; In the first iteration step, the master problem is solved to obtain the current energy storage configuration scheme and the lower bound of the total system cost; In the second iteration step, the current energy storage configuration is fixed, the sub-problems are solved, the worst-case scenario that makes the system operating cost the highest is found within the preset uncertain set of new energy output, and the corresponding upper bound of the total system cost is obtained. Add the worst-case scenario identified in the subproblem as a new constraint to the main problem; Repeat the first and second iteration steps until the difference between the upper and lower bounds of the total system cost satisfies the preset convergence condition. The energy storage configuration scheme obtained at this time is the optimal configuration scheme.
[0013] Secondly, the present invention provides a robust configuration system for electrochemical energy storage that supports the transmission of energy from new energy bases, comprising: The energy storage optimization configuration model construction module is used to construct an objective function based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, and to establish an energy storage optimization configuration model that considers system operating costs and energy storage investment costs. An uncertainty constraint integration module is used to establish constraints for the energy storage optimization configuration model, taking into account the DC channel capacity, the operating characteristics of energy storage equipment, and the uncertainty of new energy output. The two-stage algorithm solution module is used to solve the energy storage optimization configuration model based on the nested column constraint generation algorithm to obtain the optimal configuration scheme of energy storage power and capacity.
[0014] Thirdly, the present invention provides a computer device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the robust configuration method for electrochemical energy storage that supports the transmission of new energy bases.
[0015] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of a robust configuration method for electrochemical energy storage supporting the transmission of energy from new energy bases.
[0016] The beneficial effects of this invention are as follows: This invention establishes an objective function for an energy storage optimization configuration model that considers system operating costs and energy storage investment costs. With the goal of minimizing the total system cost, it abandons the traditional optimization objective focused primarily on investment costs and innovatively integrates system operating costs, carbon emission costs, wind and solar curtailment penalty costs, and energy storage investment costs into a unified life-cycle optimization framework. By introducing a clustering generation technique based on typical daily operating scenarios, a multi-scenario operating cost model considering seasonal characteristics and weather types is established, achieving coordinated optimization of energy storage configuration between long-term investment and short-term scheduling. Considering DC channel capacity, energy storage equipment operating characteristics, and the uncertainty of renewable energy output, constraints are established for the energy storage optimization configuration model, ensuring that the DC power transmission curve of renewable energy bases can meet the renewable energy output conditions under different scenarios while maintaining a consistent DC channel power transmission scheme. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is an overall flowchart of a robust configuration method for electrochemical energy storage that supports the transmission of new energy from bases, provided by the present invention.
[0019] Figure 2 This is a typical daily wind power prediction curve in a simulation example of a robust configuration method for electrochemical energy storage that supports the transmission of new energy from bases, provided by this invention.
[0020] Figure 3 This is a typical daily photovoltaic prediction curve in a simulation example of a robust configuration method for electrochemical energy storage that supports the transmission of new energy from bases, provided by this invention.
[0021] Figure 4 This is a simulation example of the DC power transmission curve of a 4 million kW coal-fired power plant, provided by the present invention, for a robust configuration method of electrochemical energy storage that supports the transmission of new energy from bases.
[0022] Figure 5 This is a simulation example of the DC power transmission curve of a 2 million kWh coal-fired power plant in a method for robust configuration of electrochemical energy storage to support the transmission of new energy from bases, provided by this invention. Detailed Implementation
[0023] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.
[0024] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a robust configuration method for electrochemical energy storage to support the transmission of new energy from bases, including: S1: Construct an objective function based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, and establish an energy storage optimization configuration model that considers system operating costs and energy storage investment costs; S2: Considering the DC channel capacity, the operating characteristics of energy storage equipment, and the uncertainty of new energy output, establish the constraints of the energy storage optimization configuration model; S3: Solve the energy storage optimization configuration model based on the nested column constraint generation algorithm to obtain the optimal configuration scheme of energy storage power and capacity.
[0025] It should be noted that through steps S1-S3, a robust optimization model was established that uniformly considers the economics of the entire life cycle, incorporates the uncertainty of wind and solar power output, and strictly meets the physical constraints of system operation. An efficient decomposition algorithm was used to solve the model, which ultimately provides a set of electrochemical energy storage system configuration schemes for large-scale new energy base transmission systems that can still ensure power supply security and channel utilization under extreme fluctuation scenarios and are economically optimal throughout the entire life cycle.
[0026] Example 2, refer to Figure 1 As an embodiment of the present invention, based on the previous embodiment, a robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases is provided, comprising: In this embodiment, the step S1 above, which involves constructing an objective function based on energy storage device configuration parameters, new energy power generation state variables, and conventional power supply operation state variables, and establishing an energy storage optimization configuration model that considers system operating costs and energy storage investment costs, includes: Based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, an objective function is constructed for an energy storage optimization configuration model that considers system operating costs and energy storage investment costs.
[0027] The constructed objective function uses the total system cost C total With minimization as the objective, this approach abandons the traditional optimization goal primarily focused on investment costs. Instead, it innovatively integrates system operating costs, carbon emission costs, wind and solar curtailment penalties, and energy storage investment costs into a unified lifecycle optimization framework. By introducing clustering generation technology based on typical daily operating scenarios, a multi-scenario operating cost model considering seasonal characteristics and weather types was established, achieving coordinated optimization of energy storage configuration between long-term investment and short-term dispatch.
[0028] Specifically, the objective function expression is as follows: in, s Indicates a scene, C Inv , C Ope This represents the investment cost and system operating cost of energy storage. c P and c E These are the cost coefficients for energy storage power and capacity, respectively. T life The service life of new energy sources; r The discount rate for the investment, calculated on an annual basis; c e This is the carbon emission cost coefficient; c cur This refers to the penalty coefficient for wind and solar power curtailment. c g This is the operating cost coefficient for coal-fired power plants; and The power and capacity of the energy storage device; p s Representing a scene s The probability of occurrence. and The predicted and actual renewable energy outputs for typical days are shown separately. For coal-fired power generation, This refers to the CO2 emissions from coal-fired power plants.
[0029] In this embodiment, the constraints for establishing the energy storage optimization configuration model in step S2 above, considering DC channel capacity, energy storage device operating characteristics, and uncertainty in new energy output, include: Considering the DC transmission capacity, the operating characteristics of energy storage devices, and the uncertainty of renewable energy output, constraints are established for the energy storage optimization configuration model. The DC power transmission curve of renewable energy bases should meet the renewable energy output conditions under different scenarios, while maintaining the same DC power transmission scheme.
[0030] Specifically, the constraints include: 1) DC channel capacity constraint: Limiting the transmitted power to the upper limit of the transmission channel, the expression is: in, This represents the upper limit of the DC transmission capacity. This is DC power transmission.
[0031] 2) Operational constraints of new energy bases: including power balance, energy storage charging and discharging coordination, etc., expressed as: in, and These are the discharge and charging power of energy storage, respectively.
[0032] 3) Energy storage device operation constraints: covering charge and discharge power limits, state of energy (SOC) range, and mutually exclusive conditions for charge and discharge states; in, and These are 0-1 variables representing the energy storage discharge / charge operating states, respectively.
[0033] 4) Uncertainty Constraints on Renewable Energy Output: To ensure system power balance after the emergence of uncertainties in renewable energy output, a modeling method for the uncertain set of wind and solar power output based on time uncertainty budgeting is proposed. The fluctuations in wind and solar power output are described as bounded uncertain sets, and a time uncertainty budget is introduced to enhance the system's adaptability to extreme fluctuations. The uncertain set characterizing the uncertainty of renewable energy can effectively describe the spatiotemporal correlation characteristics of prediction errors, expressed as: in, Contributing to the uncertainties of new energy sources and As an auxiliary variable, it describes whether the output of new energy sources reaches the boundary of the uncertain set. Budget for uncertain timeframes.
[0034] In this embodiment, the step S3 above, which uses a nested column constraint generation algorithm to solve the energy storage optimization configuration model and obtain the optimal configuration scheme for energy storage power and capacity, includes: The energy storage configuration problem is decomposed into a two-stage optimization problem: the first stage (main problem) determines the optimal configuration scheme of energy storage power and capacity; the second stage (sub-problem) simulates the system response under the worst-case output scenario during typical daily operation. Through iterative solving of the main problem and sub-problems, the energy storage configuration scheme is continuously improved until it converges to the optimal solution that meets the robustness requirements. The algorithm has a clear flow and good convergence and engineering practicality.
[0035] Specifically, the energy storage optimization configuration model is decomposed into a two-stage sub-Bruker optimization model for the collaborative optimization configuration of the energy storage system, as follows: Where x and p represent the investment decision variables and operational decision variables in this scenario, respectively; The output of photovoltaic power is represented by A, B, C, D, E, F, G, e, f, and g, which are constant coefficient matrices and constraint matrices, respectively. The two-stage bipolar optimization model is decomposed into a main problem of solving the energy storage configuration scheme and a subproblem of optimizing energy storage operation under the worst-case photovoltaic scenario. The main problem corresponds to the first stage of the energy storage optimization configuration model, and the subproblem corresponds to the second stage. Introducing the auxiliary variable φ, the main problem can be expressed in the following form: The subproblem can be represented in the following form: Among them, x* represents the computational output of the main problem.
[0036] The specific solution process is as follows: The energy storage configuration model is decomposed into a main problem (investment decision) and a sub-problem (operation simulation), and then iteratively solved: the main problem determines the optimal power and capacity configuration of energy storage given a set of worst-case scenarios; the sub-problem, under the current energy storage configuration, finds the worst-case scenario that maximizes system operating costs within a preset set of uncertain wind and solar power output. First, a basic scheme without considering uncertainties is initialized and solved, then an iterative loop is entered: solving the main problem to obtain the current configuration scheme and the lower bound of the total system cost; fixing this configuration scheme, solving the sub-problem to obtain the corresponding worst-case scenarios and the upper bound of the total cost. By continuously adding new worst-case scenarios identified by the sub-problems back to the main problem as constraints, the upper and lower bounds are iteratively updated until the difference between the upper and lower bounds is less than the preset convergence tolerance ε. At this point, the algorithm converges to the optimal energy storage configuration scheme that meets the robustness requirements.
[0037] Example 3 illustrates a robust configuration method for electrochemical energy storage supporting the transmission of renewable energy from a renewable energy base. It should be noted that the technical solution for a robust configuration system for electrochemical energy storage supporting the transmission of renewable energy from a renewable energy base is based on the same concept as the aforementioned robust configuration method for electrochemical energy storage supporting the transmission of renewable energy from a renewable energy base. Details not described in detail in the technical solution for the robust configuration system for electrochemical energy storage supporting the transmission of renewable energy from a renewable energy base in this example can be found in the description of the aforementioned robust configuration method for electrochemical energy storage supporting the transmission of renewable energy from a renewable energy base.
[0038] This embodiment also provides a robust electrochemical energy storage configuration system to support the transmission of energy from new energy bases, including: The energy storage optimization configuration model construction module is used to construct an objective function based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, and to establish an energy storage optimization configuration model that considers system operating costs and energy storage investment costs. An uncertainty constraint integration module is used to establish constraints for the energy storage optimization configuration model, taking into account the DC channel capacity, the operating characteristics of energy storage equipment, and the uncertainty of new energy output. The two-stage algorithm solution module is used to solve the energy storage optimization configuration model based on the nested column constraint generation algorithm to obtain the optimal configuration scheme of energy storage power and capacity.
[0039] This embodiment also provides an electronic device applicable to a robust configuration method for electrochemical energy storage supporting the transmission of energy from new energy bases, including: The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement a robust electrochemical energy storage configuration method for supporting the transmission of new energy from a base, as proposed in the above embodiments.
[0040] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a robust electrochemical energy storage configuration method for supporting the transmission of new energy bases as proposed in the above embodiments.
[0041] The storage medium proposed in this embodiment belongs to the same inventive concept as the robust configuration method of electrochemical energy storage for supporting the transmission of new energy bases proposed in the above embodiment. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.
[0042] Example 4, refer to Figures 2-5 Tables 1-3 illustrate one embodiment of the present invention, providing a robust configuration method for electrochemical energy storage to support the transmission of new energy from bases. To verify the beneficial effects of the present invention, scientific demonstration is conducted through simulation experiments.
[0043] Taking a "desert" new energy base in a certain region as an example for analysis: Due to the significant fluctuations in wind and solar power, wind and solar data and load forecast data from typical days over twelve months are selected for calculation. The typical day wind and solar forecast curves and DC power transmission curves are shown below. Figures 2-5 As shown in Table 1, this embodiment uses the load curve of the mid-to-late stage of the life cycle to obtain the planning results to meet the needs of load growth. The conventional power parameters are shown in Table 1, the unit life is set to 20 years, and the discount rate is 0.08.
[0044] Table 1 Parameters of Conventional Units
[0045] This embodiment sets up two sets of calculation examples, as shown in Table 2.
[0046] Table 2 Example Settings
[0047] Table 3 shows the energy storage configuration results under different wind and solar power ratios. Comparing the results of Example 1 and Example 2, as the prediction error of new energy sources increases, i.e., more severe new energy scenarios emerge, the required energy storage scale increases to meet the requirements of new energy absorption rate, new energy power ratio, and peak supply guarantee capacity. In summary, the two-stage robust optimization model proposed in this invention can find the most unfavorable new energy handling scenarios for new energy absorption and peak power supply guarantee of the power system.
[0048] Table 3. Energy storage optimization configuration results under different new energy prediction errors
[0049] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A robust configuration method for electrochemical energy storage to support the transmission of energy from new energy bases, characterized in that, include: Based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, an objective function is constructed, and an energy storage optimization configuration model considering system operating costs and energy storage investment costs is established. Considering the DC channel capacity, the operating characteristics of energy storage equipment, and the uncertainty of new energy output, constraints are established for the energy storage optimization configuration model; The optimal configuration scheme of energy storage power and capacity is obtained by solving the energy storage optimization configuration model based on the nested column constraint generation algorithm.
2. The robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases as described in claim 1, characterized in that, The establishment of an energy storage optimization configuration model that considers system operating costs and energy storage investment costs, based on the objective function constructed from energy storage device configuration parameters, new energy power generation state variables, and conventional power supply operating state variables, includes: Based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, an objective function is constructed with the goal of minimizing the total system cost. The total system cost includes system operating costs and energy storage investment costs.
3. The robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases as described in claim 2, characterized in that, The method for constructing an objective function based on energy storage device configuration parameters, new energy power generation state variables, and conventional power supply operation state variables, and establishing an energy storage optimization configuration model that considers system operating costs and energy storage investment costs, also includes: The system operating cost is calculated through a multi-scenario operating cost model, which is generated based on clustering of typical daily operating scenarios and takes into account seasonal characteristics and weather types, covering system operating costs, carbon emission costs, and wind and solar curtailment penalty costs. Energy storage investment costs are calculated based on the total life cycle cost.
4. The robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases as described in claim 3, characterized in that, The constraints for establishing the energy storage optimization configuration model, taking into account DC channel capacity, energy storage device operating characteristics, and uncertainties in new energy output, include: Establish DC channel capacity constraints to limit the transmitted power from exceeding the transmission limit. Establish operational constraints for new energy bases to maintain system power balance. System power balance is related to conventional power output, actual new energy output, energy storage charging and discharging power, and DC power transmission.
5. A robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases, as described in claim 4, characterized in that... The constraints for establishing the energy storage optimization configuration model, taking into account DC channel capacity, energy storage device operating characteristics, and uncertainties in new energy output, also include: Establish operational constraints for energy storage devices to limit the range of charging and discharging power and the range of stored energy states, and ensure that charging and discharging states are mutually exclusive; Establish constraints on the uncertainty of new energy output, and model the output fluctuations by using a bounded set of uncertainties based on time uncertainty budgeting to control the degree of accumulation of uncertainty in the time dimension.
6. The robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases as described in claim 5, characterized in that, The nested column constraint generation algorithm is used to solve the energy storage optimization configuration model to obtain the optimal configuration scheme of energy storage power and capacity, including: The energy storage optimization configuration model is decomposed into a two-stage optimization problem, including the main problem of determining the energy storage configuration scheme and the sub-problem of simulating the worst operating scenario under a given configuration; The main problem and sub-problems are solved iteratively based on a nested column constraint generation algorithm.
7. A robust configuration method for electrochemical energy storage supporting the transmission of new energy from bases, as described in claim 6, characterized in that... The nested column constraint generation algorithm is used to solve the energy storage optimization configuration model to obtain the optimal configuration scheme of energy storage power and capacity, including: The iterative solution process includes: Initialize the energy storage configuration scheme; In the first iteration step, the master problem is solved to obtain the current energy storage configuration scheme and the lower bound of the total system cost; In the second iteration step, the current energy storage configuration is fixed, the sub-problems are solved, the worst-case scenario that makes the system operating cost the highest is found within the preset uncertain set of new energy output, and the corresponding upper bound of the total system cost is obtained. Add the worst-case scenario identified in the subproblem as a new constraint to the main problem; Repeat the first and second iteration steps until the difference between the upper and lower bounds of the total system cost satisfies the preset convergence condition. The energy storage configuration scheme obtained at this time is the optimal configuration scheme.
8. A robust electrochemical energy storage configuration system for supporting the transmission of new energy from bases, comprising the method described in any one of claims 1 to 7, characterized in that, include: The energy storage optimization configuration model construction module is used to construct an objective function based on the configuration parameters of energy storage devices, the state variables of new energy power generation, and the operating state variables of conventional power sources, and to establish an energy storage optimization configuration model that considers system operating costs and energy storage investment costs. An uncertainty constraint integration module is used to establish constraints for the energy storage optimization configuration model, taking into account the DC channel capacity, the operating characteristics of energy storage equipment, and the uncertainty of new energy output. The two-stage algorithm solution module is used to solve the energy storage optimization configuration model based on the nested column constraint generation algorithm to obtain the optimal configuration scheme of energy storage power and capacity.
9. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 7.