Hybrid energy storage configuration method and system for manganese-based lithium ion battery

Abstract

The invention discloses a hybrid energy storage configuration method and system containing a manganese-based lithium ion battery, and belongs to the technical field of energy storage power station configuration.The method comprises the steps that electrical indexes and carbon emission indexes of all nodes of a power grid before the manganese-based lithium ion battery is installed for energy storage are calculated; performing weighted calculation on the electrical index and the carbon emission index to obtain a comprehensive index, and screening access nodes of the manganese-based lithium ion battery and lithium iron phosphate battery hybrid energy storage power station by adopting the comprehensive index; establishing a target function and a constraint condition by taking the minimum dispatching cost of power grid dispatching as a target, and substituting the access node of the manganese-based lithium ion battery and lithium iron phosphate battery hybrid energy storage power station into the target function and the constraint condition for solving to obtain an optimal configuration operation scheme of the manganese-based lithium ion battery and the lithium iron phosphate battery in the energy storage power station. According to the method, optimal schemes of a power type unit and an energy type unit in the power station are determined, and the optimal configuration method of the hybrid energy storage power station containing the manganese-based lithium ion battery is obtained.

Description

Technical Field

[0001] The invention belongs to the technical field of energy storage power station configuration, and particularly relates to a configuration method and system for a hybrid energy storage containing manganese-based lithium-ion batteries. Background Art

[0002] The development of energy storage technology plays a core and crucial role in building a smart grid and realizing renewable energy generation. With the rapid development of new energy, energy storage systems are an important part of the new energy industry. Manganese-based lithium-ion batteries are a new type of power energy storage unit with great potential in the application of power grid-side energy storage power stations. Studying their hybrid configuration scheme with traditional energy storage units will improve energy utilization efficiency and reduce operating costs.

[0003] Manganese-based lithium-ion batteries are power energy storage units with large instantaneous power but small stored energy, suitable for suppressing voltage fluctuations; lithium iron phosphate batteries are energy energy storage units with small instantaneous power but large stored energy, suitable for peak shaving and valley filling to reduce carbon emissions. During the construction of an energy storage power station, how to calculate and optimize the access location of the energy storage power station and the battery unit configuration scheme will enable the energy storage power station to better serve the new power system. The prior art does not give a specific configuration scheme. Summary of the Invention

[0004] In order to solve the problems existing in the prior art, the invention provides a configuration method and system for a hybrid energy storage containing manganese-based lithium-ion batteries. This method screens the energy storage access nodes through voltage sensitivity and node marginal carbon intensity; solves the minimum operating objective function of the power grid to determine the optimal scheme of the power type unit and energy type unit inside the power station, and obtains the optimal configuration method of the hybrid energy storage power station containing manganese-based lithium-ion batteries.

[0005] In order to solve the above technical problems, the technical solution adopted by the invention is as follows: In the first aspect, the invention provides a configuration method for a hybrid energy storage containing manganese-based lithium-ion batteries, including: Calculating the electrical indexes and carbon emission indexes of all nodes in the power grid before installing the manganese-based lithium-ion battery energy storage; Calculating the electrical indexes and carbon emission indexes by weighting to obtain a comprehensive index, and screening the access nodes of the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries by using the comprehensive index; Taking the minimum dispatching cost of power grid dispatching as the goal, establishing an objective function and constraint conditions, and substituting the access nodes of the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries into the objective function and constraint conditions for solution to obtain the optimal configuration operation scheme of the manganese-based lithium-ion batteries and lithium iron phosphate batteries in the energy storage power station.

[0006] As a further improvement of the invention, the calculation of the electrical indexes and carbon emission indexes of all nodes in the power grid before installing the manganese-based lithium-ion battery energy storage includes: Screen the historical typical daily operation data of the power grid before installing the manganese-based lithium-ion battery energy storage, calculate the power flow of the typical daily power grid, and calculate the carbon emission flow based on the power flow; Calculate the voltage sensitivity based on the power flow. Taking the influence degree of the node injection power on the overall voltage of the system as the electrical index, form the node voltage sensitivity matrix ; Calculate the node marginal carbon intensity based on the carbon emission flow. Taking the influence degree of the node injection power on the overall carbon emission intensity of the system as the carbon emission index, form the node marginal carbon intensity matrix 。

[0007] As a further improvement of the present invention, the node voltage sensitivity matrix Specifically:

[0008] In the formula is the partial derivative of the system voltage with respect to the node injection power, and the calculation formula is

[0009] In the formula: is all time periods within a day; is the number of all nodes in the power grid; is at time node voltage; is at time node injected active power; is at time node injected reactive power.

[0010] As a further improvement of the present invention, the node marginal carbon intensity matrix Specifically:

[0011] In the formula is the partial derivative of the system voltage with respect to the node injection power, and the calculation formula is

[0012] In the formula: is all time periods within a day; is the number of all nodes in the power grid; is at time node carbon emission intensity; is at time node injected active power; At moment the node injects reactive power.

[0013] As a further improvement of the present invention, the weighted calculation of electrical indicators and carbon emission indicators to obtain a comprehensive indicator, and the comprehensive indicator is used to screen the access nodes of the manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station, including: Comprehensive indicator is weighted by the node voltage sensitivity matrix and the node marginal carbon intensity matrix to obtain:

[0014] In the formula: is the weighting coefficient of voltage sensitivity, is the weighting coefficient of node marginal carbon intensity; Sort the comprehensive indicators of the hybrid energy storage power station and select the numbers corresponding to the top comprehensive indicators to determine the location nodes of the energy storage power stations to be built.

[0015] As a further improvement of the present invention, with the minimum dispatching cost of power grid dispatching as the goal, an objective function and constraint conditions are established, including: The power grid dispatching goal is the minimum dispatching cost, and the objective function is:

[0016] In the formula: is the power quality cost; is the energy storage power station cost; is the carbon emission cost; The constraint conditions include power grid topology constraint, power balance constraint, line power flow constraint and energy storage power station constraint.

[0017] As a further improvement of the present invention, in the objective function,

[0018] In the formula: is the node voltage deviation penalty coefficient; is the voltage of the th node at the time period; is the rated voltage of the th node at the time period;

[0019] In the formula: is the expected service life, is the investment discount factor, is the investment coefficient per unit capacity of the manganese-based lithium-ion battery, is the installed amount of manganese-based lithium-ion batteries in the is the investment coefficient per unit capacity of the manganese-based lithium-ion battery, is the installed amount of manganese-based lithium-ion batteries in the

[0020] In the formula: , , are respectively the coal consumption characteristic coefficients of the thermal power units; is the output power of the thermal power plant at time

[0021] As a further improvement of the present invention, the constraint conditions for the operation of the s-th energy storage power station are:

[0022]

[0023]

[0024] In the formula: is the power of the s-th energy storage power station at time is the maximum output power per unit of manganese-based lithium-ion battery; is the maximum output power per unit of lithium iron phosphate battery; is the s-th energy storage power station SOE at time is the maximum capacity per unit of manganese-based lithium-ion battery; is the maximum capacity per unit of lithium iron phosphate battery; , are respectively the charge and discharge efficiencies; , are respectively the charge and discharge powers of the s-th energy storage power station at time

[0025] In the second aspect, the present invention provides a hybrid energy storage configuration system containing manganese-based lithium-ion batteries, including: An index calculation module, used to calculate the electrical indexes and carbon emission indexes of all nodes of the power grid before installing the manganese-based lithium-ion battery energy storage; A weighted calculation module is used to calculate the electrical index and carbon emission index by weighting to obtain a comprehensive index, and the comprehensive index is used to screen the access nodes of the manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station; A configuration solution module is used to establish an objective function and constraint conditions with the minimum dispatching cost of power grid dispatching as the goal, and substitute the access nodes of the manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station into the objective function and constraint conditions for solution to obtain the optimal configuration operation plan of the manganese-based lithium-ion battery and lithium iron phosphate battery in the energy storage power station.

[0026] In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for configuring a hybrid energy storage system containing manganese-based lithium-ion batteries is implemented.

[0027] In a fourth aspect, the present invention provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for configuring a hybrid energy storage system containing manganese-based lithium-ion batteries is implemented.

[0028] In a fifth aspect, the present invention provides a computer program product. The computer program product includes computer instructions, and the computer instructions direct a computer to execute the method for configuring a hybrid energy storage system containing manganese-based lithium-ion batteries.

[0029] The beneficial effects of the present invention compared with the prior art are as follows: The present invention first calculates electrical indicators and carbon emission indicators. Specifically, it calculates the electrical indicators of all nodes in the power grid before installing the manganese-based lithium-ion battery energy storage, such as voltage sensitivity. The carbon emission indicator is calculated, that is, the nodal marginal carbon intensity. By calculating the electrical indicators and carbon emission indicators with weights, the nodes suitable for the access of the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries are screened out. Taking the minimum dispatching cost of power grid dispatching as the goal, the objective function and constraint conditions are established. The selected access nodes are brought into the objective function and constraint conditions for solution, and the optimal configuration operation plan of the manganese-based lithium-ion battery and the lithium iron phosphate battery in the energy storage power station is obtained. This method not only considers the electrical characteristics of the power grid, but also introduces the carbon emission indicator, so that it can comprehensively consider the electrical and carbon emission indicators, more comprehensively evaluate the access nodes of the energy storage power station, and ensure the rationality of the site selection. By solving the objective function and constraint conditions, the optimal configuration plan of the power type unit (such as manganese-based lithium-ion battery) and the energy type unit (such as lithium iron phosphate battery) inside the energy storage power station can be obtained, so as to improve the operation efficiency and economy of the energy storage power station. This method takes the minimum dispatching cost of power grid dispatching as the goal, helps to reduce the operation cost of the energy storage power station, and improves the overall benefit. By reasonably configuring the energy storage power station, the hybrid energy storage configuration method and system containing manganese-based lithium-ion batteries comprehensively consider the electrical characteristics of the power grid and the carbon emission indicator, and realize the optimal operation effect and the lowest operation cost of the energy storage power station by optimizing the energy storage configuration and reducing the dispatching cost. This method is of great significance for promoting the development of clean energy and improving the energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following introduces the related technical solution drawings in the embodiments of the present invention or the prior art. It should be understood that the drawings introduced below are only for clearly expressing some embodiments of the technical solutions in the present invention for the convenience of those skilled in the art. Without creative efforts, other drawings can also be obtained based on these drawings.

[0031] Figure 1 It is a flowchart of the hybrid energy storage configuration method containing manganese-based lithium-ion batteries of the present invention; Figure 2 It is a system diagram of a hybrid energy storage configuration containing manganese-based lithium-ion batteries provided by the present invention; Figure 3 It is a schematic diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation of the present invention. For the step numbers in the following embodiments, they are only set for the convenience of elaboration and explanation, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0033] In the description of the present invention, unless otherwise clearly defined, terms such as "set", "installed", and "connected" should be understood in a broad sense. Those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0034] The siting and power capacity configuration of an energy storage power station are the keys to energy storage construction. The present invention proposes a method and system for configuring a hybrid energy storage containing manganese-based lithium-ion batteries, which is used to determine the siting and power capacity configuration of a hybrid energy storage power station to ensure that the hybrid energy storage power station obtains the optimal operation effect and the lowest operation cost during system operation.

[0035] As Figure 1 shown, the first object of the present invention is to provide a method for configuring a hybrid energy storage containing manganese-based lithium-ion batteries, including the following steps: Step 1: Calculate the electrical indexes of all nodes in the power grid before installing the manganese-based lithium-ion battery energy storage: voltage sensitivity and carbon emission index: nodal marginal carbon intensity; Step 2: Calculate the electrical indexes and carbon emission indexes by weighting, and screen the nodes for connecting the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries; Step 3: Taking the minimum dispatching cost of the power grid dispatching as the goal, establish an objective function and constraint conditions, and substitute the nodes for connecting the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries into the objective function and constraint conditions for solution to obtain the optimal configuration operation plan of the manganese-based lithium-ion batteries and lithium iron phosphate batteries in the energy storage power station.

[0036] In the above solution, the energy storage access nodes are screened through voltage sensitivity and nodal marginal carbon intensity; the lowest operation objective function of the power grid is solved to determine the optimal plan of the power type unit and the energy type unit inside the power station. The optimal configuration method of the hybrid energy storage power station containing manganese-based lithium-ion batteries is obtained.

[0037] Furthermore, the present invention calculates the power flow and carbon emission flow in the same period according to the typical operation data of the power grid, screens the energy storage access nodes by calculating the electro-carbon sensitivity index; adopts a hybrid configuration of manganese-based lithium-ion batteries and lithium iron phosphate batteries in the energy storage power station, taking into account the requirements of suppressing power grid fluctuations and energy conservation and emission reduction.

[0038] The following describes each step of the present invention in detail with specific embodiments: Step 1: Calculate the electrical indicators of all nodes in the power grid before installing the manganese-based lithium-ion battery energy storage: voltage sensitivity, carbon emission indicator: nodal marginal carbon intensity; the specific steps are as follows: S11, Screen the historical typical daily operation data of the power grid before installing the manganese-based lithium-ion battery energy storage, calculate the power flow of the typical day power grid, and calculate the carbon emission flow based on the power flow at the same time.

[0039] S12, Calculate the voltage sensitivity based on the power flow, and use the influence degree of the nodal injection power on the overall system voltage as the electrical indicator to form a nodal voltage sensitivity matrix .

[0040]

[0041] In the formula is the partial derivative of the system voltage with respect to the nodal injection power, and the calculation formula is:

[0042] In the formula: is all time periods within a day; is the number of all nodes in the power grid; is at time nodal voltage; is at time nodal injected active power; is at time nodal injected reactive power.

[0043] S13, Calculate the nodal marginal carbon intensity based on the carbon emission flow, and use the influence degree of the nodal injection power on the overall system carbon emission intensity as the carbon emission indicator to form a nodal marginal carbon intensity matrix .

[0044]

[0045] In the formula is the partial derivative of the system voltage with respect to the nodal injection power, and the calculation formula is:

[0046] In the formula: is all time periods within a day; is the number of all nodes in the power grid; is at time nodal carbon emission intensity; At time the active power injected into the node; At time the reactive power injected into the node.

[0047] Step 2: Calculate the electrical index and carbon emission index by weighting, and screen the access nodes of the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries. The specific steps are as follows: S21, Comprehensive index From the node voltage sensitivity matrix and the node marginal carbon intensity matrix weighted to obtain:

[0048] In the formula: is the weighting coefficient of voltage sensitivity, is the weighting coefficient of node marginal carbon intensity; S22, If the number of energy storage power stations to be built is , sort the comprehensive indexes of the hybrid energy storage power station, select the numbers corresponding to the first comprehensive indexes to determine the selected nodes.

[0049] Step 3: Calculate the optimal capacity configuration scheme of manganese-based lithium-ion batteries and lithium iron phosphate batteries, which specifically includes the following steps: S31, The grid dispatching goal is the minimum dispatching cost, and the objective function is constructed as follows:

[0050] In the formula: is the power quality cost; is the energy storage power station cost; is the carbon emission cost.

[0051]

[0052] In the formula: is the node voltage deviation penalty coefficient; is the voltage of the th node at the time period; is the rated voltage of the th node at the

[0053]

[0054] In the formula: is the expected service life, is the investment discount factor, is the investment coefficient per unit capacity of the manganese-based lithium-ion battery, is the installed capacity of the manganese-based lithium-ion battery in the is the investment coefficient per unit capacity of the manganese-based lithium-ion battery, is the installed capacity of the manganese-based lithium-ion battery in the

[0055] In the formula: , , are the coal consumption characteristic coefficients of the thermal power unit respectively; is the output power of the th thermal power plant at time

[0056] S32, the constraint conditions include conventional constraints such as power grid topology constraints, power balance constraints, and line power flow constraints, and also include energy storage power station constraints. Specifically, the energy storage power station constraints are related to the configuration of manganese-based lithium-ion batteries and lithium iron phosphate batteries.

[0057] Specifically, the operation constraint of the s-th energy storage power station is

[0058]

[0059]

[0060] In the formula: is the power of the th energy storage power station in the time period; is the maximum output power per unit of manganese-based lithium-ion battery; is the maximum output power per unit of lithium iron phosphate battery; is the SOE of the th energy storage power station in the time period; , are the charge and discharge efficiencies respectively; , are the charge and discharge powers of the th energy storage power station in the

[0061] After the objective function and constraints are constructed, input data such as the power station connection nodes into the objective function and constraints for solution, and the optimal configuration operation plans of manganese-based lithium-ion batteries and lithium iron phosphate batteries in S energy storage power stations can be obtained.

[0062] As described above, the carbon emission intensity of the nodes near the new energy power station is low, but the node voltage is easily affected by the power fluctuation of the new energy power station, resulting in a large node voltage volatility and poor power quality. Through the method proposed in this application, more power-type energy storage units will be configured in the energy storage power station near the new energy power station to respond to the new energy fluctuation in a timely manner; for the nodes near the thermal power station with stable voltage and high power quality, but large node carbon emission intensity, through the method of this application, more energy-type energy storage units will be configured in the energy storage power station near the thermal power station to shave peaks and fill valleys and reduce the carbon emission intensity of the power grid.

[0063] As Figure 2 shown, the second object of the present invention is to provide a hybrid energy storage configuration system containing manganese-based lithium-ion batteries. Based on the above-mentioned hybrid energy storage configuration method of manganese-based lithium-ion batteries, the system includes: An index calculation module 100 for calculating the electrical indexes and carbon emission indexes of all nodes in the power grid before installing the manganese-based lithium-ion battery energy storage; A weighted calculation module 200 for weighted calculating the electrical indexes and carbon emission indexes to obtain a comprehensive index, and using the comprehensive index to screen the nodes for connecting the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries; A configuration solution module 300 for taking the minimum dispatching cost of the power grid dispatching as the goal, establishing an objective function and constraints, and bringing the nodes for connecting the hybrid energy storage power station of manganese-based lithium-ion batteries and lithium iron phosphate batteries into the objective function and constraints for solution to obtain the optimal configuration operation plans of manganese-based lithium-ion batteries and lithium iron phosphate batteries in the energy storage power station.

[0064] As Figure 3 shown, the third object of the embodiment of the present invention is to provide an electronic device, including a memory 701, a processor 702, and a computer program stored in the memory 701 and executable on the processor. When the processor executes the computer program, the above-mentioned hybrid energy storage configuration method of manganese-based lithium-ion batteries is implemented. It also includes a communication interface 703 and a bus 704.

[0065] The fourth object of the embodiment of the present invention is to provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned hybrid energy storage configuration method of manganese-based lithium-ion batteries is implemented.

[0066] The fifth object of the embodiments of the present invention is to provide a computer program product, which includes computer instructions that direct a computer to execute the above-described manganese-based lithium-ion battery hybrid energy storage configuration method.

[0067] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured article including an instruction device, and the instruction device implements the processes Figure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0068] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0069] The present invention can be in the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, readable storage media, optical memory, etc.) containing computer-usable program code.

[0070] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0071] Obviously, the described embodiments are only partial embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0072] Finally, 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 them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A hybrid energy storage configuration method for manganese-based lithium-ion batteries, characterized in that: include: Calculate the electrical and carbon emission indicators of all nodes in the power grid before installing manganese-based lithium-ion battery energy storage; The electrical index and carbon emission index are weighted to obtain the comprehensive index, and the comprehensive index is used to select the access nodes of manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station; Taking the minimum dispatching cost of power grid dispatching as the goal, the objective function and constraints are established, and the access nodes of the manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station are brought into the objective function and constraints to solve them, and the optimal configuration and operation plan of the manganese-based lithium-ion battery and lithium iron phosphate battery in the energy storage power station is obtained.

2. The method for configuring hybrid energy storage of manganese-based lithium-ion batteries according to claim 1, characterized in that: The calculation of electrical indicators and carbon emission indicators of all nodes in the power grid before installing manganese-based lithium-ion battery energy storage includes: Filter the historical typical daily operation data of the power grid before installing manganese-based lithium-ion battery energy storage, calculate the typical daily power flow of the power grid, and calculate the carbon emission flow based on the power flow; The voltage sensitivity is calculated based on the power flow, and the influence of the node injection power on the overall system voltage is used as the electrical index to form a node voltage sensitivity matrix ; The node marginal carbon intensity is calculated based on the carbon emission trend, and the influence of the node injection power on the overall carbon emission intensity of the system is used as the carbon emission index to form the node marginal carbon intensity matrix .

3. The hybrid energy storage configuration method of manganese-based lithium-ion batteries according to claim 2, characterized in that: The node voltage sensitivity matrix Specifically: In the formula is the system voltage to node The partial derivative of the injected power is given by Where: For all periods of the day; is the number of all nodes in the power grid; for time Node voltage; for time The node injects active power; for time The node injects reactive power.

4. The hybrid energy storage configuration method of manganese-based lithium-ion batteries according to claim 2, characterized in that: The node marginal carbon intensity matrix Specifically: In the formula is the system voltage to node The partial derivative of the injected power is given by Where: For all periods of the day; is the number of all nodes in the power grid; for time Node carbon emission intensity; for time The node injects active power; for time The node injects reactive power.

5. The hybrid energy storage configuration method of manganese-based lithium-ion batteries according to claim 2, characterized in that: The weighted calculation of electrical indicators and carbon emission indicators obtains comprehensive indicators, and the comprehensive indicators are used to screen access nodes of manganese-based lithium-ion batteries and lithium iron phosphate battery hybrid energy storage power stations, including: Comprehensive indicators From the node voltage sensitivity matrix and the node marginal carbon intensity matrix Weighted to get: Where: is the weighting coefficient of voltage sensitivity, is the weighting coefficient of the marginal carbon intensity of the node; The comprehensive indicators of hybrid energy storage power stations Sort, Select Before The number corresponding to the comprehensive indicator is determined The site selection node for the energy storage power station to be built.

6. The method for configuring hybrid energy storage of manganese-based lithium-ion batteries according to claim 1, characterized in that: The objective function and constraint conditions are established with the minimum dispatching cost of power grid dispatching as the goal, including: The grid dispatching goal is the minimum dispatching cost, so the objective function is: Where: is the power quality cost; The cost of the energy storage power station; for the cost of carbon emissions; The constraints include grid topology constraints, power balance constraints, line flow constraints and energy storage power station constraints.

7. The method for configuring hybrid energy storage of manganese-based lithium-ion batteries according to claim 6, characterized in that: In the objective function, Where: is the node voltage deviation penalty coefficient; for Time period Node voltage; for Time period Node voltage rating; Where: is the expected useful life, is the investment discount factor, is the unit capacity investment coefficient of manganese-based lithium-ion batteries, For the The number of manganese-based lithium-ion batteries installed in energy storage power stations; is the unit capacity investment coefficient of manganese-based lithium-ion batteries, For the The number of manganese-based lithium-ion batteries installed in energy storage power stations; Where: , , are the coal consumption characteristic coefficients of thermal power units; For the Thermal power plants Output power at all times.

8. The method for configuring hybrid energy storage of manganese-based lithium-ion batteries according to claim 6, characterized in that: The constraints for the operation of the sth energy storage power station are: Where: For the Energy storage power stations Power during the period; is the maximum output power of a unit manganese-based lithium-ion battery; is the maximum output power of the unit lithium iron phosphate battery; For the Energy storage power stations Time period SOE; is the maximum capacity of a unit manganese-based lithium-ion battery; The maximum capacity of a unit lithium iron phosphate battery; , are charge and discharge efficiency respectively; , They are Energy storage power stations The charging and discharging power during the time period.

9. A method for configuring a hybrid energy storage system of a manganese-based lithium-ion battery, characterized in that: include: Index calculation module, used to calculate the electrical index and carbon emission index of all nodes in the power grid before installing manganese-based lithium-ion battery energy storage; The weighted calculation module is used to weight the electrical index and carbon emission index to obtain the comprehensive index, and use the comprehensive index to screen the access nodes of the manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station; The configuration solving module is used to establish the objective function and constraints with the minimum dispatching cost of the power grid dispatching as the goal, bring the access nodes of the manganese-based lithium-ion battery and lithium iron phosphate battery hybrid energy storage power station into the objective function and constraint conditions for solving, and obtain the optimal configuration operation plan of the manganese-based lithium-ion battery and lithium iron phosphate battery in the energy storage power station.

10. An electronic device, characterized in that: It comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the hybrid energy storage configuration method of manganese-based lithium-ion batteries when executing the computer program described in claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the manganese-based lithium-ion battery hybrid energy storage configuration method described in claims 1 to 8 is implemented.

12. A computer program product, characterized in that The computer program product includes computer instructions, which instruct a computer to execute the manganese-based lithium-ion battery hybrid energy storage configuration method described in claims 1 to 8.

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