Active power distribution method and system for new energy and manganese-based energy storage system

Abstract

The invention discloses a new energy and manganese-based energy storage system active power distribution method and system, and belongs to the technical field of energy storage, and the method comprises the steps: building a primary frequency modulation model of a multi-type energy storage participation power grid system according to a lithium manganate battery-containing hybrid energy storage system; acquiring power grid frequency change of the hybrid energy storage system containing the lithium manganate battery based on the primary frequency modulation model; when the frequency change of the power grid exceeds a frequency modulation dead zone range, the lithium manganate battery participates in primary frequency modulation of the power grid, and droop control is started; the lithium manganate battery participates in primary frequency modulation of a power grid, and the method comprises the following steps: determining frequency modulation coefficients of equipment according to power grid frequency change and maximum power of the equipment; based on the frequency modulation coefficient, frequency modulation compensation power is calculated according to lithium manganate battery energy storage and flywheel energy storage SOC; and determining lithium manganate battery energy storage, flywheel energy storage and final frequency modulation power of the synchronous unit according to the frequency modulation compensation power. The method can improve the power grid stability.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy and energy storage grid-connected operation control, and specifically relates to a new energy and manganese-based energy storage system active power distribution method. Background Art

[0002] Manganese-based lithium-ion battery (Lithium Manganese Oxide Battery) is a lithium-ion battery that uses lithium manganese oxide (LiMn2O4) as the positive electrode material. This type of battery is widely used in electric vehicles, energy storage systems and other fields due to its high energy density, long cycle life and low self-discharge rate. Manganese-based lithium-ion batteries use manganese as the positive electrode material to replace the resource requirements of nickel and cobalt in traditional batteries, and have environmental and cost advantages. At present, the research and application of manganese-based lithium-ion batteries are constantly breaking through to achieve higher energy density and better performance.

[0003] At present, the control mode of new energy stations equipped with energy storage is unclear, and the technical requirements related to control are not clear. The new national standard revision has not yet involved the specific technical requirements after the configuration of energy storage in new energy stations. The control of new energy stations equipped with energy storage lacks technical basis and guiding principles, and its ability to support grid control as a flexible adjustment resource needs to be further explored. How to regulate and manage new energy stations equipped with energy storage requires a unified understanding, especially as energy transformation continues to advance, the physical form and operating characteristics of the power system change accordingly, and new energy stations have prominent problems such as voltage regulation and stability, frequency regulation and stability, short-circuit capacity and dynamic reactive power. It is necessary to study the control mode of new energy stations that takes into account stability under new scenarios. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a method and system for allocating active power between a new energy source and a manganese-based energy storage system. The method can guide the dynamic coordinated operation between the manganese-based energy storage system and the new energy power generation unit to achieve effective frequency regulation and stable operation of the power system.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: In a first aspect, the present invention provides a method for allocating active power of a new energy and manganese-based energy storage system, comprising: Obtain the state of charge of manganese-based lithium-ion batteries and the active output of new energy power generation units operating in MPPT mode; The real-time load reduction operation level of new energy is calculated based on the active output of the new energy power generation unit operating in the MPPT mode; The real-time load reduction operation level of new energy and the charge state of manganese-based lithium-ion batteries are used as input variables of the controller; the controller outputs the frequency regulation demand allocation coefficient based on the unit operation status and frequency regulation capacity according to the fuzzy logic rules of different frequency regulation scenarios; The frequency regulation demand allocation coefficient output by the controller is applied to the output control link of the new energy storage combined system, and participates in the frequency regulation of the dynamic coordinated operation of the manganese-based energy storage system and the new energy power generation.

[0006] As a further improvement of the present invention, the input variable of the controller is: the state of charge of the manganese-based lithium-ion battery SOC t , new energy power generation load reduction and reserve level x t ; Among them, the state of charge of manganese-based lithium-ion batteries SOC t Reflecting energy storage t The amount of electricity stored at any given moment; a function of the percentage of renewable energy generation left in reserve when load is reduced x t Reflects the power generation unit t The ability to participate in frequency regulation at all times is calculated as follows:

[0007] In the formula, Δ P R,t for t Frequency modulation requirements of the time system; c t Reserve level for load shedding of generating units; P m,t for t The power generation unit operates in the MPPT mode at all times.

[0008] As a further improvement of the present invention, the output variable of the controller is: frequency modulation demand allocation coefficient e t The frequency regulation demand allocation coefficient is dynamically determined by the controller and is used to determine the dynamic allocation of active demand between the power generation unit and the battery unit in the process of the joint system actively participating in the system frequency regulation; the frequency regulation power Δ borne by the power generation unit and the battery unit for frequency response P G,t and Δ P ES,t Dynamically determined by the frequency regulation demand allocation coefficient.

[0009] As a further improvement of the present invention, the real-time load reduction operation level of the new energy is calculated based on the active output of the new energy power generation unit operating in the MPPT mode, including:

[0010] Among them, Δ P G,t and Δ P ES,t They are t The change in active output of new energy generation and energy storage for frequency response at the moment, Δ P G,t and Δ P ES,t They are frequency modulation power for the power generation unit and the battery unit respectively.

[0011] As a further improvement of the present invention, the fuzzy logic rules of different frequency modulation scenarios include: Use fuzzy linguistic variables to describe the state of the input variables: VL means very low, L means low, M means medium, H means high, and VH means very high; The fuzzy logic reasoning rules in different frequency modulation scenarios are as follows: 1) When the system frequency f When it increases, the battery unit is in a charging state, and a lower SOC value means that the battery unit has a higher ability to store energy from the grid, and the power generation unit has a smaller degree of load reduction; When the SOC value is low and x t When it is higher, the frequency modulation demand allocation coefficient e The higher value will be taken; When the SOC value is high and x t When it is higher, the frequency modulation demand allocation coefficient e The lower value will be taken; When the SOC value is low and x t When the frequency modulation demand allocation coefficient is low, e The higher value will be taken; 2) When the system frequency f When it decreases, the battery unit is in a discharge state, and the power generation unit generates additional active power to support system frequency recovery; a higher SOC value means that the energy storage has sufficient power reserves to generate active power to the grid for frequency support; When the SOC value is high and x t When the frequency modulation demand allocation coefficient is low, e The higher value will be taken; When the SOC value is low and x t When it is higher, the frequency modulation demand allocation coefficient e The lower value will be taken; When the SOC value is low and x t When the frequency modulation demand allocation coefficient is low, eThe higher value will be taken.

[0012] As a further improvement of the present invention, when the system frequency f When it increases, the fuzzy logic reasoning rule is:

[0013] When the system frequency f When it is reduced, the fuzzy logic reasoning rule is:

[0014] In a second aspect, the present invention provides an active power distribution system for a new energy and manganese-based energy storage system, comprising: The energy storage device uses a manganese-based energy storage system controlled by an independent energy storage grid-connected inverter; The power generation unit generates electricity by converting mechanical energy into electrical energy; The controller is used to make decisions based on the fuzzy logic rules of different frequency regulation scenarios, and the joint system actively participates in the dynamic allocation of active power demand between the power generation unit and the battery unit during the system frequency regulation process. The input variables of the controller are: the charge state of the manganese-based lithium-ion battery and the reserve level of new energy power generation load reduction, and the output variable is: the frequency regulation demand allocation coefficient.

[0015] As a further improvement of the present invention, the input variable of the controller is: the state of charge of the manganese-based lithium-ion battery SOC t , new energy power generation load reduction and reserve level x t ; Among them, the state of charge of manganese-based lithium-ion batteries SOC t Reflecting energy storage t The amount of electricity stored at any given moment; a function of the percentage of renewable energy generation left in reserve when load is reduced x t Reflects the power generation unit t The ability to participate in frequency regulation at all times is calculated as follows:

[0016] In the formula, Δ P R,t for t Frequency modulation requirements of the time system; c t Reserve level for load shedding of generating units; P m,t for t The power generation unit operates in the MPPT mode at all times.

[0017] As a further improvement of the present invention, the output variable of the controller is: frequency modulation demand allocation coefficient e t ,The frequency regulation demand allocation coefficient is dynamically determined by the controller and is used to decide the dynamic allocation of active demand between the generation units and the battery units in the process of the joint system actively participating in the system frequency regulation.

[0018] As a further improvement of the present invention, the controller outputs a frequency modulation demand allocation coefficient based on the unit operation status and frequency modulation capability according to fuzzy logic rules of different frequency modulation scenarios; The fuzzy logic rules for different frequency modulation scenarios include: Use fuzzy linguistic variables to describe the state of the input variables: VL means very low, L means low, M means medium, H means high, and VH means very high; The fuzzy logic reasoning rules in different frequency modulation scenarios are as follows: 1) When the system frequency f When it increases, the battery unit is in a charging state, and a lower SOC value means that the battery unit has a higher ability to store energy from the grid, and the power generation unit has a smaller degree of load reduction; When the SOC value is low and x t When it is higher, the frequency modulation demand allocation coefficient e The higher value will be taken; When the SOC value is high and x t When it is higher, the frequency modulation demand allocation coefficient e The lower value will be taken; When the SOC value is low and x t When the frequency modulation demand allocation coefficient is low, e The higher value will be taken; 2) When the system frequency f When it decreases, the battery unit is in a discharge state, and the power generation unit generates additional active power to support system frequency recovery; a higher SOC value means that the energy storage has sufficient power reserves to generate active power to the grid for frequency support; When the SOC value is high and x t When the frequency modulation demand allocation coefficient is low, e The higher value will be taken; When the SOC value is low and x t When it is higher, the frequency modulation demand allocation coefficient e The lower value will be taken; When the SOC value is low and x t When the frequency modulation demand allocation coefficient is low, e The higher value will be taken.

[0019] As a further improvement of the present invention, when the system frequencyf When it increases, the fuzzy logic reasoning rule is:

[0020] When the system frequency f When it is reduced, the fuzzy logic reasoning rule is:

[0021] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the active power distribution method of the new energy and manganese-based energy storage system when executing the computer program.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for allocating active power of the new energy and manganese-based energy storage system is implemented.

[0023] In a fifth aspect, the present invention provides a computer program product, which includes computer instructions, and the computer instructions instruct a computer to execute the active power distribution method of the new energy and manganese-based energy storage system.

[0024] The beneficial effects of the present invention compared with the prior art are as follows: By obtaining the state of charge (SOC) of the manganese-based lithium-ion battery, which reflects the remaining power and charging state of the battery, the active output of the new energy power generation unit in the maximum power point tracking (MPPT) mode is obtained. The MPPT mode is designed to enable the power generation unit to output the maximum power under different environmental conditions. According to the active output of the new energy power generation unit in the MPPT mode, the real-time load reduction operation level of the new energy is calculated. This step is to appropriately restrict the power generation of new energy when necessary to ensure the stable operation of the power system and the effective use of energy storage equipment. The real-time load reduction operation level of the new energy and the state of charge of the manganese-based lithium-ion battery are used as input variables of the controller. The controller outputs the frequency regulation demand allocation coefficient based on the unit operation status and frequency regulation capacity according to the preset fuzzy logic rules, which take into account different frequency regulation scenarios and requirements. The frequency regulation demand allocation coefficient output by the controller is applied to the output control link of the new energy storage combined system. This method can guide the dynamic coordinated operation between the manganese-based energy storage system and the new energy power generation unit to achieve effective frequency regulation and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the embodiments of the present invention or the drawings of related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 It is a schematic diagram of frequency modulation dynamic allocation based on fuzzy logic algorithm; Figure 2 Schematic diagram of the membership function of input and output variables; (a) is the membership function of the input variable SOC; (b) is the membership function of the input variable x in the frequency increase scenario; (c) is the membership function of the input variable x in the frequency decrease scenario; (d) is the membership function of the output variable allocation coefficient; Figure 3 This is the structural diagram of the new energy storage combined system; Figure 4 It is the input-output relationship of fuzzy logic control when the system frequency decreases; Figure 5 It is a curve diagram of energy storage SOC value; Figure 6 It is the bar graph of total system power balance; Figure 7 Dynamic frequency curves of the system under different modes. DETAILED DESCRIPTION

[0027] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0028] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0029] New energy sources can provide frequency regulation services for large power grids through control, reduce frequency regulation pressure, and promote the grid to maintain frequency stability. Rapidly responsive battery energy storage systems are used in power systems with a high proportion of new energy, which can effectively reduce grid frequency fluctuations and improve the controllability and stability of large power grid frequencies. The participation of new energy sources such as wind power and photovoltaics in frequency regulation with manganese-based energy storage systems can improve the shortcomings of frequency regulation performance of traditional units alone and improve the stability of grid frequency.

[0030] In order to achieve dynamic coordination between a manganese-based energy storage system and new energy sources to meet frequency regulation requirements, the present invention provides a method for allocating active power between new energy sources and a manganese-based energy storage system, comprising: S1, obtaining the state of charge of the manganese-based lithium-ion battery and the active output of the new energy power generation unit operating in the MPPT mode; In the above scheme, by adjusting the load shedding level of the renewable energy generation unit and the output of the energy storage equipment in real time, the renewable energy storage combined system can more flexibly respond to the changing needs of the power system. The coordinated operation of manganese-based lithium-ion batteries and renewable energy generation units helps to smooth the volatility of renewable energy output and improve the safety and stability of the power grid.

[0031] S2, calculates the real-time load reduction operation level of the new energy source according to the active output of the new energy power generation unit operating in the MPPT mode; S3, takes the real-time load reduction operation level of new energy and the charge state of manganese-based lithium-ion batteries as input variables of the controller; the controller outputs the frequency regulation demand allocation coefficient based on the unit operation status and frequency regulation capacity according to the fuzzy logic rules of different frequency regulation scenarios; In the above scheme, the controller adopts fuzzy logic rules and can make intelligent decisions according to the needs of different frequency modulation scenarios, thereby improving the adaptability and robustness of the system.

[0032] S4, applying the frequency regulation demand allocation coefficient output by the controller to the output control link of the new energy storage combined system, and participating in the frequency regulation of the dynamic coordinated operation of the manganese-based energy storage system and the new energy power generation.

[0033] In the above scheme, the method can reasonably allocate active power, ensure that the energy storage device and the new energy power generation unit operate in the best state, thereby improving energy utilization efficiency. By reasonably controlling the charging and discharging process of the energy storage device, the occurrence of overcharging and overdischarging can be avoided, thereby extending the service life of the manganese-based lithium-ion battery.

[0034] The present invention is mainly based on the fuzzy logic algorithm frequency modulation demand dynamic allocation controller, the working principle of the controller is as follows: Firstly, by quantifying the real-time load-shedding operation level of new energy and the state of charge of manganese-based lithium-ion batteries as input variables of the controller, the controller can accurately reflect the real-time operation status of each unit in the manganese-based energy storage system and the new energy combined system; Secondly, based on the analysis of actual frequency regulation demand, fuzzy logic rules for different frequency regulation scenarios are designed to obtain the frequency regulation demand allocation coefficient based on the unit operation status and frequency regulation capacity; Finally, the controller is embedded in the joint system output control link to realize the dynamic coordinated operation of the manganese-based energy storage system and new energy power generation to participate in frequency regulation.

[0035] Under the dynamic allocation of frequency regulation demand of the present invention, the active reserve margin of renewable energy power generation and the limited capacity of the manganese-based energy storage system are fully utilized, thereby improving the economy of the combined system operation.

[0036] The schematic diagram of frequency modulation dynamic allocation based on fuzzy logic algorithm is as follows Figure 1 As shown. The real-time load reduction operation level of new energy and the charge state of manganese-based lithium-ion batteries are used as input variables of the controller; according to the actual frequency regulation demand analysis, fuzzy logic rules for different frequency regulation scenarios are designed to obtain the frequency regulation demand allocation coefficient of the operating state and frequency regulation capacity of the manganese-based energy storage system and new energy power generation unit in the joint system, so as to realize the dynamic coordinated operation of the manganese-based energy storage system and new energy power generation to participate in frequency regulation.

[0037] The input variables of the controller are: battery state of charge SOC t , new energy power generation load reduction and reserve level x t is the input variable of the controller.

[0038] Among them, the battery state of charge SOC t Reflecting energy storage t The amount of electricity stored at any given moment. Function of the percentage of reserve for renewable energy generation load shedding x t Reflects the power generation unit t The ability to participate in frequency regulation at all times is calculated as follows: (1) In the formula, Δ P R,t for t Frequency modulation requirements of the time system; c t Reserve level for load shedding of generating units; P m,t for t The power generation unit operates in the MPPT mode at all times.

[0039] The output variable of the controller is: The output is the frequency modulation demand allocation coefficient e t , the frequency modulation demand allocation coefficient is dynamically determined by the controller.

[0040] Frequency modulation demand allocation coefficient e t It can decide the dynamic allocation of active power demand between the power generation unit and the battery unit in the process of the joint system actively participating in the system frequency regulation. When the total frequency regulation demand of the joint system is certain, the frequency regulation power Δ P G,t and Δ P ES,t Dynamically determined by the frequency regulation demand allocation coefficient.

[0041] (2) Δ P G,t and Δ P ES,t for t The change in active power output of renewable energy generation and energy storage for frequency response at each moment. When the total active power frequency regulation demand of the joint system is constant, these two values ​​are given by e t Determined complementary relationship.

[0042] The fuzzy logic reasoning process of the controller first defines the membership function to describe the fuzzy variables. The control effect under the conditions of triangular and trapezoidal membership functions is more ideal, and the fuzzy segmentation of the input and output space can be performed. Therefore, triangular and trapezoidal membership functions are used to describe the fuzzy variables.

[0043] In order to achieve dynamic coordination between power generation units and battery units to meet the system frequency regulation requirements, a frequency regulation demand dynamic allocation controller based on fuzzy logic algorithm is designed to determine the frequency regulation requirements that power generation units and battery units in the combined system need to bear, thereby achieving coordinated operation of the wind energy-energy storage combined system.

[0044] Select triangle and trapezoid membership functions to perform fuzzy segmentation of input and output space and perform fuzzy logic control. The membership functions of input and output variables are as follows: Figure 2 shown.

[0045] For input variables SOC t and x t , define fuzzy linguistic variables to describe the state of the input variables: VL (very low); L (low); M (medium); H (high); VH (very high). For the output variable frequency modulation demand allocation coefficient e t, define its fuzzy linguistic variables to be the same as the input variables. Figure 1-2 (a) SOC When the value is lower than 0.1, the battery power is too low. In order to extend the battery life, the corresponding membership function value is VL, and the manganese-based energy storage system will stop its discharge process. When the energy storage rated capacity is constant after optimization, SOC can reflect the frequency response capability of energy storage.

[0046] Next, we introduce the fuzzy logic reasoning rules in different frequency modulation scenarios.

[0047] 1) f Fuzzy logic reasoning table when rising When the system frequency increases, the battery unit is in a charging state. A lower SOC value means that the battery unit has a higher ability to store energy from the power grid. At this time, the load reduction of the power generation unit can be smaller to improve the economy of system frequency regulation.

[0048] When the SOC value is low and x t When it is higher, the frequency modulation demand allocation coefficient e t A higher value will be taken, which means that the battery system will bear more frequency regulation requirements; When the SOC value is high and x t When it is higher, the frequency modulation demand allocation coefficient e t A lower value will be taken, which means that more frequency regulation demand will be borne by the power generation unit load shedding; When the SOC value is low and x t When it is lower, the frequency modulation demand allocation coefficient e t A higher value will be taken, indicating that the battery system will take priority in meeting the frequency regulation demand.

[0049] Table 1 Fuzzy logic reasoning table when frequency increases

[0050] 2) f Fuzzy logic reasoning table when reducing When the system frequency decreases, the battery unit is in a discharge state, and the power generation unit should increase active power to support the system frequency recovery. A higher SOC value means that the energy storage has sufficient power reserves to send active power to the grid for frequency support.

[0051] When the SOC value is high and x t When it is lower, the frequency modulation demand allocation coefficient e t A higher value will be taken, which means that more frequency regulation needs will be borne by energy storage; When the SOC value is low and x t When it is higher, the frequency modulation demand allocation coefficient e t A lower value will be taken, which means that more frequency regulation demand is borne by the power generation unit; When the SOC value is low and x t When it is lower, the frequency modulation demand allocation coefficient e t A higher value will be taken, indicating that energy storage will be given priority in meeting frequency regulation needs.

[0052] Table 2 Fuzzy logic reasoning table when frequency decreases

[0053] The second object of the present invention is to provide an active power distribution system for a new energy and manganese-based energy storage system, comprising: The energy storage device uses a manganese-based energy storage system controlled by an independent energy storage grid-connected inverter; The power generation unit generates electricity by converting mechanical energy into electrical energy; The controller is used to make decisions based on the fuzzy logic rules of different frequency regulation scenarios, and the joint system actively participates in the dynamic allocation of active power demand between the power generation unit and the battery unit during the system frequency regulation process. The input variables of the controller are: the charge state of the manganese-based lithium-ion battery and the reserve level of new energy power generation load reduction, and the output variable is: the frequency regulation demand allocation coefficient.

[0054] Furthermore, the frequency regulation demand dynamic allocation controller based on fuzzy logic algorithm of the present invention can meet the frequency regulation demand through dynamic power allocation between new energy power generation units and manganese-based energy storage systems. Based on the analysis of actual frequency regulation demand, fuzzy logic rules for different frequency regulation scenarios are designed to obtain the frequency regulation demand allocation coefficient based on the operating status and frequency regulation capacity of the power generation unit and battery unit.

[0055] As an example, the structure of the new energy storage combined system is shown in Figure 3. This embodiment takes the wind energy-energy storage combined system as an example, including an energy storage device, a power generation unit and an energy storage grid-connected inverter, as well as a designed controller. The SOC value of the energy storage device and the load reduction operation level of the power generation unit can dynamically reflect the operating status of the combined system. In the wind energy-energy storage combined system, the power generation unit generates electricity by converting the mechanical energy generated by the blades driven by wind energy into electrical energy; the energy storage unit is controlled by its independent energy storage grid-connected inverter, so the energy storage has the characteristic of quickly tracking power instructions.

[0056] The wind energy-energy storage combined system realizes the dynamic allocation of frequency regulation power demand between wind farms and energy storage units. Energy storage can absorb energy from the grid to maintain its own SOC level when the system frequency increases, and cooperate with the power generation unit to generate active power to participate in system frequency support when the frequency drops; the power generation unit can change the load reduction level to minimize the overall operating cost of the wind farm while meeting the system frequency regulation requirements.

[0057] Taking into account the economic impact of long-term load shedding of power generation units and the contradiction between energy storage investment costs and system frequency regulation requirements, dynamic allocation of frequency regulation power requirements can be achieved between wind farms and energy storage units within the combined system, allowing battery units with limited capacity to be coordinated with wind turbines.

[0058] In order to verify the economic and effectiveness of the optimal configuration of energy storage capacity and the coordinated control strategy in the wind energy-energy storage system to participate in frequency regulation control, a Figure 3 The wind energy-energy storage combined system shown in the figure has a wind farm output of 200MW, and is equipped with battery units for auxiliary frequency regulation to form a wind energy-energy storage combined system.

[0059] The wind farm is represented by an equivalent DFIG model, and a battery unit for auxiliary frequency regulation is configured to form a wind energy-energy storage system. The battery unit uses manganese-based lithium-ion batteries, which are very suitable for frequency regulation control due to their high cyclability, high ramp rate and short response time.

[0060] Construct a capacity optimization model and optimize the parameters in the model to calculate the unit energy cost of energy storage l v is the base value, l v The value is 5×10 5 $ / MWh, all cost parameters are normalized. The normalized values ​​of the variable parameters in the energy storage capacity optimization model are shown in Table 3.

[0061] Table 3 Variable parameters in the capacity optimization model

[0062] The energy storage capacity required for the system is optimized, and the optimal energy storage configuration scheme for the simulation system is obtained according to the energy storage capacity optimization model. The energy storage configuration required for the wind energy-energy storage combined system has a rated capacity of 28.92MWh and a rated power of 40MW.

[0063] This embodiment takes the system frequency reduction scenario as an example. When the system has continuous load changes, fuzzy logic control is performed in multiple time periods. According to the formulated fuzzy logic control rules, the fuzzy logic control input-output relationship is obtained as follows: Figure 4 shown.

[0064] Taking into account the volatility of actual wind speed, in order to simplify the analysis, the reserved reserve capacity of the power generation unit is set to 10% of the maximum output power under MPPT control, and the initial SOC value of the energy storage is set to 0.4. The change curve of the energy storage SOC value is shown in Figure 5 shown.

[0065] In the process of frequency regulation of wind power and energy storage combined system, the frequency regulation strategy of wind power and energy storage is determined according to the output of fuzzy logic controller, the output of power generation unit during load reduction operation and the charging and discharging power of energy storage system are determined. Figure 6 As shown in the figure, it can be seen from the simulation results that through the fuzzy logic control method, the active output of wind power and energy storage in the wind energy-energy storage combined system is coordinated in real time, and the response system frequency is stable.

[0066] Specifically, this embodiment selects the load level in one of the time periods and the results of the optimized allocation of active power output of wind power and energy storage to verify the control effect of the proposed dynamic optimization allocation strategy on the system dynamic frequency. It also compares the control effect of the system dynamic frequency in the case where the power generation unit does not use the assistance of the battery unit and the power generation unit adopts MPPT control without participating in the frequency mode, and the power generation unit adopts MPPT control without participating in the frequency but considers the participation of energy storage in the frequency modulation mode. The system dynamic frequency curves under different modes are shown in Figure 2. Figure 7 shown.

[0067] By comparing the system dynamic frequency curves under different control modes, the optimized allocation strategy considering the frequency regulation characteristics of wind power and energy storage is developed. Through the coordinated cooperation of wind power and energy storage, the power generation unit fully exploits its frequency regulation capability through load reduction and standby, and the lowest frequency point is 49.75Hz. When wind power adopts MPPT control mode without participating in frequency response and does not consider the auxiliary mode of energy storage frequency regulation, the dynamic frequency characteristics are the worst, and the lowest frequency point drops to 49.56Hz. After considering energy storage to participate in frequency regulation control, the lowest frequency point is 49.67Hz, and the frequency characteristics are improved, but compared with the wind-storage coordinated mode, the lowest frequency point differs by 0.08Hz. It can be seen that the optimized allocation strategy considering the frequency regulation characteristics of wind power and energy storage can obtain the optimal system dynamic frequency characteristics through the coordinated cooperation of wind power and energy storage.

[0068] The second object of the present invention is to provide an active power distribution system for a new energy and manganese-based energy storage system. Based on the above-mentioned active power distribution method for a new energy and manganese-based energy storage system, the system includes: Building a module for building a primary frequency regulation model of multi-type energy storage participating in the power grid system based on a hybrid energy storage system containing lithium manganese oxide batteries; An acquisition module, used for acquiring a grid frequency change of a hybrid energy storage system containing lithium manganese oxide batteries based on the primary frequency modulation model; The frequency modulation module is used for the lithium manganese oxide battery to participate in the primary frequency modulation of the power grid and start the droop control when the power grid frequency changes beyond the frequency modulation dead zone range; the lithium manganese oxide battery participates in the primary frequency modulation of the power grid, including: determining the frequency modulation coefficient of each device according to the power grid frequency change and the maximum power of each device; based on the frequency modulation coefficient, calculating the frequency modulation compensation power according to the lithium manganese oxide battery energy storage and the flywheel energy storage SOC; determining the final frequency modulation power of the lithium manganese oxide battery energy storage, the flywheel energy storage and the synchronous unit according to the frequency modulation compensation power.

[0069] The third object of the embodiment of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for allocating active power of new energy and manganese-based energy storage system when executing the computer program. It also includes a communication interface and a bus.

[0070] The fourth objective of an embodiment of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned new energy and manganese-based energy storage system active power distribution method is implemented.

[0071] A fifth objective of an embodiment of the present invention is to provide a computer program product, which includes computer instructions, and the computer instructions instruct a computer to execute the above-mentioned new energy and manganese-based energy storage system active power distribution method.

[0072] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure one A process or multiple processes and / or boxes Figure one A function specified in one or more boxes.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure one A process or multiple processes and / or boxes Figure one The steps for the functions specified in one or more boxes.

[0074] The present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, readable storage media, optical storage, etc.) containing computer-usable program codes.

[0075] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure one A process or multiple processes and / or boxes Figure one A device that provides the functions specified in a block or multiple blocks.

[0076] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for allocating active power of a new energy and manganese-based energy storage system, characterized in that: include: Obtain the state of charge of manganese-based lithium-ion batteries and the active output of new energy power generation units operating in MPPT mode; The real-time load reduction operation level of new energy is calculated based on the active output of the new energy power generation unit operating in the MPPT mode; The real-time load reduction operation level of new energy and the charge state of manganese-based lithium-ion batteries are used as input variables of the controller; the controller outputs the frequency regulation demand allocation coefficient based on the unit operation status and frequency regulation capacity according to the fuzzy logic rules of different frequency regulation scenarios; The frequency regulation demand allocation coefficient output by the controller is applied to the output control link of the new energy storage combined system, and participates in the frequency regulation of the dynamic coordinated operation of the manganese-based energy storage system and the new energy power generation.

2. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 1, characterized in that: The input variables of the controller are: the state of charge of the manganese-based lithium-ion battery SOC t , new energy power generation load reduction and reserve level χ t ; Among them, the state of charge of manganese-based lithium-ion batteries SOC t Reflecting energy storage t The amount of electricity stored at any given moment; a function of the percentage of renewable energy generation left in reserve when load is reduced χ t Reflects the power generation unit t The ability to participate in frequency regulation at all times is calculated as follows: In the formula, Δ P R,t for t Frequency modulation requirements of the time system; γ t Reserve level for load shedding of generating units; P m,t for t The power generation unit operates in the MPPT mode at all times.

3. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 1, characterized in that: The output variable of the controller is: frequency modulation demand allocation coefficient ε t The frequency regulation demand allocation coefficient is dynamically determined by the controller and is used to determine the dynamic allocation of active demand between the power generation unit and the battery unit in the process of the joint system actively participating in the system frequency regulation; the frequency regulation power Δ borne by the power generation unit and the battery unit for frequency response P G,t and Δ P ES,t Dynamically determined by the frequency regulation demand allocation coefficient.

4. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 2, characterized in that: The real-time load reduction operation level of new energy is calculated based on the active output of the new energy power generation unit operating in the MPPT mode, including: Among them, Δ P G,t and Δ P ES,t They are t The change in active output of new energy generation and energy storage for frequency response at the moment, Δ P G,t and Δ P ES,t They are frequency modulation power for the power generation unit and the battery unit respectively.

5. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 2, characterized in that: The fuzzy logic rules for different frequency modulation scenarios include: Use fuzzy linguistic variables to describe the state of the input variables: VL means very low, L means low, M means medium, H means high, and VH means very high; The fuzzy logic reasoning rules in different frequency modulation scenarios are as follows: 1) When the system frequency f When it increases, the battery unit is in a charging state, and a lower SOC value means that the battery unit has a higher ability to store energy from the grid, and the power generation unit has a smaller degree of load reduction; When the SOC value is low and χ t When it is higher, the frequency modulation demand allocation coefficient ε The higher value will be taken; When the SOC value is high and χ t When it is higher, the frequency modulation demand allocation coefficient ε The lower value will be taken; When the SOC value is low and χ t When the frequency modulation demand allocation coefficient is low, ε The higher value will be taken; 2) When the system frequency f When it decreases, the battery unit is in a discharge state, and the power generation unit generates additional active power to support system frequency recovery; a higher SOC value means that the energy storage has sufficient power reserves to generate active power to the grid for frequency support; When the SOC value is high and χ t When the frequency modulation demand allocation coefficient is low, ε The higher value will be taken; When the SOC value is low and χ t When it is higher, the frequency modulation demand allocation coefficient ε The lower value will be taken; When the SOC value is low and χ t When the frequency modulation demand allocation coefficient is low, ε The higher value will be taken.

6. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 5, characterized in that: When the system frequency f When it increases, the fuzzy logic reasoning rule is: When the system frequency f When it is reduced, the fuzzy logic reasoning rule is: Reasoning is performed based on fuzzy logic reasoning rules in different frequency modulation scenarios.

7. A new energy and manganese-based energy storage system active power distribution system, characterized in that: include: The energy storage device uses a manganese-based energy storage system controlled by an independent energy storage grid-connected inverter; The power generation unit generates electricity by converting mechanical energy into electrical energy; The controller is used to make decisions based on the fuzzy logic rules of different frequency regulation scenarios, and the joint system actively participates in the dynamic allocation of active power demand between the power generation unit and the battery unit during the system frequency regulation process. The input variables of the controller are: the charge state of the manganese-based lithium-ion battery and the reserve level of new energy power generation load reduction, and the output variable is: the frequency regulation demand allocation coefficient.

8. The active power distribution system of the new energy and manganese-based energy storage system according to claim 7 is characterized in that: The input variables of the controller are: the state of charge of the manganese-based lithium-ion battery SOC t , new energy power generation load reduction and reserve level χ t ; Among them, the state of charge of manganese-based lithium-ion batteries SOC t Reflecting energy storage t The amount of electricity stored at any given moment; a function of the percentage of renewable energy generation left in reserve when load is reduced χ t Reflects the power generation unit t The ability to participate in frequency regulation at all times is calculated as follows: In the formula, Δ P R,t for t Frequency modulation requirements of the time system; γ t Reserve level for load shedding of generating units; P m,t for t The power generation unit operates in the MPPT mode at all times.

9. The active power distribution system of the new energy and manganese-based energy storage system according to claim 7 is characterized in that: The output variable of the controller is: frequency modulation demand allocation coefficient ε t ,The frequency regulation demand allocation coefficient is dynamically determined by the controller and is used to decide the dynamic allocation of active demand between the generation units and the battery units in the process of the joint system actively participating in the system frequency regulation.

10. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 8, characterized in that: The controller outputs the frequency regulation demand allocation coefficient based on the unit operation status and frequency regulation capacity according to the fuzzy logic rules of different frequency regulation scenarios; The fuzzy logic rules for different frequency modulation scenarios include: Use fuzzy linguistic variables to describe the state of the input variables: VL means very low, L means low, M means medium, H means high, and VH means very high; The fuzzy logic reasoning rules in different frequency modulation scenarios are as follows: 1) When the system frequency f When it increases, the battery unit is in a charging state, and a lower SOC value means that the battery unit has a higher ability to store energy from the grid, and the power generation unit has a smaller degree of load reduction; When the SOC value is low and χ t When it is higher, the frequency modulation demand allocation coefficient ε The higher value will be taken; When the SOC value is high and χ t When it is higher, the frequency modulation demand allocation coefficient ε The lower value will be taken; When the SOC value is low and χ t When the frequency modulation demand allocation coefficient is low, ε The higher value will be taken; 2) When the system frequency f When it decreases, the battery unit is in a discharge state, and the power generation unit generates additional active power to support system frequency recovery; a higher SOC value means that the energy storage has sufficient power reserves to generate active power to the grid for frequency support; When the SOC value is high and χ t When the frequency modulation demand allocation coefficient is low, ε The higher value will be taken; When the SOC value is low and χ t When it is higher, the frequency modulation demand allocation coefficient ε The lower value will be taken; When the SOC value is low and χ t When the frequency modulation demand allocation coefficient is low, ε The higher value will be taken.

11. The method for allocating active power of a new energy and manganese-based energy storage system according to claim 10, characterized in that: When the system frequency f When it increases, the fuzzy logic reasoning rule is: When the system frequency f When it is reduced, the fuzzy logic reasoning rule is: Reasoning is performed based on fuzzy logic reasoning rules in different frequency modulation scenarios.

12. 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 active power distribution method of the new energy and manganese-based energy storage system when executing the computer program described in claims 1 to 6.

13. 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 active power distribution method of the new energy and manganese-based energy storage system described in claims 1 to 6 is implemented.

14. A computer program product, characterized in that The computer program product includes computer instructions, and the computer instructions instruct a computer to execute the active power distribution method of the new energy and manganese-based energy storage system described in claims 1 to 6.

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