Multi-type energy storage coordination control method and system on new energy power station side

Abstract

The application discloses a new energy power station side multi-type energy storage coordinated control method and system, an energy storage system is configured in a new energy power station, an application mode of the energy storage system includes a first application mode and a second application mode, the energy storage system includes a power type energy storage system and a battery energy storage system; energy storage power demands in various application modes are calculated in parallel; the energy storage total power demand is calculated and coordinately distributed according to the energy storage power demands in various application modes, and the power type energy storage system and the battery energy storage system are controlled to charge and discharge under the constraint of the safe and stable operation boundary of the energy storage system. The application can realize that the multi-type energy storage system efficiently meets the energy storage demand in the complex process of reducing the abandoned power rate + compensating the power prediction error demand for 24 hours, inertia support and random high-frequency occurrence of primary frequency modulation demand.

Description

Technical Field

[0001] This invention belongs to the field of electrical engineering technology, specifically relating to a multi-type energy storage coordinated control method and system for new energy power plants. Background Technology

[0002] The development of new energy sources is rapid, and a high-proportion new energy power system is about to be formed. However, due to the volatility and intermittency of wind and solar power, and the use of power electronic equipment for grid connection, the problem of power curtailment is prominent in terms of power absorption. Furthermore, the development of new energy as the main power source will severely degrade the system's frequency characteristics and safety and stability. Looking to the future, the absorption and safe operation of a high-proportion new energy power system will face severe challenges. The current situation of relying solely on conventional energy for regulation urgently needs to be changed. New energy should have the ability to actively support the system and share the responsibility and obligation for the safe and stable operation of the system with conventional energy sources.

[0003] Energy storage features energy time-shifting, rapid response, and flexible deployment. Applying energy storage in new energy power plants can improve the adjustability and controllability of the power plants, increase the confidence capacity of new energy power plants, and provide a power source for the active support of new energy power plants. It can effectively solve problems such as large fluctuations in new energy output and insufficient participation in grid regulation. It is an important technical means to improve the absorption of new energy and solve the problem of insufficient active support capacity of new energy.

[0004] Currently, the application requirements of new energy power plants for energy storage mainly include four application modes: inertia support, primary frequency regulation, compensation for power prediction errors, and reduction of curtailment rate. These four application modes have overlapping and coupled technical requirements for energy storage in terms of time sequence. In addition, considering that the charge and discharge cycle number of battery energy storage systems is relatively limited, how to achieve the same energy storage system to take into account the four application scenarios through multiple types of energy storage is an urgent problem to be solved.

[0005] Existing technologies include coordinated control methods for energy storage systems in new energy power plants, which are applied in the mode of compensating for power prediction errors and reducing curtailment rates, and coordinated control methods for energy storage systems in new energy power plants, which are applied in the mode of improving the inertia support and primary frequency regulation capabilities of new energy power plants. However, there is no coordinated control method for multiple types of energy storage systems in new energy power plants that takes into account the four application modes of compensating for power prediction errors, reducing curtailment rates, inertia support, and primary frequency regulation. Summary of the Invention

[0006] The purpose of this invention is to provide a multi-type energy storage coordinated control method and system for new energy power plants to overcome the defects of existing technologies. This invention can enable multi-type energy storage systems to efficiently meet the energy storage needs of complex processes such as reducing curtailment rate and compensating for power prediction errors 24 hours a day, inertia support, and random high-frequency occurrence of primary frequency regulation requirements.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] Multi-type energy storage coordinated control methods on the new energy power plant side include:

[0009] In a new energy power plant, an energy storage system is configured. The application modes of the energy storage system include a first application mode and a second application mode. The energy storage system includes a power-type energy storage system and a battery energy storage system.

[0010] Parallel calculation of energy storage power requirements under various application modes;

[0011] The total energy storage power demand is calculated and coordinated based on the energy storage power demand under various application modes, and the charging and discharging of power-type energy storage systems and battery energy storage systems are controlled under the constraints of the safe and stable operation boundary of the energy storage system.

[0012] Furthermore, the parallel calculation of energy storage power requirements under each application mode specifically includes: calculating the energy storage power requirements under the first application mode and calculating the energy storage power requirements under the second application mode.

[0013] The first application mode is the inertia support and primary frequency regulation application mode, and the second application mode is the power curtailment rate reduction and power prediction error compensation application mode.

[0014] Furthermore, the calculation of the energy storage power requirement under the first application mode specifically involves:

[0015] The real-time frequency f of the energy storage system is collected at a preset first sampling time interval. t ;

[0016] Based on the real-time frequency f of the energy storage system t Calculate the real-time frequency deviation Δf of the energy storage system. t =f t -50 and real-time frequency volatility

[0017] Determine the real-time frequency deviation Δf t Has the frequency dead zone been exceeded? d ;

[0018] If it exceeds this range, then it is based on the real-time frequency f of the energy storage system. t Calculate the droop coefficient ξ of the energy storage system configured in the new energy power plant participating in the primary frequency regulation of the power grid. t ;

[0019]

[0020] And it satisfies the following constraints:

[0021] -0.1≤ξ t≤0.1

[0022] when And ξ t When ξ > 0, it is corrected to: ξ t =0;

[0023] In the formula, f t f is the real-time frequency of the energy storage system. N f represents the power grid frequency. d This indicates the primary frequency regulation dead zone of the new energy power plant, and δ% represents the primary frequency regulation droop rate. This represents the actual output power of the new energy power station at time t. This indicates the installed capacity of new energy power plants;

[0024] Based on ξ t Calculate the power demand of the energy storage system for the first application mode. When the power command of the energy storage system is negative, the energy storage system charges; when the power command of the energy storage system is positive, the energy storage system discharges.

[0025]

[0026] In the formula, This represents the energy storage power demand under the first application mode at time t;

[0027] If not crossed, then based on Calculate the real-time power grid inertia support requirements:

[0028]

[0029] In the formula, K represents the demand supported by the power grid's inertia at time t. 惯性 This represents the virtual inertia coefficient by which the energy storage system participates in inertia support.

[0030] Furthermore, the calculation of the energy storage power requirement under the second application mode specifically involves:

[0031] Obtain day-ahead power forecast data samples of new energy power plants and dispatched power curtailment data;

[0032] Real-time acquisition of power generation data from new energy power plants at a preset second sampling time interval.

[0033] Real-time acquisition of SOC value of battery energy storage system

[0034] Determine if the current time is a period of power rationing; if so, calculate the power demand of the energy storage system at the current time. If not, then calculate the power prediction error of the new energy power plant in real time.

[0035] Determine the range of power prediction error values, if If true, then determine the real-time SOC value of the battery energy storage system. Establishment, calculation of energy storage power demand under the second application mode. if This is not valid; calculate the energy storage power demand under the second application mode.

[0036] if If this is not the case, then the power prediction error range is checked again. If true, then determine the real-time SOC value of the battery energy storage system. Established, it executes maximum charging, realizes SOC callback of the battery energy storage system, and calculates the energy storage power requirement as follows: if This is not true; the calculated energy storage power requirement is...

[0037] if This is not true; the calculated energy storage power requirement is...

[0038] in, This represents the power prediction error of the new energy power plant at time t. This represents the energy storage power demand under the second application mode at time t. This represents the upper limit of the output of the renewable energy power plant at time t within the power rationing period issued by the dispatch center. This represents the actual output power of the new energy power station at time t. Let α represent the predicted output power of the renewable energy power plant at time t, and let α represent the allowable error bandwidth for the power prediction of the renewable energy power plant. This represents the SOC value of the battery energy storage system at time t. This indicates the installed capacity of new energy power plants.

[0039] Furthermore, the calculation and coordinated allocation of the real-time total energy storage power demand based on the energy storage power demand under various application modes specifically includes:

[0040] Real-time input of energy storage power demand in the first application mode And the energy storage power demand fed back in the second application mode

[0041] Using the first sampling time interval of the first application mode as the calculation time interval for the total power demand, the total energy storage power demand that takes into account multiple modes is calculated in real time.

[0042] A frequency domain decomposition algorithm is used to decompose the total power demand of energy storage into high-frequency power commands and low-frequency power commands. The low-frequency power command is then used as the power command for the battery energy storage system. High-frequency power commands are used as the power commands for power-type energy storage systems.

[0043] judge Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed to step A1; simultaneously determine... Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed to step A2.

[0044] Step A1: Determine Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed directly to step B1.

[0045] Step A2: Determine Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed directly to step B2.

[0046] Step B1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails to function, proceed to step C1.

[0047] Step B2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, proceed to step C2.

[0048] Step C1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails, directly issue a power command. For battery energy storage systems;

[0049] Step C2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, a power command is directly issued. Power-type energy storage systems;

[0050] in, This is expressed as the SOC value of the battery energy storage system at time t+1. This is expressed as the SOC value of the power-type energy storage system at time t+1. This indicates the upper limit of the SOC (State of Charge) of the battery energy storage system. This indicates the lower limit of the State of Charge (SOC) of the battery energy storage system. This indicates the upper limit of the State of Charge (SOC) of a power-type energy storage system. This indicates the lower limit of the State of Charge (SOC) of the power energy storage system.

[0051] A multi-type energy storage coordinated control system for new energy power plants includes:

[0052] Energy storage system configuration module: used to configure energy storage systems in new energy power plants. The application modes of the energy storage system include a first application mode and a second application mode. The energy storage system includes a power-type energy storage system and a battery energy storage system.

[0053] Energy storage power demand calculation module: used to calculate the energy storage power demand in parallel under various application modes;

[0054] Coordination and control module: It is used to calculate and coordinate the total energy storage power demand based on the energy storage power demand under various application modes, and control the charging and discharging of power-type energy storage system and battery energy storage system under the constraints of the safe and stable operation boundary of energy storage system.

[0055] Furthermore, the energy storage power demand calculation module includes a first calculation module and a second calculation module, wherein:

[0056] First calculation module: used to calculate the energy storage power requirement under the first application mode;

[0057] Second calculation module: used to calculate the energy storage power demand in the second application mode;

[0058] The first application mode is the inertia support and primary frequency regulation application mode, and the second application mode is the power curtailment rate reduction and power prediction error compensation application mode.

[0059] Furthermore, the implementation process of the first computing module is as follows:

[0060] The real-time frequency f of the energy storage system is collected at a preset first sampling time interval. t ;

[0061] Based on the real-time frequency f of the energy storage system t Calculate the real-time frequency deviation Δf of the energy storage system. t =f t -50 and real-time frequency volatility

[0062] Determine the real-time frequency deviation Δf t Has the frequency dead zone been exceeded? d ;

[0063] If it exceeds this range, then it is based on the real-time frequency f of the energy storage system. t Calculate the droop coefficient ξ of the energy storage system configured in the new energy power plant participating in the primary frequency regulation of the power grid. t ;

[0064]

[0065] And it satisfies the following constraints:

[0066] -0.1≤ξ t ≤0.1

[0067] when And ξ t When ξ > 0, it is corrected to: ξ t =0;

[0068] In the formula, f t f is the real-time frequency of the energy storage system. N f represents the power grid frequency. d This indicates the primary frequency regulation dead zone of the new energy power plant, and δ% represents the primary frequency regulation droop rate. This represents the actual output power of the new energy power station at time t. This indicates the installed capacity of new energy power plants;

[0069] Based on ξ t Calculate the power demand of the energy storage system for the first application mode. When the power command of the energy storage system is negative, the energy storage system charges; when the power command of the energy storage system is positive, the energy storage system discharges.

[0070]

[0071] In the formula, This represents the energy storage power demand under the first application mode at time t;

[0072] If not crossed, then based on Calculate the real-time power grid inertia support requirements:

[0073]

[0074] In the formula, K represents the demand supported by the power grid's inertia at time t. 惯性 This represents the virtual inertia coefficient by which the energy storage system participates in inertia support.

[0075] Furthermore, the implementation process of the second calculation module is as follows:

[0076] Obtain day-ahead power forecast data samples of new energy power plants and dispatched power curtailment data;

[0077] Real-time acquisition of power generation data from new energy power plants at a preset second sampling time interval.

[0078] Real-time acquisition of SOC value of battery energy storage system

[0079] Determine if the current time is a period of power rationing; if so, calculate the power demand of the energy storage system at the current time. If not, then calculate the power prediction error of the new energy power plant in real time.

[0080] Determine the range of power prediction error values, if If true, then determine the real-time SOC value of the battery energy storage system. Establishment, calculation of energy storage power demand under the second application mode. if This is not valid; calculate the energy storage power demand under the second application mode.

[0081] if If this is not the case, then the power prediction error range is checked again. If true, then determine the real-time SOC value of the battery energy storage system. Established, it executes maximum charging, realizes SOC callback of the battery energy storage system, and calculates the energy storage power requirement as follows: if This is not true; the calculated energy storage power requirement is...

[0082] if This is not true; the calculated energy storage power requirement is...

[0083] in, This represents the power prediction error of the new energy power plant at time t. This represents the energy storage power demand under the second application mode at time t. This represents the upper limit of the output of the renewable energy power plant at time t within the power rationing period issued by the dispatch center. This represents the actual output power of the new energy power station at time t. Let α represent the predicted output power of the renewable energy power plant at time t, and let α represent the allowable error bandwidth for the power prediction of the renewable energy power plant. This represents the SOC value of the battery energy storage system at time t. This indicates the installed capacity of new energy power plants.

[0084] Furthermore, the coordination control module is implemented as follows:

[0085] Real-time input of energy storage power demand in the first application mode And the energy storage power demand fed back in the second application mode

[0086] Using the first sampling time interval of the first application mode as the calculation time interval for the total power demand, the total energy storage power demand that takes into account multiple modes is calculated in real time.

[0087] A frequency domain decomposition algorithm is used to decompose the total power demand of energy storage into high-frequency power commands and low-frequency power commands. The low-frequency power command is then used as the power command for the battery energy storage system. High-frequency power commands are used as the power commands for power-type energy storage systems.

[0088] judge Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed to step A1; simultaneously determine... Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed to step A2.

[0089] Step A1: Determine Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed directly to step B1.

[0090] Step A2: Determine Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed directly to step B2.

[0091] Step B1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails to function, proceed to step C1.

[0092] Step B2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, proceed to step C2.

[0093] Step C1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails, directly issue a power command. For battery energy storage systems;

[0094] Step C2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, a power command is directly issued. Power-type energy storage systems;

[0095] in, This is expressed as the SOC value of the battery energy storage system at time t+1. This is expressed as the SOC value of the power-type energy storage system at time t+1. This indicates the upper limit of the SOC (State of Charge) of the battery energy storage system. This indicates the lower limit of the State of Charge (SOC) of the battery energy storage system. This indicates the upper limit of the State of Charge (SOC) of a power-type energy storage system. This indicates the lower limit of the State of Charge (SOC) of the power energy storage system.

[0096] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the multi-type energy storage coordinated control method on the side of the new energy power station.

[0097] Compared with the prior art, the present invention has the following beneficial technical effects:

[0098] This invention is applicable to the coordinated control of multiple types of energy storage at new energy power plants. In this scenario, it is necessary to consider four application modes: inertia support, primary frequency regulation, power prediction error compensation, and reduction of curtailment rate. This invention combines inertia support and primary frequency regulation into the first application mode, and combines reduction of curtailment rate and power prediction error compensation into the second application mode. By simultaneously calculating and superimposing the energy storage power demand under different application modes, the total energy storage power demand of multiple types of energy storage systems is obtained. Under the constraints of the safe and stable operation boundary of the energy storage system, the energy storage system is coordinated and allocated, and the charging and discharging of power-type energy storage systems and battery energy storage systems are controlled. This enables multiple types of energy storage systems to efficiently meet the energy storage demand during the complex process of continuous 24-hour reduction of curtailment rate and power prediction error compensation, and random occurrence of inertia support and primary frequency regulation demand.

[0099] Furthermore, this invention first considers the differences in sample data based on different modes, the consistency in technical principles, and the combination and overlap in timing. It merges the inertia support and primary frequency regulation modes, and the power prediction error compensation and curtailment reduction modes. By parallel calculation of the energy storage power demand of the two merged modes and feeding it back to the main program, the energy storage demand of the two modes is superimposed in real time in the main program. Considering the characteristics of battery energy storage systems, which have long energy storage time but few cycles, a frequency decomposition algorithm is used to allocate the high-frequency part of the total power demand of the energy storage system to the power-type energy storage system and the low-frequency part to the battery energy storage system. The power commands of the power-type energy storage system and the battery energy storage system are checked and corrected under the constraints of rated charge and discharge power capacity and SOC operating range of the power-type energy storage system and the battery energy storage system, respectively. The charging and discharging of the power-type energy storage system and the battery energy storage system are controlled. Finally, multiple types of energy storage systems can efficiently meet the energy storage demand in the complex process of reducing curtailment rate and compensating for power prediction error for 24 hours, while the inertia support and primary frequency regulation demand appear randomly. Attached Figure Description

[0100] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0101] Figure 1 This is a schematic diagram illustrating the coupling and crossover process of multiple application modes of energy storage systems in new energy power plants;

[0102] Figure 2 A schematic diagram illustrating the charging and discharging power requirements of energy storage systems in new energy power plants under multiple application modes;

[0103] Figure 3 A schematic diagram of the droop curve for configuring energy storage systems in new energy power plants to participate in the primary frequency regulation of the power grid;

[0104] Figure 4 Flowchart for inertia support and primary frequency modulation control;

[0105] Figure 5 Flowchart for reducing power curtailment rate and compensating for power prediction error control;

[0106] Figure 6 To control the main program flowchart. Detailed Implementation

[0107] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0108] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0109] This invention aims to balance improving power grid absorption with actively supporting the power grid. It involves configuring energy storage systems in renewable energy power plants. The application modes of these energy storage systems include reducing curtailment rates, compensating for power prediction errors, providing inertia support, and primary frequency regulation. In balancing these multiple application modes, the energy storage system will face a complex process: continuously reducing curtailment rates and compensating for power prediction errors 24 hours a day, while simultaneously providing inertia support and primary frequency regulation, which occur randomly. Figure 1 As shown, it is necessary to achieve real-time dynamic response to the energy storage requirements that are coupled and cross-cutting under multiple application modes.

[0110] The charging and discharging power requirements of various application modes for different types of energy storage systems are calculated based on different real-time data, and these data sampling intervals are also different, such as... Figure 2 As shown.

[0111] against Figure 2 The following explanation is provided:

[0112] (1) Multiple application modes include: “Reducing curtailment rate” application mode, “Compensating for power prediction error” application mode, “Inertia support” application mode, and “Primary frequency regulation” application mode.

[0113] (2) In the "inertia support" application mode and the "primary frequency regulation" application mode, the power demand calculation of the energy storage system needs to be based on the real-time frequency data of the power grid, and the sampling interval of the real-time frequency data is no more than 100ms. Moreover, in terms of technical principle, the "inertia support" application mode and the "primary frequency regulation" application mode have non-overlapping and temporal continuity, so they are merged into the "inertia support + primary frequency regulation" application mode, which is defined as the first application mode in this invention.

[0114] In both the "Reducing Curtailment Rate" and "Compensating for Power Prediction Errors" application modes, the power demand calculation of the energy storage system requires real-time power data from renewable energy power plants, day-ahead power prediction data from renewable energy power plants, and power curtailment data issued by the dispatch center for renewable energy power plants. This data is sampled in real-time at 1-minute intervals. Furthermore, during periods when renewable energy power plant output is restricted, the power prediction accuracy of the renewable energy power plants is not assessed. Therefore, the "Reducing Curtailment Rate" and "Compensating for Power Prediction Errors" application modes do not overlap in time. Since both modes operate on a daily cycle, their combined duration is 24 hours, demonstrating temporal continuity. Therefore, these two application modes are merged into the "Reducing Curtailment Rate + Compensating for Power Prediction Errors" application mode, which is defined as the second application mode in this invention.

[0115] (3) To achieve the goal of balancing multiple modes, the time-series superposition of the energy storage charging and discharging power demands of new energy power plants under each mode will yield the total energy storage power demand of the energy storage system under the goal of balancing multiple modes. Referring to the "Technical Specification for Power System Grid-Source Coordination" (DL / T1870-2018), new energy sources (wind farms, photovoltaic power plants) achieve primary frequency regulation by retaining active power reserves or configuring energy storage equipment, and utilizing corresponding active power control systems or adding independent control devices. Under high-frequency disturbances in the power grid, when the active power drops to 10% of the rated output, downward adjustment is no longer necessary. Therefore, the droop curve for new energy power plants configuring energy storage systems to participate in primary frequency regulation of the power grid is as follows: Figure 3 As shown, the primary frequency modulation dead time is set to f. d The droop rate is set at 2%, and the maximum load limit is set at no less than 10% of the rated load.

[0116] Specifically, the multi-type energy storage coordinated control method for new energy power plants that takes into account both improving the absorption level and actively supporting the power grid is divided into three parts in terms of process: the main control program, the inertia support and primary frequency regulation control part, and the power curtailment rate reduction and power prediction error compensation control part.

[0117] First, this invention uses multiple types of energy storage systems as the control object. It applies multiple types of energy storage systems in scenarios that take into account four application modes: inertia support, primary frequency regulation, power prediction error compensation, and reduction of curtailment rate. The control strategy is divided into a main control program, an inertia support and primary frequency regulation control part, and a curtailment rate reduction and power prediction error compensation control part. By simultaneously calculating and superimposing the energy storage demand under different application modes, the total energy storage power demand of multiple types of energy storage systems is obtained. In view of the characteristics of battery energy storage systems, which have long energy storage time but few cycle times, a frequency decomposition algorithm is used to allocate the high-frequency part of the total energy storage power demand to the power-type energy storage system and the low-frequency part to the battery energy storage system. This enables multiple types of energy storage systems to efficiently meet the energy storage demand in the complex process of reducing curtailment rate and compensating for power prediction error for 24 hours continuously, while inertia support and primary frequency regulation demand occur randomly.

[0118] Secondly, this invention considers the actual situation of the differences and consistency of sample data, the differences and consistency of technical principles, and the continuity and coupling of timing among different modes. It merges the inertia support and primary frequency regulation application modes and defines them as the first application mode. It merges the power prediction error compensation and curtailment rate reduction application modes and defines them as the second application mode. The energy storage power demand of the first application mode and the second application mode is calculated in real time in parallel and fed back to the main program. In the main program, the energy storage demand of the two modes is superimposed in real time to obtain the real-time total energy storage power demand.

[0119] Finally, based on the aforementioned real-time total energy storage power demand, this invention employs a frequency decomposition algorithm to decompose the total energy storage power demand into high-frequency and low-frequency components. The high-frequency component is used as the power command for the power-type energy storage system, and the low-frequency component is used as the power command for the battery energy storage system. The power commands of the power-type energy storage system and the battery energy storage system are then verified and corrected under the constraints of the rated charge and discharge power capabilities and SOC operating range of the power-type energy storage system and the battery energy storage system, respectively, to control the charging and discharging of the power-type energy storage system and the battery energy storage system.

[0120] The main flow of the control method of the present invention is described below:

[0121] (1) Flowchart of inertia support and primary frequency regulation control, as follows Figure 4 As shown, it can be described as:

[0122] Step 1: Acquire the real-time frequency f of the energy storage system at sampling intervals no greater than 100ms. t .

[0123] Step 2: Referring to DL / T1870-2018 "Technical Specification for Power System Grid-Source Coordination", based on the system's real-time frequency f t Calculate the real-time frequency deviation Δf of the system t =ft -50, Real-time frequency volatility

[0124] Step 3: Determine the real-time frequency deviation Δf t Has the frequency dead zone been exceeded? d If the frequency dead zone is crossed once, proceed to step four; otherwise, proceed to step five.

[0125] Step 4: Refer to the droop curve function for wind farm participation in grid primary frequency regulation and the real-time frequency f based on the energy storage system given in the "Technical Specification for Power System Grid-Source Coordination" (DL / T1870-2018). t Calculate the droop coefficient ξ of the energy storage system configured in the new energy power plant participating in the primary frequency regulation of the power grid. t for:

[0126]

[0127] And it satisfies the following constraints:

[0128] -0.1≤ξ t ≤0.1

[0129] when And ξ t When ξ > 0, it is corrected to: ξ t =0.

[0130] In the formula, f t f is the real-time frequency of the energy storage system. N f represents the power grid frequency. d This indicates the primary frequency regulation dead zone of the new energy power plant, and δ% represents the primary frequency regulation droop rate. This represents the actual output power of the new energy power station at time t. This indicates the installed capacity of new energy power plants;

[0131] Based on ξ t In calculation mode 1, for the real-time power demand of the energy storage system, the energy storage system power command is defined as negative for energy storage charging, and positive for energy storage discharging.

[0132]

[0133] In the formula, This represents the energy storage power demand under the first application mode at time t.

[0134] Step 5: Based on Calculate the real-time power grid inertia support requirements:

[0135]

[0136] In the formula, K represents the demand supported by the power grid's inertia at time t. 惯性 This represents the virtual inertia coefficient by which the energy storage system participates in inertia support.

[0137] Step 6: Return the energy storage system power command to the main program.

[0138] (2) Flowchart for reducing curtailment rate and compensating for power prediction error control, as follows: Figure 5 As shown, it can be described as:

[0139] Step 1: Input the day-ahead power forecast data sample of the new energy power plant, and input the power curtailment data of the dispatch;

[0140] Step 2: Collect real-time power generation data of the new energy power plant at 1-minute sampling intervals.

[0141] Step 3: Real-time acquisition of the SOC value of the battery energy storage system

[0142] Step 4: Determine if the current time is during a power rationing period. If yes, proceed to Step 5; otherwise, proceed to Step 6.

[0143] Step 5: Calculate the current power demand of the energy storage system. And feed back the power demand of the energy storage system to the main program;

[0144] Step Six: Real-time calculation of power prediction error for new energy power plants

[0145] Step 7: Determine the range of power prediction error values. If If successful, proceed to step eight; otherwise, proceed to step eleven.

[0146] Step 8: Determine the real-time SOC value of the battery energy storage system. If If successful, proceed to step nine; otherwise, proceed to step ten.

[0147] Step Nine: Because in the compensated power prediction error mode, the combined output of "new energy + energy storage" tracks the day-ahead prediction value of the new energy power station within a certain error range. During this process, the charging and discharging power demand of the energy storage system is not a fixed value, but a power range. Selecting any value within this range allows "new energy + energy storage" to track the predicted value of the new energy power station within the required error bandwidth. To enable the battery energy storage system to simultaneously possess good charging and discharging capabilities, a battery energy storage system SOC callback strategy is added to the control strategy. That is, when the battery energy storage system SOC is at a high level, the system is controlled to maximize discharge; when the battery energy storage system SOC is at a low level, the system is controlled to maximize charging. Therefore, the energy storage power demand under mode 2 is calculated as follows: And feedback is sent to the main program;

[0148] Step 10: Calculate the energy storage power requirement under Mode 2: And feedback is sent to the main program;

[0149] Step 11: Determine the range of power prediction error values. If If successful, proceed to step twelve; otherwise, proceed to step fifteen.

[0150] Step 12: Determine the real-time SOC value of the battery energy storage system. If If successful, proceed to step thirteen; otherwise, proceed to step fourteen.

[0151] Step 13: Perform maximum charging to achieve SOC callback of the battery energy storage system, and calculate the energy storage power requirement. And feedback is sent to the main program;

[0152] Step Fourteen: Calculate the energy storage power requirement as follows And feedback is sent to the main program;

[0153] Step 15: Calculate the energy storage power requirement as follows: And then report back to the main program.

[0154] in, This represents the power prediction error of the new energy power plant at time t. This represents the energy storage power demand under the second application mode at time t. This represents the upper limit of the output of the renewable energy power plant at time t within the power rationing period issued by the dispatch center. This represents the actual output power of the new energy power station at time t. Let α represent the predicted output power of the renewable energy power plant at time t, and let α represent the allowable error bandwidth for the power prediction of the renewable energy power plant. This represents the SOC value of the battery energy storage system at time t. This indicates the installed capacity of new energy power plants.

[0155] (3) Control the main program flowchart, such as Figure 6 As shown, it can be described as:

[0156] Step 1: Input the energy storage power demand fed back from Mode 1 in real time Real-time input mode 2 feedback of energy storage power demand

[0157] Step 2: Using the command interval of Mode 1 as the calculation time interval for total power demand, calculate the total energy storage power demand that takes into account multiple modes in real time.

[0158] Step 3: Use a frequency domain decomposition algorithm to decompose the total energy storage power demand to obtain high-frequency power commands and low-frequency power commands;

[0159] Step 4: Use low-frequency power commands as power commands for the battery energy storage system. High-frequency power commands are used as the power commands for power-type energy storage systems.

[0160] Step 5: Judgment Is it valid? If so, amend it. Proceed to step 7.1; if the condition is not met, proceed to step 6.1; simultaneously determine... Is it valid? If so, amend it. Proceed to step 7.2; if the condition is not met, proceed to step 6.2.

[0161] Step Six (including steps 6.1-6.2):

[0162] Step 6.1: Determine Is it valid? If so, amend it. Proceed to step 7.1; if the condition is not met, proceed directly to step 7.1.

[0163] Step 6.2: Determine Is it valid? If so, amend it. Proceed to step 7.2; if the condition is not met, proceed directly to step 7.2.

[0164] Step 7 (including steps 7.1-7.2):

[0165] Step 7.1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails to function, proceed to step 8.1.

[0166] Step 7.2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, proceed to step 8.2.

[0167] Step 8 (including steps 8.1-8.2):

[0168] Step 8.1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails, directly issue a power command. For battery energy storage systems;

[0169] Step 8.2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, a power command is directly issued. For power-type energy storage systems.

[0170] Step 9: Then proceed to the next control loop.

[0171] in, This is expressed as the SOC value of the battery energy storage system at time t+1. This is expressed as the SOC value of the power-type energy storage system at time t+1. This indicates the upper limit of the SOC (State of Charge) of the battery energy storage system. This indicates the lower limit of the State of Charge (SOC) of the battery energy storage system. This indicates the upper limit of the State of Charge (SOC) of a power-type energy storage system. This indicates the lower limit of the State of Charge (SOC) of the power energy storage system.

[0172] This invention also provides a multi-type energy storage coordinated control system for new energy power plants, comprising:

[0173] Energy storage system configuration module: Configure an energy storage system in a new energy power station. The application modes of the energy storage system include a first application mode and a second application mode. The energy storage system includes a power-type energy storage system and a battery energy storage system.

[0174] Energy storage power demand calculation module: used to calculate the energy storage power demand under various application modes in parallel; the energy storage power demand calculation module includes a first calculation module and a second calculation module, wherein: the first calculation module: used to calculate the energy storage power demand under the first application mode; the first application mode is the inertia support and primary frequency regulation application mode;

[0175] The implementation process of the first calculation module is as follows:

[0176] The real-time frequency f of the energy storage system is collected at a preset first sampling time interval. t ;

[0177] Based on the real-time frequency f of the energy storage system t Calculate the real-time frequency deviation Δf of the energy storage system. t =f t -50 and real-time frequency volatility

[0178] Determine the real-time frequency deviation Δf t Has the frequency dead zone been exceeded? d;

[0179] If it exceeds this range, then it is based on the real-time frequency f of the energy storage system. t Calculate the droop coefficient ξ of the energy storage system configured in the new energy power plant participating in the primary frequency regulation of the power grid. t ;

[0180]

[0181] And it satisfies the following constraints:

[0182] -0.1≤ξ t ≤0.1

[0183] when And ξ t When ξ > 0, it is corrected to: ξ t =0;

[0184] In the formula, f t f is the real-time frequency of the energy storage system. N f represents the power grid frequency. d This indicates the primary frequency regulation dead zone of the new energy power plant, and δ% represents the primary frequency regulation droop rate. This represents the actual output power of the new energy power station at time t. This indicates the installed capacity of new energy power plants;

[0185] Based on ξ t Calculate the power demand of the energy storage system for the first application mode. When the power command of the energy storage system is negative, the energy storage system charges; when the power command of the energy storage system is positive, the energy storage system discharges.

[0186]

[0187] In the formula, This represents the energy storage power demand under the first application mode at time t;

[0188] If not crossed, then based on Calculate the real-time power grid inertia support requirements:

[0189]

[0190] In the formula, K represents the demand supported by the power grid's inertia at time t. 惯性 This represents the virtual inertia coefficient by which the energy storage system participates in inertia support.

[0191] The second calculation module is used to calculate the energy storage power demand under the second application mode, which is an application mode to reduce the curtailment rate and compensate for power prediction errors.

[0192] The implementation process of the second calculation module is as follows:

[0193] Obtain day-ahead power forecast data samples of new energy power plants and dispatched power curtailment data;

[0194] Real-time acquisition of power generation data from new energy power plants at a preset second sampling time interval.

[0195] Real-time acquisition of SOC value of battery energy storage system

[0196] Determine if the current time is a period of power rationing; if so, calculate the power demand of the energy storage system at the current time. If not, then calculate the power prediction error of the new energy power plant in real time.

[0197] Determine the range of power prediction error values, if If true, then determine the real-time SOC value of the battery energy storage system. Establishment, calculation of energy storage power demand under the second application mode. if This is not valid; calculate the energy storage power demand under the second application mode.

[0198] if If this is not the case, then the power prediction error range is checked again. If true, then determine the real-time SOC value of the battery energy storage system. Established, it executes maximum charging, realizes SOC callback of the battery energy storage system, and calculates the energy storage power requirement as follows: if This is not true; the calculated energy storage power requirement is...

[0199] if This is not true; the calculated energy storage power requirement is...

[0200] in, This represents the power prediction error of the new energy power plant at time t. This represents the energy storage power demand under the second application mode at time t. This represents the upper limit of the output of the renewable energy power plant at time t within the power rationing period issued by the dispatch center. This represents the actual output power of the new energy power station at time t. Let α represent the predicted output power of the renewable energy power plant at time t, and let α represent the allowable error bandwidth for the power prediction of the renewable energy power plant. This represents the SOC value of the battery energy storage system at time t. This indicates the installed capacity of new energy power plants.

[0201] Coordination and control module: It is used to calculate and coordinate the total energy storage power demand based on the energy storage power demand under various application modes, and control the charging and discharging of power-type energy storage system and battery energy storage system under the constraints of the safe and stable operation boundary of energy storage system, so as to realize the coordinated control of multiple types of energy storage on the new energy power station side.

[0202] The coordination and control module implementation process is as follows:

[0203] Real-time input of energy storage power demand in the first application mode And the energy storage power demand fed back in the second application mode

[0204] Using the first sampling time interval of the first application mode as the calculation time interval for the total power demand, the total energy storage power demand that takes into account multiple modes is calculated in real time.

[0205] A frequency domain decomposition algorithm is used to decompose the total power demand of energy storage into high-frequency power commands and low-frequency power commands. The low-frequency power command is then used as the power command for the battery energy storage system. High-frequency power commands are used as the power commands for power-type energy storage systems.

[0206] judge Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed to step A1; simultaneously determine... Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed to step A2.

[0207] Step A1: Determine Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed directly to step B1.

[0208] Step A2: Determine Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed directly to step B2.

[0209] Step B1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails to function, proceed to step C1.

[0210] Step B2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, proceed to step C2.

[0211] Step C1: Determine and Is it valid? If so, amend it. And issue power commands If the battery energy storage system fails, directly issue a power command. For battery energy storage systems;

[0212] Step C2: Determine and Is it valid? If so, amend it. And issue power commands If the condition is not met for a power-type energy storage system, a power command is directly issued. Power-type energy storage systems;

[0213] in, This is expressed as the SOC value of the battery energy storage system at time t+1. This is expressed as the SOC value of the power-type energy storage system at time t+1. This indicates the upper limit of the SOC (State of Charge) of the battery energy storage system. This indicates the lower limit of the State of Charge (SOC) of the battery energy storage system. This indicates the upper limit of the State of Charge (SOC) of a power-type energy storage system. This indicates the lower limit of the State of Charge (SOC) of the power energy storage system.

[0214] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0215] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0216] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0217] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the pending claims of the invention.

Claims

1. A method for coordinated control of multiple types of energy storage at a new energy power plant, characterized in that, include: In a new energy power plant, an energy storage system is configured. The application modes of the energy storage system include a first application mode and a second application mode. The energy storage system includes a power-type energy storage system and a battery energy storage system. Parallel calculation of energy storage power requirements under various application modes; The total energy storage power demand is calculated and coordinated based on the energy storage power demand under various application modes, and the charging and discharging of power-type energy storage systems and battery energy storage systems are controlled under the constraints of the safe and stable operation boundary of the energy storage system. The parallel computing of energy storage power requirements under various application modes specifically includes: calculating the energy storage power requirements under the first application mode and calculating the energy storage power requirements under the second application mode. The first application mode is the inertia support and primary frequency regulation application mode, and the second application mode is the power curtailment rate reduction and power prediction error compensation application mode. The calculation of the energy storage power requirement under the first application mode is specifically as follows: The real-time frequency of the energy storage system is collected at a preset first sampling time interval. ; Real-time frequency based on energy storage system Calculate the real-time frequency deviation of the energy storage system and real-time frequency volatility ; Determine real-time frequency deviation Has the frequency dead zone been crossed? ; If it exceeds the limit, then it is based on the real-time frequency of the energy storage system. Calculate the droop coefficient of the energy storage system configured in the new energy power plant for participation in the primary frequency regulation of the power grid. ; And it satisfies the following constraints: when and When, it was corrected to: ; In the formula, For the real-time frequency of the energy storage system, Indicates the power grid frequency. This indicates the primary frequency regulation dead zone of a new energy power plant. This represents the diastolic rate of a single frequency modulation. This represents the actual output power of the new energy power station at time t. This indicates the installed capacity of new energy power plants; based on Calculate the power demand of the energy storage system for the first application mode. When the power command of the energy storage system is negative, the energy storage system charges; when the power command of the energy storage system is positive, the energy storage system discharges. In the formula, This represents the energy storage power demand under the first application mode at time t; If not crossed, then based on Calculate the real-time power grid inertia support requirements: In the formula, This indicates the demand supported by the power grid's inertia at time t. This represents the virtual inertia coefficient by which the energy storage system participates in inertia support; The calculation of the energy storage power requirement under the second application mode is specifically as follows: Obtain day-ahead power forecast data samples of new energy power plants and dispatched power curtailment data; The actual output power of the new energy power plant at time t is collected in real time at a preset second sampling time interval. ; Real-time acquisition of SOC value of battery energy storage system ; Determine if the current time is a period of power rationing; if so, calculate the power demand of the energy storage system at the current time. If not, then calculate the power prediction error of the new energy power plant in real time. ; Determine the range of power prediction error values, if If true, then determine the real-time SOC value of the battery energy storage system. Establishment, calculation of energy storage power demand under the second application mode. ,if This is not valid; calculate the energy storage power demand under the second application mode. ; if If this is not the case, then the power prediction error range is checked again. If true, then determine the real-time SOC value of the battery energy storage system. Established, it executes maximum charging, realizes SOC callback of the battery energy storage system, and calculates the energy storage power requirement as follows: ,if This is not true; the calculated energy storage power requirement is... ; if This is not true; the calculated energy storage power requirement is... ; in, This represents the power prediction error of the new energy power plant at time t. This represents the energy storage power demand under the second application mode at time t. This represents the upper limit of the output of the renewable energy power plant at time t within the power rationing period issued by the dispatch center. This represents the actual output power of the new energy power station at time t. This represents the predicted output power of the new energy power plant at time t. This represents the allowable error bandwidth value for power prediction of new energy power plants. This represents the SOC value of the battery energy storage system at time t. This indicates the installed capacity of new energy power plants.

2. The multi-type energy storage coordinated control method on the new energy power station side according to claim 1, characterized in that, The calculation and coordinated allocation of the real-time total energy storage power demand based on the energy storage power demand under various application modes is as follows: Real-time input of energy storage power demand in the first application mode at time t And the energy storage power demand in the second application mode at time t ; Using the first sampling time interval of the first application mode as the calculation time interval for the total power demand, the total energy storage power demand that takes into account multiple modes is calculated in real time. ; A frequency domain decomposition algorithm is used to decompose the total power demand of energy storage into high-frequency power commands and low-frequency power commands. The low-frequency power command is then used as the power command for the battery energy storage system. High-frequency power commands will be used as the power commands for power-type energy storage systems. ; judge Is it valid? If so, amend it. If the condition is not met, proceed to step B1; otherwise, proceed to step A1. Simultaneously, determine... Is it valid? If so, amend it. If the condition is not met, proceed to step B2; otherwise, proceed to step A2. Step A1: Determine Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed directly to step B1. Step A2: Determine Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed directly to step B2. Step B1: Determine Is it valid? If so, amend it. and issue power commands If the battery energy storage system fails to function, proceed to step C1. Step B2: Determine Is it valid? If so, amend it. and issue power commands If the condition is not met for a power-type energy storage system, proceed to step C2. Step C1: Determine Is it valid? If so, amend it. and issue power commands If the battery energy storage system fails, directly issue a power command. For battery energy storage systems; Step C2: Determine Is it valid? If so, amend it. and issue power commands If the condition is not met for a power-type energy storage system, a power command is directly issued. Power-type energy storage systems; in, This is expressed as the SOC value of the battery energy storage system at time t+1. This is expressed as the SOC value of the power-type energy storage system at time t+1. This indicates the upper limit of the SOC (State of Charge) of the battery energy storage system. This indicates the lower limit of the State of Charge (SOC) of the battery energy storage system. This indicates the upper limit of the State of Charge (SOC) of a power-type energy storage system. This indicates the lower limit of the State of Charge (SOC) of the power energy storage system.

3. A multi-type energy storage coordinated control system for new energy power plants, characterized in that: include: Energy storage system configuration module: used to configure energy storage systems in new energy power plants. The application modes of the energy storage system include a first application mode and a second application mode. The energy storage system includes a power-type energy storage system and a battery energy storage system. Energy storage power demand calculation module: used to calculate the energy storage power demand in parallel under various application modes; Coordination and control module: It is used to calculate and coordinate the total energy storage power demand based on the energy storage power demand under various application modes, and control the charging and discharging of power-type energy storage system and battery energy storage system under the constraints of the safe and stable operation boundary of energy storage system. The energy storage power demand calculation module includes a first calculation module and a second calculation module, wherein: First calculation module: used to calculate the energy storage power requirement under the first application mode; Second calculation module: used to calculate the energy storage power demand in the second application mode; The first application mode is the inertia support and primary frequency regulation application mode, and the second application mode is the power curtailment rate reduction and power prediction error compensation application mode. The implementation process of the first calculation module is as follows: The real-time frequency of the energy storage system is collected at a preset first sampling time interval. ; Real-time frequency based on energy storage system Calculate the real-time frequency deviation of the energy storage system and real-time frequency volatility ; Determine real-time frequency deviation Has the frequency dead zone been crossed? ; If it exceeds the limit, then it is based on the real-time frequency of the energy storage system. Calculate the droop coefficient of the energy storage system configured in the new energy power plant for participation in the primary frequency regulation of the power grid. ; And it satisfies the following constraints: when and When, it was corrected to: ; In the formula, For the real-time frequency of the energy storage system, Indicates the power grid frequency. This indicates the primary frequency regulation dead zone of a new energy power plant. This represents the diastolic rate of a single frequency modulation. This represents the actual output power of the new energy power station at time t. This indicates the installed capacity of new energy power plants; based on Calculate the power demand of the energy storage system for the first application mode. When the power command of the energy storage system is negative, the energy storage system charges; when the power command of the energy storage system is positive, the energy storage system discharges. In the formula, This represents the energy storage power demand under the first application mode at time t; If not crossed, then based on Calculate the real-time power grid inertia support requirements: In the formula, This indicates the demand supported by the power grid's inertia at time t. This represents the virtual inertia coefficient by which the energy storage system participates in inertia support; The implementation process of the second calculation module is as follows: Obtain day-ahead power forecast data samples of new energy power plants and dispatched power curtailment data; The actual output power of the new energy power plant at time t is collected in real time at a preset second sampling time interval. ; Real-time acquisition of SOC value of battery energy storage system ; Determine if the current time is a period of power rationing; if so, calculate the power demand of the energy storage system at the current time. If not, then calculate the power prediction error of the new energy power plant in real time. ; Determine the range of power prediction error values, if If true, then determine the real-time SOC value of the battery energy storage system. Establishment, calculation of energy storage power demand under the second application mode. ,if This is not valid; calculate the energy storage power demand under the second application mode. ; if If this is not the case, then the power prediction error range is checked again. If true, then determine the real-time SOC value of the battery energy storage system. Established, it executes maximum charging, realizes SOC callback of the battery energy storage system, and calculates the energy storage power requirement as follows: ,if This is not true; the calculated energy storage power requirement is... ; if This is not true; the calculated energy storage power requirement is... ; in, This represents the power prediction error of the new energy power plant at time t. This represents the energy storage power demand under the second application mode at time t. This represents the upper limit of the output of the renewable energy power plant at time t within the power rationing period issued by the dispatch center. This represents the actual output power of the new energy power station at time t. This represents the predicted output power of the new energy power plant at time t. This represents the allowable error bandwidth value for power prediction of new energy power plants. This represents the SOC value of the battery energy storage system at time t. This indicates the installed capacity of new energy power plants.

4. The multi-type energy storage coordinated control system for the new energy power station side according to claim 3, characterized in that, The coordination and control module implementation process is as follows: Real-time input of energy storage power demand in the first application mode at time t And the energy storage power demand in the second application mode at time t ; Using the first sampling time interval of the first application mode as the calculation time interval for the total power demand, the total energy storage power demand that takes into account multiple modes is calculated in real time. ; A frequency domain decomposition algorithm is used to decompose the total power demand of energy storage into high-frequency power commands and low-frequency power commands. The low-frequency power command is then used as the power command for the battery energy storage system. High-frequency power commands will be used as the power commands for power-type energy storage systems. ; judge Is it valid? If so, amend it. If the condition is not met, proceed to step B1; otherwise, proceed to step A1. Simultaneously, determine... Is it valid? If so, amend it. If the condition is not met, proceed to step B2; otherwise, proceed to step A2. Step A1: Determine Is it valid? If so, amend it. Proceed to step B1; if the condition is not met, proceed directly to step B1. Step A2: Determine Is it valid? If so, amend it. Proceed to step B2; if the condition is not met, proceed directly to step B2. Step B1: Determine Is it valid? If so, amend it. and issue power commands If the battery energy storage system fails to function, proceed to step C1. Step B2: Determine Is it valid? If so, amend it. and issue power commands If the condition is not met for a power-type energy storage system, proceed to step C2. Step C1: Determine Is it valid? If so, amend it. and issue power commands If the battery energy storage system fails, directly issue a power command. For battery energy storage systems; Step C2: Determine Is it valid? If so, amend it. and issue power commands If the condition is not met for a power-type energy storage system, a power command is directly issued. Power-type energy storage systems; in, This is expressed as the SOC value of the battery energy storage system at time t+1. This is expressed as the SOC value of the power-type energy storage system at time t+1. This indicates the upper limit of the SOC (State of Charge) of the battery energy storage system. This indicates the lower limit of the State of Charge (SOC) of the battery energy storage system. This indicates the upper limit of the State of Charge (SOC) of a power-type energy storage system. This indicates the lower limit of the State of Charge (SOC) of the power energy storage system.

5. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the multi-type energy storage coordinated control method on the new energy power station side as described in claim 1 or 2.

Images