Optimized cooperative control method and system for dynamic reconfigurable hybrid energy storage

Abstract

The invention discloses an optimization cooperative control method and system for dynamic reconfigurable hybrid energy storage, and belongs to the technical field of energy storage control, and the method comprises the steps: dividing an energy storage operation time scale into a plurality of first time scales; dividing each first time scale into a plurality of second time scales, taking the minimum difference value between the energy storage charge state of the target position and the average energy storage charge state as a target, and calculating the switching operation state of the energy type energy storage in the hybrid energy storage in a rolling manner based on the first time scales; and on the basis of the switching operation state of the energy type energy storage, the sum of the difference value of the energy storage charge state and the average energy storage charge state and the difference value of the power instruction of the power type energy storage and the actual power instruction of the power type energy storage is minimum as a target, and the switching operation state of the power type energy storage in the hybrid energy storage is calculated in a rolling manner on the basis of a second time scale. According to the method, the problem that energy type and power type energy storage multi-time-scale cooperative control in the dynamic reconfigurable hybrid energy storage system is lacked in the prior art is solved.

Description

Technical Field

[0001] This invention relates to an optimized collaborative control method and system for dynamically reconfigurable hybrid energy storage, belonging to the field of energy storage control technology. Background Technology

[0002] In recent years, the proportion of new energy sources such as wind power and photovoltaics in the power system has continued to increase. To mitigate their volatility and intermittency, new energy power plants are widely equipped with hybrid energy storage systems. Energy storage, represented by batteries, provides long-term power support, while power storage, represented by supercapacitors, handles short-term high-rate charging and discharging demands. The combination of the two can enhance power response capabilities across multiple time scales and improve economic efficiency. Traditional energy storage systems mostly adopt fixed series-parallel topologies, but differences in the characteristics of energy storage units lead to a "bottleneck effect," limiting system efficiency; moreover, unit failures can easily trigger system-level cascading reactions. Dynamically reconfigurable network technology achieves flexible connection of energy storage units through low-power semiconductor switches, and achieves fault isolation and unit balancing through switch state adjustments, significantly improving equipment lifespan and safety. However, this technology is currently only applied to single-type energy storage systems, and research on topology design, balancing management, and cross-time scale collaborative control in hybrid energy storage scenarios is still lacking.

[0003] Existing dynamic reconfigurable control strategies are all designed for single energy storage types and cannot be adapted to hybrid energy storage systems. Hybrid energy storage requires coordination of the characteristics of energy-type and power-type units at different time scales, but current technologies lack both a topology architecture suitable for hybrid energy storage and a multi-time-scale hierarchical collaborative control framework. Specific shortcomings include: optimization methods based on state-space models are computationally time-consuming and prone to local optima; switching control methods based on state-of-charge ranking are not economically viable; and switching decision methods based on deep learning have poor interpretability and are dependent on data quality. In addition, existing methods also face engineering challenges such as reconfigurable short-circuit protection and integrated electrothermal management. Therefore, there is an urgent need to develop dynamic reconfigurable topologies and multi-time-scale collaborative control methods for hybrid energy storage systems to achieve efficient collaborative control of energy-type and power-type energy storage. Summary of the Invention

[0004] The purpose of this invention is to provide an optimized collaborative control method and system for dynamically reconfigurable hybrid energy storage. By using multi-timescale rolling optimization and mixed integer linear programming, the switching operation states of the two are coordinated to minimize the energy storage state of charge deviation and power command tracking error, thereby solving the problem of multi-timescale collaborative control of energy-type and power-type energy storage in existing dynamically reconfigurable hybrid energy storage systems.

[0005] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution.

[0006] In a first aspect, the present invention provides an optimized collaborative control method for dynamically reconfigurable hybrid energy storage, comprising:

[0007] The power command for energy-type energy storage and the power command for power-type energy storage in hybrid energy storage are calculated using a filtering function.

[0008] The timescale of energy storage operation is divided into several first timescales;

[0009] Each first time scale is divided into several second time scales;

[0010] The first objective function is established based on the energy storage state of charge using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The switching operation state of energy storage in the mixed energy storage is calculated on a rolling basis based on the first time scale.

[0011] Based on the switching operation state of energy-type energy storage, a second objective function is established using mixed integer linear programming according to the energy storage state of charge and the power command of energy-type energy storage and the power command of power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The switching operation state of power-type energy storage in the mixed energy storage is calculated on a rolling basis based on the second time scale.

[0012] Energy storage is controlled in a coordinated manner based on the switching operation status of energy-type energy storage and power-type energy storage.

[0013] Furthermore, the power command for the energy-type energy storage and the power command for the power-type energy storage are respectively expressed as:

[0014] ;

[0015] ;

[0016] In the formula, Indicates a hybrid energy storage power command. Power commands indicating energy storage Power commands indicating power-type energy storage Indicates time The time constant is denoted by s, which represents the complex frequency domain operator.

[0017] Furthermore, the first objective function is expressed as:

[0018] ;

[0019] In the formula, This indicates taking the minimum value. Indicates the first Line number The state of charge of columnar energy storage on the first time scale. Indicates the first Line number The average state of charge of columnar energy storage within the first time scale. This indicates the total number of rows in the energy storage arrangement. This indicates the total number of columns in the energy storage arrangement.

[0020] Furthermore, the constraints of the first objective function include: current calculation constraints, energy storage state of charge calculation constraints, first power command constraints, current range constraints, energy storage state of charge range constraints, and first switching constraints.

[0021] Furthermore, the current calculation constraint is expressed as:

[0022] ;

[0023] In the formula, Indicates the first Line number The current of column-type energy storage, This represents the total current of energy storage. This represents a pre-defined auxiliary variable used to represent the first... Line number The switch of the column energy storage type is closed and the first Column total When a switch is closed, there is The current is distributed evenly among the batteries;

[0024] The constraints for calculating the energy storage state of charge are expressed as follows:

[0025] ;

[0026] In the formula, Indicates time The corresponding number Line number The state of charge of columnar energy storage on the first time scale. Indicates time The corresponding number Line number The state of charge of columnar energy storage on the first time scale. This indicates the period of rolling on the first time scale. Indicates the first Line number Battery capacity for column-type energy storage;

[0027] The first power command constraint is expressed as:

[0028] ;

[0029] In the formula, This indicates that the state estimation is obtained from the measurement information. Line number The voltage of column-type energy storage, This represents the maximum steady-state current of energy storage. Indicates the current number Line number The on / off state of column-type energy storage;

[0030] The current range constraint is expressed as follows:

[0031] ;

[0032] The energy storage state of charge range constraint is expressed as follows:

[0033] ;

[0034] In the formula, This represents the minimum state of charge of energy storage within the first time scale. This represents the maximum state of charge of energy storage within the first time scale;

[0035] The first switch constraint is: when the first... When all switches of the column-type energy storage are in the open state, the first one is turned on. Bypass switch corresponding to column-type energy storage.

[0036] Furthermore, the calculation formula for the current calculation constraint is expressed as follows:

[0037] ;

[0038] In the formula, Indicates the first Columnar energy storage The current is evenly distributed among the batteries. Indicates the first Columnar energy storage The batteries were not evenly distributed.

[0039] Furthermore, the second objective function is expressed as:

[0040] The second objective function is expressed as:

[0041] ;

[0042] In the formula, This indicates taking the minimum value. Indicates the first Line number State of charge of power-type energy storage in the second time scale. Indicates the first Line number The average state of charge of column-type energy storage over the second time scale. This indicates the total number of rows in the power-type energy storage arrangement. This indicates the total number of columns in the power-type energy storage arrangement. A weighting coefficient representing the difference between the state of charge (SBC) of power-type energy storage and the average SBC. Power command representing power-type energy storage Actual power command for power-type energy storage The weighting coefficients of the difference, where .

[0043] Furthermore, the constraints of the second objective function include: current calculation constraints, energy storage state of charge calculation constraints, second power command constraints, voltage range constraints, energy storage state of charge range constraints, and second switching constraints.

[0044] Furthermore, the second power command constraint is expressed as:

[0045] ;

[0046] In the formula, This indicates the maximum voltage of the power storage capacitor. Indicates the first Line number The current of power-type energy storage;

[0047] The voltage range constraint is expressed as follows:

[0048] ;

[0049] In the formula, Indicates the current number Line number The switching state of column-type energy storage. Indicates the current number Line number The switching states of column-type energy storage. Indicates the first All switches for the column-type energy storage are in the off state. This represents the average voltage of energy storage. Indicates the safety factor. Indicates the first Line number The voltage of power-type energy storage, Indicates the current number Line number Switching status of column-type energy storage;

[0050] The second switch constraint is:

[0051] When the power command of the power storage is in the same direction, the switch of the forward voltage capacitor is turned on;

[0052] When the power command of the power storage is reversed, the switch for reverse voltage is turned on.

[0053] The bypass switch is activated when both the forward voltage capacitor switch and the reverse voltage capacitor switch are in the open state. However, the forward voltage capacitor switch, the reverse voltage capacitor switch, and the bypass switch cannot be activated simultaneously.

[0054] Secondly, the present invention provides an optimized and coordinated control system for dynamically reconfigurable hybrid energy storage, comprising:

[0055] The power command calculation module is used to calculate the power command of energy-type energy storage and power-type energy storage in hybrid energy storage using a filtering function.

[0056] The first time scale division module is used to divide the energy storage operation time scale into several first time scales;

[0057] The second time scale division module is used to divide each first time scale into several second time scales;

[0058] The switching operation state calculation module for energy-type energy storage is used to establish a first objective function based on the energy storage state of charge using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The module calculates the switching operation state of energy-type energy storage in the mixed energy storage based on the first time scale.

[0059] The power-type energy storage switching operation state calculation module is used to establish a second objective function based on the switching operation state of energy-type energy storage, according to the energy storage state of charge and the power command of energy-type energy storage and the power command of power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The module calculates the switching operation state of power-type energy storage in the hybrid energy storage on a rolling basis based on the second time scale.

[0060] The collaborative control module is used to collaboratively control energy storage based on the switching operation states of energy-type energy storage and power-type energy storage.

[0061] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0062] This invention addresses the efficiency loss caused by the "bottleneck effect" in traditional fixed topologies by optimizing the switching state of energy-type energy storage on a first time scale, aiming to minimize the difference between the energy storage's state of charge (SBC) and the average SBC. Simultaneously, it optimizes the switching state of power-type energy storage on a second time scale, minimizing both SBC deviation and power command tracking error, overcoming the adaptability limitations of single-energy-type dynamic reconfiguration methods in hybrid energy storage scenarios. Ultimately, it achieves the organic coupling of the long-term power support capability of energy-type energy storage and the short-term high-rate response capability of power-type energy storage, significantly improving the power response accuracy, equipment utilization, and operational economy of hybrid energy storage systems. This solves the problem of multi-timescale coordinated control of energy-type and power-type energy storage in dynamically reconfigurable hybrid energy storage systems, a problem lacking in existing technologies. Attached Figure Description

[0063] Figure 1 This is a flowchart illustrating an optimized and coordinated control method for dynamically reconfigurable hybrid energy storage provided in an embodiment of the present invention.

[0064] Figure 2 This is a schematic diagram of the structure of the dynamic reconfigurable hybrid energy storage simulation model for accessing a wind farm provided in an embodiment of the present invention;

[0065] Figure 3 This is a schematic diagram of the energy storage state-of-charge curve under constant output conditions provided in an embodiment of the present invention;

[0066] Figure 4 This is a schematic diagram of the energy storage state-of-charge curve under the control of the sorting comparison method under constant output conditions provided in this embodiment of the invention.

[0067] Figure 5 This is a schematic diagram of the standard deviation of the state of charge of energy storage under constant output conditions provided in an embodiment of the present invention.

[0068] Figure 6 This is a schematic diagram of the overall power curves of energy storage, wind farms, and power stations under fluctuating output conditions provided in an embodiment of the present invention.

[0069] Figure 7 This is a schematic diagram of the power command curve of the converter after filtering under fluctuating output conditions provided in an embodiment of the present invention;

[0070] Figure 8 This is a schematic diagram of the power component curves of energy-type energy storage and power-type energy storage under fluctuating output conditions provided in the embodiments of the present invention;

[0071] Figure 9 This is a schematic diagram of the energy storage state-of-charge curve under the fluctuating output condition controlled by the embodiment of the present invention;

[0072] Figure 10This is a schematic diagram of the standard deviation curve of the state of charge of energy storage under the fluctuating output condition controlled by the embodiment of the present invention;

[0073] Figure 11 This is a schematic diagram of the current curve under the fluctuating output condition controlled by the embodiment of the present invention;

[0074] Figure 12 This is a schematic diagram of the voltage curve under the fluctuating output condition controlled by the embodiment of the present invention. Detailed Implementation

[0075] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0076] Example 1

[0077] like Figure 1 As shown in the figure, this embodiment introduces an optimized collaborative control method for dynamically reconfigurable hybrid energy storage, including:

[0078] Step 1: Calculate the power command for energy-type energy storage and the power command for power-type energy storage in hybrid energy storage using the filtering function.

[0079] This invention uses a filtering wave function to perform frequency domain separation of the power command of a hybrid energy storage system. It uses low-pass filtering characteristics to extract the slowly changing power component of energy-type energy storage and high-pass filtering characteristics to extract the rapidly changing power component of power-type energy storage, thereby achieving precise decoupling of the power command between energy-type and power-type energy storage and providing a foundation for subsequent hierarchical control.

[0080] Step 2: Divide the energy storage operation timescale into several first timescales.

[0081] This invention discretizes the operating timescale of an energy storage system into multiple first timescale units, establishes a multi-timescale control framework, and enables energy-type energy storage to focus on energy management over a long timescale, while power-type energy storage focuses on power compensation over a short timescale, thus meeting the energy storage characteristic matching requirements under different timescales.

[0082] Step 3: Divide each first time scale into several second time scales.

[0083] This invention further subdivides each first time scale into a second time scale, constructing a nested time scale control structure. Through refined control of the second time scale, it achieves rapid response of power-type energy storage and stable regulation of energy-type energy storage, thereby improving the tracking accuracy and response speed of the hybrid energy storage system to dynamic power fluctuations.

[0084] Step 4: Based on the energy storage state of charge, a first objective function is established using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The switching operation state of energy-type energy storage in the hybrid energy storage is calculated on a rolling basis based on the first time scale.

[0085] This invention constructs a first objective function based on mixed integer linear programming, with the goal of minimizing the deviation between the state of charge (SOC) of energy storage and the average SOC. It calculates the switching state of energy storage through rolling optimization on the first time scale, ensuring the stability of the SOC during long-term operation of energy storage and avoiding overcharging and over-discharging.

[0086] Step 5: Based on the switching operation state of energy-type energy storage, a second objective function is established using mixed integer linear programming according to the energy storage state of charge and the power command of energy-type energy storage and power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge, and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The switching operation state of power-type energy storage in the hybrid energy storage is calculated on a rolling basis based on the second time scale.

[0087] Based on the determination of the switching state of energy-type energy storage, this invention establishes a dual-objective optimization function through mixed integer linear programming, while minimizing the state-of-charge deviation of power-type energy storage and the tracking error of actual power command. Based on the rolling calculation of the second time scale, the switching state of power-type energy storage is optimized, thereby achieving high-precision power compensation and dynamic balance of state of charge of power-type energy storage.

[0088] Step 6: Coordinate the control of energy storage based on the switching operation status of energy-type energy storage and power-type energy storage.

[0089] This invention forms a hierarchical hybrid energy storage control strategy by coordinating the switching states of energy-type and power-type energy storage. Energy-type energy storage is responsible for system energy balance and long-term support, while power-type energy storage is responsible for instantaneous power compensation and short-term adjustment, ultimately achieving efficient, stable, and coordinated operation of the hybrid energy storage system.

[0090] Example 2

[0091] Based on the same inventive concept as Embodiment 1, this embodiment introduces the implementation steps of an optimized collaborative control method for dynamically reconfigurable hybrid energy storage, including:

[0092] Step 1: Calculate the power command for energy-type energy storage and the power command for power-type energy storage in hybrid energy storage using the filtering function.

[0093] In this embodiment, the power command for the energy-type energy storage and the power command for the power-type energy storage are respectively represented as:

[0094] ;

[0095] ;

[0096] In the formula, Indicates a hybrid energy storage power command. Power commands indicating energy storage Power commands indicating power-type energy storage Indicates time The time constant is denoted by s, which represents the complex frequency domain operator.

[0097] Step 2: Divide the energy storage operation timescale into several first timescales.

[0098] In this embodiment, the first time scale is preset to 10 seconds.

[0099] Step 3: Divide each first time scale into several second time scales.

[0100] In this embodiment, the second time scale is preset to 1 second.

[0101] Step 4: Based on the energy storage state of charge, a first objective function is established using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The switching operation state of energy-type energy storage in the hybrid energy storage is calculated on a rolling basis based on the first time scale.

[0102] In this embodiment, the first objective function is expressed as:

[0103] ;

[0104] In the formula, This indicates taking the minimum value. Indicates the first Line number The state of charge of columnar energy storage on the first time scale. Indicates the first Line number The average state of charge of columnar energy storage within the first time scale. This indicates the total number of rows in the energy storage arrangement. This indicates the total number of columns in the energy storage arrangement.

[0105] In this embodiment, the constraints of the first objective function include: current calculation constraints, energy storage state of charge calculation constraints, first power command constraints, current range constraints, energy storage state of charge range constraints, and first switching constraints.

[0106] In this embodiment, the current calculation constraint is expressed as:

[0107] In this embodiment, the constraints for calculating the state of charge of the energy storage are expressed as follows:

[0108] ;

[0109] In the formula, Indicates time The corresponding number Line number The state of charge of columnar energy storage on the first time scale. Indicates time The corresponding number Line number The state of charge of columnar energy storage on the first time scale. This indicates the period of rolling on the first time scale. Indicates the first Line number Battery capacity for column-type energy storage.

[0110] In this embodiment, the calculation formula for the current calculation constraint is expressed as follows:

[0111] ;

[0112] In the formula, Indicates the first Columnar energy storage The current is evenly distributed among the batteries. Indicates the first Columnar energy storage The batteries were not evenly distributed.

[0113] In this embodiment, the first power command constraint is represented as:

[0114] ;

[0115] In the formula, This indicates that the state estimation is obtained from the measurement information. Line number The voltage of column-type energy storage, This represents the maximum steady-state current of energy storage. Indicates the current number Line number The on / off state of column-type energy storage;

[0116] In this embodiment, the current range constraint is expressed as:

[0117] ;

[0118] In this embodiment, the energy storage state of charge range constraint is expressed as:

[0119] ;

[0120] In the formula, This represents the minimum state of charge of energy storage within the first time scale. This represents the maximum state of charge of energy storage within the first time scale;

[0121] In this embodiment, the first switch constraint is: when the first... When all switches of the column-type energy storage are in the open state, the first one is turned on. Bypass switch corresponding to column-type energy storage.

[0122] Step 5: Based on the switching operation state of energy-type energy storage, establish a second objective function using mixed integer linear programming according to the energy storage state of charge and the power command of energy-type energy storage and power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge, and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The switching operation state of power-type energy storage in the hybrid energy storage is calculated on a rolling basis based on the second time scale.

[0123] In this embodiment, the second objective function is expressed as:

[0124] The second objective function is expressed as:

[0125] ;

[0126] In the formula, This indicates taking the minimum value. Indicates the first Line number State of charge of power-type energy storage in the second time scale. Indicates the first Line number The average state of charge of column-type energy storage over the second time scale. This indicates the total number of rows in the power-type energy storage arrangement. This indicates the total number of columns in the power-type energy storage arrangement. A weighting coefficient representing the difference between the state of charge (SBC) of power-type energy storage and the average SBC. Power command representing power-type energy storage Actual power command for power-type energy storage The weighting coefficients of the difference, where .

[0127] In this embodiment, the constraints of the second objective function include: current calculation constraints, energy storage state of charge calculation constraints, second power command constraints, voltage range constraints, energy storage state of charge range constraints, and second switching constraints.

[0128] In this embodiment, the second power command constraint is expressed as:

[0129] ;

[0130] In the formula, This indicates the maximum voltage of the power storage capacitor. Indicates the first Line number The current of power-type energy storage.

[0131] In this embodiment, the voltage range constraint is expressed as:

[0132] ;

[0133] In the formula, Indicates the current number Line number The switching state of column-type energy storage. Indicates the current number Line number The switching states of column-type energy storage. Indicates the first All switches for the column-type energy storage are in the off state. This represents the average voltage of energy storage. Indicates the safety factor. Indicates the first Line number The voltage of power-type energy storage, Indicates the current number Line number The switching state of column power type energy storage.

[0134] In this embodiment, the second switch constraint is:

[0135] When the power command of the power storage is in the same direction, the switch of the forward voltage capacitor is turned on;

[0136] When the power command of the power storage is reversed, the switch for reverse voltage is turned on.

[0137] The bypass switch is activated when both the forward voltage capacitor switch and the reverse voltage capacitor switch are in the open state. However, the forward voltage capacitor switch, the reverse voltage capacitor switch, and the bypass switch cannot be activated simultaneously.

[0138] Step 6: Coordinate the control of energy storage based on the switching operation status of energy-type energy storage and power-type energy storage.

[0139] Figure 2 This is a schematic diagram of the structure of the dynamic reconfigurable hybrid energy storage simulation model for accessing a wind farm provided in this embodiment of the invention. This embodiment operates based on the dynamic reconfigurable hybrid energy storage simulation model, and the parameters of the dynamic reconfigurable hybrid energy storage simulation model are shown in Table 1:

[0140] Table 1 Main System Parameters

[0141] Parameter name numerical values Single battery capacity 206Ah Rated voltage of a single battery 3.2V Number of batteries connected in series in a single energy storage unit 16 strings Number of energy storage units 4 in 6 strings single supercapacitor capacitance value 3000F Single supercapacitor withstand voltage 2.7V Number of series and parallel capacitors in a single power energy storage unit 25 strings of 10 Number of power-type energy storage units 2 in parallel 4 strings Inverter capacity 125kW Number of reconfigurable energy storage units in each box 4 Number of containers in the energy storage station 20 wind farm rated capacity 100MW

[0142] Table 2 shows a comparison of the solution speed between the proposed method and the nonlinear method. The average computation time of the nonlinear method is 10.953 s, while the proposed method in this embodiment only takes 0.0876 s, demonstrating a significant speed advantage and meeting the requirements of online optimization.

[0143] Table 2 Comparison of Optimized Solution Time

[0144] Serial Number Nonlinear optimization The proposed method 1 10.3s 0.066s 2 12.8s 0.075s 3 11.3s 0.065s 4 9.50s 0.115s 5 15.6s 0.106s 6 10.9s 0.103s 7 7.34s 0.094s 8 13.6s 0.110s 9 7.89s 0.056s 10 10.3s 0.086s

[0145] In this embodiment, the battery state of charge changes under constant output conditions are as follows: Figures 3-5 As shown in the figure. The method proposed in this embodiment can reduce the standard deviation of the state of charge from 8% to around 0%, while the sorting control can only reduce it to 4%, thus doubling the balancing effect.

[0146] In this embodiment, the overall power curves of energy storage, wind farm, and power station under fluctuating output conditions are as follows: Figure 6 As shown, the wind turbine outputs fluctuating power. Setting energy storage power commands can smooth out wind power fluctuations, and the results show that the effect of smoothing fluctuations is excellent.

[0147] In this embodiment, the power command curve of the converter after filtering and the power component curves of energy-type energy storage and power-type energy storage under fluctuating output conditions are as follows: Figure 7 , Figure 8 As shown, the fluctuating power output is filtered to form high-frequency and low-frequency components, which are decoupled and output in a multi-time scale and multi-energy storage manner. The actual power closely tracks the command value, avoiding high-frequency charging and discharging of energy-type energy storage and long-term charging and discharging of power-type energy storage, thus increasing the overall service life and safety of energy storage.

[0148] In this embodiment, the energy storage state-of-charge curve and the energy storage state-of-charge standard deviation curve under fluctuating output conditions are as follows: Figure 9 , Figure 10 As shown, it also maintained a relatively good state of charge balance effect, with the energy storage standard deviation gradually decreasing from 8% to around 0%.

[0149] In this embodiment, the current curve and voltage curve under fluctuating output conditions are as follows: Figure 11 , Figure 12 As shown, under the current constraint, the energy storage current did not exceed the limit. Due to the continuous reconfiguration of the network, the voltage at the network port fluctuated continuously, but after the DC-DC converter was changed, the voltage input to the inverter port remained at a constant safe value.

[0150] In summary, the method proposed in this embodiment combines the advantages of hybrid energy storage, extends the energy storage life, avoids the "weakest link effect," and also ensures operational safety.

[0151] This embodiment proposes a multi-timescale hierarchical optimization and collaborative control strategy: at the low-frequency scale, battery switching states are optimized based on mixed-integer linear programming, simultaneously achieving state-of-charge (POC) balancing and low-frequency power command tracking; at the high-frequency scale, a supercapacitor switching optimization model is constructed to drive the capacitor to quickly compensate for high-frequency power fluctuations. Finally, a case study analysis of energy storage integrated into a wind farm is conducted. The results show that the hybrid energy storage power components controlled by the proposed method can be effectively decoupled from the output; the POC balancing effect and solution efficiency under the proposed method are superior to traditional methods, improving the efficiency, economy, and safety of the power station.

[0152] Example 3

[0153] like Figure 2 As shown, SOC represents the state of charge of the energy storage. Based on the same inventive concept as other embodiments, this embodiment introduces an optimized and coordinated control system for dynamically reconfigurable hybrid energy storage, including:

[0154] The power command calculation module is used to calculate the power command of energy-type energy storage and power-type energy storage in hybrid energy storage using a filtering function.

[0155] The first time scale division module is used to divide the energy storage operation time scale into several first time scales;

[0156] The second time scale division module is used to divide each first time scale into several second time scales;

[0157] The switching operation state calculation module for energy-type energy storage is used to establish a first objective function based on the energy storage state of charge using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The module calculates the switching operation state of energy-type energy storage in the mixed energy storage based on the first time scale.

[0158] The power-type energy storage switching operation state calculation module is used to establish a second objective function based on the switching operation state of energy-type energy storage, according to the energy storage state of charge and the power command of energy-type energy storage and the power command of power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The module calculates the switching operation state of power-type energy storage in the hybrid energy storage on a rolling basis based on the second time scale.

[0159] The collaborative control module is used to collaboratively control energy storage based on the switching operation status of energy-type energy storage and the switching operation status of power-type energy storage.

[0160] The specific functions of each module described above are explained in the relevant content of the method in Embodiment 1, and will not be repeated here.

[0161] Example 4

[0162] Based on the same inventive concept as other embodiments, this embodiment describes a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the methods of Embodiment 1 or 2 described above.

[0163] Example 5

[0164] Based on the same inventive concept as other embodiments, this embodiment introduces a computer program product, including computer instructions that, when executed by a processor, implement the steps of the methods described in Embodiment 1 or 2 above.

[0165] In summary, this invention addresses the efficiency loss caused by the "bottleneck effect" in traditional fixed topologies by optimizing the switching state of energy-type energy storage on a first time scale, aiming to minimize the difference between the energy storage state of charge (SBC) and the average SBC. Simultaneously, it optimizes the switching state of power-type energy storage on a second time scale, minimizing both SBC deviation and power command tracking error, thus overcoming the adaptability limitations of single-energy-type dynamic reconfiguration methods in hybrid energy storage scenarios. Ultimately, it achieves the organic coupling of the long-term power support capability of energy-type energy storage and the short-term high-rate response capability of power-type energy storage, significantly improving the power response accuracy, equipment utilization, and operational economy of hybrid energy storage systems. This solves the problem of multi-time-scale coordinated control of energy-type and power-type energy storage in dynamically reconfigurable hybrid energy storage systems in existing technologies.

[0166] 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.

[0167] 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 1 A device that provides the functions specified in one or more boxes.

[0168] 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.

[0169] 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.

[0170] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. An optimized collaborative control method for dynamically reconfigurable hybrid energy storage, characterized in that, include: The power command for energy-type energy storage and the power command for power-type energy storage in hybrid energy storage are calculated using a filtering function. The timescale of energy storage operation is divided into several first timescales; Each first time scale is divided into several second time scales; The first objective function is established based on the energy storage state of charge using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The switching operation state of energy storage in the mixed energy storage is calculated on a rolling basis based on the first time scale. Based on the switching operation state of energy-type energy storage, a second objective function is established using mixed integer linear programming according to the energy storage state of charge and the power command of energy-type energy storage and the power command of power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The switching operation state of power-type energy storage in the mixed energy storage is calculated on a rolling basis based on the second time scale. Energy storage is controlled in a coordinated manner based on the switching operation status of energy-type energy storage and power-type energy storage.

2. The optimized and coordinated control method for dynamically reconfigurable hybrid energy storage according to claim 1, characterized in that, The power command for the energy-type energy storage and the power command for the power-type energy storage are respectively expressed as: ； ； In the formula, Indicates a hybrid energy storage power command. Power commands indicating energy storage Power commands indicating power-type energy storage Indicates time The time constant is denoted by s, which represents the complex frequency domain operator.

3. The optimized and coordinated control method for dynamically reconfigurable hybrid energy storage according to claim 2, characterized in that, The first objective function is expressed as: ； In the formula, This indicates taking the minimum value. Indicates the first Line 1 The state of charge of columnar energy storage on the first time scale. Indicates the first Line 1 The average state of charge of columnar energy storage within the first time scale. This indicates the total number of rows in the energy storage arrangement. This indicates the total number of columns in the energy storage arrangement.

4. The optimized and coordinated control method for dynamically reconfigurable hybrid energy storage according to claim 3, characterized in that, The constraints of the first objective function include: current calculation constraints, energy storage state of charge calculation constraints, first power command constraints, current range constraints, energy storage state of charge range constraints, and first switching constraints.

5. The optimized and coordinated control method for dynamically reconfigurable hybrid energy storage according to claim 4, characterized in that, The current calculation constraint is expressed as follows: ； In the formula, Indicates the first Line 1 The current of column-type energy storage, This represents the total current of energy storage. This represents a pre-defined auxiliary variable used to represent the first... Line 1 The switch of the column energy storage type is closed and the first Column total When a switch is closed, there is The current is distributed evenly among the individual batteries; The constraints for calculating the energy storage state of charge are expressed as follows: ； In the formula, Indicates time The corresponding number Line 1 The state of charge of columnar energy storage on the first time scale. Indicates time The corresponding number Line 1 The state of charge of columnar energy storage on the first time scale. This indicates the period of rolling on the first time scale. Indicates the first Line 1 Battery capacity for column-type energy storage; The first power command constraint is expressed as: ； In the formula, This indicates that the state estimation is obtained from the measurement information. Line 1 The voltage of column-type energy storage, This represents the maximum steady-state current of energy storage. Indicates the current number Line 1 The on / off state of column-type energy storage; The current range constraint is expressed as follows: ； The energy storage state of charge range constraint is expressed as follows: ； In the formula, This represents the minimum state of charge of energy storage within the first time scale. This represents the maximum state of charge of energy storage within the first time scale; The first switch constraint is: when the first... When all switches of the column-type energy storage are in the open state, the first one is turned on. Bypass switch corresponding to column-type energy storage.

6. The optimized collaborative control method for dynamically reconfigurable hybrid energy storage according to claim 5, characterized in that, The calculation formula for the current calculation constraint is expressed as follows: ； In the formula, Indicates the first Columnar energy storage The current is evenly distributed among the batteries. Indicates the first Columnar energy storage The batteries were not evenly distributed.

7. The optimized collaborative control method for dynamically reconfigurable hybrid energy storage according to claim 1, characterized in that, The second objective function is expressed as: ； In the formula, This indicates taking the minimum value. Indicates the first Line 1 State of charge of power-type energy storage in the second time scale. Indicates the first Line 1 The average state of charge of column-type energy storage over the second time scale. This indicates the total number of rows in the power-type energy storage arrangement. This indicates the total number of columns in the power-type energy storage arrangement. A weighting coefficient representing the difference between the state of charge (SBC) of power-type energy storage and the average SBC. Power command representing power-type energy storage Actual power command for power-type energy storage The weighting coefficients of the difference, where .

8. The optimized and coordinated control method for dynamically reconfigurable hybrid energy storage according to claim 7, characterized in that, The constraints of the second objective function include: current calculation constraints, energy storage state of charge calculation constraints, second power command constraints, voltage range constraints, energy storage state of charge range constraints, and second switching constraints.

9. The optimized collaborative control method for dynamically reconfigurable hybrid energy storage according to claim 8, characterized in that, The second power command constraint is expressed as follows: ； In the formula, This indicates the maximum voltage of the power storage capacitor. Indicates the first Line 1 The current of power-type energy storage; The voltage range constraint is expressed as follows: ； In the formula, Indicates the current number Line 1 The switching state of column-type energy storage. Indicates the current number Line 1 The switching states of column-type energy storage. Indicates the first All switches for the column-type energy storage are in the off state. This represents the average voltage of energy storage. Indicates the safety factor. Indicates the first Line 1 The voltage of power-type energy storage, Indicates the current number Line 1 Switching status of column-type energy storage; The second switch constraint is: When the power command of the power storage is in the same direction, the switch of the forward voltage capacitor is turned on; When the power command of the power storage is reversed, the switch for reverse voltage is turned on. The bypass switch is activated when both the forward voltage capacitor switch and the reverse voltage capacitor switch are in the open state. However, the forward voltage capacitor switch, the reverse voltage capacitor switch, and the bypass switch cannot be activated simultaneously.

10. An optimized and coordinated control system for dynamically reconfigurable hybrid energy storage, characterized in that, include: The power command calculation module is used to calculate the power command of energy-type energy storage and power-type energy storage in hybrid energy storage using a filtering function. The first time scale division module is used to divide the energy storage operation time scale into several first time scales; The second time scale division module is used to divide each first time scale into several second time scales; The switching operation state calculation module for energy-type energy storage is used to establish a first objective function based on the energy storage state of charge using mixed integer linear programming. The objective is to minimize the difference between the energy storage state of charge at the target location and the average energy storage state of charge. The module calculates the switching operation state of energy-type energy storage in the mixed energy storage based on the first time scale. The power-type energy storage switching operation state calculation module is used to establish a second objective function based on the switching operation state of energy-type energy storage, according to the energy storage state of charge and the power command of energy-type energy storage and the power command of power-type energy storage. The objective is to minimize the sum of the difference between the energy storage state of charge at the target location and the average energy storage state of charge and the difference between the power command of power-type energy storage and the actual power command of power-type energy storage. The module calculates the switching operation state of power-type energy storage in the hybrid energy storage on a rolling basis based on the second time scale. The collaborative control module is used to collaboratively control energy storage based on the switching operation status of energy-type energy storage and the switching operation status of power-type energy storage.

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