Energy storage power control method based on coupling operation of multiple energy storage controllers

Abstract

The invention provides an energy storage power control method based on coupling operation of multiple energy storage controllers, and relates to the technical field of power system energy storage. The energy storage power control method based on coupling operation of multiple energy storage controllers comprises the following steps: establishing a central scheduling platform; collecting state information from the energy storage device through the central scheduling platform; predicting a load demand in a period of time in the future by using a load prediction algorithm; formulating a work plan of each energy storage device; and dynamically adjusting the work plan according to the actual situation. According to the invention, a central scheduling system is established to collect the state information of each energy storage device, and the optimal working mode of each energy storage device is calculated according to real-time load prediction data and the current state of the energy storage device. In this way, efficient operation of the whole energy storage system can be achieved, the operation cost of a power system is effectively reduced, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system energy storage, and in particular to an energy storage power control method based on the coupled operation of multiple energy storage controllers. Background Art

[0002] With the widespread application of renewable energy and the development of smart grids, the role of energy storage systems in power systems has become increasingly prominent. However, a single energy storage controller often has limitations in controlling energy storage power and is difficult to meet the needs of complex power systems. Therefore, a method for controlling energy storage power based on the coupled operation of multiple energy storage controllers is needed to improve the performance and reliability of energy storage systems.

[0003] As the proportion of renewable energy generation continues to increase, the power system has a growing demand for energy storage technology. However, a single energy storage unit has limitations in coping with large-scale, rapidly changing power demand. Existing energy storage control systems often only consider the optimal operation of a single energy storage unit, while ignoring the collaborative work between multiple energy storage units. Therefore, how to effectively manage and control multiple energy storage units so that they can play a greater role in the power system has become an urgent problem to be solved. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the deficiencies in the prior art, the present invention provides an energy storage power control method based on the coupled operation of multiple energy storage controllers, which solves the problem of how to effectively manage and control multiple energy storage units so that they can play a greater role in the power system.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for controlling energy storage power based on the coupled operation of multiple energy storage controllers, comprising the following steps:

[0008] Step 1: Create a platform:

[0009] Establishing a central dispatching platform that integrates the data interfaces of all energy storage devices;

[0010] Step 2: Collect information:

[0011] Collecting status information from the energy storage device through the central dispatching platform;

[0012] Step 3: Determine load demand:

[0013] Determine the target of energy storage power control according to the needs of the power system, and use the load forecasting algorithm to predict the load demand in the future;

[0014] Step 4: Develop a work plan:

[0015] Formulate a work plan for each energy storage device according to the load forecast result and the current state of the energy storage device;

[0016] Step 5: Adjust the status:

[0017] Sending instructions to the energy storage device via a communication network to adjust its charging and discharging state;

[0018] Step 6: Dynamic Adjustment:

[0019] Monitor the system operation in real time and dynamically adjust the work plan according to actual conditions.

[0020] As mentioned above, a central dispatching system is established to collect the status information of each energy storage device, and the optimal working mode of each energy storage device is calculated based on the real-time load forecast data and the current status of the energy storage device. In this way, the efficient operation of the entire energy storage system can be achieved, the operating cost of the power system can be effectively reduced, and the energy utilization efficiency can be improved.

[0021] Preferably, in step one, the energy storage device includes but is not limited to a battery energy storage system, a supercapacitor energy storage system and a flywheel energy storage system.

[0022] Preferably, in step 2, the status information includes but is not limited to remaining power, maximum charge and discharge power limit, temperature and health status.

[0023] Preferably, in step three, the load forecasting algorithm includes but is not limited to a machine learning algorithm, a time series analysis algorithm and a neural network algorithm.

[0024] Preferably, in step 4, the formulation of the work plan is achieved by using an optimization algorithm, which includes but is not limited to a genetic algorithm, a particle swarm optimization algorithm, and a mixed integer linear programming algorithm.

[0025] Preferably, in step five, the communication network includes but is not limited to a wireless communication network, a wired communication network or a combination of the two.

[0026] Preferably, in step six, the dynamic adjustment further includes:

[0027] (1) When an abnormality is detected in the state of the energy storage device, it automatically switches to the backup working mode to maintain the normal operation of the system;

[0028] (2) Adjust the load forecast results according to changes in external environmental conditions, such as weather forecast data.

[0029] As described above, by real-time monitoring and dynamic adjustment of the work plan, the present invention can cope with emergencies in the power system, such as abnormal state of the energy storage device or changes in external environmental conditions, thereby ensuring the stability and reliability of the system.

[0030] Preferably, the energy storage power control method based on the coupled operation of multiple energy storage controllers also includes:

[0031] (1) Setting up a user interface on the central dispatching platform so that operators can view the status of the energy storage system and perform manual intervention;

[0032] (2) Collecting and storing historical operating data of the energy storage device for subsequent analysis and optimization.

[0033] As mentioned above, by setting up a user interface on the central dispatching platform, operators can view the status of the energy storage system in real time and perform manual intervention, which not only improves the flexibility of the system, but also enhances the control ability of the energy storage system. At the same time, the historical operation data of the energy storage device is collected and stored, providing rich data support for subsequent analysis and optimization. Through data analysis, the operation strategy of the energy storage system can be further optimized and the overall performance of the system can be improved.

[0034] (III) Beneficial effects

[0035] The present invention provides a method for controlling energy storage power based on the coupled operation of multiple energy storage controllers, which has the following beneficial effects:

[0036] 1. Establish a central dispatching system to collect the status information of each energy storage device, and calculate the optimal working mode of each energy storage device based on the real-time load forecast data and the current status of the energy storage device. In this way, the efficient operation of the entire energy storage system can be achieved, the operating cost of the power system can be effectively reduced, and the energy utilization efficiency can be improved.

[0037] 2. Through real-time monitoring and dynamic adjustment of the work plan, the present invention can respond to emergencies in the power system, such as abnormal state of the energy storage device or changes in external environmental conditions, thereby ensuring the stability and reliability of the system.

[0038] 3. By setting up a user interface on the central dispatching platform, operators can view the status of the energy storage system in real time and perform manual intervention, which not only improves the flexibility of the system but also enhances the control ability of the energy storage system.

[0039] 4. Collect and store historical operation data of energy storage devices, providing rich data support for subsequent analysis and optimization. Through data analysis, the operation strategy of the energy storage system can be further optimized and the overall performance of the system can be improved.

[0040] In summary, the present invention provides a method for controlling energy storage power based on the coupled operation of multiple energy storage controllers, which not only improves the performance and reliability of the energy storage system, but also provides a strong guarantee for the stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic flow chart of the control method of the present invention;

[0042] Figure 2 It is a schematic flow chart of the control method of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Embodiment 1:

[0045] like Figure 1 As shown, an embodiment of the present invention provides an energy storage power control method based on the coupled operation of multiple energy storage controllers, comprising the following steps:

[0046] Step 1: Create a platform:

[0047] Establish a central dispatching platform that integrates the data interfaces of all energy storage devices;

[0048] Step 2: Collect information:

[0049] Collect status information from energy storage devices through a central dispatch platform;

[0050] Step 3: Determine load demand:

[0051] Determine the target of energy storage power control according to the needs of the power system, and use the load forecasting algorithm to predict the load demand in the future;

[0052] Step 4: Develop a work plan:

[0053] Formulate a work plan for each energy storage device based on the load forecast results and the current status of the energy storage device;

[0054] Step 5: Adjust the status:

[0055] Send instructions to the energy storage device through the communication network to adjust its charging and discharging status;

[0056] Step 6: Dynamic Adjustment:

[0057] Monitor system operation in real time and dynamically adjust work plans based on actual conditions.

[0058] In summary, by establishing a central dispatching system to collect the status information of each energy storage device, and calculating the optimal working mode of each energy storage device based on the real-time load forecast data and the current status of the energy storage device, the efficient operation of the entire energy storage system can be achieved, the operating cost of the power system can be effectively reduced, and the energy utilization efficiency can be improved.

[0059] Embodiment 2:

[0060] like Figure 1 As shown, an embodiment of the present invention provides an energy storage power control method based on the coupled operation of multiple energy storage controllers, comprising the following steps:

[0061] Step 1: Create a platform:

[0062] Establish a central dispatching platform that integrates the data interfaces of all energy storage devices, including but not limited to battery energy storage systems, supercapacitor energy storage systems, and flywheel energy storage systems;

[0063] Step 2: Collect information:

[0064] Collecting status information from energy storage devices through a central dispatching platform, where the status information includes but is not limited to remaining power, maximum charge and discharge power limit, temperature, and health status;

[0065] Step 3: Determine load demand:

[0066] Determine the target of energy storage power control according to the demand of the power system, and use the load forecasting algorithm to predict the load demand in the future, where the load forecasting algorithm includes but is not limited to machine learning algorithm, time series analysis algorithm and neural network algorithm;

[0067] Step 4: Develop a work plan:

[0068] Formulate a work plan for each energy storage device according to the load forecast result and the current state of the energy storage device, wherein the work plan is formulated by using an optimization algorithm, and the optimization algorithm includes but is not limited to a genetic algorithm, a particle swarm optimization algorithm, and a mixed integer linear programming algorithm;

[0069] Step 5: Adjust the status:

[0070] Sending instructions to the energy storage device via a communication network to adjust its charge and discharge state, wherein the communication network includes but is not limited to a wireless communication network, a wired communication network, or a combination of the two;

[0071] Step 6: Dynamic Adjustment:

[0072] Monitor the system operation in real time and dynamically adjust the work plan according to the actual situation. Secondly, dynamic adjustment also includes:

[0073] (1) When an abnormality is detected in the state of the energy storage device, it automatically switches to the backup working mode to maintain the normal operation of the system;

[0074] (2) Adjust the load forecast results according to changes in external environmental conditions, such as weather forecast data.

[0075] In summary, by real-time monitoring and dynamically adjusting the work plan, the present invention can cope with emergencies in the power system, such as abnormal state of the energy storage device or changes in external environmental conditions, thereby ensuring the stability and reliability of the system.

[0076] Embodiment three:

[0077] The difference between this embodiment and the second embodiment is that the energy storage power control method based on the coupled operation of multiple energy storage controllers further includes:

[0078] (1) Setting up a user interface on the central dispatching platform so that operators can view the status of the energy storage system and perform manual intervention;

[0079] (2) Collect and store historical operating data of energy storage devices for subsequent analysis and optimization.

[0080] In summary, by setting up a user interface on the central dispatching platform, operators can view the status of the energy storage system in real time and perform manual intervention, which not only improves the flexibility of the system, but also enhances the control ability of the energy storage system; at the same time, the historical operation data of the energy storage device is collected and stored, providing rich data support for subsequent analysis and optimization. Through data analysis, the operation strategy of the energy storage system can be further optimized and the overall performance of the system can be improved.

[0081] Embodiment 4:

[0082] There are three energy storage controllers A, B, and C, which are connected to different nodes of the power system. First, a central dispatching platform is established, which integrates the data interfaces of the three energy storage controllers A, B, and C, and considers the power transmission and mutual influence between the controllers. Then, the control objectives are determined to be power balance and voltage stability. The control strategy is designed as follows:

[0083] Power allocation strategy: According to the load demand and energy storage capacity of each node, the output power of the three energy storage controllers is reasonably allocated. For example, when the load of node A is large, the output power of energy storage controller A is increased, while the output power of energy storage controllers B and C is reduced.

[0084] Coordinated control strategy: When the power system experiences voltage fluctuations, the three energy storage controllers work together to adjust the output power to maintain voltage stability. For example, when the voltage increases, the output power of the energy storage controller is reduced; when the voltage decreases, the output power of the energy storage controller is increased.

[0085] After implementing the control strategy, the operating status of the energy storage system is monitored in real time, including parameters such as power, voltage, and current. The control strategy is adjusted and optimized by evaluating the effect of the control strategy, such as power balance, voltage stability, and other indicators.

[0086] Embodiment five:

[0087] In a large energy storage system, there are several energy storage controllers distributed in different geographical locations. In order to achieve effective control of energy storage power, an energy storage power control method based on the coupled operation of multiple energy storage controllers is adopted.

[0088] First, a central dispatching platform is established, taking into account factors such as communication delay and power transmission loss. Then, the control goal is to improve the reliability and efficiency of the energy storage system. The control strategy is designed as follows:

[0089] The central dispatching platform collects status information from energy storage devices, including but not limited to remaining power, maximum charge and discharge power limits, temperature, and health status, and works together to achieve distributed control of energy storage power. For example, when a certain energy storage controller fails, other energy storage controllers can automatically adjust the output power to ensure the normal operation of the system.

[0090] According to the needs of the power system, the target of energy storage power control is determined, and the load forecasting algorithm is used to predict the load demand in the future. The load forecasting algorithm includes but is not limited to machine learning algorithms, time series analysis algorithms and neural network algorithms, which optimize the output power of each energy storage controller to improve the efficiency and economy of the system.

[0091] According to the load forecast results and the current status of the energy storage device, a work plan for each energy storage device is formulated, wherein the work plan is formulated by using an optimization algorithm, and the optimization algorithm includes but is not limited to a genetic algorithm, a particle swarm optimization algorithm, and a mixed integer linear programming algorithm.

[0092] Send instructions to the energy storage device through the communication network to adjust its charging and discharging status, monitor the system operation in real time, and dynamically adjust the work plan according to the actual situation. Secondly, dynamic adjustment also includes:

[0093] (1) When an abnormality is detected in the state of the energy storage device, it automatically switches to the backup working mode to maintain the normal operation of the system;

[0094] (2) Adjust the load forecast results according to changes in external environmental conditions, such as weather forecast data. At the same time, continuously improve and optimize the control strategy to adapt to the changing needs of the power system.

[0095] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling energy storage power based on the coupled operation of multiple energy storage controllers, characterized in that: The following steps are involved: Step 1: Create a platform: Establishing a central dispatching platform that integrates the data interfaces of all energy storage devices; Step 2: Collect information: Collecting status information from the energy storage device through the central dispatching platform; Step 3: Determine load demand: Determine the target of energy storage power control according to the needs of the power system, and use the load forecasting algorithm to predict the load demand in the future; Step 4: Develop a work plan: Formulate a work plan for each energy storage device according to the load forecast result and the current state of the energy storage device; Step 5: Adjust the status: Sending instructions to the energy storage device via a communication network to adjust its charging and discharging state; Step 6: Dynamic Adjustment: Monitor the system operation in real time and dynamically adjust the work plan according to actual conditions.

2. The energy storage power control method based on the coupled operation of multiple energy storage controllers according to claim 1 is characterized in that: In step one, the energy storage device includes but is not limited to a battery energy storage system, a supercapacitor energy storage system and a flywheel energy storage system.

3. The energy storage power control method based on the coupled operation of multiple energy storage controllers according to claim 1 is characterized in that: In step 2, the status information includes but is not limited to remaining power, maximum charge and discharge power limit, temperature and health status.

4. The energy storage power control method based on the coupled operation of multiple energy storage controllers according to claim 1 is characterized in that: In step three, the load forecasting algorithm includes but is not limited to a machine learning algorithm, a time series analysis algorithm, and a neural network algorithm.

5. The energy storage power control method based on the coupled operation of multiple energy storage controllers according to claim 1 is characterized in that: In step 4, the work plan is formulated by using an optimization algorithm, which includes but is not limited to a genetic algorithm, a particle swarm optimization algorithm, and a mixed integer linear programming algorithm.

6. The energy storage power control method based on the coupled operation of multiple energy storage controllers according to claim 1 is characterized in that: In step five, the communication network includes but is not limited to a wireless communication network, a wired communication network or a combination of the two.

7. The energy storage power control method based on the coupled operation of multiple energy storage controllers according to claim 1 is characterized in that: In step six, the dynamic adjustment further includes: (1) When an abnormality is detected in the state of the energy storage device, it automatically switches to the backup working mode to maintain the normal operation of the system; (2) Adjust the load forecast results according to changes in external environmental conditions, such as weather forecast data.

8. A method for controlling energy storage power based on coupled operation of multiple energy storage controllers according to any one of claims 1 to 7, characterized in that: Also includes: (1) Setting up a user interface on the central dispatching platform so that operators can view the status of the energy storage system and perform manual intervention; (2) Collecting and storing historical operating data of the energy storage device for subsequent analysis and optimization.

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