Artificial intelligence-based energy storage power management system, method and device

Abstract

The application provides an energy storage power management system, method and device based on artificial intelligence, comprising: analyzing the energy distribution state of the region where the energy storage power is located and the electric vehicle charging distribution state through big data statistical analysis; constructing a charging energy storage power supply distribution scheduling platform according to the region energy distribution state and the electric vehicle charging distribution state, and performing energy storage power supply distribution scheduling distribution; according to the charging energy storage power supply distribution scheduling platform, the charging energy storage power supply distribution scheduling platform is networked with the terminal, the electric vehicle charging terminal and the mobile terminal, and a charging energy storage power supply distribution scheduling control network is constructed; according to the charging energy storage power supply distribution scheduling control network, an artificial intelligence energy storage power management model is constructed and trained and optimized, the energy storage power supply distribution scheduling distribution is intelligently managed to adapt to the region energy distribution state, and the energy storage power supply distribution scheduling distribution is continuously improved to adapt to the region energy distribution and the electric vehicle charging distribution.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for energy storage power supply in new energy distributed power sources, and more specifically, to an energy storage power management system, method, and device based on artificial intelligence. Background Technology

[0002] Currently, with the development of new energy power technologies, regional energy distribution is uneven. Problems remain to be solved, including how to analyze the energy and electric vehicle charging distribution in the region where energy storage power is located, how to address the imbalance between charging energy storage power and regional energy and electric vehicle charging, how to construct a charging energy storage scheduling and control network, how to utilize cloud computing power and the communication network between electric vehicle charging and mobile terminals, how to improve energy storage power management and allocation to adapt to regional energy distribution and electric vehicle charging distribution, and how to improve energy distribution and power scheduling and allocation. Therefore, it is necessary to propose an artificial intelligence-based energy storage power management system, method, and device to at least partially solve the problems existing in the current technology. Summary of the Invention

[0003] The summary of this invention introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. The summary of this invention does not mean that it attempts to limit the key features and essential technical features of the claimed technical solution, nor does it mean that it attempts to determine the scope of protection of the claimed technical solution.

[0004] To at least partially solve the above problems, the present invention provides an artificial intelligence-based energy storage power management system, comprising:

[0005] The regional energy distribution statistics subsystem uses big data statistical analysis to determine the energy distribution status and electric vehicle charging status of the regions where energy storage power sources are located.

[0006] The charging and energy storage power distribution and dispatching subsystem constructs a charging and energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status, and performs energy storage power distribution and dispatching allocation.

[0007] The charging energy storage dispatch and control network subsystem, based on the charging energy storage power distribution and dispatch platform, connects the charging energy storage power distribution and dispatch platform with the cloud, electric vehicle charging terminals and mobile terminals to form a communication network and construct a charging energy storage power distribution and dispatch control network.

[0008] The AI-powered energy storage management subsystem constructs and trains an AI-powered energy storage management model based on the charging energy storage power distribution and dispatch control network. It intelligently manages the distribution and dispatch of energy storage power to adapt to the regional energy distribution status and continuously improves the rational adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution.

[0009] Preferably, the regional energy distribution statistics subsystem includes:

[0010] The energy distribution information acquisition subsystem acquires big data information on the energy distribution of the energy storage power source's location through energy big data collection.

[0011] The electric vehicle charging statistics subsystem obtains statistical pattern data of electric vehicle charging information based on the statistics of electric vehicle charging information.

[0012] The energy charging status analysis subsystem analyzes the energy distribution status and electric vehicle charging status of the region where the energy storage power source is located based on big data information on energy distribution and statistical data on electric vehicle charging information.

[0013] Regional energy distribution big data information includes: natural energy distribution and power grid energy distribution and charging information.

[0014] Preferably, the charging energy storage power distribution and dispatching subsystem includes:

[0015] The energy storage power distribution and dispatching subsystem constructs a charging and energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status.

[0016] The distributed dispatch platform control subsystem, based on the charging energy storage power distributed dispatch platform, performs distributed dispatch and allocation control of energy storage power, controls the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and controls the power output of the allocated energy storage power to adapt to the electric vehicle charging distribution status.

[0017] The deployment of the charging and energy storage power distribution and dispatching platform includes areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information.

[0018] Preferably, the charging and energy storage dispatch control network subsystem includes:

[0019] The dispatch platform cloud communication subsystem transmits data between the charging and energy storage power distribution dispatch platform and the cloud based on the charging and energy storage power distribution dispatch platform.

[0020] The platform's electric vehicle terminal networking subsystem utilizes cloud communication data transmission to connect electric vehicle charging terminals and mobile terminal communication networks, constructing a distributed scheduling and control network for charging and energy storage power sources.

[0021] Preferably, the artificial intelligence-based energy storage power management subsystem includes:

[0022] The intelligent power management model training subsystem constructs an artificial intelligence energy storage power management model based on the charging energy storage power distribution and dispatch control network, and uses cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model.

[0023] The intelligent energy storage power management subsystem optimizes the intelligent energy storage power management model, intelligently manages the distribution and allocation of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy of energy storage power to continuously improve the rational adaptation of energy storage power distribution and electric vehicle charging distribution to the regional energy distribution.

[0024] This invention relates to an artificial intelligence-based energy storage power management method, comprising:

[0025] S01 uses big data statistical analysis to determine the energy distribution and electric vehicle charging distribution in the region where the energy storage power source is located.

[0026] S02, Based on the regional energy distribution and electric vehicle charging distribution, construct a charging energy storage power distribution and dispatching platform to carry out energy storage power distribution and dispatching.

[0027] S03, Based on the charging energy storage power distribution and dispatching platform, connect the charging energy storage power distribution and dispatching platform with the cloud, electric vehicle charging terminals and mobile terminals to form a communication network and build a charging energy storage power distribution and dispatching control network.

[0028] S04. Based on the charging and energy storage power distribution and dispatch control network, construct an artificial intelligence energy storage power management model and train and optimize it to intelligently manage the distribution and dispatch of energy storage power to adapt to the regional energy distribution status and continuously improve the reasonable adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution.

[0029] Preferably, S01 includes:

[0030] S011, acquire big data information on the energy distribution of the energy storage power source in the region through energy big data collection;

[0031] S012, Based on the statistics of electric vehicle charging information, obtain statistical data on the patterns of electric vehicle charging information;

[0032] S013, Based on big data information on energy distribution and statistical data on electric vehicle charging information, analyze the energy distribution status and electric vehicle charging status of the region where the energy storage power source is located through big data statistical analysis.

[0033] Regional energy distribution big data information includes: natural energy distribution and power grid energy distribution and charging information.

[0034] Preferably, S02 includes:

[0035] S021. Based on the regional energy distribution and electric vehicle charging distribution, construct a charging energy storage power distribution and dispatching platform.

[0036] S022, Based on the charging energy storage power distribution and dispatching platform, carry out energy storage power distribution and dispatching control, control the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and control the power output of the distributed energy storage power to adapt to the electric vehicle charging distribution status.

[0037] The deployment of the charging and energy storage power distribution and dispatching platform includes areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information.

[0038] Preferably, S03 includes:

[0039] S031, Dispatch platform cloud communication subsystem, according to the charging energy storage power distribution dispatch platform, conducts platform-to-cloud communication data transmission between the charging energy storage power distribution dispatch platform and the cloud.

[0040] S032, the platform's electric vehicle terminal networking subsystem, utilizes cloud communication data transmission to connect electric vehicle charging terminals and mobile terminal communication networks, constructing a distributed scheduling and control network for charging and energy storage power sources.

[0041] S041. Based on the charging energy storage power distribution and dispatch control network, construct an artificial intelligence energy storage power management model, and use cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model.

[0042] S042, by optimizing the intelligent energy storage power management model, intelligently manages the distribution and scheduling of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy of energy storage power, continuously improving the rational adaptation of the distribution and scheduling of energy storage power to the regional energy distribution and electric vehicle charging distribution.

[0043] The artificial intelligence-based energy storage power management device includes: the circuit control device of the artificial intelligence-based energy storage power management system as described above.

[0044] Compared with the prior art, the present invention has at least the following beneficial effects:

[0045] This invention provides an artificial intelligence-based energy storage power management system, method, and apparatus, which can improve the matching of new energy power management with the balanced distribution of regional energy; more accurately analyze the distribution of energy and electric vehicle charging in the region where the energy storage power is located; improve the energy utilization rate of balanced scheduling between charging energy storage power and regional energy and electric vehicle charging; construct a charging energy storage scheduling and control network and utilize cloud computing power and electric vehicle charging and mobile terminal communication networks to significantly improve information transmission and energy transmission efficiency; improve the adaptation of energy storage power management and allocation to regional energy distribution and make energy storage power adapt to regional energy distribution and electric vehicle charging distribution; significantly improve the continuous optimization of energy distribution and power scheduling and allocation; and has significant implications and remarkable effects.

[0046] The artificial intelligence-based energy storage power management system, method, and apparatus described in this invention, along with other advantages, objectives, and features of this invention, will be partly apparent from the following description and partly understood by those skilled in the art through study and practice of this invention. Attached Figure Description

[0047] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0048] Figure 1 This is a diagram of an embodiment of the artificial intelligence-based energy storage power management system described in this invention.

[0049] Figure 2 This is a diagram of an embodiment of the pneumatic clutch assembly of the artificial intelligence-based energy storage power management system described in this invention. Detailed Implementation

[0050] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments, so that those skilled in the art can implement it based on the specification; as shown in the figures, the present invention provides an artificial intelligence-based energy storage power management system, including:

[0051] The regional energy distribution statistics subsystem uses big data statistical analysis to determine the energy distribution status and electric vehicle charging status of the regions where energy storage power sources are located.

[0052] The charging and energy storage power distribution and dispatching subsystem constructs a charging and energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status, and performs energy storage power distribution and dispatching allocation.

[0053] The charging energy storage dispatch and control network subsystem, based on the charging energy storage power distribution and dispatch platform, connects the charging energy storage power distribution and dispatch platform with the cloud, electric vehicle charging terminals and mobile terminals to form a communication network and construct a charging energy storage power distribution and dispatch control network.

[0054] The AI-powered energy storage management subsystem constructs and trains an AI-powered energy storage management model based on the charging energy storage power distribution and dispatch control network. It intelligently manages the distribution and dispatch of energy storage power to adapt to the regional energy distribution status and continuously improves the rational adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution.

[0055] The principles and effects of the above technical solution are as follows: Regional Energy Distribution Statistics Subsystem 01 analyzes the energy distribution status and electric vehicle charging distribution status of the region where the energy storage power source is located through big data statistical analysis; Charging Energy Storage Power Source Distributed Dispatch and Scheduling Subsystem 02 constructs a charging energy storage power source distributed dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status, and performs distributed dispatching and allocation of energy storage power sources; Charging Energy Storage Dispatch and Control Network Subsystem 03 connects the charging energy storage power source distributed dispatching platform with the cloud, electric vehicle charging terminals, and mobile terminals to form a communication network, constructing a charging energy storage power source distributed dispatching and control network; Artificial Intelligence Energy Storage Power Source Management Subsystem 04 constructs an artificial intelligence energy storage power source management model based on the charging energy storage power source distributed dispatching and control network, and trains and optimizes it for intelligent management of energy storage power sources. The energy storage power distribution and dispatch system adapts to the regional energy distribution status, continuously improving the rational adaptation of energy storage power distribution and electric vehicle charging distribution. It enhances the balance between new energy power management and regional energy distribution, enabling more accurate analysis of the energy and electric vehicle charging distribution in the region where the energy storage power is located. It improves the energy utilization rate of balanced dispatch between charging energy storage power and regional energy and electric vehicle charging. It can construct a charging energy storage dispatch and control network and utilize cloud computing power and electric vehicle charging and mobile terminal communication networks to significantly improve information transmission and energy transmission efficiency. It improves the adaptation of energy storage power management and dispatch to regional energy distribution and enables energy storage power to adapt to regional energy and electric vehicle charging distribution. It significantly improves the continuous optimization of energy distribution and power dispatch and dispatch. This has significant implications and remarkable effects.

[0056] In one embodiment, a regional energy distribution statistics subsystem includes:

[0057] The energy distribution information acquisition subsystem acquires big data information on the energy distribution of the energy storage power source's location through energy big data collection.

[0058] The electric vehicle charging statistics subsystem obtains statistical pattern data of electric vehicle charging information based on the statistics of electric vehicle charging information.

[0059] The energy charging status analysis subsystem analyzes the energy distribution status and electric vehicle charging status of the region where the energy storage power source is located based on big data information on energy distribution and statistical data on electric vehicle charging information.

[0060] Regional energy distribution big data information includes: natural power distribution and charging information, as well as power grid distribution and charging information.

[0061] The principle and effects of the above technical solution are as follows: The energy distribution information acquisition subsystem 11 acquires energy distribution big data information of the region where the energy storage power source is located through energy big data acquisition; the electric vehicle charging statistics subsystem 12 acquires statistical data on electric vehicle charging information patterns based on electric vehicle charging information statistics; the energy charging status analysis subsystem 13 analyzes the energy distribution status and electric vehicle charging distribution status of the region where the energy storage power source is located through big data statistical analysis based on the energy distribution big data information and the electric vehicle charging information patterns; the regional energy distribution big data information includes: natural power distribution charging information and grid power distribution charging information; it can improve the matching of new energy power source management with regional energy distribution balance, and can more accurately analyze the location of the energy storage power source. Regional energy and electric vehicle charging distribution; when the overlap between the charging areas of electric vehicles and the charging areas of natural and grid power is higher, the allocation of energy storage power sources to the natural energy distribution will be higher; when the overlap between the charging areas of electric vehicles and the charging areas of natural and grid power is higher, the allocation of energy storage power sources to the grid power distribution will be higher; and the allocation will be dynamically scheduled according to the charging information of natural and grid power and the charging status of electric vehicles, thereby improving the management of new energy sources and the balance of regional energy distribution, reducing scheduling efficiency and allocation differences.

[0062] In one embodiment, the charging energy storage power distribution and dispatching subsystem includes:

[0063] The energy storage power distribution and dispatching subsystem constructs a charging and energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status.

[0064] The distributed dispatch platform control subsystem, based on the charging energy storage power distributed dispatch platform, performs distributed dispatch and allocation control of energy storage power, controls the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and controls the power output of the allocated energy storage power to adapt to the electric vehicle charging distribution status.

[0065] The deployment of the charging and energy storage power distribution and dispatching platform includes areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information.

[0066] The principles and effects of the above technical solution are as follows: The energy storage power distribution and dispatching subsystem constructs a charging energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status; the distribution and dispatching platform control subsystem performs energy storage power distribution and dispatching control based on the charging energy storage power distribution and dispatching platform, controlling the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and controlling the power output of the distributed energy storage power to adapt to the electric vehicle charging distribution status; the deployment of the charging energy storage power distribution and dispatching platform includes deployment in areas with dense regional energy distribution information and dense electric vehicle charging distribution information; it can improve the energy utilization rate of balanced dispatching between charging energy storage power and regional energy and electric vehicle charging; the charging energy storage power distribution and dispatching platform includes energy dispatching path planning based on the regional energy distribution status, combined with regional energy supply of natural electricity, grid electricity, or emergency power generation centralized charging energy storage power, optimizing charging energy supply and energy dispatching paths.

[0067] In one embodiment, the charging energy storage scheduling and control network subsystem includes:

[0068] The dispatch platform cloud communication subsystem transmits data between the charging and energy storage power distribution dispatch platform and the cloud based on the charging and energy storage power distribution dispatch platform.

[0069] The platform's electric vehicle terminal networking subsystem utilizes cloud communication data transmission to connect electric vehicle charging terminals and mobile terminal communication networks, constructing a distributed scheduling and control network for charging and energy storage power sources.

[0070] The principle and effect of the above technical solution are as follows: The cloud communication subsystem of the dispatching platform transmits data between the charging energy storage power distribution dispatching platform and the cloud based on the charging energy storage power distribution dispatching platform; the electric vehicle terminal networking subsystem of the platform uses cloud communication data transmission to connect the electric vehicle charging terminal and the mobile terminal communication network to build a charging energy storage power distribution dispatching control network; it can build a charging energy storage dispatching control network and utilize cloud computing power and the electric vehicle charging and mobile terminal communication network to significantly improve information transmission and energy transmission efficiency.

[0071] In one embodiment, the artificial intelligence-based energy storage power management subsystem includes:

[0072] The intelligent power management model training subsystem constructs an artificial intelligence energy storage power management model based on the charging energy storage power distribution and dispatch control network, and uses cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model.

[0073] The intelligent energy storage power management subsystem optimizes the intelligent energy storage power management model, intelligently manages the distribution and allocation of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy of energy storage power to continuously improve the rational adaptation of energy storage power distribution and electric vehicle charging distribution to the regional energy distribution.

[0074] The principles and effects of the above technical solution are as follows: The intelligent power management model training subsystem constructs an artificial intelligence energy storage power management model based on the charging energy storage power distribution and dispatch control network, and uses cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model; The intelligent energy storage power management subsystem, through optimizing the intelligent energy storage power management model, intelligently manages the distribution and dispatch of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy distribution of energy storage power, continuously improving the rational adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution; It can improve the adaptation of energy storage power management and allocation to the regional energy distribution and make energy storage power adapt to the regional energy distribution and electric vehicle charging distribution; It significantly improves the continuous optimization of energy distribution and power dispatch and allocation; It has great significance and significant effects.

[0075] This invention relates to an artificial intelligence-based energy storage power management method, comprising:

[0076] S01 uses big data statistical analysis to determine the energy distribution and electric vehicle charging distribution in the region where the energy storage power source is located.

[0077] S02, Based on the regional energy distribution and electric vehicle charging distribution, construct a charging energy storage power distribution and dispatching platform to carry out energy storage power distribution and dispatching.

[0078] S03, Based on the charging energy storage power distribution and dispatching platform, connect the charging energy storage power distribution and dispatching platform with the cloud, electric vehicle charging terminals and mobile terminals to form a communication network and build a charging energy storage power distribution and dispatching control network.

[0079] S04. Based on the charging and energy storage power distribution and dispatch control network, construct an artificial intelligence energy storage power management model and train and optimize it to intelligently manage the distribution and dispatch of energy storage power to adapt to the regional energy distribution status and continuously improve the reasonable adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution.

[0080] The principle and effects of the above technical solution are as follows: Through big data statistical analysis of the energy distribution and electric vehicle charging distribution in the region where the energy storage power source is located; based on the regional energy distribution and electric vehicle charging distribution, a charging energy storage power source distribution and dispatching platform is constructed to perform energy storage power source distribution and dispatching; based on the charging energy storage power source distribution and dispatching platform, a communication network is established with the cloud, electric vehicle charging terminals, and mobile terminals to construct a charging energy storage power source distribution and dispatching control network; based on the charging energy storage power source distribution and dispatching control network, an artificial intelligence energy storage power source management model is constructed and trained and optimized to intelligently manage the distribution and dispatching of energy storage power sources to adapt to the regional energy distribution, continuously improving the distribution and dispatching capabilities of energy storage power sources. The energy storage system can be rationally adapted to the regional energy distribution and electric vehicle charging distribution; it can improve the management of new energy sources and the balanced matching of regional energy distribution; it can more accurately analyze the regional energy and electric vehicle charging distribution of energy storage sources; it can improve the energy utilization rate of balanced scheduling between charging energy storage sources and regional energy and electric vehicle charging; it can build a charging energy storage scheduling and control network and utilize cloud computing power and electric vehicle charging and mobile terminal communication networks to significantly improve information transmission and energy transmission efficiency; it can improve the adaptation of energy storage source management and allocation to regional energy distribution and make energy storage sources adapt to regional energy and electric vehicle charging distribution; it can significantly improve the continuous optimization of energy distribution and power scheduling and allocation; it has significant significance and remarkable effects.

[0081] In one embodiment, S01 includes:

[0082] S011, acquire big data information on the energy distribution of the energy storage power source in the region through energy big data collection;

[0083] S012, Based on the statistics of electric vehicle charging information, obtain statistical data on the patterns of electric vehicle charging information;

[0084] S013, Based on big data information on energy distribution and statistical data on electric vehicle charging information, analyze the energy distribution status and electric vehicle charging status of the region where the energy storage power source is located through big data statistical analysis.

[0085] Regional energy distribution big data information includes: natural power distribution and charging information, as well as power grid distribution and charging information.

[0086] The principle and effect of the above technical solution are as follows: It acquires big data information on energy distribution in the region where the energy storage power source is located through energy big data collection; it obtains statistical data on electric vehicle charging information patterns based on electric vehicle charging information statistics; and it performs big data statistical analysis on the energy distribution status and electric vehicle charging distribution status in the region where the energy storage power source is located based on the energy distribution big data information and the electric vehicle charging information patterns. The regional energy distribution big data information includes: natural power distribution charging information and grid power distribution charging information; it can improve the matching between new energy power source management and regional energy distribution balance, and can more accurately analyze the energy and electric vehicle charging distribution in the region where the energy storage power source is located; when the natural power distribution... When the overlap between the charging information, grid power distribution, and electric vehicle charging distribution is higher, the allocation of energy storage power to the natural power distribution will be higher. Furthermore, when the overlap between the charging areas of electric vehicles and the grid power distribution is higher, the allocation of energy storage power to the grid power distribution will also be higher. Dynamic scheduling and allocation will follow the changes in the charging information and the electric vehicle charging distribution status, improving the management of new energy sources and the balance of regional energy distribution, while reducing scheduling efficiency and allocation discrepancies.

[0087] In one embodiment, S02 includes:

[0088] S021. Based on the regional energy distribution and electric vehicle charging distribution, construct a charging energy storage power distribution and dispatching platform.

[0089] S022, Based on the charging energy storage power distribution and dispatching platform, carry out energy storage power distribution and dispatching control, control the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and control the power output of the distributed energy storage power to adapt to the electric vehicle charging distribution status.

[0090] The deployment of the charging and energy storage power distribution and dispatching platform includes areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information.

[0091] The principles and effects of the above technical solution are as follows: A charging energy storage power distribution and dispatching platform is constructed based on the regional energy distribution and electric vehicle charging distribution. Based on this platform, energy storage power distribution and dispatching control is implemented, controlling the energy input of the dispatched energy storage power to adapt to the regional energy distribution and the power output of the distributed energy storage power to adapt to the electric vehicle charging distribution. The deployment of the charging energy storage power distribution and dispatching platform includes areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information. It can construct a charging energy storage dispatching and control network and utilize cloud computing power and the communication network between electric vehicle charging and mobile terminals, significantly improving information transmission and energy transmission efficiency. The charging energy storage power distribution and dispatching platform includes energy dispatching path planning based on the regional energy distribution, combined with regional energy supply of natural electricity, grid electricity, or emergency power generation centralized charging energy storage power, optimizing charging energy supply and energy dispatching paths.

[0092] In one embodiment, S03 includes:

[0093] S031, Dispatch platform cloud communication subsystem, according to the charging energy storage power distribution dispatch platform, conducts platform-to-cloud communication data transmission between the charging energy storage power distribution dispatch platform and the cloud.

[0094] S032, the platform's electric vehicle terminal networking subsystem, utilizes cloud communication data transmission to connect electric vehicle charging terminals and mobile terminal communication networks, constructing a distributed scheduling and control network for charging and energy storage power sources.

[0095] S041. Based on the charging energy storage power distribution and dispatch control network, construct an artificial intelligence energy storage power management model, and use cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model.

[0096] S042, by optimizing the intelligent energy storage power management model, intelligently manages the distribution and scheduling of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy of energy storage power, continuously improving the rational adaptation of the distribution and scheduling of energy storage power to the regional energy distribution and electric vehicle charging distribution.

[0097] The principles and effects of the above technical solution are as follows: The cloud communication subsystem of the dispatching platform, based on the charging and energy storage power distribution dispatching platform, conducts platform-to-cloud communication data transmission between the charging and energy storage power distribution dispatching platform and the cloud; the electric vehicle terminal networking subsystem of the platform, utilizing cloud communication data transmission, connects the electric vehicle charging terminals and mobile terminal communication networks to construct a charging and energy storage power distribution dispatching control network; based on the charging and energy storage power distribution dispatching control network, an artificial intelligence energy storage power management model is constructed, and cloud computing power is used to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model; through optimizing the intelligent energy storage power management model, the intelligent management of energy storage power distribution dispatching and allocation adapts to the regional energy distribution status, and allocates the input and output energy distribution of energy storage power, continuously improving the rational adaptation of energy storage power distribution dispatching and allocation to regional energy distribution and electric vehicle charging distribution; it can improve the adaptation of energy storage power management and allocation to regional energy distribution and make energy storage power adapt to regional energy distribution and electric vehicle charging distribution; it significantly improves the continuous optimization of energy distribution and power dispatching and allocation.

[0098] The present invention relates to an artificial intelligence-based energy storage power management device, comprising: a circuit control device for an artificial intelligence-based energy storage power management system as described above.

[0099] The principle and effects of the above technical solution are as follows: The present invention is an artificial intelligence-based energy storage power management device, comprising: the circuit control device of the artificial intelligence-based energy storage power management system as described above; it can improve the matching of new energy power management with regional energy distribution balance, and can more accurately analyze the energy and electric vehicle charging distribution in the region where the energy storage power is located; it can improve the energy utilization rate of balanced scheduling between charging energy storage power and regional energy and electric vehicle charging; it can construct a charging energy storage scheduling and control network and utilize cloud computing power and electric vehicle charging and mobile terminal communication networks to significantly improve information transmission and energy transmission efficiency; it can improve the adaptation of energy storage power management and allocation to regional energy distribution and make energy storage power adapt to regional energy distribution and electric vehicle charging distribution; it significantly improves the continuous optimization of energy distribution and power scheduling and allocation; and it has significant implications and remarkable effects.

[0100] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. Other modifications can be easily made by those skilled in the art. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. An artificial intelligence based energy storage power management system, characterized in that, include: The regional energy distribution statistics subsystem uses big data statistical analysis to determine the energy distribution status and electric vehicle charging status of the regions where energy storage power sources are located. The charging and energy storage power distribution and dispatching subsystem constructs a charging and energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status, and performs energy storage power distribution and dispatching allocation. The charging energy storage dispatch and control network subsystem, based on the charging energy storage power distribution and dispatch platform, connects the charging energy storage power distribution and dispatch platform with the cloud, electric vehicle charging terminals and mobile terminals to form a communication network and construct a charging energy storage power distribution and dispatch control network. The AI-powered energy storage management subsystem constructs an AI-powered energy storage management model based on the charging energy storage power distribution and dispatch control network, and trains and optimizes it to intelligently manage the distribution and dispatch of energy storage power to adapt to the regional energy distribution status, and continuously improves the rational adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution. The regional energy distribution statistics subsystem includes: The energy distribution information acquisition subsystem acquires big data information on the energy distribution of the energy storage power source's location through energy big data collection. The electric vehicle charging statistics subsystem obtains statistical pattern data of electric vehicle charging information based on the statistics of electric vehicle charging information. The energy charging status analysis subsystem analyzes the energy distribution status and electric vehicle charging status of the region where the energy storage power source is located based on big data information on energy distribution and statistical data on electric vehicle charging information. Regional energy distribution big data information includes: natural electricity distribution and charging information, as well as grid electricity distribution and charging information; When the overlap between the charging areas of electric vehicles and the charging areas of natural and grid power distribution is higher than that of electric vehicles, the energy storage power supply will be allocated more to the natural power distribution. New energy power management is matched with the balanced distribution of regional energy, and the distribution of energy and electric vehicle charging in the region where the energy storage power is located is accurately analyzed; the energy is balanced and scheduled between the charging energy storage power and regional energy and electric vehicle charging; a charging energy storage scheduling and control network is constructed and cloud computing power and electric vehicle charging and mobile terminal communication network are utilized; the energy storage power management and allocation are adapted to the regional energy distribution and the energy storage power is adapted to the regional energy distribution and electric vehicle charging distribution. The charging and energy storage power distribution and dispatching subsystem includes: The energy storage power distribution and dispatching subsystem constructs a charging and energy storage power distribution and dispatching platform based on the regional energy distribution status and electric vehicle charging distribution status. The distributed dispatch platform control subsystem, based on the charging energy storage power distributed dispatch platform, performs distributed dispatch and allocation control of energy storage power, controls the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and controls the power output of the allocated energy storage power to adapt to the electric vehicle charging distribution status. The deployment of the charging and energy storage power distribution and dispatching platform includes deployment in areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information. The charging energy storage power distribution and dispatching platform includes energy dispatching path planning based on the regional energy distribution status and the regional energy supply of natural electricity, grid electricity or emergency power generation centralized charging energy storage power, to optimize the charging energy supply and energy dispatching path.

2. The artificial intelligence-based energy storage power management system of claim 1, wherein, The charging and energy storage dispatch control network subsystem includes: The dispatch platform cloud communication subsystem transmits data between the charging and energy storage power distribution dispatch platform and the cloud based on the charging and energy storage power distribution dispatch platform. The platform's electric vehicle terminal networking subsystem utilizes cloud communication data transmission to connect electric vehicle charging terminals and mobile terminal communication networks, constructing a distributed scheduling and control network for charging and energy storage power sources.

3. The artificial intelligence-based energy storage power management system of claim 1, wherein, The AI-powered energy storage management subsystem includes: The intelligent power management model training subsystem constructs an artificial intelligence energy storage power management model based on the charging energy storage power distribution and dispatch control network, and uses cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model. The intelligent energy storage power management subsystem optimizes the intelligent energy storage power management model, intelligently manages the distribution and allocation of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy of energy storage power to continuously improve the rational adaptation of energy storage power distribution and electric vehicle charging distribution to the regional energy distribution.

4. An artificial intelligence-based energy storage power management method, characterized in that, include: S01 uses big data statistical analysis to determine the energy distribution and electric vehicle charging distribution in the region where the energy storage power source is located. S02, Based on the regional energy distribution and electric vehicle charging distribution, construct a charging energy storage power distribution and dispatching platform to carry out energy storage power distribution and dispatching. S03, Based on the charging energy storage power distribution and dispatching platform, connect the charging energy storage power distribution and dispatching platform with the cloud, electric vehicle charging terminals and mobile terminals to form a communication network and build a charging energy storage power distribution and dispatching control network. S04. Based on the charging and energy storage power distribution and dispatch control network, construct an artificial intelligence energy storage power management model and train and optimize it to intelligently manage the distribution and dispatch of energy storage power to adapt to the regional energy distribution status and continuously improve the reasonable adaptation of the distribution and dispatch of energy storage power to the regional energy distribution and electric vehicle charging distribution. S01 includes: S011, acquire big data information on the energy distribution of the energy storage power source in the region through energy big data collection; S012, Based on the statistics of electric vehicle charging information, obtain statistical data on the patterns of electric vehicle charging information; S013, Based on big data information on energy distribution and statistical data on electric vehicle charging information, analyze the energy distribution status and electric vehicle charging status of the region where the energy storage power source is located through big data statistical analysis. Regional energy distribution big data information includes: natural energy distribution and power grid energy distribution and charging information; When the overlap between the charging areas of electric vehicles and the charging areas of natural and grid power distribution is higher than that of electric vehicles, the energy storage power supply will be allocated more to the natural power distribution. New energy power management is matched with the balanced distribution of regional energy, and the distribution of energy and electric vehicle charging in the region where the energy storage power is located is accurately analyzed; the energy is balanced and scheduled between the charging energy storage power and regional energy and electric vehicle charging; a charging energy storage scheduling and control network is constructed and cloud computing power and electric vehicle charging and mobile terminal communication network are utilized; the energy storage power management and allocation are adapted to the regional energy distribution and the energy storage power is adapted to the regional energy distribution and electric vehicle charging distribution. S02 includes: S021. Based on the regional energy distribution and electric vehicle charging distribution, construct a charging energy storage power distribution and dispatching platform. S022, Based on the charging energy storage power distribution and dispatching platform, carry out energy storage power distribution and dispatching control, control the energy input of the dispatched energy storage power to adapt to the regional energy distribution status, and control the power output of the distributed energy storage power to adapt to the electric vehicle charging distribution status. The deployment of the charging and energy storage power distribution and dispatching platform includes deployment in areas with dense regional energy distribution information and areas with dense electric vehicle charging distribution information. The charging energy storage power distribution and dispatching platform includes energy dispatching path planning based on the regional energy distribution status and the regional energy supply of natural electricity, grid electricity or emergency power generation centralized charging energy storage power, to optimize the charging energy supply and energy dispatching path.

5. The artificial intelligence-based energy storage power management method according to claim 4, characterized in that, S03 includes: S031, Dispatch platform cloud communication subsystem, according to the charging energy storage power distribution dispatch platform, conducts platform-to-cloud communication data transmission between the charging energy storage power distribution dispatch platform and the cloud. S032, the platform's electric vehicle terminal networking subsystem, utilizes cloud communication data transmission to connect electric vehicle charging terminals and mobile terminal communication networks, and constructs a charging energy storage power distribution and dispatch control network. S041. Based on the charging energy storage power distribution and dispatch control network, construct an artificial intelligence energy storage power management model, and use cloud computing power to train and optimize the artificial intelligence energy storage power management model to obtain an optimized intelligent energy storage power management model. S042, by optimizing the intelligent energy storage power management model, intelligently manages the distribution and scheduling of energy storage power to adapt to the regional energy distribution status, and allocates the input and output energy of energy storage power, continuously improving the rational adaptation of the distribution and scheduling of energy storage power to the regional energy distribution and electric vehicle charging distribution.

6. An artificial intelligence-based energy storage power management device, characterized in that, include: The circuit control device for an artificial intelligence-based energy storage power management system as described in claim 1.

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