Novel intelligent energy storage system

Abstract

The invention, which belongs to the technical field of intelligent energy storage, discloses a novel intelligent energy storage system comprising a multi-source input module, a multi-mode energy storage matrix module, a dynamic adaptive hybrid topology structure module, an intelligent regulation and control module, an intelligent optimization module, an energy conversion module, a communication module and a cloud data synchronization module. According to the invention, the optimal energy conversion strategy can be selected through the energy conversion module according to the characteristics of different energy sources, and the conversion operation is executed through the efficient power electronic device, so that the energy loss is reduced, the overall efficiency is improved, and the multi-modal energy storage matrix module can be used for realizing the energy conversion according to different battery characteristics and current demand conditions. The optimal battery combination is flexibly selected for energy storage, so that the energy storage efficiency is improved, the service life of the battery is prolonged, the state parameters of each battery unit are continuously monitored in the charging process, the distribution strategy is dynamically adjusted according to the actual situation, and the optimal charging effect is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent energy storage, and specifically refers to a novel intelligent energy storage system. Background Art

[0002] With the large-scale application of renewable energy, how to effectively store these intermittent energy sources has become an important research direction. Existing energy storage systems have limitations in energy conversion efficiency, response speed, and the ability to adapt to different application scenarios;

[0003] However, the existing energy storage systems still have certain defects. During the energy conversion process, the existing energy storage systems often use a general energy conversion method due to the lack of optimization strategies for different energy types, resulting in large energy losses. Usually a single type of battery is used for energy storage, and the energy storage scheme cannot be flexibly adjusted according to different needs and application scenarios, resulting in low energy storage efficiency and short battery life. The circuit topology structure inside most energy storage systems is fixed and cannot be automatically adjusted according to real-time working status and load changes, resulting in low power transmission efficiency. Especially in the case of large load fluctuations, energy loss and system instability are prone to occur. For this reason, a new intelligent energy storage system is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a new intelligent energy storage system to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned object, the present invention provides the following technical solutions: a novel intelligent energy storage system, comprising a multi-source input module, a multi-modal energy storage matrix module, a dynamic adaptive hybrid topology structure module, an intelligent control module, an intelligent optimization module, an energy conversion module, a communication module and a cloud data synchronization module;

[0006] The multi-source input module is used to identify and access multiple types of energy sources, and transmit the acquired energy information to the intelligent control module and the energy conversion module through wireless transmission;

[0007] The energy conversion module is used to obtain energy from the multi-source input module and convert different forms of energy into an optimal storage form;

[0008] The multimodal energy storage matrix module is used to receive energy converted by the energy conversion module and store the converted energy according to different battery combinations;

[0009] The dynamic adaptive hybrid topology structure module is used to automatically adjust the internal circuit connection mode and optimize the power transmission efficiency according to the real-time working status and load;

[0010] The intelligent control module is used to receive information transmitted by the multi-source input module, monitor environmental parameters, battery status and power grid conditions in real time, and automatically adjust the operation mode of the energy storage system;

[0011] The intelligent optimization module is used to obtain data information from the intelligent control module, predict future peak power consumption periods and formulate optimal energy storage strategies;

[0012] The communication module is used to perform data exchange and remote control with the remote data synchronization module through wireless transmission;

[0013] The cloud data synchronization module is used to obtain local data and upload it to the cloud for long-term storage and analysis.

[0014] Among them, the multi-source input module identifies and accesses multiple types of energy sources, and transmits the acquired energy information to the intelligent control module and the energy conversion module through wireless transmission; detects the currently available energy sources through sensors, determines the type of each energy and its characteristic parameters based on the data fed back by the sensors, and automatically selects the appropriate interface protocol for access based on the different energy types identified, continuously monitors the state parameters of each energy source, and performs preliminary processing on the acquired data, encodes the collected data according to a predefined standard format, and establishes a wireless connection with the intelligent control module and the energy conversion module through the communication module for data transmission.

[0015] Among them, the energy conversion module obtains energy from the multi-source input module and converts different forms of energy into the optimal storage form; receives the currently available energy type and its characteristic parameters from the multi-source input module through the communication module, and initializes the internal parameters and working mode of the energy conversion module according to the received data. According to the energy source, the energy conversion module adjusts its physical interface to adapt to the energy input, selects the optimal energy conversion strategy according to the requirements of the target energy storage medium, performs energy conversion operations through power electronic devices, formats the converted energy according to predefined standards, and transmits the converted energy to the multimodal energy storage matrix module.

[0016] Among them, the multimodal energy storage matrix module receives the energy converted by the energy conversion module, stores the converted energy according to different configurations of battery combinations, obtains the energy converted by the energy conversion module in real time, selects the optimal battery combination for the current situation to store energy according to the characteristics of different types of batteries and the current demand situation, formulates an energy distribution plan based on the selected battery combination, continuously monitors the status parameters of each battery unit during the entire charging process, dynamically adjusts the distribution strategy according to the actual situation, and starts the charging process of the selected battery pack according to the distribution strategy.

[0017] Among them, the dynamic adaptive hybrid topology structure module automatically adjusts the internal circuit connection mode and optimizes the power transmission efficiency according to the real-time working status and load; the intelligent control module and the multimodal energy storage matrix module obtain the current working status information, including but not limited to load demand, battery charging and discharging status, and power grid status, construct a circuit topology structure model, simulate and calculate each model, and evaluate its energy transmission efficiency, stability and safety key indicators under different conditions. According to the evaluation results, the optimal circuit topology structure is selected, and according to the predetermined adjustment plan, the circuit structure is adjusted by controlling the corresponding hardware components.

[0018] Among them, the intelligent control module is used to receive information transmitted by the multi-source input module, monitor environmental parameters, battery status and power grid conditions in real time, and automatically adjust the operation mode of the energy storage system; obtain the currently available energy type and its characteristic parameters in the multi-source input module, and obtain environmental parameters and power grid conditions from the port, analyze the collected data, identify the current operating status of the system, and predict the future peak period of electricity demand based on historical data and current conditions according to intelligent algorithms, formulate the optimal control strategy, formulate specific control strategies based on the prediction results and real-time monitoring data, convert the formulated control strategies into specific operation instructions, and send them to the corresponding modules for execution through wireless communication.

[0019] Among them, the intelligent optimization module is used to obtain data information from the intelligent control module, predict future peak electricity consumption periods and formulate the optimal energy storage strategy; obtain real-time data from the intelligent control module, including but not limited to environmental parameters, battery status, power grid conditions and historical operation data, identify daily or seasonal electricity consumption patterns based on historical data, identify long-term trends and cyclical changes through time series analysis methods, make predictions based on data characteristics and prediction targets, predict future battery temperature conditions, and formulate the optimal control strategy based on the prediction results.

[0020] Among them, the communication module is used to exchange data and remotely control the remote data synchronization module through wireless transmission; the data collected from each module is encoded according to a predefined standard format, the formatted data is encapsulated into a data packet suitable for transmission, and the necessary header information is added, and the encapsulated data packet is sent to the remote data synchronization module through the selected wireless communication protocol, and remote control instructions are received from the remote data synchronization module, and these instructions are parsed, and according to the received instructions, the corresponding module is controlled to perform specific operations.

[0021] Among them, the cloud data synchronization module is used to obtain local data and upload it to the cloud for long-term storage and analysis; collect real-time operation data from the intelligent control module, multi-source input module, energy conversion module, and multi-modal energy storage matrix module, upload it to the cloud according to business data, set priorities for different types of data, encapsulate the data into transmission data packets, and upload it to the cloud through the communication protocol.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. The present invention can select the optimal energy conversion strategy according to the characteristics of different energy sources through the energy conversion module, and perform the conversion operation through efficient power electronic devices, thereby reducing energy loss and improving overall efficiency;

[0024] 2. The present invention can flexibly select the most suitable battery combination for energy storage according to different battery characteristics and current demand conditions through the multi-modal energy storage matrix module, which not only improves the energy storage efficiency, but also prolongs the battery life. During the charging process, the state parameters of each battery unit are continuously monitored, and the allocation strategy is dynamically adjusted according to the actual situation to ensure the best charging effect;

[0025] 3. The present invention can automatically adjust the internal circuit connection mode according to the real-time working status and load through the dynamic adaptive hybrid topology structure module, optimize the power transmission efficiency, reduce energy loss, and enhance the reliability and stability of the system;

[0026] 4. The present invention combines real-time data and historical data through an intelligent control module, uses intelligent algorithms to predict future peak electricity consumption periods, and formulates optimal control strategies. The intelligent optimization module uses time series analysis methods to identify long-term trends and cyclical changes, thereby achieving refined management of the energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a structural schematic diagram of a novel intelligent energy storage system of the present invention;

[0028] Figure 2 The operation process of a new intelligent energy storage system of the present invention is as follows Figure 1 ;

[0029] Figure 3 The operation process of a new intelligent energy storage system of the present invention is as follows Figure 2 ;

[0030] Figure 4 The operation process of a new intelligent energy storage system of the present invention is as follows Figure 3 . DETAILED DESCRIPTION

[0031] 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.

[0032] Example

[0033] See also Figure 1-Figure 4 As shown, the present invention provides a technical solution: including a multi-source input module, a multi-modal energy storage matrix module, a dynamic adaptive hybrid topology structure module, an intelligent control module, an intelligent optimization module, an energy conversion module, a communication module and a cloud data synchronization module;

[0034] The multi-source input module is used to identify and access multiple types of energy sources, and transmit the acquired energy information to the intelligent control module and the energy conversion module through wireless transmission;

[0035] The energy conversion module is used to obtain energy from the multi-source input module and convert different forms of energy into an optimal storage form;

[0036] The multimodal energy storage matrix module is used to receive energy converted by the energy conversion module and store the converted energy according to different battery combinations;

[0037] The dynamic adaptive hybrid topology structure module is used to automatically adjust the internal circuit connection mode and optimize the power transmission efficiency according to the real-time working status and load;

[0038] The intelligent control module is used to receive information transmitted by the multi-source input module, monitor environmental parameters, battery status and power grid conditions in real time, and automatically adjust the operation mode of the energy storage system;

[0039] The intelligent optimization module is used to obtain data information from the intelligent control module, predict future peak power consumption periods and formulate optimal energy storage strategies;

[0040] The communication module is used to perform data exchange and remote control with the remote data synchronization module through wireless transmission;

[0041] The cloud data synchronization module is used to obtain local data and upload it to the cloud for long-term storage and analysis.

[0042] Among them, the multi-source input module identifies and accesses multiple types of energy sources, and transmits the acquired energy information to the intelligent control module and the energy conversion module through wireless transmission; detects the currently available energy sources through sensors, determines the type of each energy and its characteristic parameters based on the data fed back by the sensors, and automatically selects the appropriate interface protocol for access based on the different energy types identified, continuously monitors the state parameters of each energy source, and performs preliminary processing on the acquired data, encodes the collected data according to a predefined standard format, and establishes a wireless connection with the intelligent control module and the energy conversion module through the communication module for data transmission.

[0043] Among them, the energy conversion module obtains energy from the multi-source input module and converts different forms of energy into the optimal storage form; receives the currently available energy type and its characteristic parameters from the multi-source input module through the communication module, and initializes the internal parameters and working mode of the energy conversion module according to the received data. According to the energy source, the energy conversion module adjusts its physical interface to adapt to the energy input, selects the optimal energy conversion strategy according to the requirements of the target energy storage medium, performs energy conversion operations through power electronic devices, formats the converted energy according to predefined standards, and transmits the converted energy to the multimodal energy storage matrix module.

[0044] Among them, the multimodal energy storage matrix module receives the energy converted by the energy conversion module, stores the converted energy according to different configurations of battery combinations, obtains the energy converted by the energy conversion module in real time, selects the optimal battery combination for the current situation to store energy according to the characteristics of different types of batteries and the current demand situation, formulates an energy distribution plan based on the selected battery combination, continuously monitors the status parameters of each battery unit during the entire charging process, dynamically adjusts the distribution strategy according to the actual situation, and starts the charging process of the selected battery pack according to the distribution strategy.

[0045] Among them, the dynamic adaptive hybrid topology structure module automatically adjusts the internal circuit connection mode and optimizes the power transmission efficiency according to the real-time working status and load; the intelligent control module and the multimodal energy storage matrix module obtain the current working status information, including but not limited to load demand, battery charging and discharging status, and power grid status, construct a circuit topology structure model, simulate and calculate each model, and evaluate its energy transmission efficiency, stability and safety key indicators under different conditions. According to the evaluation results, the optimal circuit topology structure is selected, and according to the predetermined adjustment plan, the circuit structure is adjusted by controlling the corresponding hardware components.

[0046] Among them, the intelligent control module is used to receive information transmitted by the multi-source input module, monitor environmental parameters, battery status and power grid conditions in real time, and automatically adjust the operation mode of the energy storage system; obtain the currently available energy type and its characteristic parameters in the multi-source input module, and obtain environmental parameters and power grid conditions from the port, analyze the collected data, identify the current operating status of the system, and predict the future peak period of electricity demand based on historical data and current conditions according to intelligent algorithms, formulate the optimal control strategy, formulate specific control strategies based on the prediction results and real-time monitoring data, convert the formulated control strategies into specific operation instructions, and send them to the corresponding modules for execution through wireless communication.

[0047] Among them, the intelligent optimization module is used to obtain data information from the intelligent control module, predict future peak electricity consumption periods and formulate the optimal energy storage strategy; obtain real-time data from the intelligent control module, including but not limited to environmental parameters, battery status, power grid conditions and historical operation data, identify daily or seasonal electricity consumption patterns based on historical data, identify long-term trends and cyclical changes through time series analysis methods, make predictions based on data characteristics and prediction targets, predict future battery temperature conditions, and formulate the optimal control strategy based on the prediction results.

[0048] Among them, the communication module is used to exchange data and remotely control the remote data synchronization module through wireless transmission; the data collected from each module is encoded according to a predefined standard format, the formatted data is encapsulated into a data packet suitable for transmission, and the necessary header information is added, and the encapsulated data packet is sent to the remote data synchronization module through the selected wireless communication protocol, and remote control instructions are received from the remote data synchronization module, and these instructions are parsed, and according to the received instructions, the corresponding module is controlled to perform specific operations.

[0049] Among them, the cloud data synchronization module is used to obtain local data and upload it to the cloud for long-term storage and analysis; collect real-time operation data from the intelligent control module, multi-source input module, energy conversion module, and multi-modal energy storage matrix module, upload it to the cloud according to business data, set priorities for different types of data, encapsulate the data into transmission data packets, and upload it to the cloud through the communication protocol.

[0050] Working principle: The multi-source input module detects the currently available energy sources through sensors, determines the type of each energy source and its characteristic parameters based on the data fed back by the sensors, automatically selects the appropriate interface protocol for access based on the identified different energy types, continuously monitors the state parameters of each energy source, and performs preliminary processing on the acquired data. After encoding, a wireless connection is established with the intelligent control module and the energy conversion module through the communication module for data transmission. The energy conversion module receives the currently available energy type and its characteristic parameters from the multi-source input module, initializes the internal parameters and working mode, adjusts the physical interface to adapt to the energy input according to the energy source, and selects the optimal energy conversion strategy according to the requirements of the target energy storage medium. Execute energy conversion operations, format the converted energy and transmit it to the multimodal energy storage matrix module. The multimodal energy storage matrix module obtains the energy converted by the energy conversion module in real time, selects the optimal battery combination for energy storage according to the characteristics of different types of batteries and the current demand situation, formulates an energy distribution plan, continuously monitors the state parameters of each battery unit during the charging process, and dynamically adjusts the distribution strategy according to the actual situation. The charging process of the selected battery pack is started according to the distribution strategy. The dynamic adaptive hybrid topology structure module obtains the current working status information, constructs the circuit topology structure model and performs simulation calculations, evaluates the energy transmission efficiency, stability and safety key indicators of different models under different conditions, and selects the optimal circuit Topology structure, implement circuit structure adjustment by controlling corresponding hardware components according to the predetermined adjustment plan, the intelligent control module obtains the current available energy type and its characteristic parameters as well as environmental parameters and power grid conditions, analyzes the collected data to identify the current system operation status, predicts the future peak period of electricity demand based on historical data and current conditions and formulates the optimal control strategy, converts the formulated control strategy into specific operation instructions and sends them to the corresponding modules for execution through wireless communication, the intelligent optimization module obtains real-time data of the intelligent control module, identifies daily or seasonal electricity consumption patterns based on historical data, and identifies long-term trends and cyclical changes through time series analysis methods, and makes predictions based on data characteristics and prediction targets. And formulate the optimal control strategy, the communication module will encode the data collected from each module according to the predefined standard format and encapsulate it into a data packet suitable for transmission, and send the encapsulated data packet to the remote data synchronization module through the selected wireless communication protocol, receive remote control instructions from the remote data synchronization module and parse these instructions, and control the corresponding module to perform specific operations according to the received instructions. The cloud data synchronization module collects real-time operation data from modules such as the intelligent control module, multi-source input module, energy conversion module, and multi-modal energy storage matrix module, uploads it to the cloud according to business data, sets priorities for different types of data, encapsulates the data into transmission data packets, and uploads them to the cloud through the communication protocol for long-term storage and analysis.

[0051] 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.

[0052] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A new intelligent energy storage system, characterized by: It includes multi-source input module, multi-modal energy storage matrix module, dynamic adaptive hybrid topology structure module, intelligent control module, intelligent optimization module, energy conversion module, communication module and cloud data synchronization module; The multi-source input module is used to identify and access multiple types of energy sources, and transmit the acquired energy information to the intelligent control module and the energy conversion module through wireless transmission; The energy conversion module is used to obtain energy from the multi-source input module and convert different forms of energy into an optimal storage form; The multimodal energy storage matrix module is used to receive energy converted by the energy conversion module and store the converted energy according to different battery combinations; The dynamic adaptive hybrid topology structure module is used to automatically adjust the internal circuit connection mode and optimize the power transmission efficiency according to the real-time working status and load; The intelligent control module is used to receive information transmitted by the multi-source input module, monitor environmental parameters, battery status and power grid conditions in real time, and automatically adjust the operation mode of the energy storage system; The intelligent optimization module is used to obtain data information from the intelligent control module, predict future peak power consumption periods and formulate optimal energy storage strategies; The communication module is used to perform data exchange and remote control with the remote data synchronization module through wireless transmission; The cloud data synchronization module is used to obtain local data and upload it to the cloud for long-term storage and analysis.

2. A novel intelligent energy storage system according to claim 1, characterized in that: The multi-source input module identifies and accesses multiple types of energy sources, and transmits the acquired energy information to the intelligent control module and the energy conversion module through wireless transmission; detects the currently available energy sources through sensors, determines the type of each energy and its characteristic parameters based on the data fed back by the sensors, and automatically selects the appropriate interface protocol for access based on the identified different energy types, continuously monitors the state parameters of each energy source, and preliminarily processes the acquired data, encodes the collected data according to a predefined standard format, and establishes a wireless connection with the intelligent control module and the energy conversion module through the communication module for data transmission.

3. A novel intelligent energy storage system according to claim 1, characterized in that: The energy conversion module obtains energy from the multi-source input module and converts different forms of energy into the optimal storage form; receives the currently available energy type and its characteristic parameters from the multi-source input module through the communication module; initializes the internal parameters and working mode of the energy conversion module based on the received data; adjusts its physical interface to adapt to the energy input based on the energy source; selects the optimal energy conversion strategy based on the requirements of the target energy storage medium; performs energy conversion operations through power electronic devices, formats the converted energy according to predefined standards, and transmits the converted energy to the multi-modal energy storage matrix module.

4. A novel intelligent energy storage system according to claim 1, characterized in that: The multimodal energy storage matrix module receives energy converted by the energy conversion module, stores the converted energy according to different configurations of battery combinations, obtains the energy converted by the energy conversion module in real time, selects the optimal battery combination for the current situation to store energy according to the characteristics of different types of batteries and the current demand situation, formulates an energy distribution plan based on the selected battery combination, continuously monitors the status parameters of each battery unit during the entire charging process, dynamically adjusts the distribution strategy according to the actual situation, and starts the charging process of the selected battery pack according to the distribution strategy.

5. A novel intelligent energy storage system according to claim 1, characterized in that: The dynamic adaptive hybrid topology structure module automatically adjusts the internal circuit connection mode and optimizes the power transmission efficiency according to the real-time working status and load; the intelligent control module and the multimodal energy storage matrix module obtain the current working status information, including but not limited to load demand, battery charging and discharging status, and power grid status, construct a circuit topology structure model, simulate and calculate each model, evaluate its energy transmission efficiency, stability and safety key indicators under different conditions, select the optimal circuit topology structure according to the evaluation results, and implement the circuit structure adjustment by controlling the corresponding hardware components according to the predetermined adjustment plan.

6. A novel intelligent energy storage system according to claim 1, characterized in that: The intelligent control module is used to receive information transmitted by the multi-source input module, monitor environmental parameters, battery status and power grid conditions in real time, and automatically adjust the operation mode of the energy storage system; obtain the currently available energy type and its characteristic parameters in the multi-source input module, and obtain environmental parameters and power grid conditions from the port, analyze the collected data, identify the current operation status of the system, predict the future peak period of electricity demand based on historical data and current conditions and intelligent algorithms, formulate the optimal control strategy, formulate specific control strategies based on the prediction results and real-time monitoring data, convert the formulated control strategies into specific operation instructions, and send them to the corresponding modules for execution through wireless communication.

7. A novel intelligent energy storage system according to claim 1, characterized in that: The intelligent optimization module is used to obtain data information from the intelligent control module, predict future peak power consumption periods, and formulate optimal energy storage strategies; obtain real-time data from the intelligent control module, including but not limited to environmental parameters, battery status, power grid conditions, and historical operating data, identify daily or seasonal power consumption patterns based on historical data, identify long-term trends and cyclical changes through time series analysis methods, make predictions based on data characteristics and prediction targets, predict future battery temperature conditions, and formulate optimal control strategies based on the prediction results.

8. A novel intelligent energy storage system according to claim 1, characterized in that: The communication module is used to exchange data and remotely control the remote data synchronization module through wireless transmission; the data collected from each module is encoded according to a predefined standard format, the formatted data is encapsulated into a data packet suitable for transmission, and necessary header information is added, and the encapsulated data packet is sent to the remote data synchronization module through the selected wireless communication protocol, remote control instructions are received from the remote data synchronization module, and these instructions are parsed, and according to the received instructions, the corresponding module is controlled to perform specific operations.

9. A novel intelligent energy storage system according to claim 1, characterized in that: The cloud data synchronization module is used to obtain local data and upload it to the cloud for long-term storage and analysis; collect real-time operation data from the intelligent control module, multi-source input module, energy conversion module, and multi-modal energy storage matrix module, upload it to the cloud according to business data, set priorities for different types of data, encapsulate the data into transmission data packets, and upload it to the cloud through the communication protocol.

Images