Robustness strategy optimization method for user side energy storage

Abstract

The invention relates to the technical field of power generation and energy storage, and discloses a user-side energy storage oriented robustness strategy optimization method, which comprises a robustness strategy optimization system, and the robustness strategy optimization system comprises a user-side energy storage facility digital twinborn model, a user-side energy storage facility digital twinborn model, a user-side energy storage facility digital twinborn model and a user-side energy storage facility digital twinborn model. The user side energy storage facility digital twinborn model comprises a real-time data acquisition module, a data processing module, a digital twinborn model construction module, a strategy optimization module, a user interaction module, an energy storage control module and an energy storage equipment state monitoring module. By integrating a real-time data acquisition module, a data processing module, a digital twin model construction module, a strategy optimization module, a user interaction module, an energy storage control module and an energy storage equipment state monitoring module, the running state of the energy storage equipment can be monitored and adjusted in real time, so that the running efficiency of the energy storage equipment is improved, and the service life of the energy storage equipment is prolonged; and through real-time monitoring and optimization strategies, safe and stable operation of the energy storage method is ensured, and a comprehensive solution is provided for management of the user side energy storage equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation and energy storage, and in particular to a robustness strategy optimization method for user-side energy storage. Background Art

[0002] In recent years, with the continuous development of my country's economy, users' energy demand has continued to increase. The widespread use of renewable energy power generation methods on the user side has further increased the user's demand for flexibility due to the uncertainty of output. Under the time-of-use electricity price strategy, industrial users want to reduce operating costs such as electricity bills while expanding economic output and improve their own operating efficiency. They are faced with the challenge of improving their own energy flexibility. With the promotion and implementation of peak and valley time-of-use electricity prices, the widespread use of demand-side load response resources, and the continuous development of diversified energy storage methods, the application mode of energy storage technology on the user side has become more diversified.

[0003] At present, there are still many problems in the mechanism and operation strategy of intelligent operation and regulation of energy storage facilities on the user side: First, the stability and safety of the current power grid operation is mainly regulated by a multi-energy complementary regulation method. The volatility and randomness of new energy will have an adverse impact on the stability and safety of the power grid, and this method has certain limitations; second, it is not conducive to the consumption of energy itself. The traditional peak-shaving method observes the load fluctuations of the power grid and adjusts the output power of the generator sets in the network. It requires the generator sets to have a higher peak-shaving capacity, and the frequent start and stop of the units also causes a waste of fuel resources. In comparison, the large-scale energy storage method regulated from the load side has more significant advantages in peak shaving and valley filling. The application prospects are broader, so it is an effective and necessary measure to study the configuration of user-side energy storage facilities and study smart operation optimization strategies to improve the method regulation capabilities; third, domestic electric vehicle charging, microgrids, etc. are developing rapidly, and the entire user-side energy method lacks the inclusion of energy storage methods in demand-side management. The current mechanism is complex and research is lacking. It is urgent to rely on algorithm and software innovation to improve the control and management level of energy storage methods. With the advancement of new energy technology, user-side energy storage has become an important part of new power methods, but due to the low level of digital operation of existing energy storage facilities, it is impossible to fully consider the influence of complex factors such as battery performance, user load, and electricity price system in operation, resulting in insignificant energy storage benefits.

[0004] To this end, we propose a robust strategy optimization method for user-side energy storage. Summary of the invention

[0005] The present invention mainly solves the technical problems existing in the above-mentioned prior art and provides a robust strategy optimization method for user-side energy storage.

[0006] In order to achieve the above-mentioned objectives, the present invention adopts the following technical scheme: a robust strategy optimization method for user-side energy storage, including a robust strategy optimization system, the robust strategy optimization system including a digital twin model of a user-side energy storage facility, the digital twin model of the user-side energy storage facility including a real-time data acquisition module, a data processing module, a digital twin model construction module, a strategy optimization module, a user interaction module, an energy storage control module and an energy storage device status monitoring module, the real-time data acquisition module including a voltage sensor, a current sensor and a temperature sensor, the real-time data acquisition module is used to collect the operating data of the energy storage device in real time, the data processing module including a data cleaning unit and a format conversion unit, and the data processing module is responsible for preprocessing the collected data.

[0007] Preferably, the digital twin model construction module constructs a digital twin model of the energy storage device based on the processed data to achieve virtual mapping and simulation of the actual energy storage device.

[0008] Preferably, the digital twin model construction module includes a mechanism simulation module, a numerical simulation module and a data-driven modeling module.

[0009] Preferably, the mechanism simulation module is used to simulate the operation of the user-side energy storage device under different working conditions, and to predict the performance and life of the energy storage device by establishing an accurate mathematical model.

[0010] Preferably, the numerical simulation module uses computer simulation technology to simulate various scenarios of energy storage devices in actual applications to evaluate the impact of different control strategies on device performance.

[0011] Preferably, the data-driven modeling module collects a large amount of historical operating data and uses a machine learning algorithm to establish a prediction model, thereby achieving accurate prediction of the future behavior of the energy storage device.

[0012] Preferably, the strategy optimization module formulates an optimal energy storage strategy based on the results of mechanism simulation, numerical simulation and data-driven modeling, combined with the actual needs of the user side.

[0013] Preferably, the strategy optimization module includes an energy storage strategy generation unit and a strategy evaluation unit.

[0014] Preferably, the energy storage strategy generation unit is responsible for generating a preliminary energy storage strategy based on the simulation results of the digital twin model.

[0015] Preferably, the strategy evaluation unit evaluates and optimizes the generated strategy to ensure the feasibility and economy of the strategy in practical application.

[0016] Preferably, the user interaction module provides a user-friendly interface, so that the user can easily understand the operating status of the energy storage device and adjust the energy storage strategy according to their own needs.

[0017] Preferably, the energy storage control module is responsible for adjusting the operating parameters of the energy storage device in real time according to the instructions of the strategy optimization module to achieve the optimal energy storage effect.

[0018] Preferably, the energy storage control module includes an energy storage device control unit and an energy storage device status monitoring unit.

[0019] Preferably, the energy storage device control unit adjusts the operating parameters of the energy storage device in real time according to the instructions of the strategy optimization module to achieve the optimal energy storage effect.

[0020] Preferably, the energy storage device status monitoring unit is responsible for real-time monitoring of the operating status of the energy storage device, ensuring that the device operates within a safe range and promptly discovering potential faults and problems.

[0021] Preferably, the energy storage device status monitoring module is used to monitor the operating status of the energy storage device in real time, ensure the safe and stable operation of the equipment, and promptly alarm when an abnormality occurs.

[0022] Preferably, the energy storage device status monitoring module includes a battery voltage monitoring unit, a battery temperature monitoring unit and a battery health status monitoring unit.

[0023] Preferably, the battery voltage monitoring unit is responsible for real-time monitoring of the voltage value of each battery cell in the energy storage device to ensure that the voltage of the battery cell is within a safe range and to avoid battery damage caused by overcharging or over-discharging.

[0024] Preferably, the battery temperature monitoring unit monitors the temperature of the battery unit in real time, because the battery generates heat during the charging and discharging process, and excessively high temperature may cause the battery performance to deteriorate or even cause safety problems.

[0025] Preferably, the battery health status monitoring unit evaluates the health status of the battery and predicts the remaining life of the battery by analyzing the charge and discharge curves, internal resistance and other parameters of the battery unit, thereby providing a scientific basis for the maintenance and replacement of the user-side energy storage equipment.

[0026] Preferably, the battery health status monitoring unit includes battery internal resistance monitoring, battery charge and discharge cycle number monitoring and battery aging degree evaluation. Through battery internal resistance monitoring, battery charge and discharge cycle number monitoring and battery aging degree evaluation, the system can fully understand the health status of the battery, so as to perform maintenance or replacement in time when the battery performance drops to a certain level, thereby ensuring the long-term stable operation of the energy storage system. It can also optimize the charge and discharge strategy according to the battery health status data, extend the battery life and reduce the user's maintenance cost.

[0027] The robustness strategy optimization method for user-side energy storage includes the above-mentioned robustness strategy optimization system, and specifically includes the following steps:

[0028] Step 1: Collect data: Collect the operating data of the energy storage device through the real-time data acquisition module, including key parameters of voltage, current and temperature;

[0029] Step 2: Data processing: Use the data processing module to clean and convert the collected data to ensure that the data quality meets the requirements of subsequent analysis and modeling;

[0030] Step 3: Model building: The digital twin model building module builds a digital twin model of the energy storage device based on the processed data to achieve virtual mapping and simulation of the actual energy storage device;

[0031] Step 4: Formulate strategy: The strategy optimization module combines the results of mechanism simulation, numerical simulation and data-driven modeling to formulate the optimal energy storage strategy to ensure the feasibility and economy of the strategy in practical application;

[0032] Step 5: Adjust strategy: The user interaction module provides users with a friendly interface, allowing users to easily understand the operating status of energy storage equipment and adjust energy storage strategies according to their own needs;

[0033] Step 6: Adjust parameters: The energy storage control module adjusts the operating parameters of the energy storage equipment in real time according to the instructions of the strategy optimization module to achieve the optimal energy storage effect;

[0034] Step 7: Status monitoring: The energy storage equipment status monitoring module monitors the operating status of the energy storage equipment in real time to ensure the safe and stable operation of the equipment and promptly alarms when an abnormality occurs;

[0035] Step 8: Maintenance and replacement: Make equipment maintenance and replacement decisions based on the data provided by the energy storage equipment status monitoring module to ensure the long-term stable operation of the energy storage method.

[0036] The present invention provides a robustness strategy optimization method for user-side energy storage, which has the following beneficial effects:

[0037] 1. This robust strategy optimization method for user-side energy storage integrates real-time data acquisition module, data processing module, digital twin model construction module, strategy optimization module, user interaction module, energy storage control module and energy storage equipment status monitoring module. It can monitor and adjust the operating status of energy storage equipment in real time, which not only improves the operating efficiency and life of energy storage equipment, but also ensures the safe and stable operation of the energy storage method through real-time monitoring and optimization strategy, providing a comprehensive solution for the management of user-side energy storage equipment.

[0038] 2. This robust strategy optimization method for user-side energy storage sets up a digital twin model of user-side energy storage facilities. Through the construction of the digital twin model, it realizes accurate virtual mapping and simulation of energy storage equipment, providing a scientific basis for the formulation of energy storage strategies.

[0039] 3. This robust strategy optimization method for user-side energy storage sets up a strategy optimization module and a user interaction module. The strategy optimization module combines a variety of simulation and modeling technologies to ensure the optimality and economy of the energy storage strategy and meet the actual needs of the user side. The introduction of the user interaction module enables users to understand the operating status of the energy storage equipment more intuitively and adjust the strategy according to their own needs, thereby improving the user experience.

[0040] 4. This robust strategy optimization method for user-side energy storage, by setting up an energy storage control module and an energy storage equipment status monitoring module, the real-time adjustment function of the energy storage control module ensures that the energy storage equipment can maintain the optimal operating state under various working conditions, further improving the energy storage effect. The real-time monitoring and alarm functions of the energy storage equipment status monitoring module can promptly detect potential faults and problems, ensuring the safe and stable operation of the energy storage method.

[0041] 5. This robustness strategy optimization method for user-side energy storage provides a scientific basis for the maintenance and replacement of energy storage equipment by setting up a battery health status monitoring unit and through the evaluation and prediction functions of the battery health status monitoring unit, thereby extending the service life of the equipment and reducing maintenance costs.

[0042] 6. This robust strategy optimization method for user-side energy storage can fully understand the health status of the battery through battery internal resistance monitoring, battery charge and discharge cycle monitoring and battery aging degree evaluation, so that timely maintenance or replacement can be carried out when the battery performance drops to a certain level, ensuring the long-term stable operation of the energy storage system. It can also optimize the charge and discharge strategy based on the battery health status data, extend the battery life and reduce the user's maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a method module diagram of the present invention;

[0044] Figure 2 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0045] Example 1: Robustness strategy optimization method for user-side energy storage, such as Figure 1 As shown, the digital twin model of the user-side energy storage facility includes a real-time data acquisition module, a data processing module, a digital twin model construction module, a strategy optimization module, a user interaction module, an energy storage control module and an energy storage device status monitoring module. The real-time data acquisition module includes a voltage sensor, a current sensor and a temperature sensor. The real-time data acquisition module is used to collect the operating data of the energy storage device in real time. By integrating the real-time data acquisition module, the data processing module, the digital twin model construction module, the strategy optimization module, the user interaction module, the energy storage control module and the energy storage device status monitoring module, the operating status of the energy storage device can be monitored and adjusted in real time, which not only improves the operating efficiency and life of the energy storage equipment, but also ensures the safe and stable operation of the energy storage method through real-time monitoring and optimization strategies, and provides a comprehensive solution for the management of user-side energy storage equipment.

[0046] Embodiment 2: Based on Embodiment 1, Figure 1 As shown, the data processing module includes a data cleaning unit and a format conversion unit. The data processing module is responsible for preprocessing the collected data. The digital twin model construction module constructs a digital twin model of the energy storage device according to the processed data to realize virtual mapping and simulation of the actual energy storage device. The digital twin model construction module includes a mechanism simulation module, a numerical simulation module and a data-driven modeling module. The mechanism simulation module is used to simulate the operation of the user-side energy storage device under different working conditions, and predict the performance and life of the energy storage device by establishing an accurate mathematical model. By setting up a digital twin model of the user-side energy storage facility and building a digital twin model, accurate virtual mapping and simulation of the energy storage device are realized, providing a scientific basis for the formulation of energy storage strategies.

[0047] Embodiment 3: Based on Embodiment 1 and Embodiment 2, Figure 1As shown in the figure, the numerical simulation module uses computer simulation technology to simulate various scenarios of energy storage equipment in actual applications to evaluate the impact of different control strategies on equipment performance. The data-driven modeling module collects a large amount of historical operation data and uses machine learning algorithms to establish a prediction model, thereby realizing accurate prediction of the future behavior of energy storage equipment. The strategy optimization module formulates the optimal energy storage strategy based on the results of mechanism simulation, numerical simulation and data-driven modeling, combined with the actual needs of the user side. The strategy optimization module includes an energy storage strategy generation unit and a strategy evaluation unit. The energy storage strategy generation unit is responsible for generating a preliminary energy storage strategy based on the simulation results of the digital twin model. The strategy evaluation unit evaluates and optimizes the generated strategy to ensure the feasibility and economy of the strategy in actual application. By setting up a strategy optimization module and a user interaction module, the strategy optimization module combines a variety of simulation and modeling technologies to ensure the optimality and economy of the energy storage strategy and meet the actual needs of the user side. The introduction of the user interaction module enables users to understand the operating status of the energy storage equipment more intuitively and adjust the strategy according to their own needs, thereby improving the user experience.

[0048] Embodiment 4: Based on Embodiment 1, Embodiment 2 and Embodiment 3, Figure 1As shown, the user interaction module provides users with a friendly interface, allowing users to easily understand the operating status of the energy storage device and adjust the energy storage strategy according to their own needs. The energy storage control module is responsible for adjusting the operating parameters of the energy storage device in real time according to the instructions of the strategy optimization module to achieve the best energy storage effect. The energy storage control module includes an energy storage device control unit and an energy storage device status monitoring unit. The energy storage device control unit adjusts the operating parameters of the energy storage device in real time according to the instructions of the strategy optimization module to achieve the best energy storage effect. The energy storage device status monitoring unit is responsible for real-time monitoring of the operating status of the energy storage device to ensure that the equipment operates within a safe range and promptly discovers potential faults and problems. The energy storage device status monitoring module is used to monitor the operating status of the energy storage device in real time to ensure that the equipment operates safely and stably, and promptly alarm when an abnormality occurs. The energy storage device status monitoring module includes a battery voltage monitoring unit, a battery temperature monitoring unit and a battery health status monitoring unit. The battery voltage monitoring unit is responsible for real-time monitoring of the voltage value of each battery cell in the energy storage device to ensure that the voltage of the battery cell is within a safe range and to avoid battery damage caused by overcharging or over-discharging. The battery temperature monitoring unit monitors the temperature of the battery cell in real time, because the battery generates heat during the charging and discharging process. Excessive temperature may cause battery performance degradation or even cause safety problems. The battery health status monitoring unit evaluates the health status of the battery and predicts the remaining life of the battery by analyzing the charging and discharging curves, internal resistance and other parameters of the battery cell, thereby providing a scientific basis for the maintenance and replacement of user-side energy storage equipment. By setting up an energy storage control module and an energy storage device status monitoring module, the real-time adjustment function of the energy storage control module ensures that the energy storage device can maintain the optimal operating state under various working conditions, further improving the energy storage effect. The real-time monitoring and alarm functions of the energy storage device status monitoring module can promptly detect potential faults and problems, ensuring the safe and stable operation of the energy storage method.

[0049] Embodiment 5: Based on Embodiment 1, Embodiment 2, Embodiment 3 and Embodiment 4, Figure 1 As shown, the battery health status monitoring unit includes battery internal resistance monitoring, battery charge and discharge cycle number monitoring and battery aging degree evaluation. Through battery internal resistance monitoring, battery charge and discharge cycle number monitoring and battery aging degree evaluation, the system can fully understand the health status of the battery, so as to perform maintenance or replacement in time when the battery performance drops to a certain level, ensuring the long-term stable operation of the energy storage system. It can also optimize the charge and discharge strategy according to the battery health status data, extend the battery life and reduce the user's maintenance cost.

[0050] Embodiment 6: Based on Embodiment 1, Embodiment 2, Embodiment 3, Embodiment 4 and Embodiment 5, Figure 2As shown, the robust strategy optimization method for user-side energy storage includes the above-mentioned robust strategy optimization system, which specifically includes the following steps: Step 1: Data collection: The operating data of the energy storage device, including the key parameters of voltage, current and temperature, are collected through the real-time data acquisition module; Step 2: Data processing: The collected data is cleaned and formatted using the data processing module to ensure that the data quality meets the needs of subsequent analysis and modeling; Step 3: Model construction: The digital twin model construction module constructs a digital twin model of the energy storage device based on the processed data to achieve virtual mapping and simulation of the actual energy storage device; Step 4: Strategies: The strategy optimization module combines the results of mechanism simulation, numerical simulation and data-driven modeling to formulate the optimal energy storage strategy to ensure the feasibility and economy of the strategy in practical applications; Step 5: Strategy adjustment: User interaction The interactive module provides users with a friendly interface, allowing users to easily understand the operating status of the energy storage equipment and adjust the energy storage strategy according to their own needs; Step 6: Adjust parameters: The energy storage control module adjusts the operating parameters of the energy storage equipment in real time according to the instructions of the strategy optimization module to achieve the optimal energy storage effect; Step 7: Status monitoring: The energy storage equipment status monitoring module monitors the operating status of the energy storage equipment in real time to ensure the safe and stable operation of the equipment, and promptly alarms when an abnormality occurs; Step 8: Maintenance and replacement: According to the data provided by the energy storage equipment status monitoring module, equipment maintenance and replacement decisions are made to ensure the long-term stable operation of the energy storage method. By setting up a battery health status monitoring unit and through the evaluation and prediction functions of the battery health status monitoring unit, a scientific basis is provided for the maintenance and replacement of energy storage equipment, which extends the service life of the equipment and reduces maintenance costs.

[0051] The working principle of the present invention is as follows: First, the real-time data acquisition module continuously collects the key operating parameters of the energy storage device, such as voltage, current and temperature, to provide real-time data support for subsequent data processing and analysis. Secondly, the data processing module cleans and converts the collected data to ensure that the data quality meets the needs of subsequent analysis and modeling. Then, the digital twin model construction module constructs a digital twin model of the energy storage device based on the processed data to achieve virtual mapping and simulation of the actual energy storage device. Next, the strategy optimization module combines the results of mechanism simulation, numerical simulation and data-driven modeling to formulate the optimal energy storage strategy to ensure the feasibility and economy of the strategy in practical applications. The user interaction module provides users with a friendly interface, allowing users to easily understand the operating status of the energy storage device and optimize it according to their own needs. The energy storage strategy is adjusted according to demand. The energy storage control module adjusts the operating parameters of the energy storage equipment in real time according to the instructions of the strategy optimization module to achieve the optimal energy storage effect. The energy storage equipment status monitoring module monitors the operating status of the energy storage equipment in real time to ensure the safe and stable operation of the equipment, and promptly alarms when an abnormality occurs. Finally, according to the data provided by the energy storage equipment status monitoring module, equipment maintenance and replacement decisions are made to ensure the long-term stable operation of the energy storage method. Through this comprehensive method, not only can the efficient operation of the energy storage equipment be achieved, but also the energy storage strategy can be flexibly adjusted according to user needs, while ensuring the safe, stable and long-term operation of the energy storage method. In addition, by real-time monitoring and evaluation of the battery health status, the present invention can also provide a scientific basis for the maintenance and replacement of energy storage equipment, thereby extending the service life of the equipment and reducing maintenance costs.

[0052] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A robust strategy optimization method for user-side energy storage, characterized in that: It includes a robust strategy optimization system, which includes a digital twin model of user-side energy storage facilities. The digital twin model of user-side energy storage facilities includes a real-time data acquisition module, a data processing module, a digital twin model construction module, a strategy optimization module, a user interaction module, an energy storage control module and an energy storage equipment status monitoring module. The real-time data acquisition module includes a voltage sensor, a current sensor and a temperature sensor.

2. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The data processing module includes a data cleaning unit and a format conversion unit.

3. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The digital twin model construction module includes a mechanism simulation module, a numerical simulation module and a data-driven modeling module.

4. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The strategy optimization module includes an energy storage strategy generation unit and a strategy evaluation unit.

5. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The energy storage control module includes an energy storage device control unit and an energy storage device state monitoring unit.

6. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The energy storage device status monitoring module includes a battery voltage monitoring unit, a battery temperature monitoring unit and a battery health status monitoring unit.

7. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The battery health status monitoring unit includes battery internal resistance monitoring, battery charge and discharge cycle number monitoring and battery aging degree assessment.

8. The robustness strategy optimization method for user-side energy storage according to claim 1, characterized in that: The robustness strategy optimization system comprising any one of claims 1 to 7 specifically comprises the following steps: Step 1: Collect data: Collect the operating data of the energy storage device through the real-time data acquisition module, including key parameters of voltage, current and temperature; Step 2: Data processing: Use the data processing module to clean and convert the collected data to ensure that the data quality meets the requirements of subsequent analysis and modeling; Step 3: Model building: The digital twin model building module builds a digital twin model of the energy storage device based on the processed data to achieve virtual mapping and simulation of the actual energy storage device; Step 4: Formulate strategy: The strategy optimization module combines the results of mechanism simulation, numerical simulation and data-driven modeling to formulate the optimal energy storage strategy to ensure the feasibility and economy of the strategy in practical application; Step 5: Adjust strategy: The user interaction module provides users with a friendly interface, allowing users to easily understand the operating status of energy storage equipment and adjust energy storage strategies according to their own needs; Step 6: Adjust parameters: The energy storage control module adjusts the operating parameters of the energy storage equipment in real time according to the instructions of the strategy optimization module to achieve the optimal energy storage effect; Step 7: Status monitoring: The energy storage equipment status monitoring module monitors the operating status of the energy storage equipment in real time to ensure the safe and stable operation of the equipment and promptly alarms when an abnormality occurs; Step 8: Maintenance and replacement: Make equipment maintenance and replacement decisions based on the data provided by the energy storage equipment status monitoring module to ensure the long-term stable operation of the energy storage method.

Images