Hybrid energy storage management method and device, medium, electronic equipment and program product

Abstract

The invention relates to a hybrid energy storage management method and device, a medium, electronic equipment and a program product, relates to the technical field of new energy, and can improve the reliability and stability of a hybrid power generation system under complex working conditions. The method comprises the following steps: determining real-time power information output by the hybrid power generation system in a current period; determining intermediate power information according to the real-time power information and target power information corresponding to the current period, and determining a first action range corresponding to a flywheel energy storage system in the hybrid power generation system and a second action range corresponding to a compressed air energy storage system in the hybrid power generation system according to the target power information; and determining a target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first action range and the second action range, and controlling the operation state of the flywheel energy storage system and / or the compressed air energy storage system according to the target hybrid energy storage strategy.

Description

Technical Field

[0001] The present disclosure relates to the field of new energy technologies, and in particular, to a hybrid energy storage management method, device, medium, electronic device, and program product. Background Art

[0002] Currently, when the wind speed and light intensity of a new energy power generation system fluctuate violently and the load demand changes frequently, there is a situation where the energy distribution strategy cannot be adjusted in time. As a result, in complex working conditions where multiple uncertain factors are superimposed, problems such as slow response speed and unreliable energy distribution are likely to occur, and it is difficult to meet the high-efficiency operation requirements of the system, making the reliability and stability of the new energy power generation system relatively low under complex working conditions. Summary of the Invention

[0003] To solve the deficiencies of the prior art, the present disclosure provides a hybrid energy storage management method, device, medium, electronic device, and program product.

[0004] To achieve the above object, in a first aspect, the present disclosure provides a hybrid energy storage management method, the method comprising: Determining real-time power information output by a hybrid power generation system in a current period; Determining intermediate power information according to the real-time power information and target power information corresponding to the current period, and determining a first scope corresponding to a flywheel energy storage system in the hybrid power generation system and a second scope corresponding to a compressed air energy storage system in the hybrid power generation system according to the target power information; Determining a target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope, and controlling the operating states of the flywheel energy storage system and / or the compressed air energy storage system according to the target hybrid energy storage strategy.

[0005] In a second aspect, the present disclosure provides a hybrid energy storage management device, the device comprising: A determining module configured to determine real-time power information output by a hybrid power generation system in a current period; A processing module configured to determine intermediate power information according to the real-time power information and target power information corresponding to the current period, and determine a first scope corresponding to a flywheel energy storage system in the hybrid power generation system and a second scope corresponding to a compressed air energy storage system in the hybrid power generation system according to the target power information; An execution module configured to determine a target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope, and control the operating states of the flywheel energy storage system and / or the compressed air energy storage system according to the target hybrid energy storage strategy.

[0006] In a third aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0007] In a fourth aspect, the present disclosure provides an electronic device, including: a memory having a computer program stored thereon; a processor configured to execute the computer program in the memory to implement the method described in the first aspect.

[0008] In a fifth aspect, the present disclosure provides a computer program product including a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0009] Through the above technical solutions, the intermediate power information is determined according to the real-time power information and the target power information of the hybrid power generation system in the current cycle, and the first scope corresponding to the flywheel energy storage system and the second scope corresponding to the compressed air energy storage system are determined according to the target power information; the target hybrid energy storage strategy of the hybrid power generation system is determined according to the intermediate power information, the first scope, and the second scope, and the operating states of the two energy storage systems are controlled according to the target hybrid energy storage strategy, so that the hybrid power generation system can timely adjust the operating states of its two energy storage systems according to the changes in the operating conditions, meet the high-efficiency operation requirements of the system, and thus improve the reliability and stability of the hybrid power generation system under complex operating conditions.

[0010] Other features and advantages of the present disclosure will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings are used to provide a further understanding of the present disclosure, and constitute a part of the specification. Together with the following specific implementation, they are used to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings: Figure 1 is a flowchart of a hybrid energy storage management method shown according to an exemplary embodiment of the present disclosure.

[0012] Figure 2 is another flowchart of a hybrid energy storage management method shown according to an exemplary embodiment of the present disclosure.

[0013] Figure 3 is yet another flowchart of a hybrid energy storage management method shown according to an exemplary embodiment of the present disclosure.

[0014] Figure 4 is a block diagram of a hybrid energy storage management device shown according to an exemplary embodiment of the present disclosure.

[0015] Figure 5 It is a block diagram of an electronic device shown according to an exemplary embodiment of the present disclosure. Detailed Embodiments

[0016] The following will describe in detail the specific embodiments of the present disclosure with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for the purpose of illustrating and explaining the present disclosure, and are not used to limit the present disclosure.

[0017] It is worth noting that a hybrid power generation system mainly composed of renewable energy faces many challenges in terms of grid stability and power quality. The energy storage system in the hybrid power generation system is realized by the combination of flywheel energy storage and compressed air energy storage. The fast response characteristics of the flywheel and the high energy density of compressed air can effectively suppress the power fluctuations of wind power and solar power generation, and improve the stability and reliability of the power system. When the renewable energy system is connected to the grid, efficiently controlling the energy storage method of the hybrid power generation system can adjust the power output of the hybrid power generation system in real time, ensure grid stability, and thus significantly improve the utilization rate of renewable energy.

[0018] The inventors found that in the current energy management based on the integration of wind-solar hybrid energy storage, pure model control is difficult to quickly and accurately adjust itself to adapt to the dynamic changes of the power generation system when facing complex and changeable working conditions. There are deficiencies in the flexibility and response speed of its control parameter adjustment, which may cause the power generation system to have poor stability under different operating states. Although the hybrid control of the model and the algorithm combines the characteristics of both, it still cannot compare with the control model built by pure algorithms in terms of control parameter adjustment. Due to the mutual restriction of the model and the algorithm in the hybrid control method, the parameter adjustment is not efficient enough, the response speed is relatively slow, and the stability is also difficult to reach the optimal state.

[0019] Moreover, in the field of energy management of wind-solar hybrid energy storage integration, existing research mainly focuses on classical control algorithms such as particle swarm optimization algorithm and genetic algorithm. These algorithms are difficult to fully consider various dynamic factors and uncertainties under complex working conditions. When facing the drastic fluctuations of wind speed and light intensity and the frequent changes of load demand, they cannot adjust the energy distribution strategy in time, resulting in a decrease in the stability of the power generation system. And in the complex working conditions with the superposition of multiple uncertain factors, problems such as inaccurate optimization results and slow response speed are likely to occur, making it difficult to meet the requirements of efficient operation. On the other hand, due to the lack of powerful data analysis and pattern recognition capabilities, in complex working conditions, it is impossible to automatically extract key features from a large amount of data to accurately predict and respond to various changes, greatly reducing the reliability and energy utilization efficiency of the system in complex working conditions.

[0020] In view of this, the present disclosure provides a hybrid energy storage management method, device, medium, electronic device and program product, which can improve the reliability and stability of the hybrid power generation system under complex working conditions.

[0021] Figure 1 A hybrid energy storage management method shown according to an exemplary embodiment of the present disclosure. This method can be applied to electronic devices such as computers, laptops, smartphones, etc. As Figure 1 shown, this method may include the following steps: In step S101, determine the real-time power information output by the hybrid power generation system in the current cycle.

[0022] It should be noted that the hybrid power generation system can be a wind-solar hybrid energy storage power generation system that simultaneously covers wind power generation and photovoltaic power generation. The duration of each cycle can be preset according to the user's control requirements. For example, a cycle can be one hour, one day, one week, etc., and the present disclosure does not limit this.

[0023] In step S102, according to the real-time power information and the target power information corresponding to the current cycle, determine the intermediate power information, and according to the target power information, determine the first scope corresponding to the flywheel energy storage system in the hybrid power generation system and the second scope corresponding to the compressed air energy storage system in the hybrid power generation system.

[0024] It should be noted that the target power information in different cycles may be the same or different. Specifically, it can be preset according to the power consumption demand on the grid side or according to the user's power generation demand. The present disclosure does not limit this.

[0025] Among them, the scope includes, but is not limited to, the adjustment ability of its corresponding energy storage system to the fluctuations of power generation output and / or load demand. For example, the flywheel energy storage system includes the capacity for the fluctuations of power generation output and / or load demand, and the compressed air energy storage system includes the capacity for the fluctuations of power generation output and / or load demand.

[0026] Specifically, if the real-time power information includes multiple real-time powers output by the hybrid power generation system in the current cycle, then the target power information corresponding to the current cycle includes the target power corresponding to each real-time power of the hybrid power generation system in the current cycle.

[0027] Correspondingly, determining the intermediate power information according to the real-time power information and the target power information corresponding to the current cycle may include: for each moment in the current cycle, calculate the difference between the target power and the real-time power corresponding to the same moment to obtain an intermediate power value. Use the intermediate power value corresponding to each moment in the current cycle as the intermediate power information.

[0028] In step S103, according to the intermediate power information, the first scope, and the second scope, determine the target hybrid energy storage strategy of the hybrid power generation system, and according to the target hybrid energy storage strategy, control the operating states of the flywheel energy storage system and / or the compressed air energy storage system.

[0029] The present disclosure determines intermediate power information based on the real-time power information and target power information of the hybrid power generation system in the current cycle, and determines a first scope corresponding to the flywheel energy storage system and a second scope corresponding to the compressed air energy storage system according to the target power information; determines the target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope, and controls the operating states of the two energy storage systems according to the target hybrid energy storage strategy. The control model built based on pure algorithms, with its powerful computing power and flexible algorithm design, can respond more quickly to system changes, enabling the hybrid power generation system to adjust the operating states of its two energy storage systems in a timely manner according to changes in operating conditions and meet the high-efficiency operation requirements of the system. Moreover, under complex wind-solar hybrid energy storage operating conditions, it can perform precise analysis and decision-making based on real-time data, timely adjust control parameters, thereby improving the reliability and stability of the hybrid power generation system under complex operating conditions, ensuring that the wind-solar hybrid power generation system can maintain a high degree of stability and reliability under various operating conditions, and being unrestricted by the model structure, capable of optimizing the system performance more efficiently and providing more powerful guarantee for the stable operation of the wind-solar hybrid power generation system.

[0030] To facilitate a better understanding of the hybrid energy storage management method provided by the present disclosure by those skilled in the art, the steps of this method will be described in detail below.

[0031] In a feasible implementation manner, in step S101, determining the real-time power information output by the hybrid power generation system in the current cycle may include: According to the second preset constraint condition of the hybrid power generation system in the current cycle, with the goal of minimizing the output fluctuation and maximizing the output of the hybrid power generation system, controlling the operating state of the hybrid power generation system, and obtaining the real-time power information output by the hybrid power generation system in this operating state, where the second preset constraint condition includes the rated power of wind power output, the rated power of photovoltaic output, and the maximum charge-discharge power of the hybrid energy storage in the hybrid power generation system.

[0032] It should be noted that the second preset constraint condition corresponding to each cycle may be the same or different. Specifically, it can be preset according to the actual operating state of the hybrid power generation system, and the present disclosure does not limit this. And the second preset constraint condition includes, but is not limited to, the rated power of wind power output, the rated power of photovoltaic output, and the maximum charge-discharge power of the hybrid energy storage in the hybrid power generation system.

[0033] Specifically, within the current cycle, with the minimum output fluctuation and maximum output of the hybrid power generation system as the objective function, based on the constraints corresponding to the rated wind power output, rated photovoltaic power output, and maximum charge-discharge power of the hybrid energy storage in the current cycle, the charge-discharge states of the flywheel energy storage system and / or compressed air energy storage system in the hybrid power generation system are controlled, and the real-time power information output by the hybrid power generation system in this operating state is obtained.

[0034] In the embodiments of the present disclosure, on the premise of satisfying the second constraint condition, the charge-discharge states of the energy storage system in the hybrid power generation system are adaptively and optimally controlled, which can maximize the utilization of the output of wind power and photovoltaic power, avoid energy waste, further improve the stability of the overall output of the hybrid power generation system on the basis of improving the output efficiency of the hybrid power generation system, ensure that the output of the hybrid power generation system matches the grid demand, reduce the impact on the grid caused by power fluctuations, improve the stability and security of the grid, and enhance the grid adaptability.

[0035] In a feasible embodiment, in step S102, according to the target power information, determining the first scope corresponding to the flywheel energy storage system in the hybrid power generation system and the second scope corresponding to the compressed air energy storage system in the hybrid power generation system may include: Performing frequency division processing on the target power information to obtain a high-frequency component and a low-frequency component; According to the high-frequency component, determining the first scope for suppressing the high-frequency component corresponding to the flywheel energy storage system in the hybrid power generation system; According to the low-frequency component, determining the second scope for suppressing the low-frequency component corresponding to the compressed air energy storage system in the hybrid power generation system.

[0036] It should be noted that the flywheel energy storage system has characteristics such as small fluctuations, small energy, and fast response during the energy storage and energy release processes, and the compressed air energy storage system has characteristics such as large fluctuations, slow operation, and high energy density during the energy storage and energy release processes. Therefore, the high-frequency component can be suppressed by the flywheel energy storage system, and the low-frequency component can be suppressed by the compressed air energy storage system.

[0037] Specifically, after determining the high-frequency component and the low-frequency component of the hybrid power generation system in the current cycle, according to the characteristics of the flywheel energy storage system and the compressed air energy storage system, the scopes of the flywheel energy storage system and the compressed air energy storage system in the current cycle are respectively determined, that is, the operation time and capacity of the flywheel energy storage system and the compressed air energy storage system in the current cycle.

[0038] In the embodiments of the present disclosure, the high-frequency component and the low-frequency component obtained by performing frequency division processing on the target power information are used to configure the operation time and capacity of the flywheel energy storage system and the compressed air energy storage system, which can avoid the problems of over-investment or under-investment, thereby reducing the energy storage cost. Moreover, the subsequent target hybrid energy storage strategy determined based on the characteristics of the flywheel energy storage system and the compressed air energy storage system in dealing with power fluctuations of different frequencies can give full play to the characteristics of these two energy storage systems, achieve resource complementarity, and improve the overall energy storage efficiency.

[0039] In a feasible embodiment, the frequency division processing of the target power to obtain a high-frequency component and a low-frequency component may include: Performing a symplectic transformation on the target power information to obtain a symplectic matrix; According to the symplectic matrix, solving the eigenvectors and eigenvalues of the Hamiltonian matrix corresponding to the symplectic matrix, where the eigenvectors represent the modal components in the target power information, and the eigenvalues represent the frequencies of the modal components; Performing a similarity transformation on the symplectic matrix according to the eigenvectors to obtain a diagonal matrix, and performing modal component reconstruction according to the diagonal matrix and the eigenvalues to obtain the high-frequency component and the low-frequency component corresponding to the target power information.

[0040] It should be noted that in the embodiments of the present disclosure, the target power information can also be processed by any existing algorithm to obtain the high-frequency component and the low-frequency component corresponding to the target power information, such as Fourier transform, wavelet transform, empirical mode decomposition, and Gaussian low-pass filter, etc. The embodiments of the present disclosure do not specifically limit this.

[0041] In the embodiments of the present disclosure, the high-frequency component and the low-frequency component are obtained by decomposing the target power information in the above manner, which can improve the energy efficiency and cycle life of the two energy storage systems in the hybrid power generation system, and further reduce the operation and maintenance cost of the hybrid power generation system. By decomposing the target power information into high-frequency and low-frequency components, and allocating the high-frequency and low-frequency components, the two energy storage systems in the hybrid power generation system can more effectively suppress power fluctuations, reduce frequency deviation and voltage fluctuations in the power grid, and improve the stability and reliability of the power grid.

[0042] In a feasible embodiment, in step S103, according to the intermediate power information, the first scope, and the second scope, determining the target hybrid energy storage strategy of the hybrid power generation system may include: For the intermediate power value of the intermediate power information at each moment, when the intermediate power value is positive, according to the first scope and the second scope, determining that the target hybrid energy storage strategy includes controlling the flywheel energy storage system and / or the compressed air energy storage system to be in the energy release state; When the intermediate power value is negative, according to the first scope and the second scope, it is determined that the target hybrid energy storage strategy includes controlling the flywheel energy storage system and / or the compressed air energy storage system to be in the energy storage state.

[0043] It should be understood that the positive or negative of the intermediate power value characterizes the operating state of the energy storage system in the hybrid power generation system. For example, when the intermediate power value is positive, the real-time power at the current moment is less than the target power, and it is necessary to control the energy storage system in the hybrid power generation system to release energy; when the intermediate power value is negative, the real-time power at the current moment is greater than the target power, and it is necessary to control the energy storage system in the hybrid power generation system to store energy.

[0044] It is worth noting that when the energy release upper limit of a single energy storage system is less than the intermediate power value, this single energy storage system cannot meet the regulation requirements of the hybrid power generation system, and it is necessary to start another energy storage system to release energy; when the remaining capacity of a single energy storage system is less than the absolute value of the intermediate power value, the capacity of this single energy storage system cannot meet the regulation requirements of the hybrid power generation system, and it is necessary to start another energy storage system to store energy.

[0045] It should be understood that based on the positive or negative of the intermediate power value, the states of the two energy storage systems at different moments in the current cycle are determined according to the scopes of the two energy storage systems. For example, when the intermediate power value is positive, according to the first scope, it is determined that the flywheel energy storage system releases energy during the first operating time in the current cycle, and according to the second scope, it is determined that the compressed air system releases energy during the second operating time in the current cycle. Then, the corresponding target hybrid energy storage strategy includes controlling the flywheel energy storage system to release energy during the first operating time in the current cycle, and / or controlling the compressed air system to release energy during the second operating time in the current cycle. Correspondingly, when the intermediate power value is negative, the corresponding target hybrid energy storage strategy includes controlling the flywheel energy storage system to store energy during the first operating time in the current cycle, and / or controlling the compressed air system to store energy during the second operating time in the current cycle.

[0046] In a feasible implementation manner, in step S103, according to the intermediate power information, the first scope, and the second scope, determining the target hybrid energy storage strategy of the hybrid power generation system may include: Determining the intermediate hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope; After obtaining the intermediate hybrid energy storage strategies corresponding to multiple cycles, based on a multi-objective learning model, according to the first preset constraint condition, determining the target hybrid energy storage strategy from multiple intermediate hybrid energy storage strategies; Among them, the output power fluctuation corresponding to the target hybrid energy storage strategy is smaller than the output power fluctuations corresponding to the remaining intermediate hybrid energy storage strategies among the multiple intermediate hybrid energy storage strategies, and the energy utilization rate corresponding to the target hybrid energy storage strategy is greater than the energy utilization rates corresponding to the remaining intermediate hybrid energy storage strategies among the multiple intermediate hybrid energy storage strategies. The multi-objective learning model is used to output the corresponding output power fluctuation value and energy utilization rate according to the hybrid energy storage strategy. The first preset constraint condition includes the hybrid energy storage charge and discharge power limit, energy storage capacity limit, and state of charge of the hybrid power generation system.

[0047] It should be noted that the training set of the multi-objective learning model can be determined in the following way: Start the hybrid power generation system, and use the rated power of wind power output, the rated power of photovoltaic output, and the maximum charge and discharge power of the hybrid energy storage in the current cycle of the hybrid power generation system as constraint conditions. With the minimum output fluctuation and maximum output of the hybrid power generation system as the goals, control the operation of the hybrid power generation system, and continuously track the output powers of the wind power generation system and the photovoltaic power generation system in the hybrid power generation system. Based on the output powers of the wind power generation system and the photovoltaic power generation system, perform rolling prediction to obtain the training set. Correspondingly, through this training set, model training is carried out to obtain a multi-objective learning model. The multi-objective learning model can output the corresponding output power fluctuation value and energy utilization rate of the hybrid power generation system according to the input intermediate hybrid energy storage strategy.

[0048] Exemplarily, as Figure 2 shown, the hybrid energy storage management method provided by the present disclosure may include the following steps: In step S101, determine the real-time power information output by the hybrid power generation system in the current cycle.

[0049] In step S102, according to the real-time power information and the target power information corresponding to the current cycle, determine the intermediate power information, and according to the target power information, determine the first scope corresponding to the flywheel energy storage system in the hybrid power generation system and the second scope corresponding to the compressed air energy storage system in the hybrid power generation system.

[0050] In step S1031, according to the intermediate power information, the first scope, and the second scope, determine the intermediate hybrid energy storage strategy of the hybrid power generation system.

[0051] In step S1032, after obtaining the intermediate hybrid energy storage strategies corresponding to multiple cycles, based on the multi-objective learning model and according to the first preset constraint condition, determine the target hybrid energy storage strategy from the multiple intermediate hybrid energy storage strategies.

[0052] In the embodiments of the present disclosure, intelligent decision-making is performed through a multi-objective learning model to select the optimal target hybrid energy storage strategy from multiple intermediate hybrid energy storage strategies, which can reduce the operating cost of the energy storage system and improve economic benefits while meeting the system requirements; the target hybrid energy storage strategy can enable the hybrid power generation system to better adapt to the intermittency and instability of renewable energy and promote the consumption and utilization of renewable energy. Moreover, the entire process requires no manual intervention, greatly improving work efficiency and accuracy.

[0053] The following uses a complete example to illustrate the hybrid energy storage management method provided by the present disclosure. As Figure 3 shown, the hybrid energy storage management method includes: In step S301, start the wind power generation system and the photovoltaic power generation system.

[0054] In step S302, control the operating states of the wind power generation system and the photovoltaic power generation system, perform real-time tracking and hybrid prediction, obtain the real-time power information of the current cycle, and execute step S305.

[0055] Specifically, the objective function in the control process is: the output fluctuation is minimized and the wind and light output is maximized. The constraint conditions include: the rated power of wind power output, the rated power of photovoltaic output, and the maximum charge and discharge power of the energy storage.

[0056] In step S303, determine the target power information corresponding to the current cycle.

[0057] Specifically, based on the flywheel energy storage system responding to high frequency and the compressed air energy storage system responding to low frequency, determine the target power information corresponding to the current cycle.

[0058] In step S304, determine the first scope of action of the flywheel energy storage system and the second scope of action of the compressed air energy storage system, and execute step S305.

[0059] In step S305, determine the intermediate hybrid energy storage strategy according to the real-time power information, the target power information, the first scope of action, and the second scope of action.

[0060] Specifically, the intermediate hybrid energy storage strategy follows the principle of real-time energy conservation.

[0061] In step S306, input the intermediate hybrid energy storage strategies corresponding to multiple cycles into the multi-objective learning model to obtain the output power fluctuation value and energy utilization rate corresponding to each intermediate hybrid energy storage strategy output by the multi-objective learning model.

[0062] Specifically, the objective function of the multi-objective learning model includes minimizing the output power fluctuation and maximizing the energy utilization rate. The constraint conditions include the energy storage charge and discharge power limit, the energy storage capacity limit, and the state of charge.

[0063] In step S307, a target hybrid energy storage strategy is obtained.

[0064] Specifically, the output power fluctuation of the target hybrid energy storage strategy is smaller than that of the remaining intermediate hybrid energy storage strategies among the intermediate hybrid energy storage strategies corresponding to multiple cycles, and the energy utilization rate corresponding to the target hybrid energy storage strategy is greater than that of the remaining intermediate hybrid energy storage strategies among the intermediate hybrid energy storage strategies corresponding to multiple cycles.

[0065] In the embodiment of the present disclosure, a unique two-layer structure is adopted for energy management, with distinct levels. In the first layer, the wind power generation system and the photovoltaic power generation system are precisely controlled. With the goal of minimizing output fluctuations and maximizing the output of wind and light, adaptive adjustment is performed based on the corresponding constraints. By real-time tracking and rolling prediction of the energy output of the wind power generation system and the photovoltaic power generation system, combined with the scheduling requirements of energy and the characteristics of flywheel suppressing high frequency and compressed air suppressing low frequency, the scope of action of the flywheel energy storage system and the compressed air energy storage system is distinguished, ensuring the real-time conservation of energy under the hybrid energy storage operation strategy and efficiently coordinating the work of each part. In the second layer, artificial intelligence is used for multi-objective deep optimization learning. With the goal of minimizing output power fluctuations and maximizing energy utilization rate, it provides strong support for improving system performance. In addition, multi-objective deep optimization learning can be performed regularly according to historical power information, adaptively optimizing decisions, promptly discovering problems and making improvements, greatly improving system stability.

[0066] Based on the same inventive concept, the present disclosure also provides a hybrid energy storage management device, as Figure 4 shown. The hybrid energy storage management device includes a determination module 401, a processing module 402, and an execution module 403.

[0067] Among them, the determination module 401 is configured to determine the real-time power information output by the hybrid power generation system in the current cycle; The processing module 402 is configured to determine intermediate power information according to the real-time power information and the target power information corresponding to the current cycle, and determine a first scope of action corresponding to the flywheel energy storage system in the hybrid power generation system and a second scope of action corresponding to the compressed air energy storage system in the hybrid power generation system according to the target power information; The execution module 403 is configured to determine the target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope of action, and the second scope of action, and control the operating states of the flywheel energy storage system and / or the compressed air energy storage system according to the target hybrid energy storage strategy.

[0068] The present disclosure determines intermediate power information based on the real-time power information and target power information of the hybrid power generation system in the current cycle, and determines a first scope corresponding to the flywheel energy storage system and a second scope corresponding to the compressed air energy storage system according to the target power information; determines the target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope, and controls the operating states of the two energy storage systems according to the target hybrid energy storage strategy. The control model built based on pure algorithms, with its powerful computing ability and flexible algorithm design, can respond more quickly to system changes, enable the hybrid power generation system to adjust the operating states of its two energy storage systems in a timely manner according to the changes in working conditions, and meet the high-efficiency operation requirements of the system. Moreover, in complex wind-solar hybrid energy storage working conditions, it can perform precise analysis and decision-making based on real-time data, adjust control parameters in a timely manner, thereby improving the reliability and stability of the hybrid power generation system under complex working conditions, ensuring that the wind-solar hybrid power generation system can maintain a high degree of stability and reliability under various working conditions, and being unrestricted by the model structure, can optimize the system performance more efficiently, and provide a more powerful guarantee for the stable operation of the wind-solar hybrid power generation system.

[0069] Optionally, the execution module 403 is configured to determine an intermediate hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope; After obtaining the intermediate hybrid energy storage strategies corresponding to multiple cycles, based on a multi-objective learning model, according to a first preset constraint condition, determine a target hybrid energy storage strategy from multiple intermediate hybrid energy storage strategies; wherein, the output power fluctuation corresponding to the target hybrid energy storage strategy is smaller than the output power fluctuations corresponding to the remaining intermediate hybrid energy storage strategies among the multiple intermediate hybrid energy storage strategies, and the energy utilization rate corresponding to the target hybrid energy storage strategy is greater than the energy utilization rates corresponding to the remaining intermediate hybrid energy storage strategies among the multiple intermediate hybrid energy storage strategies. The multi-objective learning model is used to output corresponding output power fluctuation values and energy utilization rates according to the hybrid energy storage strategy, and the first preset constraint condition includes the hybrid energy storage charge and discharge power limit, energy storage capacity limit, and state of charge of the hybrid power generation system.

[0070] Optionally, the processing module 402 is configured to perform frequency division processing on the target power information to obtain a high-frequency component and a low-frequency component; Determine a first scope for suppressing the high-frequency component corresponding to the flywheel energy storage system in the hybrid power generation system according to the high-frequency component; Determine a second scope for suppressing the low-frequency component corresponding to the compressed air energy storage system in the hybrid power generation system according to the low-frequency component.

[0071] Optionally, the processing module 402 is configured to perform a symplectic transformation on the target power information to obtain a symplectic matrix; According to the symplectic matrix, solve the eigenvectors and eigenvalues of the Hamiltonian matrix corresponding to the symplectic matrix, where the eigenvectors characterize the modal components in the target power information, and the eigenvalues characterize the frequencies of the modal components; Perform a similarity transformation on the symplectic matrix according to the eigenvectors to obtain a diagonal matrix, and perform modal component reconstruction according to the diagonal matrix and the eigenvalues to obtain the high-frequency components and low-frequency components corresponding to the target power information.

[0072] Optionally, the determination module 401 is configured to control the operating state of the hybrid power generation system with the goal of minimizing the output fluctuation and maximizing the output of the hybrid power generation system according to the second preset constraint condition of the hybrid power generation system in the current period, and obtain the real-time power information output by the hybrid power generation system in the operating state, where the second preset constraint condition includes the rated power of wind power output, the rated power of photovoltaic output, and the maximum charge and discharge power of the hybrid energy storage in the hybrid power generation system.

[0073] Optionally, the execution module 403 is configured to, for the intermediate power value of the intermediate power information at each moment, when the intermediate power value is positive, determine that the target hybrid energy storage strategy includes controlling the flywheel energy storage system and / or the compressed air energy storage system to be in the energy release state according to the first scope and the second scope; When the intermediate power value is negative, determine that the target hybrid energy storage strategy includes controlling the flywheel energy storage system and / or the compressed air energy storage system to be in the energy storage state according to the first scope and the second scope.

[0074] Regarding the hybrid energy storage management device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0075] Based on the same inventive concept, the present disclosure also provides an electronic device, including: A memory storing a computer program thereon; A processor configured to execute the computer program in the memory to implement the above hybrid energy storage management method.

[0076] The present disclosure determines intermediate power information based on the real-time power information and target power information of a hybrid power generation system in the current cycle, and determines a first scope corresponding to a flywheel energy storage system and a second scope corresponding to a compressed air energy storage system according to the target power information; determines a target hybrid energy storage strategy for the hybrid power generation system according to the intermediate power information, the first scope, and the second scope, and controls the operating states of the two energy storage systems according to the target hybrid energy storage strategy. The control model built based on pure algorithms, with its powerful computing power and flexible algorithm design, can respond more quickly to system changes, enabling the hybrid power generation system to adjust the operating states of its two energy storage systems in a timely manner with changes in working conditions, meeting the high-efficiency operation requirements of the system. Moreover, under complex wind-solar hybrid energy storage working conditions, it can perform precise analysis and decision-making based on real-time data, timely adjust control parameters, thereby improving the reliability and stability of the hybrid power generation system under complex working conditions, ensuring that the wind-solar hybrid power generation system can maintain a high degree of stability and reliability under various working conditions, and being unrestricted by the model structure, capable of more efficiently optimizing system performance, providing a more powerful guarantee for the stable operation of the wind-solar hybrid power generation system.

[0077] Figure 5 is a block diagram of an electronic device 500 shown according to an exemplary embodiment. As Figure 5 shown, the electronic device 500 may include: a processor 501, a memory 502. The electronic device 500 may further include one or more of a multimedia component 503, an input / output (I / O) interface 504, and a communication component 505.

[0078] Among them, the processor 501 is used to control the overall operation of the electronic device 500 to complete all or part of the steps in the above-mentioned hybrid energy storage management method. The memory 502 is used to store various types of data to support the operation of the electronic device 500. These data may include, for example, instructions for any application or method operating on the electronic device 500, as well as application-related data, such as real-time power information, target power information, intermediate power information, and target hybrid energy storage strategies, etc. The memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc. The multimedia component 503 may include a screen and an audio component. The screen may be a touch screen, for example, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 502 or sent through the communication component 505. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 504 provides an interface between the processor 501 and other interface modules, and the above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 505 is used for wired or wireless communication between the electronic device 500 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them. Accordingly, the communication component 505 may include: a Wi-Fi module, a Bluetooth module, and an NFC module.

[0079] In an exemplary embodiment, the electronic device 500 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned hybrid energy storage management method.

[0080] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When the program instructions are executed by a processor, the steps of the above-mentioned hybrid energy storage management method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 502 including program instructions, and the above-mentioned program instructions can be executed by the processor 501 of the electronic device 500 to complete the above-mentioned hybrid energy storage management method.

[0081] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the above-mentioned hybrid energy storage management method are implemented.

[0082] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the above-mentioned hybrid energy storage management method are implemented.

[0083] The preferred embodiments of the present disclosure have been described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0084] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present disclosure does not separately describe various possible combination manners.

[0085] Furthermore, any combination can be made among the various different embodiments of the present disclosure as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

Claims

1. A hybrid energy storage management method, characterized in that: The method comprises: Determine the real-time power information output by the hybrid power generation system in the current cycle; Determine intermediate power information according to the real-time power information and the target power information corresponding to the current cycle, and determine a first scope corresponding to the flywheel energy storage system in the hybrid power generation system and a second scope corresponding to the compressed air energy storage system in the hybrid power generation system according to the target power information; According to the intermediate power information, the first scope and the second scope, a target hybrid energy storage strategy of the hybrid power generation system is determined, and according to the target hybrid energy storage strategy, the operating state of the flywheel energy storage system and / or the compressed air energy storage system is controlled.

2. The hybrid energy storage management method according to claim 1, characterized in that: The step of determining a target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope includes: Determining an intermediate hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope; After obtaining the intermediate hybrid energy storage strategies corresponding to the multiple cycles, based on the multi-objective learning model and according to the first preset constraint condition, determining the target hybrid energy storage strategy from the multiple intermediate hybrid energy storage strategies; Among them, the output power fluctuation corresponding to the target hybrid energy storage strategy is smaller than the output power fluctuation corresponding to the remaining intermediate hybrid energy storage strategies in the multiple intermediate hybrid energy storage strategies, and the energy utilization rate corresponding to the target hybrid energy storage strategy is greater than the energy utilization rate corresponding to the remaining intermediate hybrid energy storage strategies in the multiple intermediate hybrid energy storage strategies, and the multi-objective learning model is used to output the corresponding output power fluctuation value and energy utilization rate according to the hybrid energy storage strategy, and the first preset constraint condition includes the hybrid energy storage charging and discharging power limit, energy storage capacity limit and charge state of the hybrid power generation system.

3. The hybrid energy storage management method according to any one of claim 1, characterized in that: Determining, according to the target power information, a first scope corresponding to the flywheel energy storage system in the hybrid power generation system and a second scope corresponding to the compressed air energy storage system in the hybrid power generation system, comprises: Performing frequency division processing on the target power information to obtain a high-frequency component and a low-frequency component; According to the high-frequency component, determining a first action domain corresponding to the flywheel energy storage system in the hybrid power generation system for smoothing the high-frequency component; According to the low-frequency component, a second scope of action for smoothing the low-frequency component corresponding to the compressed air energy storage system in the hybrid power generation system is determined.

4. The hybrid energy storage management method according to claim 3, characterized in that: The frequency division processing of the target power to obtain a high-frequency component and a low-frequency component includes: Performing symplectic transformation on the target power information to obtain a symplectic matrix; According to the symplectic matrix, solving the eigenvector and eigenvalue of the Hamiltonian matrix corresponding to the symplectic matrix, the eigenvector represents the modal component in the target power information, and the eigenvalue represents the frequency of the modal component; A similarity transformation is performed on the symplectic matrix according to the eigenvector to obtain a diagonal matrix, and modal components are reconstructed according to the diagonal matrix and the eigenvalue to obtain high-frequency components and low-frequency components corresponding to the target power information.

5. The hybrid energy storage management method according to any one of claims 1 to 4, characterized in that: The step of determining the real-time power information output by the hybrid power generation system in the current cycle includes: According to the second preset constraint condition of the hybrid power generation system in the current cycle, with the goal of minimizing the output fluctuation and maximizing the output of the hybrid power generation system, the operating state of the hybrid power generation system is controlled, and the real-time power information output by the hybrid power generation system in the operating state is obtained, and the second preset constraint condition includes the rated power output of wind power, the rated power output of photovoltaic power and the maximum charging and discharging power of hybrid energy storage in the hybrid power generation system.

6. The hybrid energy storage management method according to any one of claims 1 to 4, characterized in that: The step of determining a target hybrid energy storage strategy of the hybrid power generation system according to the intermediate power information, the first scope, and the second scope includes: For the intermediate power value of the intermediate power information at each moment, when the intermediate power value is positive, determining, according to the first scope and the second scope, that the target hybrid energy storage strategy includes controlling the flywheel energy storage system and / or the compressed air energy storage system to be in an energy release state; When the intermediate power value is negative, determining the target hybrid energy storage strategy according to the first scope and the second scope includes controlling the flywheel energy storage system and / or the compressed air energy storage system to be in an energy storage state.

7. A hybrid energy storage management device, characterized in that: The device comprises: A determination module, configured to determine real-time power information output by the hybrid power generation system in a current cycle; A processing module is configured to determine the intermediate power information according to the real-time power information and the target power information corresponding to the current cycle, and determine the first scope corresponding to the flywheel energy storage system in the hybrid power generation system and the second scope corresponding to the compressed air energy storage system in the hybrid power generation system according to the target power information; An execution module is configured to determine a target hybrid energy storage strategy of the hybrid power generation system based on the intermediate power information, the first scope, and the second scope, and to control the operating state of the flywheel energy storage system and / or the compressed air energy storage system according to the target hybrid energy storage strategy.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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