Dynamic regulation method and system for electric hydrogen energy storage

Abstract

This disclosure relates to a dynamic control method and system for electro-hydrogen energy storage, belonging to the field of energy management optimization and control technology. The method includes: predicting the power demand load at a set time or multiple set time periods using a power demand forecasting model corresponding to the electro-hydrogen energy storage system; determining the minimum output power of the hydrogen storage in the electro-hydrogen energy storage system at the set time or multiple set time periods based on the power demand load at the set time or multiple set time periods, the hydrogen energy conversion efficiency of the hydrogen storage in the electro-hydrogen energy storage system, and the maximum hydrogen storage output power; and determining the hydrogen reserve at the set time or multiple set time periods based on the minimum output power at the set time or multiple set time periods, the output power corresponding to the amount of hydrogen charged at a time prior to the set time or multiple set time periods, the hydrogen energy conversion efficiency, and the hydrogen reserve. This enables dynamic control of electro-hydrogen energy storage.

Description

Technical Field

[0001] This disclosure relates to the field of energy management optimization and control technology, and in particular to a dynamic regulation method and dynamic regulation system for electro-hydrogen energy storage. Background Technology

[0002] The hybrid electric-hydrogen energy storage system is an advanced energy system that combines renewable energy, battery storage, and hydrogen storage technologies to achieve efficient and stable energy management. This system aims to reduce dependence on traditional fossil fuels by utilizing renewable energy sources, while addressing the instability of energy supply and fluctuations in load demand through multiple energy storage technologies. Batteries and hydrogen storage can improve the reliability of renewable energy utilization. The energy storage system can store excess electricity when power generation exceeds load demand and release electricity when power generation falls below load demand, thus smoothing out these fluctuations. Hydrogen energy, as a long-term energy storage medium, can compensate for the volatility and intermittency of photovoltaics, promoting its large-scale development. However, it cannot respond promptly to fluctuations at the millisecond / second level. Battery storage, with its low energy density and fast response, can compensate for the short-term response of hydrogen storage. The combination of electric and hydrogen energy storage is key to improving system energy efficiency.

[0003] Hybrid energy storage systems utilize both battery and hydrogen energy storage, necessitating a balance between rapid short-term response and long-term energy storage in system scheduling. Furthermore, battery storage is extremely expensive, costing twenty to thirty times more than hydrogen storage for the same energy capacity. Therefore, reducing the cost of hybrid energy storage systems remains a challenge.

[0004] Furthermore, changes in electricity demand can occur within minutes or even seconds, and existing solutions may not be able to respond to these changes in a timely manner.

[0005] Patent CN118569086A optimizes the degradation of the electrolyzer and the regulating capacity of the hydrogen energy storage system in a hybrid electro-hydrogen energy storage system. It uses an algorithm to set a first objective function that minimizes the degradation of the electrolyzer within one operating cycle, and a second objective function that maximizes the regulating capacity of the hydrogen energy storage system within one operating cycle. This reduces battery loss and lowers costs.

[0006] However, this approach primarily focuses on two objectives: the degradation rate of the electrolyzer and the regulating capacity of the hydrogen energy storage system. It neglects other important factors of the entire system. For example, the rapid response capability of the battery energy storage system and the overall economic efficiency of the system have not been adequately considered.

[0007] Patent CN 118449173A proposes an optimized scheduling method for an electric-hydrogen hybrid energy storage system that takes into account both long-term and short-term coordination. By introducing a multi-timescale (long-cycle stage and short-cycle stage) scheduling mechanism, it solves the problem of short scheduling timescales in existing technologies, especially the difficulty in adapting to long-term hydrogen energy storage scheduling needs.

[0008] However, this patented method performs daily rolling optimization scheduling in short-cycle phases, but may overlook the need for rapid response to real-time load fluctuations. Changes in electricity demand can occur on an hourly or even minute-by-minute scale, and this solution cannot cope with such changes.

[0009] Overall, there is currently no utilization of hydrogen energy storage systems to proactively respond to loads, thus increasing the reliance on battery energy storage and consequently raising costs. Furthermore, load fluctuations at the minute / second level are not being addressed, and the advantages of battery energy storage are not being effectively utilized. Summary of the Invention

[0010] This disclosure proposes a dynamic control method for electro-hydrogen energy storage and a corresponding technical solution for an electro-hydrogen energy storage dynamic control system.

[0011] According to one aspect of this disclosure, a dynamic control method for hydrogen energy storage is provided, comprising:

[0012] The power demand forecasting model corresponding to the electric hydrogen energy storage system is used to predict the power demand load at a set time or at multiple set times (power demand forecasting load).

[0013] Based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to the hydrogen energy storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power, determine the minimum output power (minimum predicted output power) of the hydrogen energy storage in the electric hydrogen energy storage system corresponding to the set time or multiple set times.

[0014] Based on the minimum output power corresponding to the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time before the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve, the hydrogen reserve corresponding to the set time or multiple set times is determined.

[0015] Preferably, before using the power demand prediction model corresponding to the electric hydrogen energy storage system to predict the power demand load at a set time or multiple set times, the power demand prediction model is established. The method includes: acquiring a set neural network or convolutional neural network and corresponding historical load data, and using the historical load data to train the set neural network or convolutional neural network to obtain the power demand prediction model corresponding to the electric hydrogen energy storage system; wherein, the historical load data includes at least: historical power demand load.

[0016] Preferably, the historical load data further includes: external factor data affecting the historical power demand load; and / or, the external factor data corresponding to the historical power demand load includes at least one or more of the following: temperature, humidity, seasonal changes, and holiday information.

[0017] Preferably, before training the set neural network or convolutional neural network using the historical load data, outlier removal or missing value imputation is performed on the historical load data; and / or, before training the set neural network or convolutional neural network using the historical load data, normalization processing is further performed on the historical load data.

[0018] Preferably, the configured neural network or convolutional neural network is a long short-term memory network or a network based on it.

[0019] Preferably, the method for determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen energy storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power includes: determining the hydrogen energy storage output power corresponding to the power demand load based on the power demand load corresponding to the set time or multiple set times and the hydrogen energy conversion efficiency; and determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times from the maximum hydrogen energy storage output power and the hydrogen energy storage output power corresponding to the power demand load.

[0020] Preferably, the method for determining the hydrogen reserve at a set time or multiple set times based on the minimum output power at the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time preceding the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve includes: determining the output power and minimum output power corresponding to the amount of hydrogen charged under the time change at the set time or multiple set times and the time preceding the set time or multiple set times; determining the change in hydrogen reserve using the output power and minimum output power corresponding to the amount of hydrogen charged under the time change; and updating the hydrogen reserve at the set time or multiple set times based on the change in hydrogen reserve and the hydrogen reserve corresponding to the time preceding the set time or multiple set times.

[0021] Preferably, the method for determining the minimum output power corresponding to the amount of hydrogen charged under the time change corresponding to the set time or multiple set times and the time before that time includes: multiplying the time change corresponding to the set time or multiple set times at the previous time by the output power corresponding to the amount of hydrogen charged at the set time or multiple set times at the previous time, to determine the output power corresponding to the amount of hydrogen charged under the time change; or, subtracting the output power corresponding to the amount of hydrogen charged at the time before that time from the output power corresponding to the amount of hydrogen charged at the time before that time, to determine the output power corresponding to the amount of hydrogen charged under the time change.

[0022] Preferably, the method for determining the minimum output power corresponding to the amount of hydrogen charged under the time change corresponding to the set time or multiple set times and the time before that time includes: multiplying the time change corresponding to the set time or multiple set times by the minimum output power corresponding to the set time or multiple set times to determine the minimum output power under the time change; or, subtracting the minimum output power corresponding to the previous time before the set time or multiple set times from the minimum output power corresponding to the minimum output power corresponding to the set time or multiple set times to determine the minimum output power under the time change.

[0023] Preferably, the method for determining the change in hydrogen reserves using the output power corresponding to the amount of hydrogen charged under the time change and the minimum output power includes: subtracting the minimum output power under the time change from the output power corresponding to the amount of hydrogen charged under the time change to obtain the corresponding change in output power; dividing the change in output power by the hydrogen energy conversion efficiency to obtain the corresponding change in hydrogen reserves; or, dividing the output power corresponding to the amount of hydrogen charged under the time change by the hydrogen energy conversion efficiency to obtain the change in hydrogen increase; dividing the minimum output power under the time change by the hydrogen energy conversion efficiency to obtain the hydrogen consumption; and subtracting the hydrogen consumption from the change in hydrogen increase to determine the change in hydrogen reserves.

[0024] Preferably, the method for updating the hydrogen reserve corresponding to the set time or multiple time periods based on the change in hydrogen reserve and the hydrogen reserve corresponding to the time period before the set time or multiple time periods includes: adding the change in hydrogen reserve to the hydrogen reserve corresponding to the time period before the set time or multiple time periods, and then updating the hydrogen reserve corresponding to the set time or multiple time periods.

[0025] Preferably, the dynamic control method further includes: dynamically adjusting the amount of hydrogen corresponding to the hydrogen energy storage based on the updated hydrogen reserve.

[0026] Preferably, the method for dynamically adjusting the amount of hydrogen corresponding to the hydrogen energy storage based on the updated hydrogen reserve includes: obtaining the maximum hydrogen reserve corresponding to the maximum output power of the hydrogen energy storage; during the process of using the hydrogen energy storage to supply power, if the hydrogen reserve corresponding to the set time or multiple set times is less than the updated hydrogen reserve and less than the maximum hydrogen reserve, then further charging the hydrogen energy storage with hydrogen based on the updated hydrogen reserve; otherwise, not further charging the hydrogen energy storage with hydrogen until the hydrogen reserve corresponding to the set time or multiple set times is less than the updated hydrogen reserve and less than the maximum hydrogen reserve, then further charging the hydrogen energy storage with hydrogen based on the updated hydrogen reserve again.

[0027] Preferably, the dynamic control method further includes: real-time detection of the current power demand load, the current hydrogen energy storage output power, or the predicted power demand load corresponding to the current time at a set time or multiple set times (predicting the power demand load corresponding to the set time or multiple set times using the power demand prediction model corresponding to the electric hydrogen energy storage system, i.e., the predicted power demand load) or the minimum predicted output power (the minimum output power of hydrogen storage in the electric hydrogen energy storage system corresponding to the set time or multiple set times, i.e., the minimum predicted output power); based on the current power demand load and the current hydrogen energy storage output power or the predicted power demand load or the minimum predicted output power, adjusting the hydrogen energy storage in the electric hydrogen energy storage system to battery energy storage for power supply.

[0028] Preferably, the method for adjusting the hydrogen energy storage in the electro-hydrogen energy storage system to battery energy storage for power supply includes: calculating the load / power difference between the current power demand load and the current hydrogen energy storage output power or minimum predicted output power (the output power of the battery energy storage at the current time); and updating the energy storage capacity corresponding to the current time based on the load / power difference and the conversion efficiency of the battery corresponding to the battery energy storage.

[0029] Preferably, the method for updating the energy storage capacity at the current moment based on the load / power difference and the conversion efficiency of the battery corresponding to the battery energy storage includes: determining the load / power difference under the time change corresponding to the current moment and previous moments; determining the change in energy storage capacity using the load / power difference under the time change and the conversion efficiency of the battery; and updating the energy storage capacity at the current moment based on the change in energy storage capacity and the energy storage capacity corresponding to the previous moment.

[0030] Preferably, before determining the load / power difference under the time change corresponding to the current time and previous times, the determination includes: multiplying the time change corresponding to the current time and previous times by the load / power difference corresponding to the current time to determine the load / power difference under the time change corresponding to the current time and previous times; or, subtracting the load / power difference corresponding to the current time from the load / power difference corresponding to the current time and previous times (e.g., the previous time) to determine the load / power difference under the time change corresponding to the current time and previous times.

[0031] Preferably, the method for determining the change in energy storage capacity using the load / power difference under the time change and the conversion efficiency of the battery includes: dividing the load / power difference under the time change by the conversion efficiency of the battery to obtain the corresponding change (energy storage consumption).

[0032] Preferably, the method for updating the current energy storage capacity based on the change in energy storage capacity and the energy storage capacity at a previous time (e.g., the previous time) includes: subtracting the change in energy storage capacity from the energy storage capacity at a previous time to update the current energy storage capacity.

[0033] Preferably, the dynamic control method further includes: obtaining the predicted power demand load corresponding to a set time or multiple set time periods predicted by the power demand forecasting model; if the predicted power demand load corresponding to a certain time period or multiple set time periods is less than the actual power demand load corresponding to that time period, then the hydrogen energy storage in the hydrogen-electric energy storage system is adjusted to battery energy storage for power supply. This addresses the current technical problem of not processing load fluctuations at the minute / second level and not effectively utilizing the advantages of battery energy storage.

[0034] According to one aspect of this disclosure, a dynamic control method for hydrogen energy storage is provided, comprising: acquiring the current power demand load corresponding to the electric hydrogen energy storage system and the output power, maximum energy storage capacity, minimum energy storage capacity, energy storage capacity or updated energy storage capacity of the battery energy storage in the electric hydrogen energy storage system;

[0035] Using the power demand forecasting model corresponding to the electric hydrogen energy storage system, the power demand forecast load is set at a time or multiple times after the current time. Based on the power demand forecast load corresponding to the set time or multiple times, the hydrogen energy conversion efficiency and the maximum hydrogen energy output power of the hydrogen energy storage in the electric hydrogen energy storage system, the minimum output power of the hydrogen energy storage in the electric hydrogen energy storage system corresponding to the set time or multiple times is determined.

[0036] The objective function is determined based on the current power demand load, the output power of the battery energy storage, the maximum storage capacity, the minimum storage capacity, the storage capacity or the updated storage capacity, and the minimum output power of the hydrogen energy storage.

[0037] While maximizing the utilization of hydrogen energy storage, the frequency of battery use and / or deep discharge in battery energy storage are minimized. Based on the objective function, the optimized output power of the battery and the optimized output power of hydrogen energy storage system at the current moment are determined.

[0038] Preferably, the method for determining the objective function based on the current power demand load, the maximum capacity, minimum capacity, current capacity or renewed capacity of the battery energy storage, and the minimum output power of the hydrogen energy storage includes: determining the battery energy storage output power ratio corresponding to the objective function based on the current power demand load and the output power of the battery energy storage; determining the hydrogen energy storage output power ratio corresponding to the objective function based on the current power demand load and the minimum output power of the hydrogen energy storage; determining the depth of discharge percentage corresponding to the objective function based on the maximum capacity, minimum capacity, current capacity or renewed capacity of the battery energy storage; and constructing the objective function based on the battery energy storage output power ratio, the hydrogen energy storage output power ratio, and the depth of discharge percentage.

[0039] Preferably, the method for constructing the objective function based on the battery energy storage output power ratio, the hydrogen energy storage output power ratio, and the discharge depth percentage further includes: obtaining a first weighting coefficient, a second weighting coefficient, and a third weighting coefficient corresponding to the battery energy storage output power ratio, the discharge depth percentage, and the hydrogen energy storage output power ratio, respectively; assigning weights to the battery energy storage output power ratio, the discharge depth percentage, and the hydrogen energy storage output power ratio using the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, respectively; and constructing the objective function based on the weighted battery energy storage output power ratio, the hydrogen energy storage output power ratio, and the discharge depth percentage.

[0040] Preferably, the method for determining the updated storage capacity includes: determining the load / power difference under the time change corresponding to the current time and previous times; determining the change in storage capacity using the load / power difference under the time change and the conversion efficiency of the battery; and updating the storage capacity corresponding to the current time (updated storage capacity) based on the change in storage capacity and the storage capacity corresponding to the time before the current time.

[0041] Preferably, the method for determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times based on the predicted power demand load at the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power includes: determining the hydrogen energy storage output power corresponding to the predicted power demand load based on the predicted power demand load at the set time or multiple set times and the hydrogen energy conversion efficiency; and determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times from the maximum hydrogen energy storage output power and the hydrogen energy storage output power corresponding to the predicted power demand load.

[0042] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising:

[0043] The prediction unit is used to predict the power demand load at a set time or at multiple set times using the power demand prediction model corresponding to the electric hydrogen energy storage system.

[0044] The first determining unit is used to determine the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power.

[0045] The control unit is used to determine the hydrogen reserve corresponding to the set time or multiple set times based on the minimum output power corresponding to the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time before the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve.

[0046] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising:

[0047] The acquisition unit is used to acquire the current power demand load of the electric hydrogen energy storage system and the output power, maximum storage capacity, minimum storage capacity, storage capacity or updated storage capacity of the battery energy storage in the electric hydrogen energy storage system.

[0048] The second determining unit is used to utilize the power demand prediction model corresponding to the electric hydrogen energy storage system to predict the power demand load at a set time or multiple times after the current time, and to determine the minimum output power of the hydrogen storage in the electric hydrogen energy storage system at the set time or multiple times based on the power demand prediction load corresponding to the set time or multiple times, the hydrogen energy conversion efficiency corresponding to the hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power.

[0049] The objective function determination unit is used to determine the objective function based on the power demand load at the current moment, the output power of the battery energy storage, the maximum storage capacity, the minimum storage capacity, the storage capacity or the updated storage capacity, and the minimum output power of the hydrogen energy storage.

[0050] An optimization unit is used to maximize the utilization of the hydrogen energy storage while minimizing the usage frequency and / or deep discharge of the battery in the battery energy storage, and to determine the optimized battery output power and optimized hydrogen energy storage output power of the electro-hydrogen energy storage system at the current moment based on the objective function.

[0051] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory for the aforementioned dynamic control method.

[0052] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising: a computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the above-described dynamic control method.

[0053] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising: a computer program product, including a computer program / instructions, which, when executed by a processor, implements the aforementioned dynamic control method.

[0054] In this disclosure, a dynamic control method and a corresponding technical solution for an electro-hydrogen energy storage system are proposed to address the current technical problem of not being able to utilize hydrogen energy storage systems to respond to loads in advance, thereby increasing the utilization of battery energy storage and consequently increasing costs.

[0055] In the embodiments disclosed herein and other possible embodiments, in the event of a failure in the battery energy storage or hydrogen energy storage system, the system will automatically switch to standby mode or adjust the output of the remaining energy storage system to ensure uninterrupted power supply. Simultaneously, the system can also monitor the health status of the energy storage devices and detect potential problems in advance.

[0056] The above-mentioned dynamic regulation based on power demand forecasting and optimization algorithms enables efficient and rapid response to the power grid, allowing energy storage devices to operate in an efficient and intelligent manner under different load conditions.

[0057] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.

[0058] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0059] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure.

[0060] Figure 1 A flowchart illustrating a dynamic control method for hydrogen energy storage according to an embodiment of the present disclosure is provided.

[0061] Figure 2 This is a block diagram illustrating an electronic device 800 according to an exemplary embodiment;

[0062] Figure 3 This is a block diagram illustrating an electronic device 1900 according to an exemplary embodiment. Detailed Implementation

[0063] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0064] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0065] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0066] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0067] It is understood that the various method embodiments mentioned above in this disclosure can be combined with each other to form combined embodiments without violating the principle and logic. Due to space limitations, this disclosure will not elaborate further.

[0068] In addition, this disclosure also provides a dynamic control system, device, electronic equipment, computer-readable storage medium, and program product for electric hydrogen energy storage. All of the above can be used to implement any of the dynamic control methods for electric hydrogen energy storage provided in this disclosure. The corresponding technical solutions and descriptions are described in the corresponding descriptions in the method section and will not be repeated here.

[0069] Figure 1 A flowchart illustrating a dynamic control method for electro-hydrogen energy storage according to an embodiment of this disclosure is shown. Figure 1 As shown, the dynamic control method for the electro-hydrogen energy storage includes: Step S101: Predicting the power demand load (predicted power demand load) at a set time or multiple set time periods using the power demand prediction model corresponding to the electro-hydrogen energy storage system; Step S102: Determining the minimum output power (minimum predicted output power) of the hydrogen storage in the electro-hydrogen energy storage system at the set time or multiple set time periods based on the power demand load at the set time or multiple set time periods, the hydrogen energy conversion efficiency and the maximum hydrogen energy storage output power; Step S103: Determining the hydrogen reserve at the set time or multiple set time periods based on the minimum output power at the set time or multiple set time periods, the output power corresponding to the amount of hydrogen charged at a time prior to the set time or multiple set time periods, the hydrogen energy conversion efficiency and the hydrogen reserve. This addresses the current technical problem of not utilizing the hydrogen energy storage system to respond to loads in advance, thereby increasing the utilization of battery energy storage and increasing costs.

[0070] Step S101: Use the power demand forecasting model corresponding to the electric hydrogen energy storage system to predict the power demand load at a set time or at multiple set times (power demand forecasting load).

[0071] In the embodiments of this disclosure, before predicting the power demand load corresponding to a set time or multiple set time periods using the power demand prediction model corresponding to the electric hydrogen energy storage system, the power demand prediction model is established. The method includes: acquiring a set neural network or convolutional neural network and corresponding historical load data, and training the set neural network or convolutional neural network using the historical load data to obtain the power demand prediction model corresponding to the electric hydrogen energy storage system; wherein, the historical load data includes at least: historical power demand load.

[0072] In embodiments of this disclosure, the historical load data further includes: external factor data affecting the historical power demand load; and / or, the external factor data corresponding to the historical power demand load includes at least one or more of the following: temperature, humidity, seasonal changes, and holiday information.

[0073] In embodiments of this disclosure, before training the designated neural network or convolutional neural network using the historical load data, outlier removal or missing value imputation is performed on the historical load data; and / or, before training the designated neural network or convolutional neural network using the historical load data, the method further includes: normalizing the historical load data; and / or, the designated neural network or convolutional neural network is configured as a long short-term memory network or a network based thereon.

[0074] In embodiments of this disclosure and other possible implementations, firstly, 2-5 years of historical load data is required, including daily, hourly, and even minute-by-minute electricity consumption on the power grid. This data typically comes from the power company's smart meters and monitoring systems. Additionally, data on external factors that may affect electricity demand, such as weather (temperature, humidity), seasonal changes, and holiday information, also needs to be collected.

[0075] In the embodiments of this disclosure and other possible embodiments, the collected historical load data is often messy and incomplete, so preprocessing is required, including the 3σ rule to remove noise (outliers) and the mean to fill in missing values ​​to improve the prediction accuracy of the electricity demand forecasting model.

[0076] In the embodiments of this disclosure and other possible embodiments, holiday and seasonal information can be converted into one-hot encoding. Taking seasonal information as an example, we can create a four-dimensional vector for the four seasons of spring, summer, autumn and winter. If it is spring, the corresponding one-hot encoded vector is [1,0,0,0]; summer is [0,1,0,0]; autumn is [0,0,1,0]; and winter is [0,0,0,1].

[0077] In embodiments of this disclosure and other possible embodiments, continuous variables (such as air humidity and weather temperature) may need to be normalized to obtain normalized historical load data x. new For example, for air humidity data, assuming the humidity value ranges from [a, b], the following formula can be used to normalize it to the interval [0, 1].

[0078]

[0079] In embodiments of this disclosure and other possible embodiments, when processing general-scale time-series historical load data, the number of units per layer can be set between 32 and 256.

[0080] In embodiments of this disclosure and other possible embodiments, intelligent prediction algorithms based on trained historical data (historical load data) are used. For example, LSTM (Long Short-Term Memory) networks, Bi-LSTM, and xLSTM models are trained using collected historical data.

[0081] In embodiments of this disclosure and other possible embodiments, the preprocessed historical load dataset is split into a training set, a validation set, and a test set. The training set is used to train the model, the validation set is used to tune model parameters (such as hyperparameter tuning), and the test set is used to evaluate the final performance of the model.

[0082] In embodiments of this disclosure and other possible embodiments, the LSTM model is trained using training set data. During training, the model learns the mapping relationship between input features and payload values. The model parameters are gradually adjusted using iterative optimization algorithms (such as backpropagation) to minimize the loss function.

[0083] In the embodiments of this disclosure and other possible embodiments, the specific workflow of the backpropagation algorithm in LSTM is as follows: First, the error between the predicted value and the actual value is calculated, and then the gradient of the parameters of the output layer is calculated according to the loss function. This gradient will propagate back along the network.

[0084] In the embodiments of this disclosure and other possible embodiments, in LSTM, due to the special nature of its structure, the cell state and the state of each gate need to be considered when calculating the gradient. For example, for an LSTM network containing multiple time steps, when calculating the gradient at a certain time step, factors such as the input of that time step, the hidden state of the previous time step, and the cell state need to be considered. Based on the calculated gradient, an optimizer (such as Adam) is used to update the model parameters. The update method is to move the parameters in the opposite direction of the gradient according to a certain learning rate, thereby gradually reducing the value of the loss function.

[0085] In embodiments of this disclosure and other possible embodiments, the electricity demand load corresponding to the formulation of scheduling plans for hydrogen energy storage and battery energy storage is then predicted based on the trained LSTM model (electricity demand forecasting model).

[0086] Among them, f predict It is a load forecasting function (a trained LSTM model or other electricity demand forecasting models based on statistical learning or deep learning), which predicts the electricity demand load at multiple future time points (minute 1, minute 2, etc.). It will be used to develop scheduling plans for hydrogen energy storage and battery energy storage (to build energy storage system control models).

[0087] In embodiments of this disclosure and other possible embodiments, the trained LSTM model or other power demand forecasting models based on statistical learning or deep learning, by inputting historical load data of the power grid, can predict the future power demand corresponding to the formulation of scheduling plans for hydrogen energy storage and battery energy storage. Provide a demand trend over a given time period. This allows the system to prepare in advance for potential peak or off-peak electricity demand. Then, based on the predicted data (electricity demand load)... Controlling the energy storage system (energy storage system regulation model).

[0088] Step S102: Based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen energy storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power, determine the minimum output power (minimum predicted output power) of hydrogen energy storage in the electric hydrogen energy storage system corresponding to the set time or multiple set times.

[0089] In embodiments of this disclosure, the method for determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at a set time or multiple set times, based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power, includes: based on the power demand load corresponding to the set time or multiple set times. and the hydrogen energy conversion efficiency η h2 Determine the output power of hydrogen energy storage corresponding to the electricity demand load. At the maximum hydrogen storage output power P h2,max and the hydrogen energy storage output power corresponding to the aforementioned electricity demand load. In the process, the minimum output power P of hydrogen storage in the electro-hydrogen energy storage system at a set time or multiple set times is determined. h2,t+k .

[0090] In embodiments of this disclosure and other possible embodiments, the energy storage system (electro-hydrogen energy storage system) consists of two parts: battery energy storage and hydrogen energy storage. Hydrogen energy storage is preferred because it is low in cost and easy to implement for large-scale, long-term storage.

[0091] In embodiments of this disclosure and other possible embodiments, the electricity demand load predicted by the electricity demand forecasting model is... As input, hydrogen storage should be prioritized before peak load periods arrive. For example, if a peak electricity demand is expected at 3 pm, the hydrogen storage system can start preparing hydrogen reserves at 2:30 pm to ensure timely provision of the required power.

[0092] In the embodiments of this disclosure and other possible embodiments, hydrogen energy storage, after time t, corresponds to the minimum power output (minimum output power) P at time k (1, 2, 3, ...). h2,t+k The maximum hydrogen energy storage power output capacity (maximum hydrogen energy storage output power) P depends on the predicted electricity demand load and the maximum hydrogen energy storage power output capacity of the energy storage system. h2,max Electricity demand load and the hydrogen energy conversion efficiency η h2 The corresponding hydrogen energy storage power output capacity (hydrogen energy storage output power). Its scheduling model (energy storage system control model) can be expressed as:

[0093]

[0094] In embodiments of this disclosure, the method for determining the minimum output power corresponding to the amount of hydrogen charged at the time change Δt1 and / or Δt2 corresponding to the set time or multiple set times and the time preceding it includes: multiplying the time change Δt2 corresponding to the set time or multiple set times at the previous time by the output power P corresponding to the amount of hydrogen charged at the set time or multiple set times at the previous time. h2,charge,t+k-1 Determine the output power P corresponding to the amount of hydrogen charged under the time change. h2,charge,t+k-1 ·Δt2; or, the amount of hydrogen P charged at the previous time corresponding to the set time or multiple set times. h2,charge,t+k-1 The corresponding output power minus the output power P corresponding to the amount of hydrogen charged at the previous time point before the previous time point. h2,charge,t+k-2 Determine the output power P corresponding to the amount of hydrogen charged under the time change. h2,charge,t+k-1 -P h2,charge,t+k-2 .

[0095] In embodiments of this disclosure, the method for determining the minimum output power corresponding to the amount of hydrogen charged at the time change Δt1 and / or Δt2 corresponding to the set time or multiple set times and the times preceding it includes: multiplying the time change Δt1 corresponding to the set time or multiple set times by the minimum output power P corresponding to the set time or multiple set times. h2，t+k Determine the minimum output power P under the time variation. h2，t+k ·Δt1; or, the minimum output power P corresponding to the set time or multiple set times. h2，t+k Subtract the minimum output power P corresponding to the time preceding the set time or multiple set times. h2，t+k-1 Determine the minimum output power P under the time variation. h2，t+k -P h2，t+k-1 .

[0096] In embodiments of this disclosure, the method for determining the change in hydrogen reserves using the output power corresponding to the amount of hydrogen added under the time-varying amount and the minimum output power includes: subtracting the minimum output power under the time-varying amount from the output power corresponding to the amount of hydrogen added under the time-varying amount to obtain the corresponding change in output power; dividing the change in output power by the hydrogen energy conversion efficiency to obtain the corresponding change in hydrogen reserves; or, dividing the output power corresponding to the amount of hydrogen added under the time-varying amount by the hydrogen energy conversion efficiency η. h2 The change in hydrogen volume is obtained; the minimum output power under the time change is divided by the hydrogen energy conversion efficiency η. h2 The amount of hydrogen consumed is obtained; the change in hydrogen reserves is determined by subtracting the amount of hydrogen consumption from the change in hydrogen supply. or

[0097] Step S103: Determine the hydrogen reserve corresponding to the set time or multiple set times based on the minimum output power corresponding to the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time before the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve.

[0098] In embodiments of this disclosure, the method for determining the hydrogen reserve at a set time or multiple set times based on the minimum output power at the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at a time prior to the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve includes: determining the output power and minimum output power corresponding to the amount of hydrogen charged under the time variation at the set time or multiple set times and the time prior to the set time or multiple set times; and determining the change in hydrogen reserve E using the output power and minimum output power corresponding to the amount of hydrogen charged under the time variation. h2，t+k-1 Based on the change in hydrogen reserves and the hydrogen reserve E corresponding to the time preceding the set time or multiple set time points. h2，t+k-1 Update the hydrogen reserve E corresponding to the set time or multiple set times. h2，t+k .

[0099] In embodiments of this disclosure and other possible embodiments, the hydrogen reserve is then updated to ensure sufficient energy supply during peak periods. The hydrogen reserve update equation is as follows:

[0100] or,

[0101]

[0102] Among them, P h2，charge，t+k E represents the output power corresponding to the amount of hydrogen introduced at time t+k-1. h2，t+kLet E be the amount of hydrogen stored at time t+1. h2，t+k Let P be the hydrogen reserve at time t+k, and let Δt1 be configured as P. h2，t+k -1 represents the time change from time t+k-1 to t+k; Δt2 is configured as P. h2，charge，t+k-1 The change in time from t+k-2 to t+k-1; generally, the time intervals between times are equal, Δt1=Δt2.

[0103] In embodiments of this disclosure and other possible embodiments, the decision is made on whether to further charge the hydrogen storage device with hydrogen based on the updated hydrogen reserve. For example, if the current hydrogen reserve is less than the updated hydrogen reserve, then the hydrogen storage device will be further charged with hydrogen; otherwise, it will not be further charged with hydrogen.

[0104] In embodiments of this disclosure and other possible embodiments, the method for updating the hydrogen reserve corresponding to the set time or multiple time periods based on the change in the hydrogen reserve and the hydrogen reserve corresponding to the time period before the set time or multiple time periods includes: adding the change in the hydrogen reserve to the hydrogen reserve corresponding to the time period before the set time or multiple time periods, and then updating the hydrogen reserve corresponding to the set time or multiple time periods.

[0105] In embodiments of this disclosure and other possible embodiments, the method further includes: dynamically adjusting the amount of hydrogen corresponding to the hydrogen energy storage based on the updated hydrogen reserve. Specifically, the method for dynamically adjusting the amount of hydrogen corresponding to the hydrogen energy storage based on the updated hydrogen reserve includes: obtaining the maximum hydrogen reserve corresponding to the maximum output power of the hydrogen energy storage; during the process of using the hydrogen energy storage for power supply, if the hydrogen reserve corresponding to a set time or multiple set time points is less than the updated hydrogen reserve and less than the maximum hydrogen reserve, then further charging the hydrogen energy storage with hydrogen based on the updated hydrogen reserve; otherwise, not further charging the hydrogen energy storage with hydrogen until the hydrogen reserve corresponding to the set time or multiple set time points is less than the updated hydrogen reserve and less than the maximum hydrogen reserve, then further charging the hydrogen energy storage with hydrogen based on the updated hydrogen reserve again.

[0106] In embodiments of this disclosure, the method further includes: real-time detection of the current power demand load, the current hydrogen energy storage output power, or the power demand forecast load corresponding to the current time at a set time or multiple set times (the power demand load corresponding to the set time or multiple set times is predicted using the power demand forecast model corresponding to the electric hydrogen energy storage system, i.e., the power demand forecast load) or the minimum predicted output power (the minimum output power of hydrogen storage in the electric hydrogen energy storage system corresponding to the set time or multiple set times, i.e., the minimum predicted output power); based on the current power demand load and the current hydrogen energy storage output power or the power demand forecast load or the minimum predicted output power, adjusting the hydrogen energy storage in the electric hydrogen energy storage system to battery energy storage for power supply.

[0107] In embodiments of this disclosure, the method for adjusting hydrogen energy storage in the electro-hydrogen energy storage system to battery energy storage for power supply includes: calculating the load / power difference between the current power demand load and the current hydrogen energy storage output power or minimum predicted output power (the output power of the battery energy storage at the current time); and updating the energy storage capacity corresponding to the current time based on the load / power difference and the conversion efficiency of the battery corresponding to the battery energy storage.

[0108] In embodiments of this disclosure, the method for updating the energy storage capacity at the current moment based on the load / power difference and the conversion efficiency of the battery corresponding to the battery energy storage includes: determining the load / power difference under the time change corresponding to the current moment and previous moments; determining the change in energy storage capacity using the load / power difference under the time change and the conversion efficiency of the battery; and updating the energy storage capacity at the current moment based on the change in energy storage capacity and the energy storage capacity corresponding to the previous moments.

[0109] In embodiments of this disclosure, before determining the load / power difference under the time change corresponding to the current time t and previous times, the determination includes: multiplying the time change Δt corresponding to the current time t and previous times by the load / power difference (output power of battery storage at time t) P corresponding to the current time. bat，t Determine the load / power difference P under the time change corresponding to the current time and previous times. bat，t • Δt; or, the load / power difference corresponding to the current time minus the load / power difference P corresponding to the time at which the current time and the time before (e.g., the previous time) were determined. bat，t -P bat，t-1 Determine the load / power difference P under the time change corresponding to the current time t and the time t-1 before it. bat，t -P bat，t-1 .

[0110] In embodiments of this disclosure, the method for determining the change in storage capacity using the load / power difference under the time change and the conversion efficiency of the battery includes: calculating the load / power difference P under the time change Δt. bat，t ·Δt or P bat，t -P bat，t-1 Divide by the battery's conversion efficiency η bat This yields the corresponding change (energy consumption).

[0111] In embodiments of this disclosure, the method for updating the current energy storage capacity based on the change in the energy storage capacity and the energy storage capacity corresponding to a previous time (e.g., the previous time) includes: using the energy storage capacity E from a time prior to the current time. bat，t-1 Subtract the change Update the current energy storage capacity E. bat，t .

[0112] In the embodiments of this disclosure and other possible embodiments, battery energy storage is fast-responding and suitable for regulating short-term power demand load fluctuations. It is used to handle unpredictable power demand load fluctuations in the short term (minutes) or to provide the required power urgently when hydrogen energy storage is not yet able to fully meet the current power demand load.

[0113] In the embodiments of this disclosure and other possible embodiments, the energy storage system monitors the electricity demand load P at the current time t in real time. load，t The power provided by battery energy storage is compared with that provided by hydrogen energy storage (hydrogen energy storage output power). If the hydrogen energy storage power output capacity (hydrogen energy storage output power) P h2，t Unable to fully satisfy (P) h2，t <P load，t The current electricity demand load P at time t load，t Then battery energy storage will immediately intervene:

[0114] P bat，t =P load，t -P h2，t .

[0115] Where: P bat，t The output power (load / power difference) of the battery energy storage at time t.

[0116] In embodiments of this disclosure and other possible embodiments, the energy renewal equation for battery energy storage can be configured as follows:

[0117]

[0118] Among them, E bat，t Let E be the amount of electricity stored at time t. bat，t-1 The stored energy at time t-1; the battery's conversion efficiency η bat Δt is configured as P bat，t The change in time from t-1 to t;

[0119] In embodiments of this disclosure and other possible embodiments, when the electricity demand forecasting model predicts future changes in electricity demand load, the energy storage system control model will schedule in advance based on the forecast, thus reducing the response time t. response It is no longer limited to the physical response time of hydrogen energy storage, but can be started in advance through prediction.

[0120] In embodiments of this disclosure and other possible embodiments, the method further includes: obtaining the predicted power demand load corresponding to a set time or multiple set time periods predicted by the power demand forecasting model; if the predicted power demand load corresponding to a certain time period or multiple set time periods is less than the actual power demand load corresponding to that time period, then the hydrogen energy storage in the electro-hydrogen energy storage system is adjusted to battery energy storage for power supply. This addresses the current technical problem that load fluctuations at the minute / second level are not processed, and the advantages of battery energy storage are not effectively utilized.

[0121] In embodiments of this disclosure and other possible embodiments, if the prediction is accurate, the energy storage system can minimize the use of battery energy storage; if short-term power demand fluctuations cannot be accurately predicted, battery energy storage will be responsible for rapid response. Therefore, the system switching mechanism can be defined as:

[0122]

[0123] The embodiments of this disclosure also propose another dynamic control method for electro-hydrogen energy storage, including: obtaining the power demand load corresponding to the current moment of the electro-hydrogen energy storage system and the output power, maximum storage capacity, minimum storage capacity, and storage capacity or updated storage capacity of the battery energy storage in the electro-hydrogen energy storage system; using the power demand forecasting model corresponding to the electro-hydrogen energy storage system to predict the power demand load at a set time or multiple set times after the current moment, and determining the minimum output power of the hydrogen energy storage in the electro-hydrogen energy storage system at the set time or multiple set times based on the power demand forecasting load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to the hydrogen energy storage in the electro-hydrogen energy storage system, and the maximum hydrogen energy storage output power; and based on the power demand load P at the current moment t... load，t The output power P of the battery energy storage bat，t Maximum storage capacity E bat，max Minimum storage capacity E bat，minStorage capacity or replacement storage capacity E bat，t The minimum output power P of the hydrogen energy storage h2，t The objective function is determined; while maximizing the utilization of hydrogen energy storage, the frequency of battery use and / or deep discharge in battery energy storage are minimized. Based on the objective function, the optimized output power of the battery and the optimized output power of hydrogen energy storage system at the current moment are determined. More relevant details regarding the alternative dynamic control method for electro-hydrogen energy storage can be found in the description of the above method.

[0124] In embodiments of this disclosure, the method for determining an objective function based on the current power demand load, the maximum capacity, minimum capacity, or updated capacity of the battery energy storage, and the minimum output power of the hydrogen energy storage includes: determining the battery energy storage output power ratio corresponding to the objective function based on the current power demand load and the output power of the battery energy storage; determining the hydrogen energy storage output power ratio corresponding to the objective function based on the current power demand load and the minimum output power of the hydrogen energy storage; determining the depth of discharge percentage corresponding to the objective function based on the maximum capacity, minimum capacity, or updated capacity of the battery energy storage; and constructing the objective function based on the battery energy storage output power ratio, the hydrogen energy storage output power ratio, and the depth of discharge percentage.

[0125] In embodiments of this disclosure, the method for constructing the objective function based on the battery energy storage output power ratio, the hydrogen energy storage output power ratio, and the discharge depth percentage further includes: obtaining a first weighting coefficient α, a second weighting coefficient β, and a third weighting coefficient γ corresponding to the battery energy storage output power ratio, the discharge depth percentage, and the hydrogen energy storage output power ratio, respectively; and assigning the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient to the battery energy storage output power ratio, respectively. The percentage of discharge depth and the proportion of hydrogen energy storage output power Perform weight allocation; based on the weighted output power ratio of the battery energy storage, ... The proportion of hydrogen energy storage output power and the percentage of discharge depth β Construct the objective function.

[0126] In the embodiments of this disclosure and other possible embodiments, it is necessary to optimize energy storage scheduling, with the goal of minimizing the frequency of battery use and deep discharge in battery energy storage, while maximizing the utilization of hydrogen energy storage. The optimization algorithm used here is simulated annealing (GA) as an example, with the objective function being:

[0127]

[0128] The depth of charge at time t / maximum capacity represents the percentage of depth of discharge.

[0129] Wherein, α, β, and γ are configured as the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, respectively, representing the battery usage frequency, the cost of deep discharge, and the utilization effect of hydrogen energy storage; P bat,t P is the power output (output power) of the battery energy storage system (battery energy storage) at time t; load,t P is the power demand load corresponding to the battery energy storage system at the current time t; bat,max It is the maximum power output of the battery energy storage system; E bat,t The energy state of the battery storage system at time t; E bat,min Minimum energy storage limit (minimum capacity) for battery energy storage systems; E bat,max Maximum energy storage limit (maximum capacity) of battery energy storage system; P h2,t P is the power output of the hydrogen energy storage system at time t; h2,max The maximum power output of the hydrogen energy storage system; T is configured as the end time, [1,2,3,..,k,…,T].

[0130] In embodiments of this disclosure and other possible embodiments, the battery power output should be limited to its maximum power output P. bat,max Within:

[0131] 0≤P bat,t ≤P bat,max

[0132] In embodiments of this disclosure and other possible embodiments, the state of energy of the battery should be maintained between the maximum and minimum permissible capacity:

[0133] E bat,min ≤E bat,t ≤E bat,max

[0134] In the embodiments disclosed herein and other possible embodiments, the power output of hydrogen storage also has an upper limit, which cannot exceed its maximum power output P. h2,max :

[0135] 0≤P h2，t ≤P h2，max

[0136] The energy state E of hydrogen storage in the embodiments of this disclosure and other possible embodiments h2，t There are also capacity limitations:

[0137] Eh2，min ≤E h2，t ≤E h2,max

[0138] In embodiments of this disclosure and other possible embodiments, the decision variable is: battery power output (battery output power) p bat，t Hydrogen storage power output (hydrogen storage output power) P h2，t .

[0139] In embodiments of this disclosure and other possible embodiments, initialization involves selecting an initial solution (e.g., randomly generating an initial battery output power p). bat，t0 and the initial hydrogen storage output power P h2，t0 Set the initial temperature TE0. The choice of the initial temperature TE0 can affect the convergence speed and global search capability of the algorithm. Set the cooling rate β (usually 0.8 to 0.99); the cooling rate β determines the rate at which the temperature decreases. Define the stopping criteria of the algorithm, such as the maximum number of iterations or the temperature dropping to a certain set threshold.

[0140] In embodiments of this disclosure and other possible embodiments, the simulated annealing process involves performing a certain number of iterations at each decreasing temperature after the initial temperature TE0, and slightly perturbing the current solution (current battery output power, current hydrogen storage output power) by approximately ±5% to ±15%, to generate a new solution (new battery output power p). bat,tn and the new hydrogen energy storage output power P h2，tn Calculate the objective function values ​​for the current solution and the new solution respectively. If the objective function value of the new solution is better (smaller), accept the new solution as the current solution. If the objective function value of the new solution is worse, accept the new solution with a certain probability to avoid getting trapped in local optima.

[0141] In embodiments of this disclosure and other possible embodiments, this probability is given by the following formula:

[0142] Where Current Cost and New Cost are the objective function values ​​corresponding to the current solution and the new solution, respectively, and TE is the current temperature. The temperature is updated according to the cooling rate β: TE*β. If the stopping criterion is met (e.g., the temperature drops to close to 0 (e.g., less than 0.01), or the number of iterations reaches a preset maximum value (e.g., 1000 times), or the improvement of the solution is less than a certain set threshold (e.g., 0.001) for multiple consecutive iterations (e.g., 10 times), the algorithm ends; otherwise, simulated annealing is performed again.

[0143] In the embodiments of this disclosure and other possible embodiments, the solution with the minimum objective function value is selected as the final optimization result in all iterations: the optimized battery output power p corresponding to any time t (1, 2, ..., T). bat，t,opt The optimal output power P of hydrogen energy storage at any time t (1, 2, ..., T) h2，t，opt .

[0144] In the embodiments of this disclosure and other possible embodiments, hydrogen energy storage needs to be preheated to the operating temperature and prepared for gas supply in advance, and the output power P of hydrogen energy storage is optimized according to the time t. h2，t，opt It can respond in advance to achieve power output at the corresponding moment.

[0145] In embodiments of this disclosure and other possible embodiments, the method for determining the updated energy storage capacity includes: determining the load / power difference under the time change corresponding to the current time and previous times; determining the change in energy storage capacity using the load / power difference under the time change and the conversion efficiency of the battery; and updating the energy storage capacity corresponding to the current time (updated energy storage capacity) based on the change in energy storage capacity and the energy storage capacity corresponding to the time before the current time.

[0146] In embodiments of this disclosure and other possible embodiments, the method for determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at a set time or multiple set times, based on the predicted power demand load at the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power, includes: determining the hydrogen energy storage output power corresponding to the predicted power demand load based on the predicted power demand load at the set time or multiple set times and the hydrogen energy conversion efficiency; and determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times from the maximum hydrogen energy storage output power and the hydrogen energy storage output power corresponding to the predicted power demand load.

[0147] The entity executing the dynamic control method for hydrogen-electric energy storage can be a dynamic control system or device for hydrogen-electric energy storage. For example, the dynamic control method for hydrogen-electric energy storage can be executed by terminal equipment, servers, or other processing devices. The terminal equipment can be user equipment (UE), mobile devices, user terminals, terminals, cellular phones, cordless phones, personal digital assistants (PDAs), handheld devices, computing devices, vehicle-mounted devices, wearable devices, etc. In some possible implementations, the dynamic control method for hydrogen-electric energy storage can be implemented by a processor calling computer-readable instructions stored in memory.

[0148] Those skilled in the art will understand that in the above-described dynamic control method for electro-hydrogen energy storage in specific embodiments, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0149] In the embodiments of this disclosure, a corresponding dynamic control system for electro-hydrogen energy storage is also proposed, comprising: a prediction unit, used to predict the power demand load corresponding to a set time or multiple set time periods using a power demand prediction model corresponding to the electro-hydrogen energy storage system; a first determination unit, used to determine the minimum output power of the hydrogen storage in the electro-hydrogen energy storage system corresponding to the set time or multiple set time periods based on the power demand load corresponding to the set time or multiple set time periods, the hydrogen energy conversion efficiency corresponding to the hydrogen storage in the electro-hydrogen energy storage system, and the maximum hydrogen energy storage output power; and a control unit, used to determine the hydrogen reserve corresponding to the set time or multiple set time periods based on the minimum output power corresponding to the set time or multiple set time periods, the output power corresponding to the amount of hydrogen charged at a time before the set time or multiple set time periods, the hydrogen energy conversion efficiency, and the hydrogen reserve.

[0150] In the embodiments of this disclosure, a corresponding dynamic control system for electro-hydrogen energy storage is also proposed, comprising: an acquisition unit, used to acquire the current power demand load of the electro-hydrogen energy storage system and the output power, maximum storage capacity, minimum storage capacity, and storage capacity or updated storage capacity of the battery energy storage in the electro-hydrogen energy storage system; and a second determination unit, used to use the power demand prediction model corresponding to the electro-hydrogen energy storage system to predict the power demand load at a set time or multiple set times after the current time, and based on the power demand prediction load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to the hydrogen energy storage in the electro-hydrogen energy storage system, and the maximum hydrogen storage capacity. The system comprises: a power output unit, which determines the minimum output power of hydrogen storage in the electro-hydrogen energy storage system at a set time or multiple set times; an objective function determination unit, which determines an objective function based on the power demand load at the current time, the output power of the battery energy storage, the maximum storage capacity, the minimum storage capacity, the storage capacity or the updated storage capacity, and the minimum output power of the hydrogen energy storage; and an optimization unit, which determines the optimized battery output power and the optimized hydrogen energy storage output power of the electro-hydrogen energy storage system at the current time based on the objective function, while maximizing the utilization of the hydrogen energy storage and minimizing the battery usage frequency and / or deep discharge in the battery energy storage.

[0151] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory for the aforementioned dynamic control method.

[0152] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising: a computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the above-described dynamic control method.

[0153] According to one aspect of this disclosure, an electrohydrogen energy storage dynamic control system is provided, comprising: a computer program product, including a computer program / instructions, which, when executed by a processor, implements the aforementioned dynamic control method.

[0154] In this disclosure, a dynamic control method and a corresponding technical solution for an electro-hydrogen energy storage system are proposed to address the current technical problem of not being able to utilize hydrogen energy storage systems to respond to loads in advance, thereby increasing the utilization of battery energy storage and consequently increasing costs.

[0155] In the embodiments disclosed herein and other possible embodiments, in the event of a failure in the battery energy storage or hydrogen energy storage system, the system will automatically switch to standby mode or adjust the output of the remaining energy storage system to ensure uninterrupted power supply. Simultaneously, the system can also monitor the health status of the energy storage devices and detect potential problems in advance.

[0156] The above-mentioned dynamic regulation based on power demand forecasting and optimization algorithms enables efficient and rapid response to the power grid, allowing energy storage devices to operate in an efficient and intelligent manner under different load conditions.

[0157] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to execute the methods described in the above embodiments of the dynamic control method for electric hydrogen energy storage. The specific implementation can be referred to the description of the above embodiments of the dynamic control method for electric hydrogen energy storage, which will not be repeated here for the sake of brevity.

[0158] This disclosure also proposes a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the aforementioned dynamic control method for electro-hydrogen energy storage. The computer-readable storage medium can be a non-volatile computer-readable storage medium.

[0159] This disclosure also proposes an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured for the aforementioned dynamic control method for electro-hydrogen energy storage. The electronic device can be provided as a terminal, a server, or other form of device.

[0160] In summary, the hybrid electric-hydrogen energy storage system of this application improves the accuracy and response speed of load forecasting by intelligently controlling and optimizing the ratio of battery and hydrogen energy storage. The early response of hydrogen energy storage reduces the demand for battery energy storage, lowers the frequency of battery use and deep discharge, extends battery life, and reduces costs.

[0161] The key points of this application are: optimizing the scheduling of batteries and hydrogen storage through real-time monitoring and prediction of load demand; a hydrogen storage early response mechanism to fully utilize the cost advantages of hydrogen storage and reduce battery usage; and an optimized mathematical model to accurately schedule short-term and long-term load demand.

[0162] Figure 2 This is a block diagram illustrating an electronic device 800 according to an exemplary embodiment. For example, the electronic device 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, or other terminal.

[0163] Reference Figure 2 The electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0164] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0165] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of this data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 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 storage, flash memory, magnetic disk, or optical disk.

[0166] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0167] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0168] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0169] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0170] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 can detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0171] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0172] In an exemplary embodiment, the electronic device 800 may 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 perform the methods described above.

[0173] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 804 including computer program instructions that can be executed by a processor 820 of an electronic device 800 to perform the above-described method.

[0174] Figure 3 This is a block diagram illustrating an electronic device 1900 according to an exemplary embodiment. For example, the electronic device 1900 may be provided as a server. (Refer to...) Figure 3The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0175] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output (I / O) interface 1958. Electronic device 1900 can operate on an operating system stored in memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0176] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of an electronic device 1900 to perform the above-described method.

[0177] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0178] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0179] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0180] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0181] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0182] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0183] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0184] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0185] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A dynamic control method for electro-hydrogen energy storage, characterized in that, include: The power demand forecasting model corresponding to the electric hydrogen energy storage system is used to predict the power demand load at a set time or at multiple set times. Based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to the hydrogen energy storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power, determine the minimum output power of the hydrogen energy storage in the electric hydrogen energy storage system corresponding to the set time or multiple set times. Based on the minimum output power corresponding to the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time before the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve, the hydrogen reserve corresponding to the set time or multiple set times is determined.

2. The dynamic control method according to claim 1, characterized in that, Before using the power demand prediction model corresponding to the electric hydrogen energy storage system to predict the power demand load at a set time or multiple set times, the power demand prediction model is established, including: acquiring a set neural network or convolutional neural network and corresponding historical load data, and using the historical load data to train the set neural network or convolutional neural network to obtain the power demand prediction model corresponding to the electric hydrogen energy storage system; wherein, the historical load data includes at least: historical power demand load.

3. The dynamic control method according to claim 2, characterized in that, The historical load data further includes: data on external factors affecting the historical electricity demand load; wherein the data on external factors affecting the historical electricity demand load includes at least one or more of the following: temperature, humidity, seasonal variations, and holiday information; and / or, Before training the designated neural network or convolutional neural network using the historical workload data, outlier removal or missing value imputation is performed on the historical workload data; and / or, Before training the designated neural network or convolutional neural network using the historical load data, the method includes: normalizing the historical load data; and / or, The neural network or convolutional neural network is configured as a long short-term memory network or a network based on it.

4. The dynamic control method according to any one of claims 1-3, characterized in that, The step of determining the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set time periods based on the power demand load corresponding to the set time or multiple set time periods, the hydrogen energy conversion efficiency corresponding to hydrogen energy storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power includes: Based on the power demand load corresponding to the set time or multiple set times and the conversion efficiency of hydrogen energy, determine the hydrogen energy storage output power corresponding to the power demand load; Among the maximum hydrogen energy storage output power and the hydrogen energy storage output power corresponding to the power demand load, determine the minimum output power of hydrogen energy storage in the electric hydrogen energy storage system at a set time or multiple set times.

5. The dynamic control method according to any one of claims 1-3, characterized in that, The determination of the hydrogen reserve corresponding to the set time or multiple set times based on the minimum output power corresponding to the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time before the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve includes: Determine the output power and minimum output power corresponding to the amount of hydrogen charged at the set time or multiple set times and the time before the set time, respectively, based on the time change. The change in hydrogen reserves is determined by using the output power and minimum output power corresponding to the amount of hydrogen charged under the time change. Based on the change in hydrogen reserves and the amount of hydrogen reserves corresponding to the time before the set time or multiple set times, update the amount of hydrogen reserves corresponding to the set time or multiple set times.

6. The dynamic control method according to claim 5, characterized in that, Determining the minimum output power corresponding to the amount of hydrogen charged under the time change corresponding to the set time or multiple set times and the time before it includes: multiplying the time change corresponding to the set time or multiple set times in the previous time by the output power corresponding to the amount of hydrogen charged in the previous time or multiple set times, to determine the output power corresponding to the amount of hydrogen charged under the time change; or, subtracting the output power corresponding to the amount of hydrogen charged in the previous time from the output power corresponding to the amount of hydrogen charged in the time before the previous time, to determine the output power corresponding to the amount of hydrogen charged under the time change; and / or, Determining the minimum output power corresponding to the amount of hydrogen charged under the time change corresponding to the set time or multiple set times and the time before it includes: multiplying the time change corresponding to the set time or multiple set times by the minimum output power corresponding to the set time or multiple set times to determine the minimum output power under the time change; or, subtracting the minimum output power corresponding to the set time or multiple set times from the minimum output power corresponding to the time before the set time or multiple set times to determine the minimum output power under the time change; and / or The step of determining the change in hydrogen reserves by utilizing the output power corresponding to the amount of hydrogen added and the minimum output power under the time-varying hydrogen volume includes: subtracting the minimum output power under the time-varying hydrogen volume from the output power corresponding to the amount of hydrogen added under the time-varying hydrogen volume to obtain the corresponding change in output power; dividing the change in output power by the hydrogen energy conversion efficiency to obtain the corresponding change in hydrogen reserves; or, dividing the output power corresponding to the amount of hydrogen added under the time-varying hydrogen volume by the hydrogen energy conversion efficiency to obtain the change in hydrogen volume increase; dividing the minimum output power under the time-varying hydrogen volume by the hydrogen energy conversion efficiency to obtain the hydrogen consumption; and subtracting the hydrogen consumption from the change in hydrogen volume increase to determine the change in hydrogen reserves.

7. The dynamic control method according to any one of claims 1-3 and 6, characterized in that, Also includes: Real-time detection of the current power demand load, the current hydrogen energy storage output power, or the predicted power demand load or minimum predicted output power corresponding to the current time in a set time or multiple set times. Based on the current power demand load and the current hydrogen energy storage output power or the predicted power demand load or the minimum predicted output power, the hydrogen energy storage in the electro-hydrogen energy storage system is adjusted to battery energy storage for power supply.

8. The dynamic control method according to claim 7, characterized in that, The step of adjusting the hydrogen storage in the electro-hydrogen energy storage system to battery storage for power supply based on the current power demand load and the current hydrogen energy storage output power or the predicted power demand load or the minimum predicted output power includes: If the current power demand load is less than one or more of the current hydrogen energy storage output power, the predicted power demand load, or the minimum predicted output power, then the hydrogen energy storage in the electro-hydrogen energy storage system will be adjusted to battery energy storage for power supply.

9. The dynamic control method according to claim 7, characterized in that, The step of adjusting the hydrogen energy storage in the electro-hydrogen energy storage system to battery energy storage for power supply includes: calculating the current power demand load and the current hydrogen energy storage output power or the minimum predicted battery energy storage output power; and updating the current energy storage capacity based on the battery energy storage output power and the conversion efficiency of the battery corresponding to the battery energy storage.

10. The dynamic control method according to claim 9, characterized in that, The step of updating the current energy storage capacity based on the battery energy storage output power and the conversion efficiency of the corresponding battery includes: Determine the battery energy storage output power under the time change corresponding to the current moment and the moments before it; The change in energy storage capacity is determined by using the battery energy storage output power under the time change and the battery conversion efficiency. Based on the change in the stored capacity and the stored capacity at the previous time, the stored capacity at the current time is updated.

11. The dynamic control method according to claim 10, characterized in that, Before determining the battery energy storage output power under the time change corresponding to the current moment and previous moments, the process includes: The battery energy storage output power is determined by multiplying the time change corresponding to the current time and previous times by the battery energy storage output power corresponding to the current time; or, the battery energy storage output power corresponding to the current time is subtracted from the battery energy storage output power corresponding to the current time and previous times to determine the battery energy storage output power corresponding to the current time and previous times.

12. The dynamic control method according to any one of claims 10 or 11, characterized in that, Determining the change in energy storage capacity using the battery energy storage output power under the time change and the battery conversion efficiency includes: dividing the battery energy storage output power under the time change by the battery conversion efficiency to obtain the corresponding change; and / or, The step of updating the current energy storage capacity based on the change in energy storage capacity and the energy storage capacity at the previous time includes: subtracting the change in energy storage capacity from the energy storage capacity at the previous time to update the current energy storage capacity.

13. A dynamic control method for electro-hydrogen energy storage, characterized in that, include: Obtain the current power demand load corresponding to the electric hydrogen energy storage system and the output power, maximum storage capacity, minimum storage capacity, storage capacity or updated storage capacity of the battery energy storage in the electric hydrogen energy storage system; Using the power demand forecasting model corresponding to the electric hydrogen energy storage system, the power demand forecast load is set at a time or multiple times after the current time. Based on the power demand forecast load corresponding to the set time or multiple times, the hydrogen energy conversion efficiency and the maximum hydrogen energy output power of the hydrogen energy storage in the electric hydrogen energy storage system, the minimum output power of the hydrogen energy storage in the electric hydrogen energy storage system corresponding to the set time or multiple times is determined. The objective function is determined based on the current power demand load, the output power of the battery energy storage, the maximum storage capacity, the minimum storage capacity, the storage capacity or the updated storage capacity, and the minimum output power of the hydrogen energy storage. While maximizing the utilization of hydrogen energy storage, the frequency of battery use and / or deep discharge in battery energy storage are minimized. Based on the objective function, the optimized output power of the battery and the optimized output power of hydrogen energy storage system at the current moment are determined.

14. The dynamic control method according to claim 13, characterized in that, The objective function is determined based on the current electricity demand load, the maximum and minimum storage capacity of the battery energy storage, the current storage capacity or the updated storage capacity, and the minimum output power of the hydrogen energy storage, including: Based on the current power demand load and the corresponding output power of the battery energy storage, determine the proportion of battery energy storage output power corresponding to the objective function; Based on the current electricity demand load and the minimum output power of the hydrogen energy storage, determine the proportion of hydrogen energy storage output power corresponding to the objective function; The depth of discharge percentage corresponding to the objective function is determined based on the maximum capacity, minimum capacity, capacity, or updated capacity of the battery energy storage. The objective function is constructed based on the battery energy storage output power ratio, the hydrogen energy storage output power ratio, and the discharge depth percentage.

15. The dynamic control method according to claim 14, characterized in that, The objective function is constructed based on the proportion of battery energy storage output power, the proportion of hydrogen energy storage output power, and the percentage of discharge depth, including: The first weighting coefficient, the second weighting coefficient, and the third weighting coefficient corresponding to the battery energy storage output power ratio, the discharge depth percentage, and the hydrogen energy storage output power ratio are obtained respectively. The first weighting coefficient, the second weighting coefficient, and the third weighting coefficient are respectively assigned weights to the proportion of battery energy storage output power, the percentage of discharge depth, and the proportion of hydrogen energy storage output power. The objective function is constructed based on the weighted proportion of battery energy storage output power, the proportion of hydrogen energy storage output power, and the percentage of discharge depth.

16. A dynamic control system for electro-hydrogen energy storage, characterized in that, include: The prediction unit is used to predict the power demand load at a set time or at multiple set times using the power demand prediction model corresponding to the electric hydrogen energy storage system. The first determining unit is used to determine the minimum output power of hydrogen storage in the electric hydrogen energy storage system at the set time or multiple set times based on the power demand load corresponding to the set time or multiple set times, the hydrogen energy conversion efficiency corresponding to hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power. The control unit is used to determine the hydrogen reserve corresponding to the set time or multiple set times based on the minimum output power corresponding to the set time or multiple set times, the output power corresponding to the amount of hydrogen charged at the time before the set time or multiple set times, the hydrogen energy conversion efficiency, and the hydrogen reserve.

17. A dynamic control system for electro-hydrogen energy storage, characterized in that, include: processor; A memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the dynamic control method according to any one of claims 1 to 12; or, Includes: a computer-readable storage medium having stored thereon computer program instructions, which, when executed by a processor, implement the dynamic control method according to any one of claims 1 to 12; or, Includes: a computer program product, including a computer program or instructions that, when executed by a processor, implement the dynamic control method according to any one of claims 1 to 12.

18. A dynamic control system for electro-hydrogen energy storage, characterized in that, include: The acquisition unit is used to acquire the current power demand load of the electric hydrogen energy storage system and the output power, maximum storage capacity, minimum storage capacity, storage capacity or updated storage capacity of the battery energy storage in the electric hydrogen energy storage system. The second determining unit is used to utilize the power demand prediction model corresponding to the electric hydrogen energy storage system to predict the power demand load at a set time or multiple times after the current time, and to determine the minimum output power of the hydrogen storage in the electric hydrogen energy storage system at the set time or multiple times based on the power demand prediction load corresponding to the set time or multiple times, the hydrogen energy conversion efficiency corresponding to the hydrogen storage in the electric hydrogen energy storage system, and the maximum hydrogen energy storage output power. The objective function determination unit is used to determine the objective function based on the power demand load at the current moment, the output power of the battery energy storage, the maximum storage capacity, the minimum storage capacity, the storage capacity or the updated storage capacity, and the minimum output power of the hydrogen energy storage. An optimization unit is used to maximize the utilization of the hydrogen energy storage while minimizing the usage frequency and / or deep discharge of the battery in the battery energy storage, and to determine the optimized battery output power and optimized hydrogen energy storage output power of the electro-hydrogen energy storage system at the current moment based on the objective function.

19. A dynamic control system for electro-hydrogen energy storage, characterized in that, include: processor; A memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the dynamic control method according to any one of claims 13 to 15; or, Includes: a computer-readable storage medium having stored thereon computer program instructions, which, when executed by a processor, implement the dynamic control method according to any one of claims 13 to 15; or, Includes: a computer program product, including a computer program or instructions that, when executed by a processor, implement the dynamic control method according to any one of claims 13 to 15.

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