Time-sharing energy storage self-balancing power supply method and system, medium and product

Abstract

The invention discloses a time-sharing energy storage self-balancing power supply method and system, a medium and a product, and relates to the technical field of electric power engineering.According to the method, power grid electricity prices and electricity demands in a plurality of preset periods are intelligently analyzed, so that a power supply scheme and an energy storage strategy are flexibly adjusted, and the power use cost is optimized to the maximum extent. The power grid is fully used for supplying power and storing energy in the low-electricity-price period, the energy storage power supply is preferentially used in the high-electricity-price period, and the power supply scheme and the energy storage strategy are dynamically adjusted according to the electricity price trend of the follow-up preset period, so that compared with a simple mode of storing energy in the low-electricity-price period and supplying power in the high-electricity-price period in the prior art, an intermediate electricity price period is also considered; whether the electricity storage equipment needs to be charged or discharged is judged, and the economy is maximized through time-sharing measurement and calculation. The multi-cycle linkage decision-making mechanism can better deal with complex electricity price fluctuation, optimize an energy storage scheme and a power supply strategy, improve the energy utilization efficiency, and bring long-term stable cost saving for users.

Description

Technical Field

[0001] The present application relates to the field of electric power engineering technology, and in particular to a time-sharing energy storage self-balancing power supply method, system, medium and product. Background Art

[0002] In modern power systems, the balance between supply and demand is a key issue. In order to optimize the cost of electricity use, many companies and households have begun to pay attention to how to reasonably arrange electricity use and energy storage in different electricity price cycles to achieve the goal of cost saving.

[0003] In the existing technology, some solutions adjust the electricity consumption strategy within a fixed planning period to cope with electricity price fluctuations. These solutions usually formulate an overall electricity consumption plan based on historical electricity price data and electricity demand forecasts. This method takes into account the possibility of shifting peak electricity prices to low periods, which can reduce electricity costs to a certain extent.

[0004] However, with the continuous changes in the electricity market, existing technical solutions have shown some shortcomings when facing more complex electricity price fluctuations. For example, when dealing with multi-period electricity price differences, it is difficult to flexibly adjust the power supply plan and power storage plan, resulting in the potential economic benefits not being fully realized. Summary of the invention

[0005] The present application provides a time-sharing energy storage self-balancing power supply method, system, medium and product, which are used to maximize economic benefits while optimizing energy storage solutions and power supply strategies under complex electricity price fluctuations, improve energy utilization efficiency, and bring long-term and stable cost savings to users through time-sharing calculations.

[0006] In a first aspect, the present application provides a time-sharing energy storage self-balancing power supply method, which is applied to a control system, the method comprising: obtaining a grid electricity price within a plurality of preset periods and a predicted power consumption of an electric device within the plurality of preset periods; if the grid electricity price of the first preset period is lower than the preset price, determining to use a first grid power supply to power the electric device and sending a first energy storage instruction to the energy storage device, the first grid power supply being the predicted power consumption of the electric device within the first preset period, and the first energy storage instruction including the storage amount of the energy storage device within the first preset period; when the grid electricity price of the second preset period is higher than the preset price, comparing the grid electricity price of the second preset period with the grid electricity price of the third preset period, the second preset period being the next preset period of the first preset period, and the third preset period being the next preset period of the second preset period; if the grid electricity price of the third preset period is higher than the grid electricity price of the second preset period, determining whether the storage amount of the energy storage device within the first preset period is greater than the sum of the predicted power consumption of the electric device within the second preset period and the third preset period; if so, determining to use the power supply amount of the energy storage device within the second preset period and the third preset period. The power supply of the energy storage device is the storage capacity of the energy storage device in the first preset period; if not, it is determined to use the second power supply of the power grid and the power supply of the energy storage device to power the power device in the second preset period and the third preset period, and the second power supply of the power grid is the difference between the sum of the predicted power consumption of the power device in the second preset period and the third preset period and the power supply of the energy storage device; if the power grid electricity price of the third preset period is lower than the power grid electricity price of the second preset period, it is judged that the storage capacity of the energy storage device in the first preset period is Whether it is greater than the predicted power consumption of the power user in the second preset period; if so, determine to use the power supply of the energy storage device to power the power user in the second preset period; if not, determine to use the power supply of the third power grid and the power supply of the energy storage device to power the power user in the second preset period, the power supply of the third power grid being the difference between the predicted power consumption of the power user in the second preset period and the power supply of the energy storage device; in the preset third period, send a second energy storage instruction to the energy storage device, the second energy storage instruction including the storage capacity of the energy storage device in the third preset period.

[0007] By adopting the above technical solution, the control system intelligently analyzes the power grid electricity price and electricity demand within multiple preset cycles, so as to flexibly adjust the power supply plan and energy storage strategy, and realize the maximum optimization of electricity use cost. This method makes full use of the power supply and energy storage of the power grid during the low electricity price period, gives priority to the use of energy storage power supply during the high electricity price period, and dynamically adjusts the power supply plan and energy storage strategy according to the electricity price trend of the subsequent preset period. Compared with the simple method of storing energy during low electricity price periods and supplying electricity during high electricity price periods in the prior art, it also considers the intermediate electricity price period to determine whether the storage equipment needs to be charged or discharged, and maximizes the economy through time-sharing measurement. This multi-cycle linkage decision-making mechanism can better cope with complex electricity price fluctuations, optimize energy storage solutions and power supply strategies, improve energy utilization efficiency, and bring long-term and stable cost savings to users.

[0008] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining the power grid electricity price within multiple preset periods and the predicted power consumption of the power consuming equipment within the multiple preset periods, the method also includes: obtaining historical power consumption data of the power consuming equipment, the historical power consumption data including a historical power consumption plan and historical power consumption corresponding to the historical power consumption plan; taking the historical power consumption plan as an input feature, and taking the historical power consumption corresponding to the historical power consumption plan as an output feature; training a preset model through the input feature and the output feature; and obtaining a power consumption prediction model when it is determined that the accuracy of the preset model reaches a preset accuracy threshold.

[0009] By adopting the above technical solution, the control system establishes a power consumption prediction model, which greatly improves the accuracy of the predicted power consumption of power-consuming equipment within multiple preset cycles. The control system collects historical power consumption data, uses historical power consumption plans as input features, and uses historical power consumption corresponding to historical power consumption plans as output features to train the preset model until the accuracy of the preset model reaches the preset accuracy threshold. This data-driven approach can capture complex patterns and potential trends in power consumption behavior, and is more accurate than simple historical data extrapolation. In addition, high-precision power consumption forecasts provide a reliable foundation for the subsequent formulation of power supply strategies, help to more accurately balance supply and demand, avoid the risk of excessive energy storage or insufficient power supply, and further optimize overall power supply efficiency and cost control.

[0010] In combination with some embodiments of the first aspect, in some embodiments, obtaining the grid electricity price within multiple preset periods and the predicted electricity consumption of the power equipment within the multiple preset periods specifically includes: obtaining the predicted grid electricity price within the multiple preset periods from the power trading platform; correcting the predicted grid electricity price according to historical electricity price data and market supply and demand conditions to obtain the grid electricity price within the multiple preset periods; obtaining the electricity consumption plan of the power equipment within the multiple preset periods; and inputting the electricity consumption plan into the electricity consumption prediction model to obtain the predicted electricity consumption of the power equipment within the multiple preset periods.

[0011] By adopting the above technical solutions, the accuracy and reliability of obtaining grid electricity prices and predicting electricity consumption are significantly improved. The control system first obtains the predicted grid electricity prices within multiple preset periods from the power trading platform, and then corrects them in combination with historical data and market supply and demand conditions to obtain grid electricity prices within multiple preset periods. This method can better reflect the actual market trend and reduce prediction deviations. The control system uses the trained electricity consumption prediction model to input the electricity consumption plan into the electricity consumption prediction model to obtain the predicted electricity consumption. This method is more adaptable to the dynamic changes in electricity consumption patterns than traditional statistical predictions. By improving the accuracy of grid electricity prices and predicted electricity consumption, more reliable data support is provided for subsequent power supply decisions, so that better power supply strategies can be formulated and maximum economic benefits can be achieved through time-sharing measurement.

[0012] In combination with some embodiments of the first aspect, in some embodiments, if the grid electricity price in the first preset period is lower than the preset price, it is determined to use the first grid power supply to power the power-consuming device and send a first energy storage instruction to the energy storage device, the first grid power supply is the predicted power consumption of the power-consuming device in the first preset period, and the first energy storage instruction includes the storage capacity of the energy storage device in the first preset period, specifically including: determining the planned charging capacity of the energy storage device in the first preset period according to the duration of the first preset period and the maximum charging rate of the energy storage device; if the planned charging capacity of the energy storage device in the first preset period exceeds the maximum storage capacity of the energy storage device, using the maximum storage capacity of the energy storage device as the storage capacity of the energy storage device in the first preset period, and sending the first energy storage instruction to the energy storage device.

[0013] By adopting the above technical solutions, the charging strategy of the energy storage equipment is intelligently adjusted to maximize the energy storage efficiency. When the grid electricity price is lower than the preset price, the control system calculates the planned charging amount based on the duration of the preset cycle and the maximum charging rate of the energy storage equipment. At the same time, the control system also takes into account the maximum storage capacity of the energy storage equipment to ensure that the equipment limit is not exceeded. This precise charging control not only makes full use of low-priced electricity, but also avoids overcharging of energy storage equipment and prolongs the life of the equipment. By optimizing the storage capacity of each low-priced preset cycle, the control system can provide more reserve power for subsequent high-priced preset cycles, thereby maximizing cost savings through time-sharing measurement and improving energy utilization efficiency.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before the step of determining to use the first grid power supply to power the power-consuming device and sending a first energy storage instruction to the energy storage device if the grid electricity price of the first preset period is lower than the preset price, the method also includes: arranging the grid electricity prices in multiple preset periods from low to high to obtain an electricity price arrangement order; and determining the median in the electricity price arrangement order as the preset price.

[0015] By adopting the above technical solution, the preset price of the grid electricity price is dynamically determined, and the adaptive optimization of the power supply strategy is realized. By sorting the grid electricity prices in multiple preset periods from low to high and selecting the median as the preset price, the control system can automatically adapt to the electricity price fluctuation characteristics of different preset periods. This method avoids the lag and inadaptability that may be caused by fixed thresholds, making the control system more flexible and accurate in judging whether to store energy or use energy storage for power supply, and can better grasp the timing of low-price energy storage and high-price discharge, thereby maximizing economic benefits.

[0016] In combination with some embodiments of the first aspect, in some embodiments, the method also includes: calculating the actual electricity cost of each preset period based on the storage energy of the energy storage device in each preset period and the power supply source of the predicted power consumption of the power consuming equipment in each preset period; calculating the predicted electricity cost of each preset period based on the power grid electricity price in each preset period and the predicted power consumption of the power consuming equipment in each preset period; and storing the actual electricity cost and the predicted electricity cost in a preset database.

[0017] By adopting the above technical solutions, the control system calculates and stores the actual electricity costs and predicted electricity costs, and establishes a feedback mechanism for continuous optimization. By comparing the actual electricity costs (predicted electricity consumption based on energy storage equipment and grid power supply) with the predicted electricity costs (predicted electricity consumption based on grid power supply), the control system can evaluate the effectiveness of the current power supply strategy. The collection and storage of this data provides valuable historical data support for subsequent strategy optimization. By analyzing the difference between the actual electricity costs and the predicted electricity costs, the control system can continuously adjust and improve its decision-making algorithm to improve the accuracy of future predictions and decisions. This closed-loop optimization mechanism enables the control system to continuously improve itself over time, adapt to the changing electricity consumption patterns and market environment, and thus continuously improve long-term cost savings through time-sharing measurement.

[0018] In combination with some embodiments of the first aspect, in some embodiments, the method further includes: generating a grid electricity price change curve based on grid electricity prices within multiple preset periods; and determining peak electricity price periods and trough electricity price periods in the grid electricity price change curve.

[0019] By adopting the above technical solutions, the control system generates the grid electricity price change curve and determines the peak and trough periods of electricity prices, providing an intuitive and critical reference for the formulation of power supply strategies. The visualization of the electricity price change curve makes the fluctuating grid electricity prices easier to understand and analyze, which helps decision makers quickly grasp the trend of electricity price changes. By clearly identifying the peak and trough periods of electricity prices, energy storage plans and electricity consumption plans can be formulated more accurately. This clear time division helps to maximize energy storage during the trough period of electricity prices and optimize electricity consumption during the peak period of electricity prices, thereby achieving optimal cost control. At the same time, this method also provides users with intuitive electricity usage suggestions, which helps guide users to actively adjust their electricity usage behavior and further improve overall energy efficiency and cost savings.

[0020] In a second aspect, an embodiment of the present application provides a control system, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the control system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when the computer program product is run on a control system, enables the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a control system, enable the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the adoption of a dynamic decision-making mechanism with multi-cycle linkage, the present invention can cope with complex electricity price fluctuations more flexibly, effectively solving the problem of poor economic benefits caused by only considering a single cycle or fixed strategy in the prior art, and further achieving long-term stable cost savings and significant improvement in energy utilization efficiency through time-sharing measurement.

[0025] 2. Due to the adoption of a machine learning-based electricity consumption prediction model and a dynamic electricity price correction method, the present invention greatly improves the accuracy of predicted electricity consumption and grid electricity prices, effectively solves the supply and demand imbalance and economic loss problems caused by prediction bias in the prior art, and thus achieves more accurate power supply strategy formulation and higher cost savings.

[0026] 3. Due to the use of adaptive electricity price threshold setting and closed-loop optimization mechanism, the present invention can continuously improve itself and adapt to market changes, effectively solving the problem that fixed strategies in the prior art are difficult to cope with long-term market changes, thereby achieving continuous optimization of the method and long-term stable operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of a time-sharing energy storage self-balancing power supply method in an embodiment of the present application; Figure 2 This is another flow chart of the time-sharing energy storage self-balancing power supply method in the embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of the control system in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , is a flow chart of a time-sharing energy storage self-balancing power supply method in an embodiment of the present application.

[0031] S101, obtaining the power price of the power grid within a plurality of preset periods and the predicted power consumption of the power-consuming equipment within the plurality of preset periods; The preset period is used to represent the time unit for the control system to make power supply decisions, which can be hours, days or weeks, etc., and is not limited here; the power grid price refers to the price per unit of electricity charged by the power company to the user; the power equipment is used to represent various machines, devices or equipment that need electricity; the predicted power consumption refers to the power consumption that the power equipment may consume estimated by some method. Multiple preset periods are used to represent several consecutive time units for medium- and long-term power supply planning.

[0032] The control system performs this step before starting to make power supply decisions to obtain the necessary basic data. First, the control system determines the time range that needs to be planned, such as the next 24 hours, 7 days or 30 days, and divides it into multiple preset periods. Then, the control system obtains the grid electricity price within these preset periods through the data interface with the power company. At the same time, the control system calls the pre-trained power consumption prediction model, inputs the power consumption plan of the power equipment, and obtains the predicted power consumption of the power equipment in each preset period.

[0033] Optionally, under normal circumstances, obtaining the grid electricity price within multiple preset periods and the predicted electricity consumption of the power consuming equipment within the multiple preset periods can be achieved in the following ways: obtaining the predicted grid electricity price within multiple preset periods from the power trading platform; correcting the predicted grid electricity price according to historical electricity price data and market supply and demand conditions to obtain the grid electricity price within multiple preset periods; obtaining the electricity consumption plan of the power consuming equipment within multiple preset periods; inputting the electricity consumption plan into the electricity consumption prediction model to obtain the predicted electricity consumption of the power consuming equipment within multiple preset periods.

[0034] S102: if the grid electricity price in the first preset period is lower than the preset price, determine to use the first grid power supply to power the electric device and send a first energy storage instruction to the energy storage device, the first grid power supply is the predicted power consumption of the electric device in the first preset period, and the first energy storage instruction includes the storage capacity of the energy storage device in the first preset period; The first preset period represents any time unit among multiple preset periods; the preset price refers to a reference value used by the control system to judge the high or low electricity price, which is usually based on historical data and market analysis and is not limited here; the first power supply of the power grid represents the amount of electricity purchased from the power grid for power supply during the first preset period; the energy storage device refers to a device that can store electrical energy and release it when needed, such as a battery pack; the energy storage instruction is used to represent the control command sent by the control system to the energy storage device; the storage capacity refers to the amount of electrical energy stored in the energy storage device.

[0035] After obtaining the grid electricity price in multiple preset periods and the predicted power consumption of the power-consuming equipment in the multiple preset periods, the control system begins to analyze the power supply strategy of the preset periods one by one. First, the control system reads the grid electricity price and the reference preset price of the first preset period. Then, the control system uses a comparison algorithm to compare the two prices to determine whether the current grid electricity price is at a relatively low level, so as to determine whether it is suitable to store energy in the energy storage device in this preset period. The comparison result will directly affect the next decision-making process. The control system will temporarily store the comparison result for use in subsequent steps.

[0036] After determining that the power price of the power grid in the first preset period is lower than the preset price, the control system can use the low-priced electricity in the preset period for energy storage and power supply. First, the control system calculates the power supply of the first power grid, that is, the predicted power consumption of the power-consuming equipment in the first preset period. Then, the control system generates an instruction to purchase the first power supply of the power grid from the power grid to ensure the normal power supply of the power-consuming equipment. At the same time, the control system calculates the maximum storage capacity and the maximum charging rate of the energy storage device, and determines the storage capacity of the energy storage device in the first preset period in combination with the duration of the first preset period. The control system generates a first energy storage instruction containing the storage capacity of the energy storage device in the first preset period, and sends it to the energy storage device through the communication interface. In this way, the control system not only ensures the normal power consumption of the power-consuming equipment, but also maximizes the use of low-priced electricity for energy storage, and prepares for the subsequent high-priced electricity period.

[0037] Optionally, under normal circumstances, if the grid electricity price in the first preset period is lower than the preset price, determining to use the first grid power supply to power the electrical device and sending the first energy storage instruction to the energy storage device can be achieved in the following way: according to the duration of the first preset period and the maximum charging rate of the energy storage device, determine the planned charging amount of the energy storage device in the first preset period; if the planned charging amount of the energy storage device in the first preset period exceeds the maximum storage amount of the energy storage device, use the maximum storage amount of the energy storage device as the storage amount of the energy storage device in the first preset period, and send the first energy storage instruction to the energy storage device.

[0038] S103, when the grid electricity price of the second preset period is higher than the preset price, comparing the grid electricity price of the second preset period with the grid electricity price of the third preset period, the second preset period being the next preset period of the first preset period, and the third preset period being the next preset period of the second preset period; The second preset period refers to the time period immediately following the first preset period, and is used to indicate the next preset period in which the electricity price may change. The third preset period refers to the time period immediately following the second preset period, and is used to indicate the trend of electricity prices in the longer term.

[0039] The control system performs this step when it detects that the grid electricity price of the second preset period is higher than the preset price. First, the control system determines that the grid electricity price of the second preset period is higher than the preset price, which indicates that a relatively high electricity price period has been entered. Subsequently, the control system further compares the grid electricity prices of the second preset period and the third preset period. This comparison is not just a simple numerical comparison, but also includes an analysis of electricity price trends. The control system may consider factors such as the magnitude of the electricity price difference, historical data for the same period, and current market supply and demand conditions to more comprehensively evaluate the trend of electricity price changes. This multi-dimensional comparison provides an important basis for subsequent energy storage methods and power supply strategy decisions, enabling the control system to better respond to different electricity price changes.

[0040] S104: If the grid electricity price of the third preset period is higher than the grid electricity price of the second preset period, determine whether the storage capacity of the energy storage device in the first preset period is greater than the sum of the predicted power consumption of the power-consuming device in the second preset period and the third preset period; The control system performs this step when it determines that the grid electricity price of the third preset period is higher than the grid electricity price of the second preset period. This situation indicates that the electricity price is showing a continuous upward trend, and the control system needs to give priority to using energy storage to cope with the high electricity price.

[0041] First, the control system determines whether the amount of energy stored in the energy storage device within the first preset period can meet the sum of the predicted power consumption of the power-consuming device in the second preset period and the third preset period. The amount of energy stored in the first preset period represents the amount of electric energy stored in the energy storage device in the first preset period of the previous low electricity price period. This judgment process involves the calculation and comparison of multiple factors. The control system will accurately calculate the current power of the energy storage device, taking into account factors such as energy storage efficiency and self-discharge rate, and at the same time combine the predicted power consumption of the power-consuming device in the second preset period and the third preset period, so as to determine whether the amount of energy stored in the energy storage device in the first preset period is greater than the sum of the predicted power consumption of the power-consuming device in the second preset period and the third preset period.

[0042] S105: If yes, determine to use the power supply of the energy storage device to power the electrical device in the second preset period and the third preset period, and the power supply of the energy storage device is the storage capacity of the energy storage device in the first preset period; If the amount of energy stored in the energy storage device in the first preset period is greater than the sum of the predicted power consumption of the power consumption device in the second preset period and the third preset period, it means that the amount of energy stored in the energy storage device in the first preset period is sufficient, and the control system will decide to completely rely on the energy storage device to supply power to the power consumption device in the second preset period and the third preset period, so as to avoid purchasing electricity from the power grid during the high electricity price period to the greatest extent. This decision not only takes into account the balance of electricity, but also includes the trade-offs of factors such as the service life of the energy storage device and the charging and discharging efficiency, and maximizes the cost saving effect through time-sharing measurement.

[0043] S106. If not, determine to use the second power grid power supply and the power supply of the energy storage device to power the electric device in the second preset period and the third preset period, and the second power supply of the power grid is the difference between the sum of the predicted power consumption of the electric device in the second preset period and the third preset period and the power supply of the energy storage device; The second grid power supply represents the additional power that needs to be purchased from the grid to make up for the insufficient power supply of the energy storage device. The control system performs this step when it determines that the power supply of the energy storage device is insufficient to fully meet the power demand of the second preset period and the third preset period. This situation usually occurs during a period of sustained high electricity prices and when the energy storage capacity is limited.

[0044] If the amount of energy stored in the energy storage device in the first preset period is less than the sum of the predicted power consumption of the power consumer in the second preset period and the third preset period, it means that the amount of energy stored in the energy storage device in the first preset period is insufficient, and the control system will use the power supply of the energy storage device to partially power the power consumer in the second preset period and the third preset period. Then, the control system calculates the difference between the sum of the predicted power consumption in the second preset period and the third preset period and the power supply of the energy storage device, that is, the power supply of the second power grid, and formulates a strategy to supplement the power supply of the power grid, purchasing the power supply of the second power grid from the power grid to support the continued operation of the power consumer. This sophisticated power balance and decision-making process ensures that the control system can maximize the use of low-cost energy storage while ensuring stable satisfaction of power demand.

[0045] S107: If the grid electricity price of the third preset period is lower than the grid electricity price of the second preset period, determine whether the storage capacity of the energy storage device in the first preset period is greater than the predicted power consumption of the power-consuming device in the second preset period; The control system performs this step when it determines that the grid electricity price in the third preset period is lower than the grid electricity price in the second preset period. This situation indicates that the electricity price is on a downward trend, and the control system needs to re-evaluate the energy storage solution and power supply strategy to adapt to this change. The control system compares the storage capacity of the energy storage device in the first preset period determined in the previous step with the predicted power consumption of the power-consuming device in the second preset period. This comparison is not just a simple numerical comparison, but also takes into account the characteristics of the power load curve, such as whether there is a peak in power consumption, whether there is a special high-power demand, etc. Through this comprehensive and in-depth analysis, the control system can provide a more accurate and reliable basis for the subsequent formulation of power supply strategies.

[0046] S108: If yes, determine to use the power supply of the energy storage device to supply power to the electrical device in the second preset period; If the control system determines that the amount of power stored in the energy storage device in the first preset period is greater than the predicted power consumption of the power consuming device in the second preset period, it means that the power consuming device can be powered by the energy storage device in the second preset period instead of purchasing electricity from the power grid, so as to minimize the electricity bill.

[0047] S109, if not, determine to use the power supply of the third power grid and the power supply of the energy storage device to power the electric device in the second preset period, and the power supply of the third power grid is the difference between the predicted power consumption of the electric device in the second preset period and the power supply of the energy storage device; If the control system determines that the amount of power stored in the energy storage device in the first preset period is less than the predicted power consumption of the power consumer in the second preset period, it means that the power supply of the energy storage device is insufficient to support the predicted power consumption of the power consumer in the second preset period, and the power grid needs to be supplemented. The third power grid power supply is the difference between the predicted power consumption of the power consumer in the second preset period and the power supply of the energy storage device, indicating the additional power that needs to be purchased from the power grid to make up for the insufficient power supply of the energy storage device. Through this sophisticated hybrid power supply strategy, the control system can optimize the power cost to the greatest extent while ensuring the reliability of power supply.

[0048] S110. In the preset third period, a second energy storage instruction is sent to the energy storage device, where the second energy storage instruction includes the storage capacity of the energy storage device in the third preset period.

[0049] The control system performs this step when it starts planning the energy storage strategy for the third preset period after completing the power supply arrangement for the second preset period. This advance planning helps the control system better cope with future changes in electricity prices and electricity demand, thereby maximizing cost savings.

[0050] Specifically, the control system will first analyze the grid electricity price of the third preset period and the predicted electricity consumption of the power-consuming equipment in the third period with the vehicle. This analysis will take into account a variety of factors, including historical data for the same period, market supply and demand forecasts, possible weather changes, etc. Based on these analyses, the control system will estimate the amount of storage energy that may be needed in the third preset period. Then, the control system will formulate a detailed energy storage plan, including the time schedule for energy storage, charging power curve, etc. This energy storage plan will take into account the load of the power grid, and try to choose to store energy during periods when the grid load is low and the electricity price is low to reduce the cost of energy storage. At the same time, the control system will also consider the characteristics of the energy storage equipment, such as charging efficiency, optimal charging power, etc., to optimize the energy storage process and extend the life of the equipment. After determining the energy storage plan, the control system will generate a detailed second energy storage instruction and send it to the energy storage equipment, and continue to monitor the energy storage process in the subsequent period to ensure that the energy storage is carried out as planned.

[0051] By adopting the above technical solution, the control system intelligently analyzes the power grid electricity price and electricity demand within multiple preset cycles, so as to flexibly adjust the power supply plan and energy storage strategy, and realize the maximum optimization of electricity use cost. This method makes full use of the power supply and energy storage of the power grid during the low electricity price period, gives priority to the use of energy storage power supply during the high electricity price period, and dynamically adjusts the power supply plan and energy storage strategy according to the electricity price trend of the subsequent preset period. Compared with the simple method of storing energy during low electricity price periods and supplying electricity during high electricity price periods in the prior art, it also considers the intermediate electricity price period to determine whether the storage equipment needs to be charged or discharged, and maximizes the economy through time-sharing measurement. This multi-cycle linkage decision-making mechanism can better cope with complex electricity price fluctuations, optimize energy storage solutions and power supply strategies, improve energy utilization efficiency, and bring long-term and stable cost savings to users.

[0052] After combining the above scenarios, the following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the time-sharing energy storage self-balancing power supply method in an embodiment of the present application.

[0053] S201, obtaining historical power consumption data of power-consuming equipment, wherein the historical power consumption data includes a historical power consumption plan and a historical power consumption corresponding to the historical power consumption plan; using the historical power consumption plan as an input feature, and using the historical power consumption corresponding to the historical power consumption plan as an output feature; training a preset model through the input features and the output features; and obtaining a power consumption prediction model when it is determined that the accuracy of the preset model reaches a preset accuracy threshold; First, the control system collects the historical power consumption plan of the power-consuming equipment within the past preset period of time (for example, within 6 months) and the historical power consumption corresponding to the historical power consumption plan. The format of the historical power consumption plan is unified, including the operation mode, operation power and operation time of the power-consuming equipment, which are not limited here. The historical power consumption represents the amount of electricity used by the power-consuming equipment under the historical power consumption plan. The control system stores the collected historical power consumption plan and the historical power consumption corresponding to the historical power consumption plan into the data set D, and the format of each data is (historical power consumption plan, historical power consumption). Among them, the historical power consumption plan is the input feature of the model training, and the historical power consumption corresponding to the historical power consumption plan is the output feature of the model training.

[0054] The control system constructs a LSTM-based recurrent neural network, which includes an input layer, two LSTM hidden layers, a fully connected layer, and an output layer. The input layer inputs the normalized historical power consumption plan, the number of hidden layer nodes is set to 64, and the number of fully connected layer nodes is set to 32. The output layer outputs the historical power consumption corresponding to the historical power consumption plan.

[0055] Next, the control system uses the Adam optimizer, the learning rate is set to 0.001, and the training batch size is 32. It can also be set according to the actual situation and is not limited here. 80% of the historical data is divided into a training set and 20% is divided into a validation set. 100 epochs are trained and the model with the highest accuracy of the validation set is saved. It can also be set according to the actual situation and is not limited here. Epoch is the process in which the training data set passes through the neural network once. In machine learning and deep learning, epoch is a unit used to measure the number of times the entire training set is repeatedly learned. Specifically, when the neural network completes a forward calculation and back propagation process, that is, all data has been processed by the network once, this completes an epoch. The control system uses binary cross entropy as the loss function and Early Stopping to prevent overfitting. When the value of the loss function exceeds the preset function threshold, the model training is determined to be completed and the power consumption prediction model is obtained. Early Stopping is a technology in deep learning and machine learning to prevent model overfitting. It determines when to stop training by monitoring the performance of the model on the validation set.

[0056] Finally, the control system inputs the input features in the validation set into the power consumption prediction model, and then obtains the predicted output of the power consumption prediction model. The predicted output of the power consumption prediction model is compared with the actual output features in the validation set, and some performance indicators such as accuracy, precision, recall, F1 score, mean square error (MSE), etc. are used to evaluate the performance of the power consumption prediction model. According to the performance of the power consumption prediction model on the validation set, the parameters of the power consumption prediction model are adjusted, including adjusting the learning rate, changing the model complexity (such as increasing or decreasing the number of layers or nodes of the neural network), modifying the regularization strength, etc. This process may require multiple iterations, each of which is adjusted based on the previous learning results to optimize the power consumption prediction model.

[0057] S202, obtaining the power grid electricity price within a plurality of preset periods and the predicted power consumption of the power-consuming equipment within a plurality of preset periods; For details, please refer to step S101, which will not be described in detail here.

[0058] S203, arranging the power grid electricity prices in a plurality of preset periods from low to high to obtain an electricity price arrangement sequence; determining the median in the electricity price arrangement sequence as the preset price; Assume that there are 5 preset periods of grid electricity prices as follows: 6:00-10:00 am: 0.8 yuan / kWh 10:00am-2:00pm: 1.2 yuan / kWh 14:00-18:00: 1.5 yuan / kWh Evening 18:00-22:00: 1.0 yuan / kWh 22:00-6:00 the next day: 0.6 yuan / kWh Arrange the grid electricity prices from low to high: 0.6 yuan / kWh (22:00-6:00 the next day) 0.8 yuan / kWh (6:00-10:00 am) 1.0 yuan / kWh (18:00-22:00) 1.2 yuan / kWh (10:00-14:00)2092 1.5 yuan / kWh (14:00-18:00) Determine the median as the preset price: In this electricity price arrangement with 5 values, the median is the third value, so the preset price is: 1.0 yuan / kWh, and this preset price corresponds to 18:00-22:00 in the evening.

[0059] In this way, the control system can obtain a grid electricity price that is neither the highest nor the lowest, but at an intermediate level as a preset price. This method can balance the grid electricity price during peak and off-peak hours, providing a reasonable reference point for electricity price management.

[0060] S204: if the grid electricity price in the first preset period is lower than the preset price, determine to use the first grid power supply to power the electric device and send a first energy storage instruction to the energy storage device, the first grid power supply is the predicted power consumption of the electric device in the first preset period, and the first energy storage instruction includes the storage capacity of the energy storage device in the first preset period; For details, please refer to step S101, which will not be described in detail here.

[0061] S205, when the grid electricity price of the second preset period is higher than the preset price, compare the grid electricity price of the second preset period with the grid electricity price of the third preset period, the second preset period being the next preset period of the first preset period, and the third preset period being the next preset period of the second preset period; For details, please refer to step S101, which will not be described in detail here.

[0062] S206: If the grid electricity price of the third preset period is higher than the grid electricity price of the second preset period, determine whether the storage capacity of the energy storage device in the first preset period is greater than the sum of the predicted power consumption of the power consumption device in the second preset period and the third preset period; For details, please refer to step S101, which will not be described in detail here.

[0063] S207: If yes, determine to use the power supply of the energy storage device to power the electrical device in the second preset period and the third preset period, and the power supply of the energy storage device is the storage amount of the energy storage device in the first preset period; For details, please refer to step S101, which will not be described in detail here.

[0064] S208, if not, determine to use the second power grid power supply and the energy storage device power supply to power the electrical device in the second preset period and the third preset period, the second power grid power supply being the difference between the sum of the predicted power consumption of the electrical device in the second preset period and the third preset period and the power supply of the energy storage device; For details, please refer to step S101, which will not be described in detail here.

[0065] S209: If the grid electricity price of the third preset period is lower than the grid electricity price of the second preset period, determine whether the storage capacity of the energy storage device in the first preset period is greater than the predicted power consumption of the power consumption device in the second preset period; For details, please refer to step S101, which will not be described in detail here.

[0066] S210: If yes, determine to use the power supply of the energy storage device to supply power to the power-consuming device in the second preset period; For details, please refer to step S101, which will not be described in detail here.

[0067] S211, if not, determine to use the power supply of the third power grid and the power supply of the energy storage device to power the power-consuming device in the second preset period, where the power supply of the third power grid is the difference between the predicted power consumption of the power-consuming device in the second preset period and the power supply of the energy storage device; For details, please refer to step S101, which will not be described in detail here.

[0068] S212, sending a second energy storage instruction to the energy storage device in a preset third period, where the second energy storage instruction includes the storage capacity of the energy storage device in the third preset period; For details, please refer to step S101, which will not be described in detail here.

[0069] S213, calculating the actual electricity fee for each preset period according to the energy storage amount of the energy storage device in each preset period and the power supply source of the power consumption of the power consumption device in each preset period; calculating the predicted electricity fee for each preset period according to the power grid electricity price in each preset period and the predicted power consumption of the power consumption device in each preset period; storing the actual electricity fee and the predicted electricity fee in a preset database; The control system determines the amount of electricity purchased from the power grid according to the steps in steps S101 to S110, and calculates the actual electricity charges of the power-consuming equipment in each preset period. If the energy storage device is not used, electricity is purchased from the power grid in each preset period, and the control system can determine the predicted electricity consumption of the power-consuming equipment in each preset period. The actual electricity charges are compared with the predicted electricity charges, and then stored in the preset database, and the effects of the energy storage scheme and power supply strategy can be analyzed to facilitate subsequent energy storage and power supply decisions.

[0070] S214. Generate a grid electricity price variation curve based on grid electricity prices in a plurality of preset periods; and determine a peak electricity price period and a trough electricity price period in the grid electricity price variation curve.

[0071] Based on step S202, the control system arranges the grid electricity prices in multiple preset periods from low to high to obtain the order of electricity price arrangement, and can determine the preset periods with the lowest grid electricity price and the highest grid electricity price, that is, the peak period of electricity price and the trough period of electricity price. The control system can also draw the grid electricity price of each preset period into a grid electricity price change curve in chronological order, and determine the highest point of the curve and the lowest point of the curve as the peak period of electricity price and the trough period of electricity price. It provides an intuitive and key reference basis for the formulation of power supply strategies. The visualization of the electricity price change curve makes the fluctuating grid electricity price easier to understand and analyze, which helps decision makers to quickly grasp the trend of electricity price changes. By clearly identifying the peak period of electricity price and the trough period of electricity price, energy storage plans and electricity consumption plans can be formulated more accurately. This clear time division helps to maximize energy storage during the trough period of electricity price and optimize electricity consumption during the peak period of electricity price, so as to achieve the best cost control. At the same time, this method also provides users with intuitive electricity consumption suggestions, which helps to guide users to actively adjust their electricity consumption behavior and further improve the overall energy utilization efficiency and cost saving effect.

[0072] The following describes the control system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the structure of a physical device of the control system in an embodiment of the present application.

[0073] It should be noted that Figure 3 The structure of the control system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0074] like Figure 3As shown, the control system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, the ROM 302 and the RAM 303 are connected to each other through the bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0075] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0076] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 309, and / or installed from a removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0077] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0078] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0079] Specifically, the control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the time-sharing energy storage self-balancing power supply method provided in the above embodiment is implemented.

[0080] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the control system described in the above embodiment; or may exist independently without being assembled into the control system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the control system, the control system implements the time-sharing energy storage self-balancing power supply method provided in the above embodiment.

[0081] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0082] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0083] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A time-sharing energy storage self-balancing power supply method, characterized in that: Applied to a control system, the method comprises: Obtaining the power price of the power grid within a plurality of preset periods and the predicted power consumption of the power-consuming equipment within the plurality of preset periods; If the grid electricity price of the first preset period is lower than the preset price, determine to use the first grid power supply to power the power-consuming device and send a first energy storage instruction to the energy storage device, the first grid power supply is the predicted power consumption of the power-consuming device in the first preset period, and the first energy storage instruction includes the storage capacity of the energy storage device in the first preset period; When the grid electricity price of the second preset period is higher than the preset price, comparing the grid electricity price of the second preset period with the grid electricity price of the third preset period, the second preset period is the next preset period of the first preset period, and the third preset period is the next preset period of the second preset period; If the grid electricity price of the third preset period is higher than the grid electricity price of the second preset period, determine whether the storage capacity of the energy storage device in the first preset period is greater than the sum of the predicted power consumption of the power-consuming device in the second preset period and the third preset period; If so, determine to use the power supply of the energy storage device to power the power-consuming device in the second preset period and the third preset period, and the power supply of the energy storage device is the storage amount of the energy storage device in the first preset period; If not, determine to use the second power grid power supply and the power supply of the energy storage device to power the power-consuming device in the second preset period and the third preset period, the second power grid power supply being the difference between the sum of the predicted power consumption of the power-consuming device in the second preset period and the third preset period and the power supply of the energy storage device; If the grid electricity price of the third preset period is lower than the grid electricity price of the second preset period, determining whether the storage capacity of the energy storage device in the first preset period is greater than the predicted power consumption of the power-consuming device in the second preset period; If so, determine to use the power supply of the energy storage device to power the power-consuming device in the second preset period; If not, determine to use the power supply of the third power grid and the power supply of the energy storage device to power the power-consuming device in the second preset period, and the power supply of the third power grid is the difference between the predicted power consumption of the power-consuming device in the second preset period and the power supply of the energy storage device; In the preset third period, a second energy storage instruction is sent to the energy storage device, wherein the second energy storage instruction includes the storage amount of the energy storage device in the third preset period.

2. The method according to claim 1, characterized in that Before the step of obtaining the power grid electricity prices within a plurality of preset periods and the predicted power consumption of the power-consuming equipment within the plurality of preset periods, the method further includes: Acquire historical power consumption data of the power-consuming device, wherein the historical power consumption data includes a historical power consumption plan and a historical power consumption corresponding to the historical power consumption plan; Taking the historical electricity consumption plan as an input feature and taking the historical electricity consumption corresponding to the historical electricity consumption plan as an output feature; Training a preset model using the input features and the output features; When it is determined that the accuracy of the preset model reaches a preset accuracy threshold, a power consumption prediction model is obtained.

3. The method according to claim 2, characterized in that The obtaining of the power grid electricity price within a plurality of preset periods and the predicted power consumption of the power-consuming equipment within the plurality of preset periods specifically includes: Obtaining the predicted grid electricity prices within the plurality of preset periods from the electricity trading platform; Correcting the predicted grid electricity price according to historical electricity price data and market supply and demand conditions to obtain grid electricity prices within the plurality of preset periods; Obtaining a power consumption plan of the power-consuming equipment within the plurality of preset periods; The power consumption plan is input into the power consumption prediction model to obtain the predicted power consumption of the power-consuming equipment within the multiple preset periods.

4. The method according to claim 1, characterized in that: If the grid electricity price of the first preset period is lower than the preset price, determining to use the first grid power supply to power the electric device and sending a first energy storage instruction to the energy storage device, the first grid power supply is the predicted power consumption of the electric device in the first preset period, and the first energy storage instruction includes the storage capacity of the energy storage device in the first preset period, specifically including: Determining a planned charge amount of the energy storage device within the first preset cycle according to the duration of the first preset cycle and the maximum charging rate of the energy storage device; If the planned charging amount of the energy storage device in the first preset cycle exceeds the maximum storage amount of the energy storage device, the maximum storage amount of the energy storage device is used as the storage amount of the energy storage device in the first preset cycle, and a first energy storage instruction is sent to the energy storage device.

5. The method according to claim 1, characterized in that Before the step of determining to use the first grid power supply to power the power-consuming device and sending a first energy storage instruction to the energy storage device if the grid power price of the first preset period is lower than the preset price, the method further includes: Arrange the power grid electricity prices in multiple preset periods from low to high to obtain an electricity price arrangement order; The median of the electricity price arrangement sequence is determined as the preset price.

6. The method according to claim 1, characterized in that The method further comprises: Calculate the actual electricity fee for each preset period according to the energy storage device's stored energy in each preset period and the power supply source of the power consumption device's predicted power consumption in each preset period; Calculate the predicted electricity fee for each preset period according to the power grid electricity price in each preset period and the predicted power consumption of the power-consuming equipment in each preset period; The actual electricity fee and the predicted electricity fee are stored in a preset database.

7. The method according to claim 1, characterized in that The method further comprises: Generate a grid electricity price change curve based on grid electricity prices within multiple preset periods; The peak period of electricity price and the valley period of electricity price are determined in the electricity price variation curve of the power grid.

8. A control system, characterized in that: The control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the control system to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a control system, the control system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a control system, the control system is caused to execute the method according to any one of claims 1 to 7.

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