User side energy storage charging and discharging method and system based on maximum demand control

Abstract

The invention discloses a user side energy storage charging and discharging method and system based on maximum demand control, and the method achieves the intelligent adjustment of the charging and discharging power through the real-time monitoring of the electrical load of a user, the electricity price of a power grid and the state of an energy storage charging and discharging system, the combination of demand prediction and an optimization control strategy, the charging in a low ebb period, and the discharging in a peak period. The maximum demand and the electric charge of the user are reduced; the system comprises a data acquisition module, a demand prediction module, a charging and discharging strategy making module, a dynamic charging and discharging control module, an SOC dynamic management module, a power grid interaction module and the like, and has the functions of real-time monitoring, fault protection, flexible adjustment, power grid interaction and the like. By dynamically adjusting the SOC upper and lower limits and the discharge depth, the system effectively prolongs the service life of the battery, has high economical efficiency, safety and environmental protection benefits, and can remarkably improve the performance of the energy storage system and the stability of a power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage technology and electric power load management technology, and in particular to a user-side energy storage charging and discharging method and system based on maximum demand control. Background Art

[0002] User-side energy storage refers to the lithium battery energy storage system used on the industrial and commercial customer side. The lithium battery energy storage equipment can be simply understood as a large power bank, which is charged when the electricity price is low and discharged for enterprise production when the electricity price is high, thereby reducing the enterprise's electricity costs.

[0003] With the growth of energy demand and the imbalance of grid load, user demand electricity charges have gradually become an important part of the electricity cost of industrial and commercial users. Existing energy storage charging and discharging control methods often only perform simple charging and discharging based on fixed time periods, without fully considering the dynamic changes of user-side loads and grid demand, resulting in low operating efficiency of energy storage systems and failure to effectively reduce users' maximum demand, causing the electricity cost of industrial and commercial customers to increase instead of decrease. At the same time, existing methods lack intelligent optimization in terms of grid interaction and energy storage system health management, which limits the application value of energy storage systems. Summary of the invention

[0004] Technical purpose: In view of the shortcomings of the existing energy storage system charging and discharging control, the present invention discloses a user-side energy storage charging and discharging method and system based on maximum demand control, which can realize intelligent charging and discharging control of the user-side energy storage system, reduce the maximum demand, and improve the operating efficiency and safety of the energy storage system.

[0005] Technical solution: To achieve the above technical objectives, the present invention adopts the following technical solution:

[0006] A user-side energy storage charging and discharging method based on maximum demand control comprises the following steps:

[0007] Start the energy storage charging and discharging system, and monitor and record the user's electricity demand and the energy storage charging and discharging system parameters in real time through the demand meter, load meter and energy storage meter. The user's electricity demand includes the real-time power consumption of each load on the user side and the real-time maximum demand power on the user side. The energy storage charging and discharging system parameters include the charging power, discharging power and SOC of the energy storage charging and discharging system.

[0008] Based on the user's historical power consumption data and real-time monitoring data, predict the maximum power demand in the future period;

[0009] According to the predicted maximum demand power in the future period, the peak and valley electricity price of the power grid, the user's electricity demand and the parameters of the energy storage charging and discharging system, the charging and discharging period planning curve and the maximum charging and discharging power are set;

[0010] During the charging and discharging time period, according to the maximum demand power and real-time monitoring data in the future period, combined with the goals of minimizing user electricity bills and optimizing the life of energy storage batteries, the charging and discharging power of the energy storage charging and discharging system is dynamically adjusted to meet the maximum charging and discharging power constraints, demand control constraints, and SOC constraints;

[0011] Dynamically adjust the SOC upper and lower limits of the energy storage charging and discharging system according to the operating status of the energy storage charging and discharging system and the health status of the battery;

[0012] When the SOC reaches the set upper limit or the charge and discharge period ends, the current charge and discharge operation is terminated, and the energy storage charge and discharge system enters the standby state, waiting for the next charge and discharge cycle.

[0013] A user-side energy storage charging and discharging system based on maximum demand control, used to implement the above-mentioned user-side energy storage charging and discharging method based on maximum demand control, comprising:

[0014] Demand meter module, used to measure and record the maximum demand power on the user side in real time;

[0015] Load meter module, used to measure and record the real-time power of multiple loads on the user side;

[0016] Energy storage meter module, used to monitor the charging power, discharging power and SOC of the energy storage charging and discharging system in real time;

[0017] The demand prediction module is used to predict the maximum demand power in the future period based on historical power consumption data and real-time monitoring data using machine learning algorithms;

[0018] The charging and discharging strategy formulation module is used to formulate the energy storage system charging and discharging plan based on the predicted maximum demand power, peak and valley electricity prices of the power grid, the energy storage charging and discharging system, and the user's electricity demand;

[0019] Dynamic charge and discharge control module, used to adjust the charge and discharge power of the energy storage charge and discharge system in real time during the charge and discharge process;

[0020] The SOC dynamic management module is used to dynamically adjust the SOC upper and lower limits according to power demand and battery health status.

[0021] Beneficial effects: The user-side energy storage charging and discharging method and system based on maximum demand control provided by the present invention has the following beneficial effects:

[0022] 1. The present invention monitors the user's power demand in real time through demand meters and load meters, obtains the real-time maximum demand power and the real-time power consumption of each load, and automatically sets the charging and discharging time periods based on the predicted maximum demand power and combined with the peak and valley electricity prices of the power grid, especially charging during the valley period of electricity prices and discharging during the peak period, thereby effectively reducing the maximum demand power. Through dynamic adjustment of the energy storage system, the system helps users reduce the demand on the power grid during peak periods and reduces the maximum demand, thereby effectively reducing the user's electricity bill expenditure, especially when the difference between peak and valley electricity prices is large.

[0023] 2. The present invention can monitor the SOC state of the energy storage charging and discharging system in real time, dynamically adjust the SOC upper and lower limits according to factors such as the battery health state and temperature, avoid the battery being in an overcharge or over-discharge state, and dynamically control the discharge depth according to the battery health state to ensure that the battery is within a healthy working range, avoid shortening the battery life due to excessive discharge, protect the battery, avoid the negative effects of overcharging and over-discharging, and thus extend the battery life.

[0024] 3. Through machine learning algorithms, historical data and real-time monitoring data are trained to continuously optimize the maximum demand prediction and the selection of charging and discharging strategies, so that the energy storage system can flexibly adjust the charging and discharging power according to the real-time load and grid conditions. At the same time, it can respond to load changes and electricity price fluctuations in real time during operation, and dynamically adjust the charging and discharging strategy of the energy storage system to ensure maximum electricity price optimization and maximum demand control. It can adapt to various scenarios of user needs and grid changes, provide more accurate and reliable power management solutions, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0026] Figure 1 This is a flow chart of the energy storage charging and discharging method of the present invention;

[0027] Figure 2 It is a structural block diagram of each electric meter of the present invention;

[0028] Figure 3 It is a structural block diagram of the energy storage charging and discharging system of the present invention. DETAILED DESCRIPTION

[0029] The present invention will be described more clearly and completely below by way of a preferred embodiment in conjunction with the accompanying drawings, but the present invention is not limited to the scope of the embodiment.

[0030] like Figure 1As shown, the present invention provides a user-side energy storage charging and discharging method based on maximum demand control, comprising the following steps:

[0031] S1. Start the energy storage charging and discharging system, and monitor and record the user's electricity demand and the energy storage charging and discharging system parameters in real time through the demand meter, load meter and energy storage meter. The user's electricity demand includes the real-time power consumption of each load on the user side and the real-time maximum demand power on the user side. The energy storage charging and discharging system parameters include the charging power, discharging power and SOC of the energy storage charging and discharging system.

[0032] Start the energy storage charging and discharging system, such as Figure 2 As shown, the real-time maximum demand power G on the user side is monitored and recorded by the demand meter. t , which includes instantaneous maximum power and daily maximum power, and monitors and records the real-time power consumption P of multiple loads on the user side through load meters i,t , where i represents the i-th load. In one embodiment, i=1, 2, ..., n, and t is a time period. The charging power Q of the energy storage charging and discharging system is monitored and recorded in real time by the energy storage meter. c,t , discharge power Q d,t and State of Charge (SOC) t The collected data is stored in the database in real time and transmitted to the control center through the communication module.

[0033] S2. Based on the user's historical electricity consumption data and real-time monitoring data, predict the maximum demand power in the future period.

[0034] Real-time monitoring data G t , P i,t The user's historical data is input into the demand forecasting module, and an adaptive machine learning model such as LSTM or ARIMA model is used to train the model through historical power consumption data. The model predicts the maximum demand power G in the future period based on real-time data. pred,t , the predicted maximum demand power G in the coming period pred,t Calculated by the following formula:

[0035] G pred,t =α·G hist,t +β·G real,t +γ

[0036] Among them, G pred,t represents the predicted maximum demand power in time period t, G hist,t represents the maximum demand power in historical period t, G real,t represents the real-time maximum demand power in the current period t, α, β and γ represent weight coefficients, which are determined according to the correlation between historical data and real-time data;

[0037] Output the maximum demand power G in the future period according to the demand prediction model pred,t , and stored for use in subsequent steps.

[0038] S3. According to the predicted maximum demand power in the future period, the peak and valley electricity price of the power grid, the user's electricity demand and the parameters of the energy storage charging and discharging system, the charging and discharging period planning curve and the maximum charging and discharging power are set;

[0039] In one embodiment, the specific steps are as follows:

[0040] S31. Obtain the predicted maximum demand power G for the future period pred,t , Grid peak and valley electricity price C t , the real-time power demand of each load on the user side P i,t And the maximum charging and discharging power Q of the energy storage charging and discharging system w,max And SOC upper and lower limits SOC min , SOC max , the specific implementation method is:

[0041] The power demand forecast module (such as ARIMA or LSTM model) is used to forecast the power demand in the future period. Based on the historical power consumption data and real-time monitoring data, the maximum power demand G in each period is predicted. pred,t , this data, as the upper limit of future load, will affect the charging and discharging power of the energy storage charging and discharging system;

[0042] Obtain electricity price information provided by power grid operators through real-time communication modules. Usually, power grid peak and valley electricity prices are time-based pricing, with high peak prices and low valley prices. Power grid electricity prices may vary significantly depending on the time period;

[0043] Collect the real-time power consumption P of each user's load i,t , including the power consumption of lighting, air conditioning, production equipment, etc. User load demand affects the charging and discharging strategy of the energy storage charging and discharging system, especially the maximum demand control;

[0044] Get the maximum charge and discharge power Q of the energy storage charging and discharging system w,max And SOC upper and lower limits SOC min , SOC max , where the maximum charge and discharge power Q w,max Limited by the technical parameters of energy storage equipment, the upper and lower limits of SOC min , SOC max Affected by factors such as battery health and temperature.

[0045] S32, according to the peak and valley electricity price of the power grid C t Divide the charging and discharging time periods, including the low electricity price period t off-peskCharging during peak electricity price period pesk Discharge is performed and charging and discharging is flexibly adjusted according to the user's electricity demand and real-time demand during the flat period. The specific implementation method is as follows:

[0046] The low-price period is usually 22:00-06:00. The electricity price is low during this period, which is suitable for charging. According to the historical electricity price data and the period information provided by the grid operator, the low-price period is determined as the charging priority period. The energy storage charging and discharging system should complete charging as much as possible during this period.

[0047] The peak electricity price period is usually 10:00-16:00. During this period, the electricity price is higher and the user's electricity demand reaches its peak. The energy storage charging and discharging system should discharge during this period to reduce the user's dependence on the power grid and reduce the electricity cost during the peak period.

[0048] The flat period is usually 06:00-10:00 and 16:00-22:00. During this period, the electricity price is relatively stable, and the charging and discharging strategy of the energy storage system can be dynamically adjusted according to the real-time load conditions. If the user's electricity demand is high, it will discharge; otherwise, it will charge.

[0049] S33, during the low electricity price period t off-peak Set charging power Q c,t To satisfy:

[0050] Q c,t =min(Q w,max ,T max -L t ,(SOC max -SOC t )·Capacity)

[0051] Where T max Indicates the maximum capacity of the user's transformer, L t Indicates the real-time total load in period t, SOC t represents the state of charge of the energy storage charging and discharging system during time period t, and Capacity represents the energy storage capacity of the energy storage charging and discharging system. According to this formula, the energy storage charging and discharging system is charged as much as possible during the off-peak period, and the charging power is subject to the maximum capacity of the transformer, the upper limit of SOC and the real-time load;

[0052] S34, during the peak electricity price period t peak Set the discharge power Q d,t To satisfy:

[0053]

[0054] Where i represents the load index, P i,tis the power consumption of the i-th load in time period t. Through this formula, it is ensured that during the peak period, the power discharged by the energy storage system can help users reduce the maximum demand and alleviate the power burden during the peak period;

[0055] S34, generating a charging and discharging period plan according to the charging and discharging period and the corresponding charging and discharging power, the specific implementation method is as follows:

[0056] Divide a day into multiple time periods (e.g., one time period per hour), and determine the charging and discharging power for each time period based on the peak and valley electricity prices of the power grid and the predicted demand power; set the charging power during the valley period, set the discharging power during the peak period, and dynamically adjust the charging and discharging power according to the real-time load during the flat period;

[0057] Combined with electricity prices, demand forecast results and SOC upper and lower limits, a charge and discharge plan curve is generated and input into the dynamic charge and discharge control module for execution.

[0058] S4. During the charging and discharging time period, according to the maximum demand power and real-time monitoring data in the future period, combined with the goals of minimizing user electricity bills and optimizing the life of energy storage batteries, dynamically adjust the charging and discharging power of the energy storage charging and discharging system to meet the maximum charging and discharging power constraints, demand control constraints and SOC constraints;

[0059] In one embodiment, the maximum charge and discharge power constraint condition satisfies:

[0060] 0≤Q c,t ≤Q w,max

[0061] 0≤Q d,t ≤Q w,max

[0062] Among them, Q c,t and Q d,t are the charging power and discharging power in time period t, Q w,max is the maximum charging and discharging power of the energy storage charging and discharging system;

[0063] The demand control constraints are satisfied:

[0064]

[0065] Where i represents the load index, P i,t is the power consumption of the i-th load in time period t;

[0066] The SOC constraints are met:

[0067] SOC min ≤SOC t ≤SOC max

[0068] Among them, SOC min and SOC max They are the minimum and maximum state of charge limits of the energy storage charging and discharging system respectively.

[0069] S5. Dynamically adjust the SOC upper and lower limits of the energy storage charging and discharging system according to the operating status of the energy storage charging and discharging system and the health status of the battery;

[0070] In one embodiment, the formula for dynamically adjusting the SOC upper and lower limits according to the operating state of the energy storage charging and discharging system and the battery health status is:

[0071] SOC min,t =SOC nominal -k·DoD

[0072] SOC max,t =SOC nominal +k·Recovery

[0073] Among them, SOC min,t and SOC max,t They represent the minimum and maximum state of charge in time period t, respectively, k represents the dynamic adjustment coefficient, DoD represents the depth of discharge, and Recovery represents the battery recovery coefficient;

[0074] At the same time, battery temperature and aging factors can also be considered to dynamically adjust the SOC upper and lower limits to avoid excessive discharge or charging of the battery under high temperature or aging conditions.

[0075] S6. When the SOC reaches the set upper limit or the charge and discharge period ends, the current charge and discharge operation is terminated, and the energy storage charge and discharge system enters a standby state, waiting for the next charge and discharge cycle.

[0076] In one embodiment, during the non-demand control period, in response to the grid demand, auxiliary services are provided to the grid, including frequency regulation and peak load shifting. The specific formula for frequency regulation is:

[0077] Q d,t =min(Q w,max ,D f (f nominal -f t ))

[0078] Among them, Q d,t is the discharge power in time period t, Q w,max is the maximum charge and discharge power of the energy storage charging and discharging system, D f is the adjustment coefficient, f nominal is the rated frequency of the power grid, f t is the real-time grid frequency in period t.

[0079] like Figure 3As shown, the present invention also provides a user-side energy storage charging and discharging system based on maximum demand control, which is used to implement the above-mentioned user-side energy storage charging and discharging method based on maximum demand control, including:

[0080] Demand meter module, used to measure and record the maximum demand power G on the user side in real time t ;

[0081] Load meter module, used to measure and record the real-time power P of multiple loads on the user side in real time i,t ;

[0082] Energy storage meter module, used to monitor the charging power Q of the energy storage charging and discharging system in real time c,t , discharge power Q d,t and SOCSOC t , providing key data for SOC management and charge and discharge control. The demand meter module, load meter module and energy storage meter module transmit the monitored data to the central control system through the communication interface and store it in the database for subsequent prediction and analysis.

[0083] The demand forecasting module is used to predict the maximum demand power G in the future period based on historical power consumption data and real-time monitoring data using machine learning models such as LSTM and ARIMA pred,t , for subsequent charging and discharging period planning and power calculation.

[0084] The charging and discharging strategy formulation module is used to formulate the energy storage system charging and discharging plan based on the predicted maximum demand power, peak and valley electricity prices of the power grid, energy storage charging and discharging system and user electricity demand. Specifically:

[0085] Divide a day into different time periods (off-peak, peak and flat periods), and determine the charging and discharging priority of each period according to the changes in grid electricity prices;

[0086] Set the charging and discharging power for each period according to the following conditions: charge during the low electricity price period and set the maximum charging power Q c,t ; Discharge during peak electricity price period, set the maximum discharge power Q d,t ; Dynamically adjust the charging and discharging power according to the actual load during the flat electricity price period;

[0087] According to the real-time monitoring and prediction results, the charging and discharging power for each period is formulated:

[0088] Q c,t =min(Q w,max ,T max -L t ,(SOC max -SOC t )·Capacity)

[0089]

[0090] Dynamic charge and discharge control module, used to adjust the charge and discharge power of the energy storage charge and discharge system in real time during the charge and discharge process;

[0091] The SOC dynamic management module is used to dynamically adjust the SOC upper and lower limits according to power demand and battery health status.

[0092] It also includes a grid interaction module, which is used to respond to grid demand during non-demand control periods and provide auxiliary services to the grid, specifically frequency regulation and demand response functions, and automatically adjust the discharge power to maintain grid stability.

[0093] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A user-side energy storage charging and discharging method based on maximum demand control, characterized in that: The following steps are involved: Start the energy storage charging and discharging system, and monitor and record the user's electricity demand and the energy storage charging and discharging system parameters in real time through the demand meter, load meter and energy storage meter. The user's electricity demand includes the real-time power consumption of each load on the user side and the real-time maximum demand power on the user side. The energy storage charging and discharging system parameters include the charging power, discharging power and SOC of the energy storage charging and discharging system. Based on the user's historical power consumption data and real-time monitoring data, predict the maximum power demand in the future period; According to the predicted maximum demand power in the future period, the peak and valley electricity price of the power grid, the user's electricity demand and the parameters of the energy storage charging and discharging system, the charging and discharging period planning curve and the maximum charging and discharging power are set; During the charging and discharging time period, according to the maximum demand power and real-time monitoring data in the future period, combined with the goals of minimizing user electricity bills and optimizing the life of energy storage batteries, the charging and discharging power of the energy storage charging and discharging system is dynamically adjusted to meet the maximum charging and discharging power constraints, demand control constraints, and SOC constraints; Dynamically adjust the SOC upper and lower limits of the energy storage charging and discharging system according to the operating status of the energy storage charging and discharging system and the health status of the battery; When the SOC reaches the set upper limit or the charge and discharge period ends, the current charge and discharge operation is terminated, and the energy storage charge and discharge system enters the standby state, waiting for the next charge and discharge cycle.

2. A user-side energy storage charging and discharging method based on maximum demand control according to claim 1, characterized in that: The maximum demand power prediction for future periods uses the following formula: G pred,t =α·G hist,t +β·G real,t +g Among them, G pred,t represents the predicted maximum demand power in time period t, G hist,t represents the maximum demand power in historical period t, G real,t represents the real-time maximum demand power in the current period t, α, β and γ represent weight coefficients, which are determined according to the correlation between historical data and real-time data.

3. A user-side energy storage charging and discharging method based on maximum demand control according to claim 1, characterized in that: The steps of setting the charge and discharge period plan curve and the maximum charge and discharge power include: Get the predicted maximum demand power G for the future period pred,t , Grid peak and valley electricity price C t , the real-time power demand of each load on the user side P i,t And the maximum charging and discharging power Q of the energy storage charging and discharging system w,max And SOC upper and lower limits SOC min , SOC max ; According to the peak and valley electricity price of the power grid C t Divide the charging and discharging time periods, including the low electricity price period t off-peak Charging during peak electricity price period peak Discharge and flexibly adjust charging and discharging according to user power demand and real-time demand during off-peak hours; During the low electricity price period off-peak Set charging power Q c,t To satisfy: Q c,t =min(Q w,max ,T max -L t ,(SOC max -SOC t )·Capacity) Where T max Indicates the maximum capacity of the user's transformer, L t Indicates the real-time total load in period t, SOC t represents the state of charge of the energy storage charging and discharging system during time period t, and Capatity represents the energy storage capacity of the energy storage charging and discharging system; During peak electricity price period peak Set the discharge power Q d,t To satisfy: Where i represents the load index, P i,t is the power consumption of the i-th load in time period t; Generate a charging and discharging period plan based on the charging and discharging period and the corresponding charging and discharging power.

4. A user-side energy storage charging and discharging method based on maximum demand control according to claim 1, characterized in that: The maximum charge and discharge power constraints meet the following conditions: 0≤Q c,t ≤Q w,max 0≤Q d,t ≤Q w,max Among them, Q c,t and Q d,t are the charging power and discharging power in time period t, Q w,max is the maximum charging and discharging power of the energy storage charging and discharging system; The demand control constraints are satisfied: Where i represents the load index, P i,t is the power consumption of the i-th load in time period t; The SOC constraints are met: SOC min ≤SOC t ≤SOC max Among them, SOC t Indicates the state of charge of the energy storage charging and discharging system during time period t, SOC min and SOC max They are the minimum and maximum state of charge limits of the energy storage charging and discharging system respectively.

5. A user-side energy storage charging and discharging method based on maximum demand control according to claim 1, characterized in that: The formula for dynamically adjusting the SOC upper and lower limits according to the operating status of the energy storage charging and discharging system and the health status of the battery is: SOC min,t =SOC nominal -k·DoD SOC max,t =SOC nominal +k·Recovery Among them, SOC min,t and SOC max,t They represent the minimum and maximum state of charge in time period t respectively, k represents the dynamic adjustment coefficient, DoD represents the depth of discharge, and Recovery represents the battery recovery coefficient.

6. A user-side energy storage charging and discharging method based on maximum demand control according to claim 1, characterized in that: During the non-demand control period, the system responds to grid demand and provides auxiliary services for the grid, including frequency regulation and peak load shifting. The specific formula for frequency regulation is: Q d,t =min(Q w,max ,D f ·(f nominal -f t )) Among them, Q d,t is the discharge power in time period t, Q w,max is the maximum charge and discharge power of the energy storage charging and discharging system, D f is the adjustment coefficient, f nominal is the rated frequency of the power grid, f t is the real-time grid frequency in period t.

7. A user-side energy storage charging and discharging system based on maximum demand control, used to implement a user-side energy storage charging and discharging method based on maximum demand control according to any one of claims 1 to 6, characterized in that: include: Demand meter module, used to measure and record the maximum demand power on the user side in real time; Load meter module, used to measure and record the real-time power of multiple loads on the user side; Energy storage meter module, used to monitor the charging power, discharging power and SOC of the energy storage charging and discharging system in real time; The demand prediction module is used to predict the maximum demand power in the future period based on historical power consumption data and real-time monitoring data using machine learning algorithms; The charging and discharging strategy formulation module is used to formulate the energy storage system charging and discharging plan based on the predicted maximum demand power, peak and valley electricity prices of the power grid, the energy storage charging and discharging system, and the user's electricity demand; Dynamic charge and discharge control module, used to adjust the charge and discharge power of the energy storage charge and discharge system in real time during the charge and discharge process; The SOC dynamic management module is used to dynamically adjust the SOC upper and lower limits according to power demand and battery health status.

8. A user-side energy storage charging and discharging system based on maximum demand control according to claim 7, characterized in that: It also includes a power grid interaction module for responding to power grid demand during non-demand control periods and providing auxiliary services to the power grid.

9. A user-side energy storage charging and discharging system based on maximum demand control according to claim 8, characterized in that: The grid interaction module has frequency regulation and demand response functions, and automatically adjusts the discharge power to maintain grid stability.

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