New energy power generation and energy storage control system

Abstract

The invention relates to the technical field of energy storage control, in particular to a new energy power generation and energy storage control system. The energy storage unit is used for storing electric energy; the energy control unit is used for monitoring the state of the energy storage unit and providing battery equalization and over-charge and over-discharge prevention functions; the energy conversion unit converts the direct current output by the energy control unit into alternating current through a PWM (Pulse Width Modulation) method; the energy management unit is used for predicting energy production and consumption and optimizing energy storage and electric energy release strategies through a linear programming optimization algorithm. According to the design of the invention, direct current and alternating current in various energy forms such as solar energy and wind energy are integrated, and long-term stable operation of the battery pack is ensured by using an efficient battery equalization method and an over-charge and over-discharge prevention protection mechanism. In addition, direct current is converted into high-quality alternating current by adopting a PWM (Pulse Width Modulation) method, so that the system can be more effectively compatible with a power grid, and the energy utilization rate of the whole system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage control, and in particular to a new energy power generation energy storage control system. Background Art

[0002] The power generation of renewable energy sources such as solar energy and wind energy is affected by weather conditions and day-night changes, resulting in unstable output; power demand varies greatly with time and location, and traditional power generation methods are often difficult to adjust quickly to meet such changes. For example, during the day when the sun is strong, solar power generation is large, but this may not be the peak of power consumption; at night or on cloudy days, power generation decreases, but peak power consumption may occur; a large number of renewable energy sources connected to the power grid will lead to instability of the power grid, especially in extreme weather conditions or equipment failures, which may cause grid frequency and voltage fluctuations and affect power supply quality; because electricity prices fluctuate with supply and demand, the lack of effective energy storage means makes it impossible for power companies to store electricity during low-price periods and sell it during high-price periods, thus missing out on economic benefits. Therefore, a new energy generation and energy storage control system is designed. Summary of the invention

[0003] The purpose of the present invention is to provide a new energy power generation and energy storage control system to solve the problems of supply and demand imbalance, power grid impact and low economic benefits raised in the above background technology.

[0004] To achieve the above object, the present invention provides a new energy generation and energy storage control system, comprising

[0005] An energy storage unit, wherein the energy storage unit is used to store electrical energy;

[0006] An energy control unit, which is used to monitor the status of the energy storage unit and provide battery balancing, overcharge and over-discharge prevention functions;

[0007] An energy conversion unit, which converts the direct current output by the energy control unit into alternating current through a PWM pulse width modulation method;

[0008] The energy management unit is used to predict energy production and consumption and optimize the strategies of energy storage and release through a linear programming optimization algorithm.

[0009] As a further improvement of the technical solution, the electric energy of the energy storage unit includes:

[0010] Direct current and alternating current from solar and wind energy.

[0011] As a further improvement of the technical solution, the energy control unit includes a battery balancing module and an overcharge and discharge prevention module;

[0012] Among them, the battery balancing module is used to ensure that each single cell in the battery pack maintains a consistent charging state;

[0013] The overcharge and overdischarge prevention module is used to prevent overcharge and overdischarge by monitoring battery voltage and temperature.

[0014] As a further improvement of the technical solution, the battery balancing module includes the following steps:

[0015] S1.1, measure the voltage of each single cell, measure the voltage of each single cell, and monitor the temperature of the battery;

[0016] S1.2. Compare the data of each single cell with the average value, identify the unbalanced cells, and determine which cells need to be balanced based on the monitored data;

[0017] S1.3, transfer energy from high-voltage batteries to low-voltage batteries through the circuit, making the voltage of the entire battery pack more uniform;

[0018] S1.4. Continuously monitor the battery status during the entire charging and discharging process to ensure that the battery pack remains balanced.

[0019] As a further improvement of the technical solution, the overcharge and overdischarge prevention module comprises the following steps:

[0020] S2.1. Define the maximum allowable charging voltage Vmax of the battery and the minimum allowable discharge voltage Vmin of the battery; monitor the voltage and temperature in real time;

[0021] S2.2, when it is detected that the battery voltage reaches the preset maximum value Vmax, the control module will cut off the charging circuit and stop charging;

[0022] S2.3. When it is detected that the battery voltage drops to the preset minimum value Vmin, the control module will cut off the discharge circuit and stop discharging.

[0023] As a further improvement of the technical solution, the direct current is converted into alternating current, comprising the following steps:

[0024] S3.1. Connect the positive and negative electrodes of the battery pack to the DC input terminals of the inverter module. Before entering the inverter module, filter the DC power through a capacitor element.

[0025] S3.2, using the PWM pulse width modulation method to convert the DC voltage into a series of pulse voltages, and converting the pulse DC voltage into AC voltage through an inverter bridge;

[0026] S3.3. Use the pulse width modulation method to simulate the required AC waveform by changing the pulse width, and control the switching frequency and phase to generate AC power that meets the standard grid frequency.

[0027] As a further improvement of the technical solution, in S3.2, the PWM pulse width modulation method is specifically:

[0028] ;

[0029] in, Indicates duty cycle; Indicates the expected average output voltage; Indicates the peak voltage of the PWM signal, usually the power supply voltage.

[0030] As a further improvement of the technical solution, in S3.3, the required AC waveform is simulated by changing the pulse width, and the switching frequency and phase are controlled, including the following steps:

[0031] S3.31, determine that the desired AC waveform output by the inverter module is a sine wave, and use a fixed frequency triangle wave as a carrier signal;

[0032] S3.32, generating a low frequency modulation signal corresponding to the desired AC waveform output by the inverter module;

[0033] S3.33, compare the triangle wave with the sine wave. When the amplitude of the modulated signal is greater than the carrier signal, the output is high level; otherwise, the output is low level, forming a PWM waveform;

[0034] S3.34, control the output frequency and phase of the PWM inverter module to match the standard frequency and phase of the power grid.

[0035] As a further improvement of the technical solution, the strategy of predicting energy production and consumption, optimizing energy storage and releasing electric energy includes the following steps:

[0036] S4.1. Collect real-time data, including weather forecasts, market prices, the status of energy storage units, performance parameters of power generation equipment, and monitor changes in load demand, including electricity consumption patterns of households and industrial users;

[0037] S4.2. Use historical data and weather forecast information to predict solar and wind power generation;

[0038] S4.3. Predict future energy consumption based on historical electricity consumption patterns and current demand trends using a long short-term memory network (LSTM), taking into account the impact of seasonal and temporal factors on electricity consumption.

[0039] S4.4. Develop a cost-effectiveness model to evaluate the cost-effectiveness of different energy use strategies;

[0040] S4.5. Use linear programming optimization algorithms to develop the best strategy for storing and releasing electricity to balance supply and demand, ensuring charging when electricity prices are low and discharging when electricity prices are high;

[0041] S4.6. Adjust the charging and discharging plan of the energy storage unit according to the optimization results, and control the working state of the energy conversion unit, including switching the energy flow between the energy storage system and the power grid.

[0042] As a further improvement of the technical solution, in S4.5, a linear programming optimization algorithm is used to formulate an optimal strategy for storing and releasing electric energy, including the following steps:

[0043] S4.51. Set the goal to minimize total cost , including the cost of purchasing electricity from the grid and the income from selling electricity to the grid, the objective function is:

[0044] ;

[0045] in, is the total number of time steps in the time period; In time the cost of purchasing electricity from the grid; It's in time Revenue from the sale of electricity to the grid; It's in time Electricity purchased from the grid; It's in time electricity sold to the grid;

[0046] S4.52. Set decision variables, including time The charging and discharging power of the energy storage unit;

[0047] S4.53. Determine the constraints: including

[0048] Energy storage capacity limitations:

[0049] ;

[0050] in, time The energy storage state, is the maximum energy storage capacity of the energy storage unit;

[0051] Charge and discharge power limit:

[0052] ;

[0053] in, is the maximum discharge power of the energy storage unit, is the maximum charging power of the energy storage unit;

[0054] Conservation of Energy:

[0055] ;

[0056] ;

[0057] in, is the charging efficiency, is the discharge efficiency, is the time interval, time The charging and discharging power of the energy storage unit;

[0058] Initial and final energy storage states:

[0059] ;

[0060] ;

[0061] in, is the initial energy storage state, is the final energy storage state;

[0062] S4.54. Combine the above objective function and constraint conditions into a linear programming model and solve it, and control the actual charging and discharging operation of the energy storage unit according to the solution result.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1. In this new energy power generation and energy storage control system, by integrating direct current and alternating current in various energy forms such as solar energy and wind energy, and using efficient battery balancing methods and protection mechanisms to prevent overcharge and discharge, the long-term stable operation of the battery pack is ensured. In addition, by using the PWM pulse width modulation method to convert direct current into high-quality alternating current, it can be more effectively compatible with the power grid, thereby improving the energy utilization of the overall system. At the same time, due to the use of advanced energy management units to predict energy production and consumption, and the use of optimization algorithms to dynamically adjust the energy storage strategy, this further enhances the reliability and response speed of the system, ensuring optimal energy storage and release at different times and conditions.

[0065] 2. In this new energy generation and energy storage control system, through the linear programming optimization algorithm in the energy management unit, the system can predict the future energy supply and demand based on market prices, weather forecasts and other factors, and formulate the best energy storage and release strategy that can both meet user needs and reduce costs. This means that the system can store more energy when electricity prices are low and release it when electricity prices are high, thereby significantly reducing users' electricity bills. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is the overall flow chart of the present invention;

[0067] The meaning of each number in the figure is:

[0068] 1. Energy storage unit; 2. Energy control unit; 3. Energy conversion unit; 4. Energy management unit. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] Example

[0071] See also Figure 1 As shown, a new energy generation and energy storage control system is provided, including

[0072] The energy storage unit 1 is used to store electrical energy;

[0073] In this embodiment, the electric energy of the energy storage unit 1 includes:

[0074] Direct current and alternating current from solar and wind energy.

[0075] An energy control unit 2, the energy control unit 2 is used to monitor the state of the energy storage unit 1 and provide battery balancing, overcharge and over-discharge prevention functions;

[0076] The state of the energy storage unit 1 includes battery voltage, current, temperature, and state of charge SOC;

[0077] In this embodiment, the energy control unit 2 includes a battery balancing module and an overcharge and discharge prevention module;

[0078] Among them, the battery balancing module is used to ensure that each single cell in the battery pack maintains a consistent charging state;

[0079] Furthermore, the battery balancing module includes the following steps:

[0080] S1.1, measure the voltage of each single cell, measure the voltage of each single cell, and monitor the temperature of the battery;

[0081] S1.2. Compare the data of each single cell with the average value, identify the unbalanced cells, and determine which cells need to be balanced based on the monitored data;

[0082] S1.3, transfer energy from high-voltage batteries to low-voltage batteries through the circuit, making the voltage of the entire battery pack more uniform;

[0083] S1.4. Continuously monitor the battery status during the entire charging and discharging process to ensure that the battery pack remains balanced.

[0084] The overcharge and overdischarge prevention module is used to prevent overcharge and overdischarge by monitoring battery voltage and temperature.

[0085] Further, the overcharge and overdischarge prevention module includes the following steps:

[0086] S2.1. Define the maximum allowable charging voltage Vmax of the battery and the minimum allowable discharge voltage Vmin of the battery; monitor the voltage and temperature in real time;

[0087] S2.2, when it is detected that the battery voltage reaches the preset maximum value Vmax, the control module will cut off the charging circuit and stop charging. In some cases, if the battery voltage drops slightly after charging is terminated but is still higher than the upper limit of normal use, it may be necessary to wait for a while before resuming charging to avoid frequent switching;

[0088] Among them, the control module is used for voltage monitoring, temperature monitoring, charging control, discharging control, and realizing the logic of preventing overcharging and overdischarging;

[0089] S2.3. When it is detected that the battery voltage drops to the preset minimum value Vmin, the control module will cut off the discharge circuit and stop discharging. In some cases, it may take the approach of gradually reducing the load instead of immediately cutting off the power supply to avoid the inconvenience caused by sudden power failure.

[0090] The energy conversion unit 3 converts the direct current output by the energy control unit 2 into alternating current through a PWM pulse width modulation method;

[0091] In this embodiment, the direct current is converted into alternating current, including the following steps:

[0092] S3.1. Connect the positive and negative electrodes of the battery pack to the DC input terminals of the inverter module. Before entering the inverter module, filter the DC power through a capacitor element to remove voltage fluctuations and ensure the quality of the DC power input to the inverter.

[0093] Among them, the inverter module includes a DC input terminal, a filter circuit, an inverter bridge, a PWM modulator, and an output terminal;

[0094] S3.2, use the PWM pulse width modulation method to convert the DC voltage into a series of pulse voltages, that is, set the duty cycle of the PWM signal according to the required output voltage, and convert the pulse DC voltage into AC voltage through an inverter bridge (IGBT or MOSFET);

[0095] Among them, by adjusting the duty cycle of the PWM signal, the amplitude of the output voltage can be controlled very accurately. This is very important for matching different load requirements or grid standards. The PWM signal has a fixed frequency, which makes it easy to design filters to suppress electromagnetic interference. Compared with continuously changing analog signals, fixed-frequency PWM signals are more likely to filter out unwanted high-frequency components. The PWM method allows for rapid adjustment of the output voltage, which is essential for dealing with transient changes in the grid, such as being able to respond quickly when the load suddenly increases or decreases. The specific PWM pulse width modulation method is:

[0096] ;

[0097] in, Represents the duty cycle, that is, the ratio of the duration of the high level to the entire cycle time, ranging from 0 to 1; Indicates the expected average output voltage; Indicates the peak voltage of the PWM signal, usually the power supply voltage.

[0098] S3.3. Use the pulse width modulation method to simulate the required AC waveform by changing the pulse width, and control the switching frequency and phase to generate AC power that meets the standard grid frequency (50Hz or 60Hz).

[0099] The desired AC waveform is simulated by varying the pulse width, as well as controlling the switching frequency and phase, including the following steps:

[0100] S3.31, determine that the desired AC waveform output by the inverter module is a sine wave, and use a triangular wave with a fixed frequency as a carrier signal;

[0101] S3.32, generating a low frequency modulation signal corresponding to the desired AC waveform output by the inverter module. If the goal is to generate a 50 Hz or 60 Hz sine wave, the signal will be a sine wave of the corresponding frequency;

[0102] S3.33, compare the triangle wave (carrier signal) with the sine wave (modulation signal). When the amplitude of the modulation signal is greater than the carrier signal, the output is high level; otherwise, the output is low level, forming a PWM waveform;

[0103] S3.34, control the output frequency and phase of the PWM inverter module to match the standard frequency and phase of the power grid.

[0104] The energy management unit 4 is used to predict energy production and consumption and optimize the strategies of energy storage and release through linear programming optimization algorithm;

[0105] In this embodiment, predicting energy production and consumption and optimizing strategies for storing and releasing electric energy include the following steps:

[0106] S4.1. Collect real-time data, including weather forecasts, market prices, the status of energy storage units, performance parameters of power generation equipment, and monitor changes in load demand, including electricity consumption patterns of households and industrial users;

[0107] S4.2. Use historical data and weather forecast information to predict solar and wind power generation;

[0108] S4.3. Predict future energy consumption based on historical electricity consumption patterns and current demand trends using a long short-term memory network (LSTM), taking into account the impact of seasonal and temporal factors on electricity consumption.

[0109] Among them, the long short-term memory network LSTM controls the state of the memory unit by introducing a specific memory unit and three gating mechanisms (input gate, forget gate, output gate), so as to capture long-term dependencies in the sequence;

[0110] S4.4. Develop a cost-effectiveness model to evaluate the cost-effectiveness of different energy use strategies;

[0111] Among them, the cost-effectiveness model includes cost function, revenue function, and net benefit function;

[0112] Furthermore, the cost function It includes the cost of purchasing electricity from the grid, the maintenance cost of the energy storage system and other related costs, specifically:

[0113] ;

[0114] In the formula, is the total number of time steps in the time period; In time the cost of purchasing electricity from the grid; It's in time Electricity purchased from the grid;

[0115] Revenue Function Includes revenue from selling electricity to the grid, specifically:

[0116] ;

[0117] In the formula, It's in time Revenue from the sale of electricity to the grid; It's in time electricity sold to the grid;

[0118] Net benefit function It is the result of subtracting the cost function from the benefit function, which represents the net benefit after considering all costs and benefits, specifically:

[0119] .

[0120] S4.5. Use linear programming optimization algorithms to develop the best strategy for storing and releasing electricity to balance supply and demand, ensuring charging when electricity prices are low and discharging when electricity prices are high;

[0121] Among them, linear programming can provide a deterministic solution, which is very important for power systems because power systems require highly reliable and predictable operation plans; when the linear programming problem meets certain conditions, it can find the global optimal solution instead of the local optimal solution. This means that under given constraints, the best energy storage and release strategy can be achieved; for many energy management and scheduling problems, linear programming provides an intuitive way to express objective functions and constraints, making the problem easy to model and solve; using linear programming optimization algorithms to formulate the best strategy for storing and releasing electric energy includes the following steps:

[0122] S4.51. Set the goal to minimize total cost , including the cost of purchasing electricity from the grid and the income from selling electricity to the grid, the objective function is:

[0123] ;

[0124] in, is the total number of time steps in the time period; In time the cost of purchasing electricity from the grid; It's in time Revenue from the sale of electricity to the grid; It's in time Electricity purchased from the grid; It's in time electricity sold to the grid;

[0125] S4.52. Set decision variables, including time The charging and discharging power of energy storage unit 1;

[0126] S4.53. Determine the constraints: including

[0127] Energy storage capacity limitations:

[0128] ;

[0129] in, time The energy storage state, is the maximum energy storage capacity of energy storage unit 1;

[0130] Charge and discharge power limit:

[0131] ;

[0132] in, is the maximum discharge power of energy storage unit 1, is the maximum charging power of energy storage unit 1;

[0133] Conservation of Energy:

[0134] ; (while charging)

[0135] ; (during discharge)

[0136] in, is the charging efficiency, is the discharge efficiency, is the time interval, time The charging and discharging power of energy storage unit 1;

[0137] Initial and final energy storage states:

[0138] ;

[0139] ;

[0140] in, is the initial energy storage state, is the final energy storage state;

[0141] S4.54. Combine the above objective function and constraint conditions into a linear programming model and solve it, and control the actual charging and discharging operation of the energy storage unit according to the solution result.

[0142] S4.6. Adjust the charging and discharging plan of the energy storage unit according to the optimization result, and control the working state of the energy conversion unit 3, including switching the energy flow between the energy storage system and the power grid.

[0143] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only preferred examples of the present invention, and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A new energy power generation and energy storage control system, characterized in that: include An energy storage unit (1), the energy storage unit (1) being used to store electrical energy; An energy control unit (2), the energy control unit (2) being used to monitor the state of the energy storage unit (1) and provide battery balancing, overcharge prevention and over-discharge prevention functions; An energy conversion unit (3), wherein the energy conversion unit (3) converts the direct current output by the energy control unit (2) into alternating current through a PWM pulse width modulation method; An energy management unit (4) is used to predict energy production and consumption and optimize energy storage and energy release strategies through a linear programming optimization algorithm.

2. The new energy power generation and energy storage control system according to claim 1 is characterized in that: The electric energy of the energy storage unit (1) comprises: Direct current and alternating current from solar and wind energy.

3. The new energy power generation and energy storage control system according to claim 1 is characterized in that: The energy control unit (2) comprises a battery balancing module and an overcharge and overdischarge prevention module; Among them, the battery balancing module is used to ensure that each single cell in the battery pack maintains a consistent charging state; The overcharge and overdischarge prevention module is used to prevent overcharge and overdischarge by monitoring battery voltage and temperature.

4. The new energy power generation and energy storage control system according to claim 3 is characterized in that: The battery balancing module comprises the following steps: S1.1, measure the voltage of each single cell, measure the voltage of each single cell, and monitor the temperature of the battery; S1.

2. Compare the data of each single cell with the average value, identify the unbalanced cells, and determine which cells need to be balanced based on the monitored data; S1.3, transfer energy from high-voltage batteries to low-voltage batteries through the circuit, making the voltage of the entire battery pack more uniform; S1.

4. Continuously monitor the battery status during the entire charging and discharging process to ensure that the battery pack remains balanced.

5. The new energy power generation and energy storage control system according to claim 3 is characterized in that: The overcharge and overdischarge prevention module comprises the following steps: S2.

1. Define the maximum allowable charging voltage Vmax of the battery and the minimum allowable discharge voltage Vmin of the battery; monitor the voltage and temperature in real time; S2.2, when it is detected that the battery voltage reaches the preset maximum value Vmax, the control module will cut off the charging circuit and stop charging; S2.

3. When it is detected that the battery voltage drops to the preset minimum value Vmin, the control module will cut off the discharge circuit and stop discharging.

6. The new energy power generation and energy storage control system according to claim 1 is characterized in that: The direct current is converted into alternating current, comprising the following steps: S3.

1. Connect the positive and negative electrodes of the battery pack to the DC input terminals of the inverter module. Before entering the inverter module, filter the DC power through a capacitor element. S3.2, using the PWM pulse width modulation method to convert the DC voltage into a series of pulse voltages, and converting the pulse DC voltage into AC voltage through an inverter bridge; S3.

3. Use the pulse width modulation method to simulate the required AC waveform by changing the pulse width, and control the switching frequency and phase to generate AC power that meets the standard grid frequency.

7. The new energy power generation and energy storage control system according to claim 6 is characterized in that: In S3.2, the PWM pulse width modulation method is specifically: ； in, Indicates duty cycle; Indicates the expected average output voltage; Indicates the peak voltage of the PWM signal, usually the power supply voltage.

8. The new energy power generation and energy storage control system according to claim 1 is characterized in that: In S3.3, the desired AC waveform is simulated by changing the pulse width, and the switching frequency and phase are controlled, including the following steps: S3.31, determine that the desired AC waveform output by the inverter module is a sine wave, and use a triangular wave with a fixed frequency as a carrier signal; S3.32, generating a low frequency modulation signal corresponding to the desired AC waveform output by the inverter module; S3.33, compare the triangle wave with the sine wave. When the amplitude of the modulated signal is greater than the carrier signal, the output is high level; otherwise, the output is low level, forming a PWM waveform; S3.34, control the output frequency and phase of the PWM inverter module to match the standard frequency and phase of the power grid.

9. The new energy power generation and energy storage control system according to claim 1, characterized in that: The strategy for predicting energy production and consumption, optimizing energy storage and releasing electric energy includes the following steps: S4.

1. Collect real-time data, including weather forecasts, market prices, the status of energy storage units, performance parameters of power generation equipment, and monitor changes in load demand, including electricity consumption patterns of households and industrial users; S4.

2. Use historical data and weather forecast information to predict solar and wind power generation; S4.

3. Predict future energy consumption based on historical electricity consumption patterns and current demand trends using a long short-term memory network (LSTM), taking into account the impact of seasonal and temporal factors on electricity consumption. S4.

4. Develop a cost-effectiveness model to evaluate the cost-effectiveness of different energy use strategies; S4.

5. Use linear programming optimization algorithms to develop the best strategy for storing and releasing electricity to balance supply and demand, ensuring charging when electricity prices are low and discharging when electricity prices are high; S4.

6. Adjust the charging and discharging plan of the energy storage unit according to the optimization result, and control the working state of the energy conversion unit (3), including switching the energy flow between the energy storage system and the power grid.

10. The new energy power generation and energy storage control system according to claim 9, characterized in that: In S4.5, a linear programming optimization algorithm is used to formulate an optimal strategy for storing and releasing electric energy, including the following steps: S5.

51. Set the goal to minimize total cost , including the cost of purchasing electricity from the grid and the income from selling electricity to the grid, the objective function is: ； in, is the total number of time steps in the time period; In time the cost of purchasing electricity from the grid; It's in time Revenue from the sale of electricity to the grid; It's in time Electricity purchased from the grid; It's in time electricity sold to the grid; S5.

52. Set decision variables, including time the charging and discharging power of the energy storage unit (1); S5.

53. Determine the constraints: including Energy storage capacity limitations: ； in, time The energy storage state, is the maximum energy storage capacity of the energy storage unit (1); Charge and discharge power limit: ； in, is the maximum discharge power of the energy storage unit (1), is the maximum charging power of the energy storage unit (1); Conservation of Energy: ； ； in, is the charging efficiency, is the discharge efficiency, is the time interval, time the charging and discharging power of the energy storage unit (1); Initial and final energy storage states: ； ； in, is the initial energy storage state, is the final energy storage state; S5.

54. Combine the above objective function and constraint conditions into a linear programming model and solve it, and control the actual charging and discharging operation of the energy storage unit according to the solution result.

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