Intelligent charging and discharging control method and system based on real-time electricity price mechanism

Abstract

The invention discloses an intelligent charging and discharging control method and system based on a real-time electricity price mechanism. The method comprises the steps that the daily electricity consumption peak-valley difference is obtained through calculation of peak electricity consumption data and valley electricity consumption data; calculating the number of energy storage cabinets connected to a power grid in the energy storage system according to the daily electricity peak-valley difference and the energy storage capacity of the energy storage cabinets, and recording the number as grid-connected data of the energy storage cabinets; automatically adjusting a charging and discharging power threshold according to the time-of-use electricity price and the electricity reference power; the load power is compared with a charging and discharging power threshold value, and the charging and discharging states of the energy storage system are switched; when the energy storage system is in the discharge state, calculating the discharge power of the energy storage system according to the load power and the rated power of the energy storage system; when the energy storage system needs to be charged, the charging power of the energy storage system is calculated according to the load power, the smooth power of the power grid and the rated power of the energy storage system; the charging and discharging plan is adaptively adjusted according to the time-of-use electricity price, the peak-valley arbitrage income is increased, power fluctuation is restrained, and harmonic pollution is avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of battery management, and particularly relates to an industrial and commercial energy storage system and a control method. BACKGROUND

[0002] An energy management system (EMS) in an energy storage system can be used in an energy storage power station for the purpose of assisting a power grid. When energy is in excess, the energy storage device is used to store energy, and when energy is needed, the energy storage device is used to release energy.

[0003] The main income mode of the current energy storage system is peak-valley arbitrage, that is, charging at a low price during the low electricity consumption valley and discharging to supply users during the high electricity consumption peak. Through preset charging and discharging plans in the EMS, the energy storage system charges according to the plan in the charging period and discharges according to the plan in the discharging period. However, in the electricity market transaction environment, the electricity price is dynamically changing, and the electricity demand of users is also dynamically changing. If the energy storage system still operates according to the preset charging and discharging plan, the inability to adapt to the dynamic electricity price fluctuation and load change will result in economic loss, and the lack of power smoothing control in the charging and discharging process will cause power fluctuation of the power grid. SUMMARY

[0004] The application provides an intelligent charging and discharging control method and system based on a real-time electricity price mechanism, which adaptively adjusts the charging and discharging plan to increase the peak-valley arbitrage income, and simultaneously suppresses power fluctuation to avoid harmonic pollution.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the application is as follows:

[0006] The application provides an intelligent charging and discharging control method based on a real-time electricity price mechanism, which includes the following steps:

[0007] Historical load data is obtained and drawn into a historical daily electricity consumption curve, the daily electricity consumption curve is used to determine a reference power, peak electricity consumption data and valley electricity consumption data, the peak electricity consumption data and the valley electricity consumption data are used to calculate a daily electricity consumption peak-valley difference, the daily electricity consumption peak-valley difference and the energy storage capacity of an energy storage cabinet are used to calculate grid-connected data of the energy storage cabinet, and the grid-connected data is used to adjust the number of energy storage cabinets connected to the power grid in the energy storage system;

[0008] The charging and discharging power threshold is automatically adjusted according to the time-of-use electricity price and the reference power, and the charging and discharging state of the energy storage system is switched by comparing the load power with the charging and discharging power threshold;

[0009] When the energy storage system is in the discharging state, the discharging power of the energy storage system is calculated according to the load power and the rated power of the energy storage system;

[0010] When the energy storage system needs to be charged, the charging power of the energy storage system is calculated based on the load power, the grid smoothing power, and the rated power of the energy storage system.

[0011] This invention provides precise quantitative configuration of energy storage cabinets, fundamentally avoiding the problems of redundant or insufficient capacity of energy storage equipment, and ensuring that the system scale and load characteristics are matched. The calculation of charging and discharging power fully considers load demand, rated energy storage capacity and grid smoothing constraints: effectively suppressing the impact of centralized charging on distribution transformers, reducing harmonic pollution and voltage fluctuations, significantly improving power quality and grid compatibility, and alleviating the expansion pressure on distribution transformer areas.

[0012] Furthermore, the daily peak-to-valley difference in electricity consumption is calculated using peak and off-peak electricity consumption data; the number of energy storage cabinets in the energy storage system is then calculated using the daily peak-to-valley difference and the energy storage capacity of the energy storage cabinets, specifically including:

[0013]

[0014]

[0015] In the formula, This refers to the peak-valley difference in daily electricity consumption. This refers to the peak power consumption in the peak power consumption data. This refers to the peak electricity consumption time in the peak electricity consumption data; This refers to the off-peak electricity consumption data. This refers to the off-peak electricity consumption time in the off-peak electricity consumption data; The number of energy storage cabinets connected to the power grid within the energy storage system is denoted as the grid connection data of the energy storage cabinets; The energy storage capacity of the energy storage cabinet; The attenuation coefficient; The energy conversion efficiency of the energy storage cabinet.

[0016] This invention calculates the number of energy storage cabinets in an energy storage system based on the peak-valley difference in daily electricity consumption and the energy storage capacity of the energy storage cabinets, thereby achieving precise quantitative configuration of energy storage cabinets. This fundamentally avoids the problems of redundancy or insufficient capacity of energy storage equipment and ensures that the system scale and load characteristics are matched.

[0017] Furthermore, the charging and discharging power thresholds are automatically adjusted based on time-of-use pricing and baseline power consumption, specifically including:

[0018]

[0019] In the formula, The charging and discharging power threshold; This is the reference power for electricity consumption. The average daily electricity price; This is the maximum daily electricity price. This is the minimum daily electricity price. This refers to the current actual electricity price; This is the sensitivity coefficient.

[0020] This invention proactively lowers the charging threshold during off-peak hours when grid pricing is low, making it easier for the system to trigger charging to absorb low-priced electricity; it raises the discharging threshold during peak hours to ensure the system releases stored energy more actively to reduce the need to purchase electricity at high prices; and it introduces a benchmark power consumption as an adjustment anchor point to strongly couple threshold changes with the user's own load characteristics, which avoids overcharging and discharging that may be caused by a single electricity price orientation, and can accurately capture fluctuation space while ensuring basic electricity demand.

[0021] Furthermore, by comparing the load power with the charge / discharge power threshold, the charging / discharge state of the energy storage system is switched, specifically including:

[0022] Response to load power Greater than the charge / discharge power threshold When necessary, the energy storage system will be switched to discharge mode;

[0023] Response to load power Less than the charge / discharge power threshold When necessary, the energy storage system will be switched to charging mode.

[0024] This invention uses real-time comparison between the charging and discharging power threshold and the actual load power to make the system state switching logic simple and efficient. This not only shortens the decision delay but also avoids the uncertainty risks brought about by complex prediction models, thereby improving the robustness and response speed of the control.

[0025] Furthermore, the discharge power of the energy storage system is calculated based on the load power and the rated power of the energy storage system, specifically including:

[0026]

[0027] In the formula, This refers to the discharge power of the energy storage system. For load power; This refers to the rated power of the energy storage system.

[0028] This invention sets a discharge limit based on rated power, fundamentally avoiding safety risks such as battery over-discharge, inverter overload, and thermal runaway, significantly improving the inherent safety of system operation and the long-term reliability of equipment. Secondly, by dynamically adjusting the discharge intensity in real-time to match load power, it achieves an intelligent on-demand energy supply mode, preventing energy waste and controlling the depth of discharge within the optimal range, effectively delaying battery capacity degradation and extending the life-cycle value of the energy storage system.

[0029] Furthermore, the charging power of the energy storage system is calculated based on the load power, grid smoothing power, and rated power of the energy storage system, specifically including:

[0030]

[0031] In the formula, The charging power for the energy storage system, For load power; The rated power of the energy storage system, To smooth power for the power grid.

[0032] This invention uses grid smoothing power as the core boundary condition, which can effectively suppress the instantaneous impact of centralized charging on the distribution network, avoid problems such as transformer reverse overload, voltage harmonic distortion, and three-phase imbalance, significantly improve power quality and grid compatibility, and reduce the pressure of distribution network expansion. Using the rated power of the energy storage system as the upper limit constraint can prevent battery overcharging, charging module overheating, and DC bus voltage exceeding limits, ensuring that the equipment operates under safe and reliable conditions.

[0033] Furthermore, the charging and discharging power of a single energy storage cabinet is determined based on the discharge power and charging power of the energy storage system; in response to the energy storage cabinet's charging and discharging power exceeding K times the rated power of the energy storage cabinet's converter, and the duration reaching the time threshold T, the corresponding energy storage cabinet is triggered to stop urgently.

[0034] This invention employs a strategy of K times rated power plus delay to intelligently identify continuous overload, and enables independent emergency stop of a single cabinet to achieve precise fault isolation, maximizing short-term support capability while ensuring safety.

[0035] Furthermore, when the grid connection voltage of the energy storage cabinet exceeds the set voltage safety range, the grid connection of the energy storage cabinet is disconnected; the voltage safety range is 380V (1-10%) to 380V (1+10%).

[0036] By setting a safe voltage range, the risk of overvoltage breakdown of power electronic devices, accelerated insulation aging, and capacitor explosion can be effectively prevented, significantly improving the intrinsic safety and cycle life of equipment. At the same time, it can prevent abnormal voltage from flowing back into the common connection point, avoiding harmonic interference and voltage fluctuations to sensitive loads and the upstream distribution network, maintaining power quality and meeting grid connection compliance requirements.

[0037] Furthermore, the system receives fault codes uploaded by the energy storage cabinet; determines the fault level of the energy storage cabinet based on the fault codes; when a level one fault occurs in the energy storage cabinet, it controls the corresponding energy storage cabinet to stop immediately; and evenly distributes the discharge power and charging power of the energy storage system to the remaining energy storage cabinets.

[0038] This invention enables a single energy storage cabinet to quickly cut off risks such as electric arcs and short circuits during emergency shutdown, preventing the spread of faults and significantly reducing the probability of equipment damage and safety accidents. It also distributes the discharge and charging power of the energy storage system evenly to the remaining energy storage cabinets, shortening fault repair time and optimizing the flexibility of asset reuse and expansion.

[0039] A second aspect of the present invention provides an intelligent charging and discharging control system based on a real-time electricity price mechanism, comprising:

[0040] The data acquisition unit acquires historical load data and plots it as a historical daily electricity consumption curve. Based on the historical daily electricity consumption curve, it determines the baseline power consumption, peak electricity consumption data, and off-peak electricity consumption data.

[0041] The decision-making unit is used to calculate the daily peak-valley difference in electricity consumption based on peak and off-peak electricity consumption data; to calculate the grid connection data of the energy storage cabinets based on the daily peak-valley difference in electricity consumption and the energy storage capacity of the energy storage cabinets; to adjust the number of energy storage cabinets connected to the grid within the energy storage system based on the grid connection data; to automatically adjust the charging and discharging power thresholds based on time-of-use electricity prices and the benchmark power consumption; and to switch the charging and discharging state of the energy storage system by comparing the load power with the charging and discharging power thresholds.

[0042] The execution unit calculates the discharge power of the energy storage system based on the load power and the rated power of the energy storage system when the energy storage system is in a discharge state; and calculates the charging power of the energy storage system based on the load power, the grid smoothing power, and the rated power of the energy storage system when the energy storage system needs to be charged.

[0043] In the discharge phase, the invention releases power on demand, avoiding ineffective venting or power shortage; in the charging phase, the grid smoothing power is introduced as a boundary condition, which effectively suppresses the impact of centralized charging on distribution transformers, reduces harmonic pollution and voltage fluctuations, significantly improves power quality and grid compatibility, and alleviates the expansion pressure on distribution transformer areas.

[0044] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the intelligent charging and discharging control method as described in the first aspect.

[0045] A fourth aspect of the present invention provides an electronic device, including a storage medium and a processor; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the intelligent charge and discharge control method described in the first aspect.

[0046] The fifth aspect of the present invention provides a computer program product, including instructions that, when executed by a processor, cause the processor to perform the intelligent charge and discharge control method described in the first aspect.

[0047] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0048] This invention acquires historical load data and plots it as a historical daily electricity consumption curve. Based on the historical daily electricity consumption curve, it determines the baseline power consumption, peak electricity consumption data, and off-peak electricity consumption data. The peak-to-valley difference of daily electricity consumption is calculated using the peak-to-valley difference and the energy storage capacity of the energy storage cabinet. The grid connection data of the energy storage cabinet is calculated based on the grid connection data. The number of energy storage cabinets connected to the grid within the energy storage system is adjusted according to the grid connection data, realizing precise quantitative configuration of energy storage cabinets. This fundamentally avoids the problem of redundancy or insufficient capacity of energy storage equipment and ensures that the system scale and load characteristics are matched.

[0049] This invention automatically adjusts the charging and discharging power thresholds based on time-of-use electricity prices and benchmark power consumption; it switches the charging and discharging states of the energy storage system by comparing the load power with the charging and discharging power thresholds; the strategy deeply integrates time-of-use electricity price signals, enabling the charging and discharging thresholds to have adaptive adjustment capabilities and automatically capture opportunities arising from electricity price fluctuations; through real-time comparison with actual load power, the system state switching logic is simple and efficient, shortening decision delays and avoiding the uncertainty risks brought about by complex prediction models, thereby improving the robustness and response speed of control.

[0050] When the energy storage system is in a discharging state, this invention calculates the discharge power of the energy storage system based on the load power and the rated power of the energy storage system; when the energy storage system needs to be charged, the charging power of the energy storage system is calculated based on the load power, the grid smoothing power, and the rated power of the energy storage system. The calculation of charging and discharging power fully considers the load demand, the rated capacity of the energy storage system, and the grid smoothing constraints: during the discharge phase, the energy is released on demand to avoid ineffective discharge or power shortage; during the charging phase, the grid smoothing power is introduced as a boundary condition, which effectively suppresses the impact of centralized charging on the distribution transformer, reduces harmonic pollution and voltage fluctuations, significantly improves power quality and grid compatibility, and alleviates the expansion pressure on distribution transformer areas. Attached Figure Description

[0051] Figure 1 This is a structural diagram of the energy storage system described in Embodiment 1 of the present invention;

[0052] Figure 2 The flowchart is for the intelligent charging and discharging control method provided in Embodiment 1 of the present invention. Detailed Implementation

[0053] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0054] Example 1

[0055] like Figure 2As shown, this embodiment provides an intelligent charging and discharging control method based on a real-time electricity price mechanism. This intelligent charging and discharging control method is applied to an energy storage system, such as... Figure 1 As shown, the energy storage system includes an energy management system (EMS) and a set number of energy storage cabinets; the energy storage cabinets upload working data to the energy management system (EMS) in real time via the Modbus TC serial port protocol; the smart meters at the grid connection point monitor the grid output power in real time, and the energy management system (EMS) communicates with the smart meters at the grid connection point via an IEC 104.

[0056] The intelligent charging and discharging control method based on the real-time electricity price mechanism specifically includes:

[0057] Historical load data is acquired and plotted as a historical daily electricity consumption curve. Based on the historical daily electricity consumption curve, the benchmark power, peak electricity consumption data, and off-peak electricity consumption data are determined. The peak-to-valley difference of daily electricity consumption is calculated using the peak and off-peak electricity consumption data.

[0058] The number of energy storage cabinets connected to the grid within the energy storage system is calculated based on the daily peak-to-valley difference in electricity consumption and the energy storage capacity of the energy storage cabinets; specifically including:

[0059]

[0060]

[0061] In the formula, This refers to the peak-valley difference in daily electricity consumption. This refers to the peak power consumption in the peak power consumption data. This refers to the peak electricity consumption time in the peak electricity consumption data; This refers to the off-peak electricity consumption data. This refers to the off-peak electricity consumption time in the off-peak electricity consumption data; This refers to the number of energy storage cabinets connected to the power grid within the energy storage system. The energy storage capacity of the energy storage cabinet; The attenuation coefficient; The energy conversion efficiency of the energy storage cabinet.

[0062] This embodiment calculates the number of energy storage cabinets in the energy storage system based on the peak-valley difference in daily electricity consumption and the energy storage capacity of the energy storage cabinets, thereby achieving precise quantitative configuration of energy storage cabinets. This fundamentally avoids the problems of redundancy or insufficient capacity of energy storage equipment and ensures that the system scale and load characteristics are matched.

[0063] The charging and discharging power thresholds are automatically adjusted based on time-of-use pricing and baseline power consumption, specifically including:

[0064]

[0065] In the formula, The charging and discharging power threshold; This is the reference power for electricity consumption. The average daily electricity price; This is the maximum daily electricity price. This is the minimum daily electricity price. This refers to the current actual electricity price; This is the sensitivity coefficient.

[0066] In this embodiment, the charging threshold is proactively lowered during off-peak hours when grid pricing is low, making it easier for the system to trigger charging to absorb low-priced electricity. During peak hours when electricity prices are high, the discharging threshold is raised to ensure that the system releases energy storage more actively to reduce the need to purchase electricity at high prices. The reference power of electricity consumption is introduced as an adjustment anchor point, so that the threshold change is strongly coupled with the user's own load characteristics. This avoids overcharging and discharging that may be caused by a single electricity price orientation, and can accurately capture the fluctuation space while ensuring basic electricity demand.

[0067] The charging and discharging states of the energy storage system are switched by comparing the load power with the charging and discharging power thresholds, specifically including:

[0068] Response to load power Greater than the charge / discharge power threshold When necessary, the energy storage system will be switched to discharge mode;

[0069] Response to load power Less than the charge / discharge power threshold When necessary, the energy storage system will be switched to charging mode.

[0070] When the energy storage system is in a discharging state, the discharge power of the energy storage system is calculated based on the load power and the rated power of the energy storage system, specifically including:

[0071]

[0072] In the formula, This refers to the discharge power of the energy storage system. For load power; This refers to the rated power of the energy storage system.

[0073] This embodiment sets the upper limit of discharge based on the rated power, fundamentally avoiding safety risks such as battery over-discharge, inverter overload, and thermal runaway, significantly improving the inherent safety of system operation and the long-term reliability of equipment. Secondly, by dynamically adjusting the discharge intensity in real time to match the load power, an intelligent on-demand energy supply mode is achieved. This prevents energy waste and controls the depth of discharge within the optimal range, effectively delaying battery capacity decay and extending the life-cycle value of the energy storage system.

[0074] When the energy storage system needs charging, the charging power of the energy storage system is calculated based on the load power, the grid smoothing power, and the rated power of the energy storage system, specifically including:

[0075]

[0076] In the formula, The charging power for the energy storage system, For load power; The rated power of the energy storage system, To smooth the power grid, in this embodiment, the smoothed power grid power is set to 0.7 times the transformer capacity. .

[0077] This embodiment uses grid smoothing power as the core boundary condition, which can effectively suppress the instantaneous impact of centralized charging on the distribution network, avoid problems such as transformer reverse overload, voltage harmonic distortion, and three-phase imbalance, significantly improve power quality and grid compatibility, and reduce the pressure of distribution network expansion. Using the rated power of the energy storage system as the upper limit constraint can prevent battery overcharging, charging module overheating, and DC bus voltage exceeding the limit, ensuring that the equipment operates under safe and reliable conditions.

[0078] The charging and discharging power of a single energy storage cabinet is determined based on the discharge and charging power of the energy storage system. In response to the energy storage cabinet's charging and discharging power exceeding K times the rated power of the energy storage cabinet's converter, and the duration reaching a time threshold T, an emergency stop is triggered for the corresponding energy storage cabinet. In this embodiment, K=1.1; T=500ms. When the grid-connected voltage of the energy storage cabinet exceeds the set voltage safety range, the grid connection of the energy storage cabinet is disconnected. The voltage safety range is 380V(1-10%) to 380V(1+10%).

[0079] This embodiment employs a K-times rated power plus delay strategy to intelligently identify continuous overloads, and enables precise fault isolation through independent emergency stop for each cabinet, maximizing short-term support capacity while ensuring safety. By setting a safe voltage range, it effectively prevents the risks of overvoltage breakdown of power electronic devices, accelerated insulation aging, and capacitor explosion, significantly improving the intrinsic safety and cycle life of the equipment. At the same time, it can prevent abnormal voltage backflow into the common connection point, avoiding harmonic interference and voltage fluctuations to sensitive loads and the upstream distribution network, maintaining power quality and meeting grid connection compliance requirements.

[0080] Receive the fault code uploaded by the energy storage cabinet; determine the fault level of the energy storage cabinet based on the fault code; when the energy storage cabinet has a level one fault, control the corresponding energy storage cabinet to stop immediately; and evenly distribute the discharge power and charging power of the energy storage system to the remaining energy storage cabinets.

[0081] This invention enables a single energy storage cabinet to quickly cut off risks such as electric arcs and short circuits during emergency shutdown, preventing the spread of faults and significantly reducing the probability of equipment damage and safety accidents. It also distributes the discharge and charging power of the energy storage system evenly to the remaining energy storage cabinets, shortening fault repair time and optimizing the flexibility of asset reuse and expansion.

[0082] Example 2

[0083] This embodiment provides an intelligent charging and discharging control system based on a real-time electricity price mechanism. The intelligent charging and discharging control system is used to execute the intelligent charging and discharging control method described in Embodiment 1. The intelligent charging and discharging control system includes:

[0084] The data acquisition unit acquires historical load data and plots it as a historical daily electricity consumption curve. Based on the historical daily electricity consumption curve, it determines the baseline power consumption, peak electricity consumption data, and off-peak electricity consumption data.

[0085] The decision-making unit is used to calculate the daily peak-valley difference in electricity consumption based on peak and off-peak electricity consumption data; to calculate the grid connection data of the energy storage cabinets based on the daily peak-valley difference in electricity consumption and the energy storage capacity of the energy storage cabinets; to adjust the number of energy storage cabinets connected to the grid within the energy storage system based on the grid connection data; to automatically adjust the charging and discharging power thresholds based on time-of-use electricity prices and the benchmark power consumption; and to switch the charging and discharging state of the energy storage system by comparing the load power with the charging and discharging power thresholds.

[0086] The execution unit calculates the discharge power of the energy storage system based on the load power and the rated power of the energy storage system when the energy storage system is in a discharging state; and calculates the charging power of the energy storage system based on the load power, the grid smoothing power, and the rated power of the energy storage system when the energy storage system needs to be charged.

[0087] Example 3

[0088] This embodiment provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the intelligent charging and discharging control method described in Embodiment 1.

[0089] Example 4

[0090] This embodiment provides an electronic device, including a storage medium and a processor; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the intelligent charge and discharge control method described in Embodiment 1.

[0091] The memory can be any electronic, magnetic, optical, or other physical storage device used to store computer programs, information, and data. The memory can be random access memory (RAM), flash memory, and disk storage, or other similar storage media, or combinations of the above. The system network element connects to at least one other network element, including the Internet, wide area network (WAN), and local area network (LAN), through at least one communication interface (wired or wireless).

[0092] The memory and processor are connected via a bus; the bus can be an ISA bus, EISA bus, VESA bus, or PCI bus, etc., and can be divided into a data bus, address bus, control bus, expansion bus, etc. The memory stores the computer program, and the processor executes the program after receiving execution instructions.

[0093] Example 5

[0094] The fifth aspect of the present invention provides a computer program product, including instructions that, when executed by a processor, cause the processor to perform the intelligent charge and discharge control method described in Embodiment 1.

[0095] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0097] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process.Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0099] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A smart charging and discharging control method based on a real-time electricity price mechanism, characterized in that, include: Historical load data is acquired and plotted as a historical daily electricity consumption curve. Based on the historical daily electricity consumption curve, the benchmark power, peak electricity consumption data, and off-peak electricity consumption data are determined. The peak-to-valley difference of daily electricity consumption is calculated using the peak and off-peak electricity consumption data. The grid connection data of the energy storage cabinet is obtained by calculating the peak-valley difference of daily electricity consumption and the energy storage capacity of the energy storage cabinet. The number of energy storage cabinets connected to the grid in the energy storage system is adjusted according to the grid connection data. The charging and discharging power thresholds are automatically adjusted based on time-of-use electricity prices and benchmark power consumption; the charging and discharging states of the energy storage system are switched by comparing the load power with the charging and discharging power thresholds. When the energy storage system is in a discharge state, the discharge power of the energy storage system is calculated based on the load power and the rated power of the energy storage system. When the energy storage system needs to be charged, the charging power of the energy storage system is calculated based on the load power, the grid smoothing power, and the rated power of the energy storage system.

2. The intelligent charging and discharging control method according to claim 1, characterized in that, The daily peak-valley difference in electricity consumption is calculated by using peak and off-peak electricity consumption data. The grid connection data for the energy storage cabinet is calculated based on the peak-valley difference in daily electricity consumption and the energy storage capacity of the cabinet. Specifically, this includes: ； ； In the formula, This refers to the peak-valley difference in daily electricity consumption. This refers to the peak power consumption in the peak power consumption data. This refers to the peak electricity consumption time in the peak electricity consumption data; This refers to the off-peak electricity consumption data. This refers to the off-peak electricity consumption time in the off-peak electricity consumption data; The number of energy storage cabinets connected to the power grid within the energy storage system is denoted as the grid connection data of the energy storage cabinets; The energy storage capacity of the energy storage cabinet; The attenuation coefficient; The energy conversion efficiency of the energy storage cabinet.

3. The intelligent charging and discharging control method according to claim 1, characterized in that, The charging and discharging power thresholds are automatically adjusted based on time-of-use pricing and baseline power consumption, specifically including: ； In the formula, The charging and discharging power threshold; This is the reference power for electricity consumption. The average daily electricity price; This is the maximum daily electricity price. This is the minimum daily electricity price. This refers to the current actual electricity price; This is the sensitivity coefficient.

4. The intelligent charging and discharging control method according to claim 1, characterized in that, The discharge power of the energy storage system is calculated based on the load power and the rated power of the energy storage system, specifically including: ； In the formula, This refers to the discharge power of the energy storage system. For load power; This refers to the rated power of the energy storage system.

5. The intelligent charging and discharging control method according to claim 1, characterized in that, The charging power of the energy storage system is calculated based on the load power, grid smoothing power, and rated power of the energy storage system, specifically including: ； In the formula, The charging power for the energy storage system, For load power; The rated power of the energy storage system, To smooth power for the power grid.

6. The intelligent charging and discharging control method according to claim 1, characterized in that, The charging and discharging power of a single energy storage cabinet is determined based on the discharge power and charging power of the energy storage system; when the charging and discharging power of the energy storage cabinet exceeds K times the rated power of the energy storage cabinet converter and the duration reaches the time threshold T, the corresponding energy storage cabinet is triggered to stop.

7. The intelligent charging and discharging control method according to claim 1, characterized in that, When the grid connection voltage of the energy storage cabinet exceeds the set safe voltage range, the grid connection of the energy storage cabinet is disconnected; the safe voltage range is 380V(1-10%) to 380V(1+10%).

8. The intelligent charging and discharging control method according to claim 1, characterized in that, Receive the fault code uploaded by the energy storage cabinet; determine the fault level of the energy storage cabinet based on the fault code; when the energy storage cabinet has a level one fault, control the corresponding energy storage cabinet to stop immediately; and evenly distribute the discharge power and charging power of the energy storage system to the remaining energy storage cabinets.

9. An intelligent charging and discharging control system based on a real-time electricity price mechanism, characterized in that, include: The data acquisition unit acquires historical load data and plots it as a historical daily electricity consumption curve. Based on the historical daily electricity consumption curve, it determines the baseline power consumption, peak electricity consumption data, and off-peak electricity consumption data. The decision-making unit is used to calculate the daily peak-valley difference in electricity consumption based on peak and off-peak electricity consumption data. The grid connection data of the energy storage cabinet is obtained by calculating the peak-valley difference of daily electricity consumption and the energy storage capacity of the energy storage cabinet. The number of energy storage cabinets connected to the grid in the energy storage system is adjusted according to the grid connection data. The charging and discharging power thresholds are automatically adjusted according to the time-of-use electricity price and the benchmark power of electricity consumption. The charging and discharging state of the energy storage system is switched by comparing the load power with the charging and discharging power thresholds. The execution unit calculates the discharge power of the energy storage system based on the load power and the rated power of the energy storage system when the energy storage system is in a discharge state; and calculates the charging power of the energy storage system based on the load power, the grid smoothing power, and the rated power of the energy storage system when the energy storage system needs to be charged.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the intelligent BMS fault early warning method as described in any one of claims 1 to 7.

11. An electronic device comprising a storage medium and a processor; said storage medium for storing instructions; characterized in that, The processor is configured to operate according to the instructions to execute the intelligent BMS fault early warning method according to any one of claims 1 to 7.

12. A computer program product, comprising instructions, characterized in that, When executed by the processor, the instruction causes the processor to perform the intelligent BMS fault early warning method as described in any one of claims 1 to 7.

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