User-side efficient energy storage management system based on big data

Abstract

The invention belongs to the technical field of energy storage management, and particularly relates to a user-side efficient energy storage management system based on big data, and the system comprises a power generation unit, an energy storage unit, a detection unit, a control platform, a power utilization plan module, and a scheduling plan module. The power generation unit generates electric energy through a power generation assembly and transmits the electric energy to the energy storage unit. Adaptation is carried out according to the actual scale of the user side, the power generation units and the storage units are correspondingly arranged according to the number of the workshops, and under the condition that no less than one set of workshops exist, the power of the multiple storage units can be connected with power supply of any workshop through the storage distribution module, that is, one workshop always adopts power grid power supply; and the power grid power supply of the other plant is switched by utilizing the power generation quantity of the two power generation units and the energy storage of the two storage units and combining the power consumption of the plant, so that the electric charge can be saved, the pressure of the user side on the regional power grid load can be reduced, and the frequency of power supply switching can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage management, and in particular to a user-side efficient energy storage management system based on big data. Background Art

[0002] Energy storage power stations can ensure the stable operation of the power system by releasing stored energy when the power supply is insufficient. For enterprises, the stability and reliability of the power system are very important. Once power outages or voltage fluctuations occur, production will be seriously affected. At the same time, energy can be stored during the low period of electricity demand, and the stored energy can be released during the peak period to meet the electricity demand. This can alleviate the contradiction between electricity supply and demand to a certain extent and reduce the electricity costs of enterprises.

[0003] At present, the energy storage management systems of enterprises often remain at the stage of peak shaving and valley filling, and cannot be flexibly adjusted according to the actual situation on the user side, resulting in the power supply of energy storage stations being useless. There are often only simple peak shaving and valley filling and backup energy storage functions, which cannot bring convenience to enterprises. At the same time, power supply switching at inappropriate times will bring hidden dangers to electricity safety. At the same time, the energy storage management system of enterprises cannot share the peak power pressure for the power grid.

[0004] Therefore, it is necessary to provide a user-side efficient energy storage management system based on big data to solve the above technical problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a user-side efficient energy storage management system based on big data, which is used to solve the problem that the energy storage management cannot be adjusted according to the actual situation on the user side, and the peak power pressure cannot be shared for the power grid.

[0006] The present invention provides a user-side efficient energy storage management system based on big data, a user-side efficient energy storage management system based on big data, the user-side efficient energy storage management system includes a power generation unit, an energy storage unit, a detection unit, a control platform, a power consumption plan module and a scheduling plan module; The power generation unit generates electrical energy using the power generation components and transmits the electricity to the energy storage unit; The energy storage unit includes an energy storage module, an energy storage monitoring module and an energy storage distribution module; Each plant on the user side corresponds to a group of power generation units and a group of storage units; The energy storage module is used to store electric energy, and the energy storage monitoring module is used to monitor the electric power data of the storage module. The storage allocation module is used to allocate energy storage according to the data of the power consumption plan module, the detection module and the big data module. The detection unit detects the voltage of the power grid and the voltage of the user area circuit; The power consumption plan module calculates the power consumption plan data based on the number and parameters of equipment used in the production plan and the equipment start-up time; The scheduling module combines the power consumption plan data, performs scheduling according to the energy storage data of the energy storage unit and the power consumption plan data of the power consumption plan module, and forms a scheduling plan; The control platform can view the energy storage of the energy storage unit, the production plan of the power consumption plan module, the energy storage and voltage data of the energy storage monitoring module, the power grid of the detection unit, and the voltage data of the user area circuit, and can adjust the production plan of the power consumption plan module and the scheduling plan of the scheduling plan module; The control platform also includes a big data module, which collects data including weather, user power consumption, electricity charges, weak power time, recycled electricity price and production plan. The above data is combined with the data of the scheduling plan module and the energy storage allocation module through the big data algorithm to optimize the scheduling plan and energy storage allocation; After the power consumption plan module calculates the power consumption plan data, the storage allocation module can arrange for the energy storage module to replenish energy through the power grid at night according to the power consumption plan data, or reserve the power of the energy storage module according to the power consumption plan data.

[0007] Preferably, the scheduling plan module makes a scheduling plan according to the remaining power in the energy storage module and the power consumption plan data, which can be divided into three modes: load mode, normal mode and low load mode; The load mode is to complete the energy storage module replenishment through the power grid at night, and directly transmit the electricity generated by the production unit to the power grid during the day, consume the energy storage module before nightfall, retain the standby energy storage, and use the power generation unit to fully replenish the energy storage module the next day; In normal mode, the energy storage module is replenished through the power grid at night, and the energy storage module is started during the day to consume its power. After the energy stored in the energy storage module is consumed, the power supply is switched from the energy storage module to the power grid; While the energy storage unit is supplying power, the power generation unit can directly transmit the power generated by the production unit to the power grid. After the energy stored in the energy storage module is completely consumed, the power generation unit will replenish the energy storage module, and after the energy storage module has completed the energy replenishment, the power generated by the power generation unit will be transmitted to the power grid; Before nightfall, the energy storage module is switched to supply power again, and the energy replenished by the power generation unit to the energy storage module is consumed; The low-load mode production equipment is started at night. On the night before the day, the energy storage module is replenished through the power grid. When the energy stored in the energy storage module is consumed to the backup energy storage, the power supply is switched from the energy storage module to the power grid. The power generation unit directly transmits the electricity generated by the production unit to the power grid while the energy storage unit is supplying power; The energy storage module's energy storage is replenished through the power grid at night.

[0008] Preferably, the detection unit detects the grid voltage. When the grid experiences multiple voltage instability or weak power within a time period, and the power reserve in the energy storage module exceeds 60%, the power supply is switched to the energy storage module first, and the time node is recorded by the big data module.

[0009] Preferably, the detection unit is set up in the user area circuit, and when any factory building experiences multiple voltage instabilities or weak power within a time period, the power supply of the factory building is switched to the corresponding storage unit for power supply.

[0010] Preferably, the data of the detection module is allocated for energy storage through the storage allocation module. When the detection module detects that the grid voltage or current has multiple anomalies in a short period of time, or the user area circuit voltage or current has multiple anomalies in a short period of time, it is necessary to quickly replenish the energy storage module through the power generation unit or the grid, so that the energy storage module can quickly replace the grid power supply.

[0011] Preferably, the user-side efficient energy storage management system establishes two groups of power generation units and two groups of storage units according to the two plant buildings on the user side; The power of the two groups of storage units can be connected to the power supply of any factory building through the storage distribution module. In this way, one factory building is always powered by the grid, while the other factory building is powered by the power generated by the two power generation units and the energy stored in the two storage units, and the grid power supply is switched according to the power consumption of the factory building.

[0012] Compared with the related art, the user-side efficient energy storage management system based on big data provided by the present invention has the following beneficial effects: 1. The scheduling plan module in the present invention allocates three modes, namely load mode, normal mode and low-load mode, according to the power consumption plan data of the power consumption plan module. In the load mode, since all the equipment is started, the load pressure on the regional power grid is relatively large. The power generation unit directly transmits the generated electricity to the power grid, which can reduce the voltage pressure of the power grid in the region and ensure the voltage safety of the equipment in the regional power grid. At the same time, when the power grid pressure is large, the power supply switching is reduced to avoid the occurrence of safety hazards. The load of the power grid in the normal mode will be smaller than that in the load mode. Switching the power supply under this working condition can reduce voltage fluctuations and avoid voltage fluctuations exceeding the voltage range of the equipment. In the low-load mode, the energy storage unit is used as backup energy storage. When an emergency power outage occurs or the power grid voltage is unstable, the power supply can be taken over to avoid the impact of direct power outage on the running equipment. At the same time, according to the scheduling plan, production is set at night to reduce electricity costs.

[0013] 2. The present invention is adapted according to the actual scale of the user side, and the power generation units and storage units are correspondingly arranged according to the number of factory buildings. When there is no less than one group of factory buildings, the power of multiple storage units can be connected to the power supply of any factory building through the storage allocation module. That is, one factory building is always powered by the power grid, while the other factory building uses the power generation of two power generation units and the energy storage of two storage units, and switches the power supply to the power grid in combination with the power consumption of the factory building. This not only saves electricity bills, but also reduces the pressure on the user side on the regional power grid load and reduces the frequency of power supply switching.

[0014] 3. The present invention collects multi-party data through the big data module, and further optimizes the scheduling plan and energy storage allocation of the scheduling plan module and the storage allocation module through the multi-party data. The scheduling plan and energy storage allocation are optimized according to the data of the weather in the user's area, the user's electricity consumption, electricity charges, weak power time, recycled electricity price and production plan, so that the scheduling plan and energy storage allocation are more in line with the actual needs of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of the control flow of a user-side efficient energy storage management system based on big data provided by the present invention; Figure 2 A schematic diagram of a flow chart of Embodiment 2 of the user-side efficient energy storage management system based on big data provided by the present invention; Figure 3 A schematic diagram of the load mode operation flow of the user-side efficient energy storage management system based on big data provided by the present invention; Figure 4 A schematic diagram of the normal mode operation flow of the user-side efficient energy storage management system based on big data provided by the present invention; Figure 5 A schematic diagram of the low-load mode operation flow of the user-side high-efficiency energy storage management system based on big data provided by the present invention. DETAILED DESCRIPTION

[0016] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. 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. Embodiment 1

[0017] A user-side efficient energy storage management system based on big data: power generation unit, energy storage unit, detection unit, control platform, power consumption plan module, and scheduling plan module; The power generation unit generates electrical energy using the power generation components and transmits the electricity to the energy storage unit; The energy storage unit includes an energy storage module, an energy storage monitoring module and an energy storage distribution module; The energy storage module is used to store electric energy, and the energy storage monitoring module is used to monitor the electric power data of the storage module. The storage allocation module is used to allocate energy storage according to the data of the power consumption plan module, the detection module and the big data module. The detection units are respectively installed in the power grid and the user area circuit to detect the voltage of the power grid and the user area circuit; The power consumption plan module calculates the power consumption plan data based on the number and parameters of equipment used in the production plan and the equipment start-up time; The equipment usage time can be estimated based on the equipment power and the production quantity in the production plan. The power consumption of a single device can be calculated by the power and usage time. By calculating how many devices are needed, the power consumption plan data required for the production plan can be estimated. The scheduling module combines the power consumption plan data, performs scheduling according to the energy storage data of the energy storage unit and the power consumption plan data of the power consumption plan module, and forms a scheduling plan; The control platform can view the energy storage of the energy storage unit, the production plan of the power consumption plan module, the energy storage and voltage data of the energy storage monitoring module, the power grid of the detection unit, and the voltage data of the user area circuit, and can adjust the production plan of the power consumption plan module and the scheduling plan of the scheduling plan module; The control platform also includes a big data module, which collects data including weather, user electricity consumption, electricity charges, low power hours, recycled electricity prices and production plans. The above data is combined with the data from the scheduling planning module and the energy storage allocation module through the big data algorithm to optimize the scheduling plan and energy storage allocation.

[0018] Establish a power generation unit according to the actual situation of the user, and transmit the electric energy generated by the power generation unit to the energy storage unit; The establishment of the power generation unit requires certain layout adjustments based on the user's location and the area occupied. For example, if the user's area has sufficient sunshine, solar panels can be used for power generation. Or, if the user's area has not only sufficient sunshine but also wind resources, a combination of solar panels and wind power can be used for power generation. The specific power generation unit needs to be combined with the user's actual situation to improve resource utilization.

[0019] One plant corresponds to a group of power generation units and a group of storage units.

[0020] The number and parameters of equipment used in the production plan and the equipment start-up time are uploaded to the power consumption plan module, and the power consumption plan module calculates the power consumption plan data based on the number and parameters of equipment; For example, in the production plan, 3,000 units of a certain product are planned to be produced on the 20th, and three devices are needed to produce for two days. According to the 8-hour work system, six shifts are required. In the power consumption plan on the 20th and 21st, these three devices need to run for 24 hours. For example, the power of a single device is 15kW; Power consumption = equipment power × power consumption time; 15kW×24h=360kWh The above is the power consumption of a single device, and the total power consumption of the three devices is 1080kWh.

[0021] Through the big data module of the control platform, the power generation of the power generation unit on that day is estimated based on the size of the power generation unit and the weather conditions of the day, and the estimated power generation is uploaded to the scheduling plan module; The energy storage monitoring module of the energy storage unit uploads the power data of the storage module to the scheduling planning module. The scheduling module makes scheduling plans based on the remaining power in the energy storage module and the power consumption plan data. The scheduling plans can be divided into three modes: load mode, normal mode and low load mode. If the load mode is that the startup ratio of user-side equipment is ≥90% and the general power-on time of the day is ≥80%, the energy storage module needs to be replenished through the power grid at night of the previous day, that is, from 9 pm to 6 am the next day.

[0022] The power grid is used for power supply during the day, and the fully loaded energy storage modules are used as backup storage.

[0023] The energy stored in the energy storage module will be consumed at night, 60%-80% can be consumed and 20%-40% can be reserved as backup energy storage, and the energy storage module will be fully replenished by the power generation unit the next day.

[0024] In load mode, since all equipment is started, the load pressure on the regional power grid is relatively large. By directly transmitting the generated electricity to the power grid through the power generation unit, the voltage pressure of the regional power grid can be reduced and the voltage safety of the equipment in the regional power grid can be ensured. At the same time, when the power grid pressure is high, the power supply switching can be reduced to avoid the occurrence of safety hazards.

[0025] In normal mode, the user-side devices are turned on for ≥70% (<90%), and the general working time on the day is ≥60% (<80%). During the night of the previous day, that is, from 9 pm to 6 am the next day, the energy storage module is replenished through the power grid, and the energy storage module is started at 6 am on the same day to consume its electricity. The support time of the energy storage module needs to be calculated based on the energy storage capacity of the energy storage module and the power consumption of all devices on the user side per hour. The time can be based on the consumption of the energy storage module within 2-3 hours.

[0026] After the energy stored in the energy storage module is consumed, the power supply is switched from the energy storage module to the grid; While the energy storage unit is supplying power, the power generation unit can directly transmit the electricity generated by the production unit to the power grid in exchange for electricity prices. After the energy stored in the energy storage module is completely consumed, the power generation unit will replenish the energy storage module, and after the energy storage module has completed replenishment, the power generated by the power generation unit will be transmitted to the power grid.

[0027] At 6 pm on the same day, the energy storage module is switched to supply power again, and the energy replenished by the power generation unit to the energy storage module is consumed.

[0028] Since some of the company's equipment is not fully turned on, its load on the power grid will be smaller than in load mode. Switching the power supply under this condition can reduce voltage fluctuations and prevent voltage fluctuations from exceeding the equipment voltage range.

[0029] In low-load mode, the user-side equipment is turned on for ≥50% (<70%), and the general working time on the day is ≥40% (<60%). In low-load mode, production equipment is often concentrated at night because the electricity price is cheaper at night. During the night before the day, that is, from 9 pm to 6 am the next day, the energy storage module is replenished through the power grid, and the energy storage module is started at 6 am on the same day to consume its electricity; The support time of the energy storage module needs to be calculated based on the energy storage capacity of the energy storage module and the power consumption of all devices on the user side per hour. The time can be based on the consumption of the energy storage module within 3-6 hours.

[0030] When the energy storage module consumes 20% of the energy, it will be used as backup energy storage and the power supply will be switched from the energy storage module to the grid; While the energy storage unit is supplying power, the power generation unit can directly transmit the electricity generated by the production unit to the power grid in exchange for electricity prices.

[0031] At the same time, the electricity generated by the power generation unit on that day is not transmitted to the energy storage module; The energy storage module's energy storage is replenished through the power grid at night.

[0032] The energy storage unit is used as backup energy storage. In the event of an emergency power outage or unstable grid voltage, it can take over the power supply to avoid the impact of direct power outage on the running equipment. At the same time, according to the scheduling plan, production can be set at night to reduce electricity costs. At the same time, the energy storage unit can be replenished through the power generation unit during the day.

[0033] In the above three modes, the specific time can be adjusted according to the storage allocation module.

[0034] It should be noted that the above three modes are mainly to reduce the frequency of switching power sources, because power supply switching may cause voltage fluctuations, which may exceed the voltage range of normal operation of the equipment, thereby affecting the performance and life of the equipment. There may also be short power supply interruptions, and each switch is accompanied by a sudden change in current. This impact may cause damage to the power system and connected devices.

[0035] The detection unit detects the grid voltage. If the grid voltage is unstable or the power is weak for many times within a time period, such as 30 minutes, and the power reserve of the energy storage module exceeds 60%, the energy storage module will be switched to power supply first, and the time node will be recorded by the big data module. Since summer is the peak season for electricity consumption, and industrial enterprises tend to maintain a high level of production activities in summer, this will lead to power supply shortages in the power grid, which not only affects the power supply quality of the power grid, but also the power grid will decide to increase electricity prices for industrial enterprises in order to ensure regional electricity consumption. In the northern region, heating may also lead to an increase in electricity consumption. Under normal circumstances, taking summer as an example, the time span is from July 10th to August 20th. Specifically, the peak electricity consumption is from 11 am to 1 pm on a single day, which often affects the regional power supply quality during the noon time period. The time node is recorded through the big data module, and the power of the energy storage module is concentrated between 11 am and 1 pm, which can greatly reduce the power supply pressure of the regional power grid and save a lot of peak electricity costs, thereby achieving the purpose of optimizing the scheduling plan.

[0036] The detection unit is set up in the user area circuit. The above shows that a group of power generation units and a group of storage units are established in a single plant. The user area circuit represents the internal circuit of a single plant. When any plant has multiple voltage instabilities or weak power in a period of time, there may be power hazards in the plant. In this case, the power supply of the plant needs to be switched to the corresponding storage unit for power supply, and power personnel are dispatched to conduct power inspections. This method can make the power supply of a single factory building relatively independent, avoiding the impact of its circuit problems on other factories, and making it easier for power personnel to troubleshoot power failures.

[0037] After the power planning module calculates the power planning data, the storage allocation module can arrange for the energy storage module to replenish energy through the power grid at night according to the power planning data, or reserve the power of the energy storage module according to the power planning data. For example, in a single factory, a work section will be reserved between two batches of products for equipment maintenance, or for packaging or trimming of the previous batch of products.

[0038] The data from the detection module is used for energy storage allocation through the storage allocation module. When the detection module detects that the grid voltage or current has multiple anomalies in a short period of time, or the voltage or current in the user area circuit has multiple anomalies in a short period of time, the energy storage module needs to be quickly replenished through the power generation unit or the grid, so that the energy storage module can quickly replace the grid power supply.

[0039] The storage allocation module allocates energy storage to the data in the big data module, which includes weather, user power consumption, electricity charges, weak power time, recycled electricity price, production plan and other data; For example, if the next day is cloudy, the energy storage module will be replenished through the power grid at night. If the power supply is weak from 11:00 am to 1:00 am on the next day, the power of the energy storage module will be reserved until 11:00 am to 1:00 am to switch the power supply to ensure stable production.

[0040] Since the electricity prices in different regions are not uniform, in some regions, the enterprises that consume more electricity have lower electricity charges, while in some regions, enterprises in certain fields will be charged more electricity charges. Therefore, the collection method of electricity charges and the recovery price are important bases for the big data module to optimize the scheduling plan; For example, if the electricity bill of user A is divided into four stages and the price is reduced successively, and the annual electricity consumption of user A far exceeds that of the fourth stage, the energy storage module can be used to reduce the electricity cost in the first two stages, and during the peak period of electricity consumption, that is, in summer when the recycled electricity price is higher, the power of the power generation unit is preferentially transmitted to the grid, and the power position of the energy storage module can be kept at around 60%.

[0041] The storage allocation module is a supplement to the scheduling plan module. The scheduling plan is mainly based on the energy storage data of the energy storage unit and the power consumption plan data of the power consumption plan module. When the system is initially established and lacks a large amount of data, it is operated with reference to known and controllable data. When the system is established, the big data module is used to complete the collection and processing of various data. The data collected by the big data module is combined with the data of the scheduling plan module and the energy storage allocation module to optimize the scheduling plan and energy storage allocation. For example, in the big data module, weather such as rainy days, snowy days and cloudy days will directly affect the power generation of the power generation unit. Therefore, when the energy storage module has a storage capacity of 60% but there is no power generation unit to replenish energy, the power supply will not be switched in the daily scheduling plan, and the energy storage module will be used as a backup power source. If there are two consecutive rainy days, the energy storage module will need to be replenished through the power grid during the night from the first day to the second day through the storage and distribution module, and the energy storage module will be consumed to 20% during the day on the second day as a backup power source. Embodiment 2

[0042] User B has two plants, each with two power generation units and two storage units.

[0043] In the big data module, if the power consumption of user B differs from that of a single power generation unit by 2 to 4 times, in order to reduce the switching of power supply, the power of two groups of storage units can be connected to the power supply of any plant through the storage allocation module, that is, one plant always uses the power grid, while the other plant uses the power generated by two power generation units and the energy storage of two storage units, and switches to the power grid in combination with the power consumption of the plant; This not only saves electricity bills, but also reduces the pressure on the regional power grid load on the B user side and reduces the frequency of power supply switching. Embodiment 3

[0044] The electricity bill data in the big data module shows that the nighttime electricity bill is often lower than the daytime electricity bill. Therefore, in the low-load mode, the scheduling module arranges part of the production at night. Since the electricity production is concentrated at night and the storage module cannot consume it during the day, the storage allocation module will no longer arrange for the storage module to replenish energy at night. The recycled electricity price data in the big data module, because the recycled voltage of the power grid is also fluctuating, when the recycled electricity price is high, the power generation unit will be given priority to transmit the electricity to the power grid. The energy loss of the power generation unit to the power grid is relatively small, about 5%, while the energy loss of the power generation unit to the energy storage module is relatively large, about 20%.

[0045] Prioritizing the transmission of generated electricity to the grid can save costs and stabilize the regional voltage. This is because the increase in recycled electricity prices mostly occurs during peak electricity consumption or when there is insufficient power generation. Both of these situations will affect the voltage stability of the regional power grid. Therefore, by uploading the electricity from the power generation unit, the voltage in the area can be stabilized.

[0046] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A user-side efficient energy storage management system based on big data, characterized in that: The user-side efficient energy storage management system includes a power generation unit, an energy storage unit, a detection unit, a control platform, a power consumption plan module and a scheduling plan module; The power generation unit generates electrical energy using the power generation components and transmits the electricity to the energy storage unit; The energy storage unit includes an energy storage module, an energy storage monitoring module and an energy storage distribution module; Each plant on the user side corresponds to a group of power generation units and a group of storage units; The energy storage module stores electric energy, and the energy storage monitoring module monitors the power data of the storage module. The storage allocation module allocates energy storage according to the data of the power consumption plan module, the detection module and the big data module. The detection unit detects the voltage of the power grid and the voltage of the user area circuit; The power consumption plan module calculates the power consumption plan data based on the number and parameters of equipment used in the production plan and the equipment start-up time; The scheduling plan module combines the power consumption plan data, performs scheduling according to the energy storage data of the energy storage unit and the power consumption plan data of the power consumption plan module, and forms a scheduling plan; The control platform checks the energy storage of the energy storage unit, the production plan of the power consumption plan module, the energy storage and voltage data of the energy storage monitoring module, the power grid of the detection unit, and the voltage data of the user area circuit, and adjusts the production plan of the power consumption plan module and the scheduling plan of the scheduling plan module; The control platform also includes a big data module, which collects data including weather, user power consumption, electricity charges, weak power time, recycled electricity price and production plan. The above data is combined with the data of the scheduling plan module and the energy storage allocation module through the big data algorithm to optimize the scheduling plan and energy storage allocation; After the power consumption plan module calculates the power consumption plan data, the storage allocation module arranges the energy storage module to replenish energy through the power grid at night according to the power consumption plan data, or reserves the power of the energy storage module according to the power consumption plan data.

2. According to claim 1, a user-side efficient energy storage management system based on big data is characterized in that: The scheduling module makes scheduling plans based on the remaining power in the energy storage module and the power consumption plan data. The scheduling plans are divided into three modes: load mode, normal mode and low load mode. The load mode is to complete the energy storage module replenishment through the power grid at night, and directly transmit the electricity generated by the production unit to the power grid during the day, consume the energy storage module before nightfall, retain the standby energy storage, and use the power generation unit to fully replenish the energy storage module the next day; In normal mode, the energy storage module is replenished through the power grid at night, and the energy storage module is started during the day to consume its power. After the energy stored in the energy storage module is consumed, the power supply is switched from the energy storage module to the power grid; While the energy storage unit is supplying power, the power generation unit directly transmits the power generated by the production unit to the power grid. After the energy stored in the energy storage module is completely consumed, the power generation unit replenishes the energy storage module, and after the energy storage module completes the energy replenishment, the power generated by the power generation unit is transmitted to the power grid; Before nightfall, the energy storage module is switched to supply power again, and the energy replenished by the power generation unit to the energy storage module is consumed; The low-load mode production equipment is started at night. On the night before the day, the energy storage module is replenished through the power grid. When the energy stored in the energy storage module is consumed to the backup energy storage, the power supply is switched from the energy storage module to the power grid. The power generation unit directly transmits the electricity generated by the production unit to the power grid while the energy storage unit is supplying power; The energy storage module's energy storage is replenished through the power grid at night.

3. According to the user-side efficient energy storage management system based on big data according to claim 1, it is characterized in that: The detection unit detects the grid voltage. When the grid experiences multiple voltage instabilities or weak power within a time period, and the power reserve in the energy storage module exceeds 60%, the power supply is switched to the energy storage module first, and the time node is recorded by the big data module.

4. According to claim 3, a user-side efficient energy storage management system based on big data is characterized in that: The detection unit is set up in the user area circuit. When any factory building experiences multiple voltage instabilities or weak power within a time period, the power supply of the factory building is switched to the corresponding storage unit for power supply.

5. A user-side efficient energy storage management system based on big data according to claim 3 or 4, characterized in that: The data from the detection module is used for energy storage allocation through the storage allocation module. When the detection module detects that the grid voltage or current has multiple anomalies in a short period of time, or the voltage or current in the user area circuit has multiple anomalies in a short period of time, the energy storage module needs to be quickly replenished through the power generation unit or the grid, so that the energy storage module can quickly replace the grid power supply.

6. The user-side efficient energy storage management system based on big data according to claim 1 is characterized in that: The user-side efficient energy storage management system establishes two groups of power generation units and two groups of storage units according to the two plant buildings on the user side; By connecting the electricity of the two groups of storage units to the power supply of any factory building through the storage and distribution module, one factory building is always powered by the grid, while the other factory building is powered by the power generated by the two power generation units and the energy stored in the two storage units, and the grid power supply is switched according to the power consumption of the factory building.

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