A distributed energy cloud management method and system

Abstract

The present application relates to the field of new energy technology, in particular to a distributed energy cloud management method and system. The present application adopts distributed energy storage to shave peak and fill valley. In addition to solar street lamps, solar panels can also be established on the roof of a building, sunshade shed and other places, and energy storage power stations are set up in some areas, and the energy of charging piles inside the community is utilized to realize distributed energy storage. A new concept of user end peak shaving and auxiliary technical means are established, and during the peak period of city power grid electricity consumption, some high-power household appliances are controlled by intelligent sockets, and during the valley period of power grid electricity consumption and the peak period of community solar power generation, some household appliances are started by intelligent sockets, and before the arrival of the peak period of electricity consumption, some household appliances are used for non-immediate electricity consumption, and the function of assisting the power grid to shave peak and fill valley at the user end is realized.

Description

Technical Field

[0001] This invention relates to the field of new energy technology, and in particular to a distributed energy cloud management method and system. Background Technology

[0002] Existing photovoltaic energy management systems include coupled photovoltaic + energy storage systems, as well as energy management systems based on operating condition analysis.

[0003] Coupled photovoltaic (PV) + energy storage system, also known as AC-to-AC PV + energy storage system, typically consists of PV modules, a grid-connected inverter, lithium batteries, an AC-coupled energy storage inverter, smart meters, current transformers (CTs), the power grid, grid-connected loads, and off-grid loads. This system allows PV power to be converted to AC by the grid-connected inverter, and then excess power is converted to DC by the AC-coupled energy storage inverter and stored in the batteries.

[0004] The operating logic is as follows: During the day, photovoltaic power generation first supplies the load, then charges the battery, and any excess power can be connected to the grid; at night, the battery discharges to supply the load, with any shortfall supplemented by the grid; when the grid experiences a power outage, the lithium battery only supplies power to off-grid loads, and grid-connected loads cannot be used. Additionally, the system allows users to set their own charging and discharging times to meet their electricity needs.

[0005] The disadvantages are:

[0006] Traditional user energy storage systems use a 48V voltage platform. However, with increasing market demand for higher capacity and efficiency in user energy storage systems, adopting a high-voltage platform of 200V or higher can improve system efficiency by more than 10%, making this a growing choice for user energy storage systems. A key challenge for user energy storage products is how to make the same energy storage system applicable to 48V low-voltage systems, 200V or higher high-voltage systems, or other systems with different voltages.

[0007] Meanwhile, due to the limited number of public charging stations, many residential communities or private residences need to install home charging stations. However, since the electricity allocated to each household in the city is fixed, while the charging stations require a lot of electricity, it is impossible to meet the needs of users for normal electricity use and charging electric vehicles at the same time.

[0008] The energy management system based on operating condition analysis consists of photovoltaic modules, batteries, loads, etc., and interacts with the power grid, with multiple operating conditions.

[0009] Working logic: Energy management strategies based on operating condition analysis, such as operating condition switching. Figure 1As shown, PPV represents photovoltaic power generation, PLoad represents load consumption, and SOC (State of Charge) represents the battery's state of charge. Operating conditions are as follows: Condition 1: Islanded operation, photovoltaic power generation; Condition 2: Grid-connected operation, grid-side converter inversion; Condition 3: Islanded operation, battery power supply; Condition 4: Grid-connected operation, grid-side converter rectification.

[0010] Switching conditions between operating modes: If SOC > 95%, and the battery is basically fully charged, the system switches from photovoltaic power generation (Mode 1) to mode 2, operating in grid-connected mode, feeding excess power generated by the photovoltaic system into the grid. If photovoltaic power generation is less than load consumption (PPV < PLoad), and photovoltaic power generation cannot meet the user's normal needs, the system switches from grid-connected operation (Mode 2) to islanded operation (Mode 3), with battery power supply. If battery SOC < 5%, and the battery is basically de-energized, the system enters mode 4, where the grid supplies power to the load and simultaneously charges the battery. If photovoltaic power generation is greater than load consumption (PPV > PLoad), the system returns to mode 1, operating in islanded mode, charging the battery. Therefore, the power supply priority is photovoltaic, battery, and grid.

[0011] Disadvantages: This surplus power grid connection model introduces batteries as energy storage components, making the photovoltaic-storage power generation system more stable. Profiting from selling electricity through grid connection makes the photovoltaic-storage power generation system economical. However, it lacks flexibility for the energy management system. This economic model relies on the grid, placing unnecessary burden on it, and still requires real-time grid power supply when photovoltaic power generation is insufficient.

[0012] In summary, current traditional user-based energy storage suffers from two main problems: firstly, it lacks an effective means of information sharing to achieve intelligent control of new energy applications and realize the goal of energy conservation and emission reduction for the whole society; secondly, traditional user-based energy storage control strategies cannot allocate energy storage according to changes in photovoltaic and load conditions.

[0013] It can only respond to set limits and cannot adjust control strategies in a timely manner according to specific application environments, thus failing to meet user comfort requirements. Energy management strategies based on operating condition analysis are needed for energy...

[0014] The management system lacks flexibility, and this economic model relies on the power grid, placing an unnecessary burden on it. Even when photovoltaic power generation is insufficient, the power grid still needs to supply power in real time. Summary of the Invention

[0015] To address the above problems, this invention provides a distributed energy cloud management method and system.

[0016] 0 In a first aspect, the present invention provides a distributed energy cloud management method, the method comprising:

[0017] Through the information loop, the user energy cloud management system can monitor and control the user load subsystem, photovoltaic power generation subsystem, energy storage configuration subsystem, charging pile configuration subsystem and grid connection control subsystem.

[0018] All electrical equipment and distributed energy storage power devices of the energy storage configuration subsystem are connected in parallel to a single electrical bus. The grid-connected control subsystem of the user energy cloud management system analyzes the distributed...

[0019] The SOC of the energy storage power source determines the charging and discharging actions of the energy storage configuration subsystem and the transmission relationship with the grid, so as to achieve a balance between power supply and demand.

[0020] Furthermore, the photovoltaic power generation system uses distributed photovoltaic panels to collect solar energy, and then...

[0021] The stabilized electricity is transmitted to the power grid through a combiner box, realizing the effective utilization of clean energy. The photovoltaic power generation system is configured with an MPPT (maximum power transmission time) control strategy on the energy cloud management platform.

[0022] Maximum Power Point Tracking (MPPT) enables the maximization of energy utilization and allows for the analysis and prediction of historical photovoltaic data.

[0023] Furthermore, the user load subsystem mainly relies on smart meters to collect and upload the electricity consumption information of load equipment, and transmit the load information to the energy cloud management system. The system calculates the load for the next day or short-term load through load prediction algorithms, and compares the predicted load data with the predicted photovoltaic data to control the maximum power point of the photovoltaic side in the future.

[0024] Furthermore, the energy storage configuration subsystem uses the BMS to collect battery information and transmits the collected information to the energy cloud management system in real time via MQTT format. By analyzing the battery's SOC (State of Charge), the system determines the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid.

[0025] Furthermore, the analysis of the battery's SOC to determine the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid specifically includes:

[0026] Peak-valley arbitrage and surplus electricity grid connection mode, which analyzes the relationship between photovoltaic power generation, load power and battery power, and combines real-time electricity price to realize the peak-valley arbitrage mode of grid connection control subsystem;

[0027] The specific strategies are as follows:

[0028] When the generating power equals the load power:

[0029] If the power grid has low electricity prices, take appropriate action based on the battery capacity:

[0030] A1. If the battery is below its operating capacity range (20%-90%), the power grid will charge the battery.

[0031] B1. The battery is within its operating capacity range, and the power grid is charging the battery with a constant current.

[0032] C1. The battery is above its operating capacity and does not function;

[0033] If the power grid experiences high electricity prices, take appropriate action based on the battery capacity:

[0034] A2. The battery is below its operating capacity, and the power grid does not activate;

[0035] B2. The battery is within its operating capacity range and is discharging at a constant power.

[0036] C2. The battery is above its operating capacity range, and the battery is discharging at a constant power.

[0037] When the power generation capacity is greater than the load capacity:

[0038] If the power grid has low electricity prices, take appropriate action based on the battery capacity:

[0039] A3. When the battery capacity is lower than the usable capacity range, the remaining power generation capacity is used to charge the battery with constant current, and the remaining power is sent to the grid.

[0040] B3. If the battery capacity exceeds the operating range, the battery will not operate, and all the excess power generated will be fed into the grid.

[0041] If the power grid experiences high electricity prices, take appropriate action based on the battery capacity:

[0042] A4. When the battery capacity is within the usable capacity range, the surplus power generated will be sent to the grid. The portion of the battery capacity exceeding the set capacity will also be sent to the grid.

[0043] B4. If the battery capacity is lower than the set capacity, all surplus power will be fed into the grid.

[0044] Furthermore, the charging pile configuration subsystem utilizes the charging pile grid-connected distribution cabinet to effectively utilize the excess power of electric vehicles. The energy cloud management system collects information from the grid-connected distribution cabinet and the remaining battery power of electric vehicles, and determines how to handle the excess power of electric vehicles by analyzing the status of the photovoltaic power generation system, user load subsystem, and energy storage configuration subsystem.

[0045] Furthermore, the grid connection control subsystem controls the grid connection control strategy of the system and records the electrical energy transmitted by the grid when there is a power shortage.

[0046] Furthermore, the analysis of the battery's SOC to determine the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid specifically includes:

[0047] Power support mode, which means that when the power supply of the photovoltaic subsystem is unstable, the battery capacity is used as a backup power source to maximize the storage of electrical energy in the battery for unforeseen needs.

[0048] The specific strategies are as follows:

[0049] When the generating power equals the load power:

[0050] A5. If the battery capacity is lower than the set maximum capacity, the power grid will charge each battery with a constant current.

[0051] B5. If the battery capacity is greater than or equal to the set maximum capacity, the battery will not operate.

[0052] When the power generation is less than the load power:

[0053] A6. If the battery charge is below the minimum value, the power grid will provide the missing power to the load;

[0054] B6. If the battery capacity is within the usable capacity range, the power grid will charge the battery with constant current while simultaneously meeting the power demand of the load side;

[0055] C6. When the battery capacity exceeds the set maximum capacity, the portion exceeding the set capacity is discharged to the load at constant power, while the remainder is powered by the power grid.

[0056] Furthermore, the information loop includes multiple branches and employs one or a hybrid communication method, such as wired or wireless transmission.

[0057] Furthermore, the distributed energy cloud management method also includes:

[0058] The entire energy system can be monitored and controlled by accessing the cloud platform via mobile or computer clients.

[0059] Secondly, the present invention provides a distributed energy cloud management system, comprising: an information management unit and an electrical management unit;

[0060] The information management unit is used to monitor and control the user load subsystem, photovoltaic power generation subsystem, energy storage configuration subsystem, charging pile configuration subsystem and grid connection control subsystem of the user energy cloud management system through the information loop;

[0061] The electrical management unit is used to connect all electrical equipment and distributed energy storage power devices of the energy storage configuration subsystem in parallel to an electrical bus. The user energy cloud management system analyzes the SOC of the distributed energy storage power to determine the charging and discharging actions of the energy storage configuration subsystem and the transmission relationship with the grid, so as to achieve a balance between power supply and demand.

[0062] Thirdly, the present invention provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0063] Memory, used to store computer programs;

[0064] The processor, when executing a program stored in memory, implements the aforementioned distributed energy cloud management method.

[0065] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-described distributed energy cloud management method.

[0066] The present invention has at least the following beneficial effects:

[0067] This invention can connect to new energy sources, achieving energy conservation and emission reduction. It establishes a solar microgrid system based on residential communities, using engineering facilities such as solar rooftops, solar walls, and solar shading panels to prioritize the use of solar photovoltaic power for public areas (streetlights, walkway lights, lawn lights, etc.). This realizes the large-scale application of solar energy in urban distributed energy systems, appropriately reducing the load pressure on the urban power grid during peak electricity consumption. Through technological means, information sharing, and intelligent control, it achieves the goal of energy conservation and emission reduction through the joint participation of the entire society.

[0068] This invention employs distributed energy storage for peak shaving and valley filling. Besides solar streetlights, solar panels can be installed on building rooftops and awnings, and energy storage power stations can be established in some areas. Distributed energy storage can also be achieved by utilizing the energy from charging piles within residential communities. A new concept and auxiliary technology for user-side peak shaving are established. During peak electricity consumption periods in the city, smart sockets are used to control the operation of some high-power-consuming household appliances in stages. During off-peak periods and peak periods of solar power generation in the community, smart sockets activate pre-set household appliances, completing non-immediate power consumption tasks for some appliances before peak hours arrive, thus achieving the function of assisting the power grid in peak shaving and valley filling at the user end.

[0069] This invention employs energy cloud management and intelligent control. Through both wireless and wired access methods, it directly connects most household appliances to the power information management system, wireless communication system, and internet system. Power supply companies and users can operate household appliances remotely via control or remote control devices, achieving direct connection between people and things, and between things themselves. This improves the automation and intelligent management level of the power grid system, enhancing residents' comfort and convenience. Building upon intelligent electricity usage, it gradually realizes intelligent water and gas management, among other integrated household energy management solutions.

[0070] This invention introduces batteries as energy storage components using a surplus grid connection mode, making the photovoltaic-storage power generation system more stable. Profiting from the sale of electricity connected to the grid, the photovoltaic-storage power generation system is economical.

[0071] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a schematic diagram of an energy management strategy based on operating condition analysis.

[0074] Figure 2 This is a flowchart of the management method according to an embodiment of the present invention;

[0075] Figure 3 This is a structural diagram of the distributed energy cloud management system according to an embodiment of the present invention;

[0076] Figure 4 This is a schematic diagram of the control strategy in an embodiment of the present invention. Detailed Implementation

[0077] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0078] To enable those skilled in the art to better understand the present invention, the principles of the present invention are explained below in conjunction with the accompanying drawings:

[0079] By combining Figure 3 The structure of the distributed energy cloud management system further illustrates the technical solution of this invention.

[0080] Firstly, this invention includes electrical circuits and information circuits. All electrical devices and distributed power sources are connected in parallel on a single electrical bus. When considering load balancing, the internal power supply and demand balance is taken into account. The information circuit includes multiple branches. Smart meters, combiner boxes, battery management systems (BMS), charging pile distribution cabinets, etc., transmit device status information to the energy management system on the cloud platform through wired and wireless communication methods. The energy management system issues control commands to control the entire distributed energy system. At the same time, the cloud platform can be accessed through mobile clients or computers to monitor and control the entire energy system.

[0081] Secondly, the distributed energy cloud management system is divided into several subsystems, including photovoltaic power generation system, user load subsystem, energy storage configuration subsystem, charging pile configuration subsystem and grid connection control subsystem.

[0082] Photovoltaic power generation systems use distributed photovoltaic panels to collect solar energy, and then transmit the regulated electricity to the power grid through combiner boxes, achieving efficient utilization of clean energy. By configuring MPPT (Maximum Power Point Tracking) control strategies on an energy cloud management platform, photovoltaic power generation systems maximize energy utilization and enable analysis and prediction of historical photovoltaic data.

[0083] Maximum Power Point Tracking (MPPT) is an electrical system that adjusts the operating state of electrical modules to enable photovoltaic panels to output more electrical energy. It can effectively store the direct current generated by solar panels in batteries, effectively solving the problem of electricity supply for domestic and industrial use in remote areas and tourist areas that cannot be covered by conventional power grids, without generating environmental pollution.

[0084] The user load subsystem mainly relies on smart meters to collect and upload power consumption information of load equipment.

[0085] Load information is transmitted to the energy cloud management system, which uses a load forecasting algorithm to calculate the short-term load for the next day or five days, and compares the predicted load data with the predicted photovoltaic data to predict future photovoltaic loads.

[0086] The maximum power point is controlled.

[0087] The energy storage configuration subsystem uses the BMS to collect battery information and transmits the collected information to the energy cloud management system in real time via MQTT format. By analyzing the battery's SOC (State of Charge), the system determines the subsequent charging and discharging actions of the energy storage subsystem and the transmission relationship with the grid.

[0088] The charging pile configuration subsystem utilizes the grid-connected power distribution cabinet of the charging piles to effectively utilize the excess power of electric vehicles. The energy cloud management system collects information from the grid-connected power distribution cabinet and the remaining battery power of electric vehicles, and determines how to handle the excess power of electric vehicles by analyzing the status of the photovoltaic power generation system, user load subsystem, and energy storage configuration subsystem.

[0089] 5. Grid-connected control subsystem: The system's surplus power grid connection strategy and the recording of grid transmission during power shortages.

[0090] Electrical energy.

[0091] like Figure 4 As shown, the energy cloud management system mainly includes four functions: 1. Subsystem interface display; 2. Data analysis and processing; 3. Control strategy; 4. System stability.

[0092] On the user side, load data is collected by smart meters and uploaded to the cloud management system. The photovoltaic subsystem, charging pile subsystem, and energy storage system are implemented through corresponding control strategies set in the converter.

[0093] Regarding data acquisition and control, once data from each subsystem is uploaded to the cloud management system, the energy cloud management system switches between different functions according to different control strategies. Users can configure these settings according to different situations, or control the entire system according to the system's default control strategy.

[0094] The analysis of the battery's SOC determines the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid, i.e., the control strategy, including peak-valley arbitrage and surplus power grid connection mode and power support mode.

[0095] Peak-valley arbitrage and surplus electricity grid connection mode, which analyzes the relationship between photovoltaic power generation, load power and battery power, and combines real-time electricity price to realize the peak-valley arbitrage mode of grid connection control subsystem;

[0096] The specific strategies are as follows:

[0097] When the generating power equals the load power:

[0098] If the power grid has low electricity prices, take appropriate action based on the battery capacity:

[0099] A1. If the battery is below its operating capacity range (20%-90%), the power grid will charge the battery.

[0100] B1. The battery is within its operating capacity range, and the power grid is charging the battery with a constant current.

[0101] C1. The battery is above its operating capacity and does not function;

[0102] If the power grid experiences high electricity prices, take appropriate action based on the battery capacity:

[0103] A2. The battery is below its operating capacity, and the power grid does not activate;

[0104] B2. The battery is within its operating capacity range and is discharging at a constant power.

[0105] C2. The battery is above its operating capacity range, and the battery is discharging at a constant power.

[0106] When the power generation capacity is greater than the load capacity:

[0107] If the power grid has low electricity prices, take appropriate action based on the battery capacity:

[0108] A3. When the battery capacity is lower than the usable capacity range, the remaining power generation capacity is used to charge the battery with constant current, and the remaining power is sent to the grid.

[0109] B3. If the battery capacity exceeds the operating range, the battery will not operate, and all the excess power generated will be fed into the grid.

[0110] If the power grid experiences high electricity prices, take appropriate action based on the battery capacity:

[0111] A4. When the battery capacity is within the usable capacity range, the surplus power generated will be sent to the grid. The portion of the battery capacity exceeding the set capacity will also be sent to the grid.

[0112] B4. If the battery capacity is lower than the set capacity, all surplus power will be fed into the grid.

[0113] Power support mode, which means that when the power supply of the photovoltaic subsystem is unstable, the battery capacity is used as a backup power source to maximize the storage of electrical energy in the battery for unforeseen needs.

[0114] The specific strategies are as follows:

[0115] When the generating power equals the load power:

[0116] A5. If the battery capacity is lower than the set maximum capacity, the power grid will charge each battery with a constant current.

[0117] B5. If the battery capacity is greater than or equal to the set maximum capacity, the battery will not operate.

[0118] When the power generation is less than the load power:

[0119] A6. If the battery charge is below the minimum value, the power grid will provide the missing power to the load;

[0120] B6. If the battery capacity is within the usable capacity range, the power grid will charge the battery with constant current while simultaneously meeting the power demand of the load side;

[0121] C6. When the battery capacity exceeds the set maximum capacity, the portion exceeding the set capacity is discharged to the load at constant power, while the remainder is powered by the power grid.

[0122] The beneficial effects of the technical solution of this invention are as follows:

[0123] 1. Total household electricity consumption metering

[0124] In this invention, the smart meter functions as a home gateway, enabling power supply departments to analyze household electricity metering. The home gateway can directly send electricity consumption data to the data center, while the data center can directly provide a data interface to the power grid company for easy access to household electricity data.

[0125] 2. Household single-appliance electricity metering

[0126] Through an intelligent electricity user management system, residents can gain real-time and comprehensive access to detailed information about their electricity consumption. This allows for the effective utilization and control of the usage time and frequency of household appliances, maximizing the use of surplus electricity from the power grid and the effective power generation from urban distributed solar photovoltaic systems. It also enables the orderly control of electricity consumption in residential communities and households during peak hours, appropriately reducing the load pressure on the urban power grid during peak hours. Through technological means, information sharing, and intelligent control, the system aims to achieve the goal of energy conservation and emission reduction through the joint participation of the entire society.

[0127] 3. Household load control

[0128] Classifying and managing household electrical appliances can solve two problems when there is a power shortage during the summer peak electricity consumption period. One is to limit the total amount of electricity used by the household to ensure basic electricity needs. During peak electricity consumption, the power supply to non-essential appliances can be automatically cut off. The other is to limit the use of non-essential appliances to ensure basic electricity needs. Under the power rationing mode, the drawbacks of power outages can be effectively solved, and the control of household electrical appliances can be truly realized.

[0129] 4. Remote control of home appliances

[0130] With the widespread application of the Internet of Things and mobile internet, residents' demand for remote control of home appliances will increase accordingly. Users can use smart terminal devices to issue remote control commands to a specific appliance via a data center or home gateway, and view the appliance's operating status in real time.

[0131] 5. Peak-valley electricity management and tiered electricity management

[0132] Establish a new concept and auxiliary technologies for peak shaving at the user end. During peak electricity consumption periods in urban power grids, smart sockets can be used to control the operation of some high-power-consuming household appliances in stages. During off-peak periods and peak periods of solar power generation in residential areas, smart sockets can activate pre-set functions for some household appliances, completing non-immediate power consumption tasks for some household appliances before peak periods arrive, thus achieving the function of assisting the power grid in peak shaving and valley filling at the user end. Currently, households passively accept peak and off-peak electricity usage without user choice or feedback. The data center should have a peak and off-peak electricity management module. When it receives peak load control information, it should notify the relevant regional home gateways to deactivate relays on some smart sockets, temporarily stopping the operation of some appliances, based on the pre-set priority order of household appliance power consumption. When the data center receives off-peak electricity information, it should notify the relevant regional home gateways to deactivate relays on some smart sockets, activating some appliances, based on pre-booked power consumption requests from household appliances.

[0133] 6. Household Electricity Consumption Analysis

[0134] By utilizing historical electricity consumption information collected from user households in the data center, and leveraging data mining and powerful cloud platform computing capabilities, the data center can provide: analysis of the electricity consumption ratio of various household appliances for each household; analysis of the electricity usage time ratio of various household appliances for each household; analysis of the peak and off-peak electricity consumption ratio for each household; analysis of the grid electricity and district electricity consumption ratio for each household; analysis of electricity consumption patterns of different households; analysis of the electricity consumption ratio of different appliances; and analysis of the electricity consumption of the same appliance from different brands.

[0135] The key technical point of this invention lies in the use of smart meters, battery BMS, and charging pile distribution cabinets to collect data from photovoltaic power generation systems, user load subsystems, energy storage configuration subsystems, charging pile configuration subsystems, and grid connection control subsystems onto an energy cloud management platform. By adjusting the control strategies on the management platform, remote control of household energy consumption can be achieved, including load electricity information analysis and prediction, photovoltaic power generation and prediction, charging pile electricity analysis, battery status, and other information. The system's operating status varies under different conditions, and excess electricity can be connected to the grid to generate revenue. Furthermore, the use of cloud platform energy management can combine the energy usage of users within a region, enabling better energy exchange between users and the power grid within the region.

[0136] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed energy cloud management method, characterized in that, The method includes: Through the information loop, the user energy cloud management system can monitor and control the user load subsystem, photovoltaic power generation subsystem, energy storage configuration subsystem, charging pile configuration subsystem and grid connection control subsystem. All electrical equipment and distributed energy storage power devices of the energy storage configuration subsystem are connected in parallel to an electrical bus. The grid-connected control subsystem of the user energy cloud management system determines the charging and discharging actions of the energy storage configuration subsystem and the transmission relationship with the grid by analyzing the SOC of the distributed energy storage power, so as to achieve a balance between power supply and demand. This includes analyzing the battery's state of charge (SOC) to determine the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid. Specifically, this includes: Peak-valley arbitrage and surplus electricity grid connection mode, which analyzes the relationship between photovoltaic power generation, load power and battery power, and combines real-time electricity price to realize the peak-valley arbitrage mode of grid connection control subsystem; The specific strategies are as follows: When the generating power equals the load power: If the power grid has low electricity prices, take appropriate action based on the battery capacity: A1. If the battery capacity is below the usable capacity range, the power grid will charge the battery; wherein, the usable capacity range is 20%-90% of the battery capacity. B1. The battery is within its operating capacity range, and the power grid is charging the battery with a constant current. C1. The battery is above its operating capacity and does not function; If the power grid experiences high electricity prices, take appropriate action based on the battery capacity: A2. The battery is below its operating capacity, and the power grid does not activate; B2. The battery is within its operating capacity range and is discharging at a constant power. C2. The battery is above its operating capacity range, and the battery is discharging at a constant power. When the power generation capacity is greater than the load capacity: If the power grid has low electricity prices, take appropriate action based on the battery capacity: A3. When the battery capacity is lower than the usable capacity range, the remaining power generation capacity is used to charge the battery with constant current, and the remaining power is sent to the grid. B3. If the battery capacity exceeds the operating range, the battery will not operate, and all the excess power generated will be fed into the grid. If the power grid experiences high electricity prices, take appropriate action based on the battery capacity: A4. When the battery capacity is within the usable capacity range, the surplus power generated will be sent to the grid. The portion of the battery capacity exceeding the set capacity will also be sent to the grid. B4. If the battery capacity is lower than the set capacity, all surplus power will be fed into the grid. Specifically, the analysis of the battery's SOC to determine the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid also includes: Power support mode, which means that when the power supply of the photovoltaic subsystem is unstable, the battery capacity is used as a backup power source to maximize the storage of electrical energy in the battery for unforeseen needs. The specific strategies are as follows: When the generating power equals the load power: A5. If the battery capacity is lower than the set maximum capacity, the power grid will charge each battery with a constant current. B5. The battery does not operate if the battery capacity is greater than or equal to the set maximum capacity. When the power generation is less than the load power: A6. If the battery charge is below the minimum value, the power grid will provide the missing power to the load; B6. If the battery capacity is within the usable capacity range, the power grid will charge the battery with constant current while simultaneously meeting the power demand of the load side; C6. When the battery capacity exceeds the set maximum capacity, the portion exceeding the set capacity is discharged to the load at constant power, while the remainder is powered by the power grid.

2. The distributed energy cloud management method according to claim 1, characterized in that, The photovoltaic power generation system uses distributed photovoltaic panels to collect solar energy, and then transmits the regulated power to the power grid through a combiner box, realizing the effective utilization of clean energy. The photovoltaic power generation system achieves maximum energy utilization by configuring MPPT control strategy on the energy cloud management platform, and realizes the analysis and prediction of photovoltaic historical data.

3. The distributed energy cloud management method according to claim 1, characterized in that, The user load subsystem mainly relies on smart meters to collect and upload electricity consumption information of load equipment, and transmits the load information to the energy cloud management system. The system calculates the load for the next day or short-term load through load prediction algorithms, and compares the predicted load data with the predicted photovoltaic data to control the maximum power point of the photovoltaic side in the future.

4. The distributed energy cloud management method according to claim 1, characterized in that, The energy storage configuration subsystem uses the BMS to collect battery information and transmits the collected information to the energy cloud management system in real time via MQTT format. By analyzing the battery's SOC, it determines the next charging and discharging actions of the energy storage subsystem and the transmission relationship with the grid.

5. A distributed energy cloud management method according to claim 1, characterized in that, The charging pile configuration subsystem utilizes the grid-connected power distribution cabinet of the charging pile to effectively utilize the excess power of electric vehicles; the energy cloud management system collects information from the grid-connected power distribution cabinet and the remaining battery information of electric vehicles, and determines how to handle the excess power of electric vehicles by analyzing the status of the photovoltaic power generation system, user load subsystem, and energy storage configuration subsystem.

6. The distributed energy cloud management method according to claim 1, characterized in that, The grid connection control subsystem controls the grid connection control strategy of the system and records the electrical energy transmitted by the grid when there is a power shortage.

7. A distributed energy cloud management method according to claim 1, characterized in that, The information loop includes multiple branches and uses one or a combination of wired and wireless communication methods.

8. A distributed energy cloud management method according to claim 1, characterized in that, The distributed energy cloud management method further includes: The entire energy system can be monitored and controlled by accessing the cloud platform via mobile or computer clients.

9. A distributed energy cloud management system, characterized in that, include: Information management unit and electrical management unit; The information management unit is used to monitor and control the user load subsystem, photovoltaic power generation subsystem, energy storage configuration subsystem, charging pile configuration subsystem and grid connection control subsystem of the user energy cloud management system through the information loop; The electrical management unit is used to connect all electrical equipment and distributed energy storage power devices of the energy storage configuration subsystem in parallel to an electrical bus. The user energy cloud management system determines the charging and discharging actions of the energy storage configuration subsystem and the transmission relationship with the grid by analyzing the SOC of the distributed energy storage power, so as to achieve a balance between power supply and demand. This includes analyzing the battery's state of charge (SOC) to determine the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid. Specifically, this includes: Peak-valley arbitrage and surplus electricity grid connection mode, which analyzes the relationship between photovoltaic power generation, load power and battery power, and combines real-time electricity price to realize the peak-valley arbitrage mode of grid connection control subsystem; The specific strategies are as follows: When the generating power equals the load power: If the power grid has low electricity prices, take appropriate action based on the battery capacity: A1. If the battery capacity is below the usable capacity range, the power grid will charge the battery; wherein, the usable capacity range is 20%-90% of the battery capacity. B1. The battery is within its operating capacity range, and the power grid is charging the battery with a constant current. C1. The battery is above its operating capacity and does not function; If the power grid experiences high electricity prices, take appropriate action based on the battery capacity: A2. The battery is below its operating capacity, and the power grid does not activate; B2. The battery is within its operating capacity range and is discharging at a constant power. C2. The battery is above its operating capacity range, and the battery is discharging at a constant power. When the power generation capacity is greater than the load capacity: If the power grid has low electricity prices, take appropriate action based on the battery capacity: A3. When the battery capacity is lower than the usable capacity range, the remaining power generation capacity is used to charge the battery with constant current, and the remaining power is sent to the grid. B3. If the battery capacity exceeds the operating range, the battery will not operate, and all the excess power generated will be fed into the grid. If the power grid experiences high electricity prices, take appropriate action based on the battery capacity: A4. When the battery capacity is within the usable capacity range, the surplus power generated will be sent to the grid. The portion of the battery capacity exceeding the set capacity will also be sent to the grid. B4. If the battery capacity is lower than the set capacity, all surplus power will be fed into the grid. Specifically, the analysis of the battery's SOC to determine the subsequent charging and discharging actions of the energy storage subsystem and its transmission relationship with the grid also includes: Power support mode, which means that when the power supply of the photovoltaic subsystem is unstable, the battery capacity is used as a backup power source to maximize the storage of electrical energy in the battery for unforeseen needs. The specific strategies are as follows: When the generating power equals the load power: A5. If the battery capacity is lower than the set maximum capacity, the power grid will charge each battery with a constant current. B5. The battery does not operate if the battery capacity is greater than or equal to the set maximum capacity. When the power generation is less than the load power: A6. If the battery charge is below the minimum value, the power grid will provide the missing power to the load; B6. If the battery capacity is within the usable capacity range, the power grid will charge the battery with constant current while simultaneously meeting the power demand of the load side; C6. When the battery capacity exceeds the set maximum capacity, the portion exceeding the set capacity is discharged to the load at constant power, while the remainder is powered by the power grid.

10. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements a distributed energy cloud management method according to any one of claims 1 to 8.

11. 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 a distributed energy cloud management method according to any one of claims 1 to 8.

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