Intelligent dispatching system and method for wind-photovoltaic micro-grid

Abstract

The invention relates to the field of micro-grids, and discloses an intelligent dispatching system and method for a wind-photovoltaic micro-grid, and the method comprises the steps: building a load historical database, obtaining load characteristics according to a load dispatching period and load historical data, and obtaining a power output planning strategy according to the load characteristics and power output data; the distributed power supply output planning module obtains a distributed power supply output planning strategy according to distributed power supply output distribution in the power supply output planning strategy, and schedules each distributed power supply according to the distributed power supply output planning strategy; and the output of each distributed power supply is obtained, the balance index of the power supply output and the load is obtained according to the load data, if the balance index is within the balance index threshold range, the power supply output and the load are balanced, and intelligent scheduling of the wind-photovoltaic micro-grid is completed. According to the method, the power output planning strategy can be dynamically adjusted, the uncertainty of wind and photovoltaic resources and the fluctuation of loads can be effectively dealt with, and the flexibility and the self-adaptability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the field of microgrids, and in particular to an intelligent dispatching system and method for a wind-photovoltaic microgrid. Background Art

[0002] With the transformation of the global energy structure and the rapid development of renewable energy, wind and solar energy, as clean and renewable energy forms, are increasingly widely used in power systems. As a small power system integrating distributed energy sources such as wind and solar energy, wind photovoltaic microgrids can not only effectively utilize renewable energy and improve energy efficiency, but also provide emergency power supply in the event of grid failure, thereby enhancing the reliability and resilience of the power system. However, the operation and management of wind photovoltaic microgrids face many challenges, especially how to achieve intelligent scheduling between distributed power sources (such as wind turbines and photovoltaic panels) and loads to ensure stable operation of the system and efficient use of energy.

[0003] Traditional microgrid dispatching methods often rely on manual experience or simple rule control, which is difficult to adapt to the uncertainty of wind and photovoltaic resources and the volatility of load. The output of wind and solar energy is greatly affected by weather conditions, and is intermittent and random, while load demand may also change due to factors such as season, weather, and time. This uncertainty on both the supply and demand sides requires the microgrid dispatching system to have a high degree of flexibility and adaptability, and be able to adjust the power output in real time to meet the load demand while ensuring the economy and reliability of the system.

[0004] In the existing technology, some microgrid dispatching systems try to estimate future wind and photovoltaic output and load demand through prediction algorithms, but the prediction accuracy is limited by many factors, such as the accuracy of meteorological data, the effectiveness of prediction models, etc. In addition, even if the prediction is accurate, how to formulate a reasonable power output planning strategy based on the prediction results and dynamically adjust it according to real-time conditions in actual operation is also a major problem. Summary of the invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an intelligent dispatching method for a wind-photovoltaic microgrid, comprising the following steps: Step 1: Establish a load history database, obtain load characteristics based on load scheduling cycle and load history data, and obtain power output planning strategy based on load characteristics and power output data; Step 2: The distributed power output planning module obtains the power generation data of each distributed power source according to the distributed power output allocation in the power output planning strategy. The distributed power output planning module obtains the distributed power output planning strategy according to the power generation data of each distributed power source and the distributed power output planning, and dispatches each distributed power source according to the distributed power output planning strategy; Step 3, obtaining the output of each distributed power source, and obtaining the balance index between the power source output and the load according to the load data. If the balance index is within the balance index threshold range, the power source output and the load are balanced, and the process goes to step 7; otherwise, the process goes to step 4; Step 4: determine the type of imbalance according to the balance index between the power output and the load. If the power output is unbalanced, proceed to step 5; if the load is unbalanced, proceed to step 6. Step 5: Collect the output data of each distributed power source, obtain the output gap of the distributed power source according to the distributed power source output in the initial distributed power source output planning strategy and the output data of each distributed power source, generate the energy storage module output scheduling strategy according to the output gap of the distributed power source, schedule the output of the energy storage module, and return to step 3; Step 6: Collect the output data of each distributed power source, obtain the excess output of the distributed power source according to the distributed power source output in the initial distributed power source output planning strategy and the output data of each distributed power source, generate the energy storage module energy storage scheduling strategy according to the excess output of the distributed power source, and schedule the energy storage module to supplement the load, and return to step 3; Step seven: Complete the intelligent dispatching of wind and photovoltaic microgrids.

[0006] Furthermore, the load characteristics are obtained according to the load dispatch cycle and the load historical data, including: The load scheduling cycle is the set execution cycle of the power supply planning output strategy; the load history data is the load data of a selected number of load scheduling cycles, and the load characteristics of the load range and time granularity are obtained according to the load data of each selected load scheduling cycle; The load characteristics of the time granularity are: the load average value and the load variation range according to the selected number of load scheduling cycles at the same time granularity. The load average value and the load variation range greater than the load average value constitute the load characteristics of the time granularity.

[0007] Furthermore, the power output planning strategy is obtained according to the load characteristics and power output data, including: According to the load average value in the load characteristics of time granularity, it is allocated to the dispatchable power source for output, and the load variation range greater than the load average value is allocated to the distributed power source for output; The dispatchable power output allocation and distributed power output allocation at each time granularity constitute the power output planning strategy.

[0008] Furthermore, the distributed power output planning module obtains a distributed power output planning strategy according to the power generation data of each distributed power source and the distributed power output planning, including: According to the output allocation of distributed power sources at time granularity, the power generation data of each distributed power source at the same time granularity are obtained respectively. According to the set output ratio, the output ratio of each distributed power source at the corresponding time granularity is obtained. According to the output ratio of each distributed power source at each corresponding time granularity, a distributed power source output planning strategy is constructed.

[0009] Furthermore, the output of each distributed power source is obtained, and a balance index between the power source output and the load is obtained according to the load data, including: The ratio of the sum of the output of each distributed power source and the output of the dispatchable power source to the load is used to obtain the balance index between the power source output and the load.

[0010] Furthermore, judging the type of imbalance according to the balance index between the power output and the load includes: If the balance index between the power output and the load is less than the balance index threshold, the power output is unbalanced; if the balance index between the power output and the load is greater than the balance index threshold, the load is unbalanced.

[0011] Furthermore, the generation of the energy storage module output dispatching strategy according to the output gap of the distributed power source includes: dispatching the corresponding output of the energy storage module to supplement the output according to the output gap of the distributed power source.

[0012] Furthermore, the generation of an energy storage scheduling strategy for the energy storage module according to the excess output of the distributed power source includes: scheduling the load corresponding to the energy storage module according to the excess output of the distributed power source to store and consume the energy.

[0013] An intelligent dispatching system for a wind-photovoltaic microgrid, applying the intelligent dispatching method for a wind-photovoltaic microgrid, comprising a load management module, a microgrid dispatching module, a distributed power output planning module, a cloud data server, an energy storage module, a communication module and a data processing module; The load management module, microgrid dispatching module, distributed power output planning module and communication module are respectively connected to the data processing module; the cloud data server is communicatively connected to the communication module; and the energy storage module is connected to the microgrid dispatching module.

[0014] The beneficial effects of the present invention are: Improving system flexibility and adaptability: By establishing a load history database and real-time monitoring of power output, the present invention can dynamically adjust the power output planning strategy, effectively deal with the uncertainty of wind and photovoltaic resources and the volatility of loads, and improve the flexibility and adaptability of the system.

[0015] Optimize energy utilization efficiency: By reasonably allocating the output of dispatchable power sources and distributed power sources, and using energy storage modules to supplement output and store energy, the present invention can maximize the use of renewable energy, reduce dependence on traditional energy, and improve energy utilization efficiency.

[0016] Enhance system stability and reliability: By real-time monitoring of the balance between power output and load, and timely adjusting the scheduling strategy of power output and energy storage modules, the present invention can effectively avoid system instability problems caused by insufficient or excessive power output, and enhance system stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a flow chart of an intelligent dispatching method for a wind-photovoltaic microgrid; Figure 2 This is a schematic diagram of the distributed generation output planning strategy flow. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0019] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0020] like Figure 1 As shown, a smart dispatching method for a wind photovoltaic microgrid comprises the following steps: Step 1: Establish a load history database, obtain load characteristics based on load scheduling cycle and load history data, and obtain power output planning strategy based on load characteristics and power output data; Step 2: The distributed power output planning module obtains the power generation data of each distributed power source according to the distributed power output allocation in the power output planning strategy. The distributed power output planning module obtains the distributed power output planning strategy according to the power generation data of each distributed power source and the distributed power output planning, and dispatches each distributed power source according to the distributed power output planning strategy; Step 3, obtaining the output of each distributed power source, and obtaining the balance index between the power source output and the load according to the load data. If the balance index is within the balance index threshold range, the power source output and the load are balanced, and the process goes to step 7; otherwise, the process goes to step 4; Step 4: determine the type of imbalance according to the balance index between the power output and the load. If the power output is unbalanced, proceed to step 5; if the load is unbalanced, proceed to step 6. Step 5: Collect the output data of each distributed power source, obtain the output gap of the distributed power source according to the distributed power source output in the initial distributed power source output planning strategy and the output data of each distributed power source, generate the energy storage module output scheduling strategy according to the output gap of the distributed power source, schedule the output of the energy storage module, and return to step 3; Step 6: Collect the output data of each distributed power source, obtain the excess output of the distributed power source according to the distributed power source output in the initial distributed power source output planning strategy and the output data of each distributed power source, generate the energy storage module energy storage scheduling strategy according to the excess output of the distributed power source, and schedule the energy storage module to supplement the load, and return to step 3; Step seven: Complete the intelligent dispatching of wind and photovoltaic microgrids.

[0021] The load characteristics are obtained according to the load dispatch cycle and the load historical data, including: The load scheduling cycle is the set execution cycle of the power supply planning output strategy; the load history data is the load data of a selected number of load scheduling cycles, and the load characteristics of the load range and time granularity are obtained according to the load data of each selected load scheduling cycle; The load characteristics of the time granularity are: the load average value and the load variation range according to the selected number of load scheduling cycles at the same time granularity. The load average value and the load variation range greater than the load average value constitute the load characteristics of the time granularity.

[0022] The power output planning strategy is obtained according to the load characteristics and power output data, including: According to the load average value in the load characteristics of time granularity, it is allocated to the dispatchable power source for output, and the load variation range greater than the load average value is allocated to the distributed power source for output; The dispatchable power output allocation and distributed power output allocation at each time granularity constitute the power output planning strategy.

[0023] like Figure 2 As shown, the distributed power output planning module obtains a distributed power output planning strategy according to the power generation data of each distributed power source and the distributed power output planning, including: According to the output allocation of distributed power sources at time granularity, the power generation data of each distributed power source at the same time granularity are obtained respectively. According to the set output ratio, the output ratio of each distributed power source at the corresponding time granularity is obtained. According to the output ratio of each distributed power source at each corresponding time granularity, a distributed power source output planning strategy is constructed.

[0024] The method of obtaining the output of each distributed power source and obtaining the balance index between the power source output and the load according to the load data includes: The ratio of the sum of the output of each distributed power source and the output of the dispatchable power source to the load is used to obtain the balance index between the power source output and the load.

[0025] The method of judging the type of imbalance according to the balance index between the power output and the load includes: If the balance index between the power output and the load is less than the balance index threshold, the power output is unbalanced; if the balance index between the power output and the load is greater than the balance index threshold, the load is unbalanced.

[0026] The generating of the energy storage module output dispatching strategy according to the output gap of the distributed power source includes: dispatching the corresponding output of the energy storage module to supplement the output according to the output gap of the distributed power source.

[0027] The generation of the energy storage scheduling strategy for the energy storage module according to the excess output of the distributed power source includes: scheduling the load corresponding to the energy storage module according to the excess output of the distributed power source to store and consume the energy.

[0028] An intelligent dispatching system for a wind-photovoltaic microgrid, applying the intelligent dispatching method for a wind-photovoltaic microgrid, comprising a load management module, a microgrid dispatching module, a distributed power output planning module, a cloud data server, an energy storage module, a communication module and a data processing module; The load management module, microgrid dispatching module, distributed power output planning module and communication module are respectively connected to the data processing module; the cloud data server is communicatively connected to the communication module; and the energy storage module is connected to the microgrid dispatching module.

[0029] The present invention provides an intelligent dispatching method for a wind-photovoltaic microgrid, the method comprising the following steps: Step 1: Establish a load history database and formulate a power output planning strategy Establish a load history database: Collect and store the load data of the microgrid over a period of time to form a load history database. These data include but are not limited to daily, weekly or monthly load changes, and the impact of specific events (such as holidays and extreme weather) on the load.

[0030] According to the load dispatch cycle and load historical data, load characteristics are obtained: Load dispatch cycle: set as the time interval for executing the power supply planning output strategy, such as every hour, every half day or every day. Load historical data: select the load data of the latest several load dispatch cycles as the basis for analysis.

[0031] Load characteristics: including load range (i.e. maximum load and minimum load) and load characteristics of time granularity. Load characteristics of time granularity refer to the calculation of the average value of the load in the selected period and the load variation range (i.e. the difference between the maximum and minimum values) at the same time granularity (such as the same hour of each day).

[0032] According to the load characteristics and power output data, the power output planning strategy is obtained: Power output data: including the output capacity of dispatchable power sources (such as gas generators, diesel generators) and distributed power sources (such as wind turbines, photovoltaic panels).

[0033] Power output planning strategy: Based on the load characteristics of time granularity, the average load value is allocated to the dispatchable power source for basic output, and the load variation range greater than the average load value is allocated to the distributed power source, using its flexibility and renewability to cope with load fluctuations. In this way, the stable supply of basic load is guaranteed, and the advantages of distributed energy are fully utilized.

[0034] Step 2: Distributed power output planning Distributed power output planning module: This module is responsible for obtaining the power generation data of each distributed power source in real time according to the distributed power output allocation in the power output planning strategy.

[0035] Obtain the distributed power output planning strategy: According to the distributed power output allocation of time granularity, obtain the actual power generation data of each distributed power source with the same time granularity. According to the set output ratio (considering the capacity, efficiency, operating status and other factors of the distributed power source), calculate the output ratio of each distributed power source at the corresponding time granularity. Based on these output ratios, form a distributed power output planning strategy to guide the actual output of each distributed power source.

[0036] Step 3: Determine the balance between power output and load Obtain the output of each distributed power source: monitor and record the actual output of each distributed power source in real time. According to the load data, obtain the balance index of power output and load: calculate the sum of the output of each distributed power source and the output of the dispatchable power source. The ratio of this sum to the current load is used as the balance index of power output and load.

[0037] Step 4: Determine the type of imbalance According to the balance index of power output and load, the imbalance type is determined: if the balance index is less than the balance index threshold, it means that the power output is insufficient to meet the load demand, which is power output imbalance. If the balance index is greater than the balance index threshold, it means that the power output exceeds the load demand, which is load imbalance.

[0038] Step 5: Deal with power output imbalance Collect the output data of each distributed power source: reconfirm the actual output of each distributed power source. According to the distributed power output in the initial distributed power output planning strategy and the output data of each distributed power source, obtain the output gap of the distributed power source: calculate the difference between the actual output and the planned output, and determine the output gap. Generate the output scheduling strategy of the energy storage module: according to the output gap, formulate the output scheduling strategy of the energy storage module (such as battery pack, supercapacitor), and schedule the output of the energy storage module to supplement the insufficient power output. Return to step three: continue to monitor the balance between power output and load to ensure stable operation of the system.

[0039] Step 6: Dealing with load imbalance Collect the output data of each distributed power source: Similarly, reconfirm the actual output of each distributed power source. According to the distributed power output in the initial distributed power output planning strategy and the output data of each distributed power source, obtain the excess output of the distributed power source: calculate the part of the actual output that exceeds the planned output, and determine the excess output. Generate the energy storage scheduling strategy for the energy storage module: According to the excess output, formulate the energy storage scheduling strategy for the energy storage module, and schedule the energy storage module to supplement the load (that is, store excess electrical energy). Return to step three: Continue to monitor the balance between power output and load to optimize system operation efficiency.

[0040] Step 7: Complete the intelligent dispatch of wind and photovoltaic microgrids When the power output and load are balanced and the system operates stably for a period of time, the intelligent dispatching process of the wind-photovoltaic microgrid can be considered completed.

[0041] Example: Application of intelligent dispatching method of wind photovoltaic microgrid in remote area microgrid Step 1: Establish a load history database and formulate a power output planning strategy Establish a load history database: In remote microgrids, load data from the past two years have been collected and stored, including weekly load changes, as well as the impact of specific events (such as farming season, winter vacation) and extreme weather (such as heavy snow, drought) on load. According to the load scheduling cycle and load history data, load characteristics are obtained: the load scheduling cycle is set to every half day. The load data of the last 12 weeks are selected as the basis for analysis. The load range (maximum load and minimum load) for each half day is calculated, as well as the load characteristics of the time granularity, that is, the load average value and load change range of the same half day every week (such as Monday morning).

[0042] According to the load characteristics and power output data, the power output planning strategy is obtained: the power output data includes the output capacity of diesel generators, wind turbines and photovoltaic panels. Based on the load characteristics of time granularity, the load average value of each half day is allocated to the diesel generator for basic output, and the load variation range greater than the load average value is allocated to wind turbines and photovoltaic panels, using their flexibility and renewability to cope with load fluctuations.

[0043] Step 2: Distributed power output planning Distributed power output planning module: This module obtains the power generation data of wind turbines and photovoltaic panels in real time. Obtain the distributed power output planning strategy: According to the distributed power output allocation every half day, obtain the actual power generation data of wind turbines and photovoltaic panels at the same time granularity.

[0044] According to the set output ratio (taking into account the capacity, efficiency, operating status and other factors of wind turbines and photovoltaic panels), the output ratio of wind turbines and photovoltaic panels is calculated every half day. Based on these output ratios, a distributed power output planning strategy is formed to guide the actual output of wind turbines and photovoltaic panels.

[0045] Step 3: Determine the balance between power output and load Obtain the output of each distributed power source: monitor and record the actual output of wind turbines and photovoltaic panels in real time. According to the load data, obtain the balance index of power output and load: calculate the sum of the output of wind turbines, photovoltaic panels and diesel generators every half day. The ratio of this sum to the current load is used as the balance index of power output and load.

[0046] Step 4: Determine the type of imbalance If the balance index is less than the balance index threshold (such as 0.9), it means that the power output is insufficient to meet the load demand and the power output is unbalanced.

[0047] If the balance index is greater than the balance index threshold (such as 1.1), it means that the power output exceeds the load demand and the load is unbalanced.

[0048] Step 5: Deal with power output imbalance Collect output data of each distributed power source: confirm the actual output of wind turbines and photovoltaic panels again. Obtain the output gap of distributed power sources: calculate the difference between the actual output and the planned output, and determine the output gap. Generate the output scheduling strategy of energy storage modules: formulate the output scheduling strategy of supercapacitors according to the output gap, and schedule the output of supercapacitors to supplement the insufficient power output. Return to step 3: continue to monitor the balance between power output and load to ensure stable operation of the system.

[0049] Step 6: Dealing with load imbalance Collect output data of each distributed power source: Similarly, confirm the actual output of wind turbines and photovoltaic panels again. Obtain the excess output of distributed power sources: Calculate the portion of actual output that exceeds the planned output and determine the excess output. Generate energy storage scheduling strategy for energy storage modules: According to the excess output, formulate energy storage scheduling strategy for supercapacitors and schedule supercapacitors for load supplementation (i.e., store excess electrical energy). Return to step three: Continue to monitor the balance between power output and load to optimize system operation efficiency.

[0050] Step 7: Complete the intelligent dispatch of wind and photovoltaic microgrids When the power output and load are balanced and the system operates stably for a period of time, the intelligent dispatching process of the wind-PV microgrid is considered to be completed.

[0051] By implementing the method of the present invention, the remote area microgrid realizes intelligent scheduling of power output and load, improves the adaptability and economy of the system, reduces dependence on traditional energy, and improves the utilization rate of renewable energy.

Claims

1. An intelligent dispatching method for a wind-photovoltaic microgrid, characterized in that: The steps include: Step 1: Establish a load history database, obtain load characteristics based on load scheduling cycle and load history data, and obtain power output planning strategy based on load characteristics and power output data; Step 2: The distributed power output planning module obtains the power generation data of each distributed power source according to the distributed power output allocation in the power output planning strategy. The distributed power output planning module obtains the distributed power output planning strategy according to the power generation data of each distributed power source and the distributed power output planning, and dispatches each distributed power source according to the distributed power output planning strategy; Step 3, obtaining the output of each distributed power source, and obtaining the balance index between the power source output and the load according to the load data. If the balance index is within the balance index threshold range, the power source output and the load are balanced, and the process goes to step 7; otherwise, the process goes to step 4; Step 4: determine the type of imbalance according to the balance index between the power output and the load. If the power output is unbalanced, proceed to step 5; if the load is unbalanced, proceed to step 6. Step 5: Collect the output data of each distributed power source, obtain the output gap of the distributed power source according to the distributed power source output in the initial distributed power source output planning strategy and the output data of each distributed power source, generate the energy storage module output scheduling strategy according to the output gap of the distributed power source, schedule the output of the energy storage module, and return to step 3; Step 6: Collect the output data of each distributed power source, obtain the excess output of the distributed power source according to the distributed power source output in the initial distributed power source output planning strategy and the output data of each distributed power source, generate the energy storage module energy storage scheduling strategy according to the excess output of the distributed power source, and schedule the energy storage module to supplement the load, and return to step 3; Step seven: Complete the intelligent dispatching of wind and photovoltaic microgrids.

2. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 1 is characterized in that: The load characteristics are obtained according to the load dispatch cycle and the load historical data, including: The load scheduling cycle is the set execution cycle of the power supply planning output strategy; the load history data is the load data of a selected number of load scheduling cycles, and the load characteristics of the load range and time granularity are obtained according to the load data of each selected load scheduling cycle; The load characteristics of the time granularity are: the load average value and the load variation range according to the selected number of load scheduling cycles at the same time granularity. The load average value and the load variation range greater than the load average value constitute the load characteristics of the time granularity.

3. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 2 is characterized in that: The power output planning strategy is obtained according to the load characteristics and power output data, including: According to the load average value in the load characteristics of time granularity, it is allocated to the dispatchable power source for output, and the load variation range greater than the load average value is allocated to the distributed power source for output; The dispatchable power output allocation and distributed power output allocation at each time granularity constitute the power output planning strategy.

4. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 1, characterized in that: The distributed power output planning module obtains a distributed power output planning strategy based on the power generation data of each distributed power source and the distributed power output planning, including: According to the output allocation of distributed power sources at time granularity, the power generation data of each distributed power source at the same time granularity are obtained respectively. According to the set output ratio, the output ratio of each distributed power source at the corresponding time granularity is obtained. According to the output ratio of each distributed power source at each corresponding time granularity, a distributed power source output planning strategy is constructed.

5. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 4 is characterized in that: The method of obtaining the output of each distributed power source and obtaining the balance index between the power source output and the load according to the load data includes: The ratio of the sum of the output of each distributed power source and the output of the dispatchable power source to the load is used to obtain the balance index between the power source output and the load.

6. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 1, characterized in that: The method of judging the type of imbalance according to the balance index between the power output and the load includes: If the balance index between the power output and the load is less than the balance index threshold, the power output is unbalanced; if the balance index between the power output and the load is greater than the balance index threshold, the load is unbalanced.

7. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 1, characterized in that: The generating of the energy storage module output dispatching strategy according to the output gap of the distributed power source includes: dispatching the corresponding output of the energy storage module to supplement the output according to the output gap of the distributed power source.

8. The intelligent dispatching method of a wind-photovoltaic microgrid according to claim 1, characterized in that: The generation of the energy storage scheduling strategy for the energy storage module according to the excess output of the distributed power source includes: scheduling the load corresponding to the energy storage module according to the excess output of the distributed power source to store and consume the energy.

9. An intelligent dispatching system for wind and photovoltaic microgrids, characterized in that: An intelligent dispatching method for a wind-photovoltaic microgrid according to any one of claims 1 to 8 is applied, comprising a load management module, a microgrid dispatching module, a distributed power output planning module, a cloud data server, an energy storage module, a communication module and a data processing module; The load management module, microgrid dispatching module, distributed power output planning module and communication module are respectively connected to the data processing module; the cloud data server is communicatively connected to the communication module; and the energy storage module is connected to the microgrid dispatching module.

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