Multi-Agent Setting Calculation Task Integrated Scheduling Method for Massive Distributed New Energy Accessing to Power Distribution Network

Integrated with new energy, the distribution network system has the ability for large-scale comprehensive control. It is more complex in the dispatching energy ability, especially for the task of setting calculation of distribution switches, which requires a high response and accurate control effect. It is difficult to use the traditional dispatching command operation strategy to meet the current distribution network environment of multi-distributed energy access. Thus, it is necessary to formulate a strategy to select multi-energy cooperative operations to improve the distribution plan and command operation strategy. To further improve the resource utilization efficiency of new energy and ensure the safe and stable operation of the distribution system, it is compulsory to accurately calculate the setting in time and space. This paper analyzes the topology control mechanism of the overall energy system and accurately determines the mutual compensation between the formation of new energy and traditional energy. The generation energy output model of each distributed new energy unit in the distribution network system is constructed, and the objective function is set to minimize the operation and management setting calculation method of the microgrid. We consider the fuzzy conditions of the peak value of the output power of the distribution network, the balance between supply and demand, and the power output capacity of the new energy at the same time, so that the fuzzy decision-making dispatching model of the distribution network is established. Through the optimized dispatching and command strategy, the system can find the balance point between energy supply and demand, promote the mutual compensation of new energy systems, and improve the power distribution efficiency. The simulation results have shown that the algorithm performance in this paper is improved by 17.2 % compared with the traditional LSTM algorithm, and the response speed and prediction accuracy of the model have great technical advantages, which plays a technical support role in the development of power distribution network and can promote the future power and related industries.