Optimal Dispatching of Active Distribution Network Based on Improved Genetic Algorithm

With the development of the global energy Internet, the framework of large power grid has been developed rapidly, but the operation of a large power grid will cause voltage and frequency fluctuations due to the changes in the regional power grid or local power grid load. When external interference occurs, the grid connected microgrid can be switched to island mode for maintenance, that is, the start time and its duration are uncertain, which greatly reduces the use effect of distributed generation. The improvement of the load forecasting ability of the active distribution network further raises the ability of the micro-grid to participate in the load forecasting control of the main grid. In this paper, a genetic algorithm is adopted to optimize the initial population to strengthen the accuracy of prediction. At the same time, the advantages of an improved genetic algorithm and a cuckoo algorithm are complementary. The advantages of the two intelligent algorithms are combined to jointly optimize the iterative optimization results. The simulation of the test function verifies that the optimization based on the improved genetic algorithm has a better optimal value and faster convergence speed compared with other algorithms. It not only increases the security of the power system and the ability to withstand the impact of the power system, but also reduces the accident rate and economic losses in a great sense.