Design of Energy Internet Power Information Management System Based on Genetic Algorithm

Aiming at the optimization problem of power information management system (PIMS) of energy Internet, this paper proposes a system design method based on Genetic Algorithm (GA). By simulating the mechanism of biological evolution, this method solves complex problems in power system by global search and optimization. In the experimental design, the real-time data of simulated power system are used, including energy output, load demand, energy storage equipment status and so on. By simulating multi-generation GA optimization in the experimental environment and comparing with the traditional algorithm, detailed experimental results are obtained. The experimental results show that PIMS based on GA is obviously superior to the traditional algorithm in energy utilization efficiency. Through the dynamic adjustment of fitness function and the flexible application of genetic operation, GA successfully found good solutions under multiple optimization objectives, and improved the efficiency of the whole system. At the same time, we observe that the system based on GA has better robustness in dealing with system uncertainties and dynamic changes. By comparing this method with the traditional algorithm, we emphasize the superiority of GA in solving complex problems in PIMS. This study provides a feasible and effective system design and optimization method for the future development of energy Internet.