Research on Dynamic Measurement System of Electrical Equipment Parameters Based on Fruit Fly Optimization Algorithm

With the continuous expansion of AC/DC interconnection scale of modern power system, a large number of renewable energy sources and energy storage devices, and the large-scale application of new components, the simulation of power system will become more and more complicated. Firstly, the basic theoretical knowledge of Fruit Fly Optimization Algorithm (FOA) is deeply studied. Aiming at its shortcomings, such as low mutation probability of search range, poor diversity of individual population, possibility of missing the optimal solution, low optimization accuracy and easy to fall into local optimum, a multi-population fusion FOA (MFOA) is proposed, which adopts strategies such as multi-population, revising evaluation function, dynamically shrinking search radius and adding local search to improve the convergence accuracy and the ability to jump out of local optimum. In order to obtain the real-time status of electrical equipment and improve the service life of equipment, a dynamic measurement algorithm of electrical equipment parameters based on component model is proposed. By analyzing the occlusion of electrical equipment, component areas are selected. Experiments show that the proposed method can accurately measure the specific parameters of electrical equipment, and has the advantage of high measurement efficiency.