Multi-Objective Planning of Transfer Capacity Distribution System Based on ESGA Genetic Algorithm

With the unremittingly growth of power demand and the increasing complexity of the power system, the optimization of the transferring capacity of the distribution system is becoming more and more important. As a key element to ensure the stability and reliability of the power system, the optimization of transferring capacity is particularly important, especially when dealing with emergencies or power demand fluctuations. However, existing studies have limitations in multi-objective planning of distribution system transferring capacity, which is difficult to fully meet the actual needs of the power system. To address this problem, this paper presents a multi-objective optimization method for distribution system transfer capacity based on an progressd ESGA (Evolutionary Strategy Genetic Algorithm) genetic algorithm. The method realizes the multi-objective optimization of the switching capacity of the distribution system by introducing the ESGA algorithm and using its powerful global search capability and the flexibility of the fitness function. Through simulation experiments on real cases, this paper verifies the effectiveness and practicality of the proposed method. The experimental results show that when the power factor is lower than the preset threshold, the system parameters need to be adjusted or technical means need to be taken to progress the power factor; while when the energy loss is too high, it may be necessary to reduce the system energy loss by optimizing the current distribution and reducing the line loss.