Fuzzy Multi-Objective Optimization Considering the Uncertainty of Distributed Generation

Distributed generation makes distribution network become more complex and requirements of distribution system become higher. Due to the uncertainty of distributed new energy, applying traditional heuristic algorithms or intelligent algorithms to distribution network reconfiguration is less stable and may fall into the local optimum, which affects the rapidity and reliability of net-work programming. In this paper, the original nonlinear reconfiguration model is converted into a mixed-integer second-order cone model by second-order cone relaxation. By deriving the re-Iaxation conditions such as phase angle relaxation and second-order cone relaxation in the model power flow equation, the reconstruction model of multi-source distribution network based on second-order cone relaxation is constructed, and MATLAB/CPLEX is used to realize the fast operation. The model is simulated based on the triangular fuzzy theory with the objective function of minimizing the network loss and the main grid power purchase, the multi-objective Pareto front and objective function boundary values are obtained considering the uncertainty of distributed power supply and load. It is verified through simulation that economic reconfiguration through method of this paper can effectively can reduce the network loss, improve the distribution of the system currents, and enhance the system economy.