Based on the research on the basis of analyzing the mechanism of polynomial fitting model, The polynomial fitting model or method was established based on intelligent optimization algorithm. The proposed method was applied to electric power system load forecasting, by a practical example’s calculation and analysis, this proposed intelligent optimization algorithm or method was verified to be feasible in the power system load forecasting, the results also showed that the method was compared with the traditional algorithm has superiority and has a broad application prospect in the field of polynomial fitting.

Multi-objective optimization model on sitting and sizing of Distributed Generation (DG) was proposed in this paper, and it was based on the comprehensive consideration of total system network loss and total deviation of node voltage, aiming at the optimization of DG’s access, the simulation tests were carried out on the 13 bus test system using Particle Swarm Optimization (PSO) algorithm that belonged to swarm intelligence algorithm, receiving the improved network loss and node voltage as the evaluation index, the mutation operator was introduced into the basic PSO algorithm, which improved the possibility to find a more optimal value ,the results showed that IPSO algorithm had strong global searching ability and rapid convergence speed for optimal allocation of Distributed Generation in the distribution network, and it created a new idea for further Distributed Generation allocation.