Power System Load Flow Distribution Research Based on Adaptive Neuro-Fuzzy Inference Systems

In the distribution of system load flow, various kinds of constraints must be satisfied. However, the determination of constraints plays a vital role to ensure the stability and security of a power system. This paper proposes a new load flow distribution model, which is based on the optimal power flow (OPF) and construct system security boundary (SB) constraints based on adaptive neuro-fuzzy inference systems (ANFIS). A differentiable function derived from the system´s SB by ANFIS is used to represent security constraints in a OPF model. According to the test and simulation of the IEEE two-area benchmark system, the effectiveness and feasibility of the proposed ANFIS method is demonstrated. Results show that the ANFIS method provides brand- new thought for the distribution of system load flow, and is feasible and efficient.