Notice of Violation of IEEE Publication Principles - Security-Boundary Constrained Optimal Power Flow Based on Adaptive Neuro-Fuzzy Inference Systems

Abstract

In optimal power flow problems, the determination of constraints plays a vital role to ensure the stability and security of a power system. This paper proposes a new approach to construct security- boundary constrained optimal power flow (SBC-OPF) model based on adaptive neuro-fuzzy inference systems (ANFIS) representation of the system security boundary (SB). In the stage of determining the OPF constraint, a closed form, differentiable function derived from the system's SB by ANFIS is used to represent security constraints in a OPF model, thereby solving the OPF model. The effectiveness and feasibility of the proposed ANFIS method is demonstrated through testing and simulation using the IEEE two-area benchmark system. Results show that the ANFIS method provides brand- new thought for SBC-OPF analysis, and is feasible and efficient.