Optimum Coordination of Directional Overcurrent Relays Using the Hybrid GA-NLP Approach

Abstract

The time of operation of overcurrent relays (OCRs) can be reduced, and at the same time, the coordination can be maintained, by selecting the optimum values of time multiplier setting (TMS) and plug setting (PS) of OCRs. This paper presents hybrid genetic algorithm (GA) - nonlinear programming (NLP) approach for determination of optimum values of TMS and PS of OCRs. GA has a drawback of, sometimes, converging to the values which may not be optimum, and NLP methods have a drawback of converging to local optimum values, if the initial choice is nearer to local optimum. This paper proposes a hybrid method to overcome the drawback of GA and NLP method, and determine the optimum settings of OCRs. The main contributions of this paper are - 1) systematic method for formulation of problem of determining optimum values of TMS and PS of OCRs in power distribution network as a constrained nonlinear optimization problem, 2) determining initial values of TMS and PS using GA technique and finding final (global optimum) values using NLP method, thus making use of the advantages of both methods (and at the same time overcoming the drawbacks of the methods).