Abstract

This paper presents an efficient and reliable evolutionary-based approach to solve the optimal reactive power dispatch (ORPD) problem. Optimal reactive power dispatch is a mixed integer, nonlinear optimization problem which includes both continuous and discrete control variables. The proposed approach employs Ensemble of Mutation and Crossover Strategies and Parameters in Differential Evolution (EPSDE) algorithm for optimizing a set of reactive power control variables such as generator voltages, tap positions of tap changing transformers and the amount of reactive compensation which maximizes reactive reserve available at generating buses. Voltage dependent reactive power limits have been accounted. Developed algorithm accounts inequality constraints not only in present operating conditions (after reactive power rescheduling) but also for predicted next interval load (with reactive power rescheduling). Proposed methodology has been implemented on IEEE 14-bus and 25-bus test systems. Performance of the methodology has been compared with Selfadaptive Differential Evolution (SaDE), Teaching Learning Based Optimization (TLBO) and Genetic Algorithm (GA) techniques based on statistical inference.

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