A New Improved Hybrid Algorithm for Optimal Reactive Power Planning

Optimal reactive power planning is one of the most challenging problems in power system operation. Different techniques including classical and modern heuristic methods have been utilized to address the problem successfully. It is observed that success of heuristic techniques largely depends on the selection of some user defined control parameters. Multiple runs are required to find the optimal values of control parameters. Again these parameters are usually problem dependent. In other words, for different problems these parameters are to be selected separately. A wrong parameter selection may even lead to premature convergence. No specific rule is available for setting these parameters. A new improved hybrid algorithm for optimal reactive power planning (ORPP) problem using differential evolution combining with chaos theory is proposed in this paper. A self adaptive parameter automation strategy is adopted is this paper. For the present work, tent map chaotic sequence is used and the proposed technique is termed as tent map differential evolution (TMDE). Minimization of loss and system cost are taken into account in problem formulation. The proposed algorithm is applied on IEEE-30 bus system in order to verify its effectiveness and efficiency. A comparison result with other recent methods is presented which shows the capability of the proposed technique in producing good quality solutions.