Multi objective optimal reactive power dispatch using a new multi objective strategy

• This paper presents a novel multi objective CPVEIHBMO for RPD problem.
• The RPD problem is formulated as a nonlinear constrained multi objective optimization problem.
• The convergence speed of this algorithm is higher than other heuristics algorithms.
• We considered NDS mechanism and fuzzy theory.
• We considered chaotic theory to enhanced search ability.

This paper presents a new multi objective Chaotic Parallel Vector Evaluated Interactive Honey Bee Mating Optimization (CPVEIHBMO) to find the feasible optimal solution of the multi objective optimal reactive power dispatch (RPD) problem with considering operational constraints of the generators. The optimal RPD problem is an important issue with non-linear structure in power industry that consists of the continuous and discrete control variables. The proposed algorithm is applied to find the settings of continuous and discrete control variables such as tap positions of tap changing transformers, generator voltages, and the amount of reactive compensation devices to optimize three conflicting and non-commensurable objective functions: voltage deviation, the total voltage stability and real power loss. For achieve a good design with different solutions in a multi objective optimization problem, Pareto dominance concept is used to generate and sort the dominated and non-dominated solutions. Also, fuzzy set theory is employed to extract the best compromise solution. The propose method has been individually examined and applied to several test systems. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multi objective optimization algorithms. The computational results reveal that the proposed algorithm has excellent convergence characteristics and is superior to other multi objective optimization algorithms. Also, the results confirm its great potential in handling the multi objective problems in power systems.