Abstract
This study presents a novel hybrid multiobjective particle swarm optimization (HMOPSO) algorithm to solve the optimal reactive power dispatch (ORPD) problem. This problem is formulated as a challenging nonlinear constrained multiobjective optimization problem considering three objectives, that is, power losses minimization, voltage profile improvement, and voltage stability enhancement simultaneously. In order to attain better convergence and diversity, this work presents the use of combing the classical MOPSO with Gaussian probability distribution, chaotic sequences, dynamic crowding distance, and self-adaptive mutation operator. Moreover, multiple effective strategies, such as mixed-variable handling approach, constraint handling technique, and stopping criteria, are employed. The effectiveness of the proposed algorithm for solving the ORPD problem is validated on the standard IEEE 30-bus and IEEE 118-bus systems under nominal and contingency states. The obtained results are compared with classical MOPSO, nondominated sorting genetic algorithm (NSGA-II), multiobjective evolutionary algorithm based on decomposition (MOEA/D), and other methods recently reported in the literature from the point of view of Pareto fronts, extreme, solutions and multiobjective performance metrics. The numerical results demonstrate the superiority of the proposed HMOPSO in solving the ORPD problem while strictly satisfying all the constraints.
Highlights
The optimal reactive power problem (ORPD) has attracted great attention in the past decades because it can greatly improve economy and security of power system
Nondominated sorting genetic algorithm II (NSGA-II) [13], strength Pareto evolutionary algorithm 2 (SPEA2) [14], Pareto archive evolution strategy II (PAES-II) [15], and multiobjective evolutionary algorithm based on decomposition (MOEA/D) [16] are the representatives of the state of the art in this area
The effectiveness and efficiency of the proposed hybrid multiobjective particle swarm optimization (HMOPSO) algorithm for solving the optimal reactive power dispatch (ORPD) problem are tested on the standard IEEE 30-bus and 118-bus power systems and the results are compared with existing popular algorithms, MOPSO, NSGA-II, multiobjective evolutionary algorithms (MOEAs)/D, and other previous methods
Summary
The optimal reactive power problem (ORPD) has attracted great attention in the past decades because it can greatly improve economy and security of power system. In [27], three objectives including real transmission losses, voltage deviation, and L-index were considered to formulate multiobjective ORPD model and an opposition-based self-adaptive modified gravitational search algorithm (OSAMGSA) was proposed as a solution technique. In [28, 29], MOPSO was utilized to solve the multiobjective optimal power flow problem by considering generation cost, transmissions loss, voltage deviations, and other functions as objectives. A new hybrid MOPSO algorithm (HMOPSO) is proposed for solving the multiobjective ORPD problem, in which three competing objectives such as real power loss minimization, voltage profile improvement, and voltage stability enhancement are optimized simultaneously in a single run. The numerical results show the superiority of HMOPSO for handling the ORPD problem
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