Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems

• Published in: Energy conversion and management Vol. 86; pp. 548 - 560
• Main Authors: Chen, Gonggui, Liu, Lilan, Song, Peizhu, Du, Yangwei
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.10.2014; Elsevier
• Subjects: Applied sciences; Buses (vehicles); Chaos theory; Chaotic improved PSO-based multi-objective optimization; Constrain-prior Pareto-dominance method; Crossover operator; Energy; Exact sciences and technology; L index; Minimization; Multi-objective optimal reactive power dispatch; Optimization; Pareto optimal; Pareto optimality; Power loss; Power losses; Searching; Voltage stability; L index; Multi-objective optimal reactive power dispatch; Power losses; Constrain-prior Pareto-dominance method; Pareto optimal; Chaotic improved PSO-based multi-objective optimization; Crossover operator; Reactive power; Improvement; Minimization; Indicator; Optimization
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2014.06.003

•New method for MOORPD problem using MOCIPSO and MOIPSO approaches.•Constrain-prior Pareto-dominance method is proposed to meet the constraints.•The limits of the apparent power flow of transmission line are considered.•MOORPD model is built up for MOORPD problem.•The achieved results by MOCIPSO and MOIPSO approaches are better than MOPSO method. Multi-objective optimal reactive power dispatch (MOORPD) seeks to not only minimize power losses, but also improve the stability of power system simultaneously. In this paper, the static voltage stability enhancement is achieved through incorporating L index in MOORPD problem. Chaotic improved PSO-based multi-objective optimization (MOCIPSO) and improved PSO-based multi-objective optimization (MOIPSO) approaches are proposed for solving complex multi-objective, mixed integer nonlinear problems such as minimization of power losses and L index in power systems simultaneously. In MOCIPSO and MOIPSO based optimization approaches, crossover operator is proposed to enhance PSO diversity and improve their global searching capability, and for MOCIPSO based optimization approach, chaotic sequences based on logistic map instead of random sequences is introduced to PSO for enhancing exploitation capability. In the two approaches, constrain-prior Pareto-dominance method (CPM) is proposed to meet the inequality constraints on state variables, the sorting and crowding distance methods are considered to maintain a well distributed Pareto optimal solutions, and moreover, fuzzy set theory is employed to extract the best compromise solution over the Pareto optimal curve. The proposed approaches have been examined and tested in the IEEE 30 bus and the IEEE 57 bus power systems. The performances of MOCIPSO, MOIPSO, and multi-objective PSO (MOPSO) approaches are compared with respect to multi-objective performance measures. The simulation results are promising and confirm the ability of MOCIPSO and MOIPSO approaches for generating lower power losses and smaller L index than MOPSO method.