Performance assessment of PSO, DE and hybrid PSO–DE algorithms when applied to the dispatch of generation and demand

• Published in: International journal of electrical power & energy systems Vol. 47; pp. 205 - 217
• Main Authors: Araújo, Thaís de Fátima, Uturbey, Wadaed
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.05.2013; Elsevier
• Subjects: Applied sciences; Demand dispatch; Differential evolution algorithm; Electrical engineering. Electrical power engineering; Electrical power engineering; Evolutionary algorithms comparison; Exact sciences and technology; Hybrid evolutionary algorithm; Operation. Load control. Reliability; Particle swarm optimization; Power networks and lines; South America; Brazil; America; Demand dispatch; Evolutionary algorithms comparison; Differential evolution algorithm; Hybrid evolutionary algorithm; Particle swarm optimization; Performance evaluation; Dispatching problem; Costs; Evolutionary algorithm; Optimization method; Load flow; Bus system; Supply demand balance; Algorithm performance; Power flow; Optimal solution; Inequality constraint; Equality constraint; Analytical method; Load management; IEEE standards; Comparative study
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2012.11.002

► Stochastic optimization algorithms results must be presented using statistical tools. ► Box plots as aiding tools to define search space strategy in evolutionary algorithms. ► Evaluation of simultaneous generation and demand dispatch via evolutionary algorithms. ► A hybrid algorithm from PSO and DE that has better performance is examined. This work presents a comparison of three evolutionary algorithms, the particle swarm optimization, the differential evolution algorithm and a hybrid algorithm derived from the previous, when applied to the generation and demand dispatch problem. An optimization problem is formulated in the context of a small grid with partially flexible demand that can be shifted along a time horizon. It is assumed that grid operator dispatches generation and flexible demand along the time horizon aiming at minimizing generation costs. Consumption restrictions associated with flexible demand are modeled by equality and inequality energy constraints. Power flow equality constraints and inequality constraints due to operational limits for each dispatch interval are represented. The paper discusses a methodology for evolutionary algorithms performance assessment and states the importance of using statistical tools. The comparison is initially conducted using the IEEE 30-bus test system. Problem dimension effect is addressed considering different number of dispatch intervals in the time horizon. Moreover, the algorithms are applied to the 192-bus system of a Brazilian distribution utility, in the particular context of a load management program for large consumers of the company. In this application, the quality of the near-optimal solution obtained with the stochastic algorithms is evaluated by comparing with an analytical optimization algorithm solution.