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ieijqp 2013, 1(2): 38-48 Back to browse issues page
Solving Reactive power dispatch and planning via multi objective Pareto Honey Bee Mating Optimization based fuzzy theory
Abstract:   (17903 Views)
The key of Reactive Power Planning (RPP), or Var planning and reactive power dispatch, are the optimal allocation of reactive power sources considering location and size. Traditionally, the locations for placing new Var sources were either simply estimated or directly assumed. Recent research works have presented some rigorous optimization based methods in RPP. The reactive power dispatch and planning is a large-scale non-convex, nonlinear programming (NLP) problem with real and discrete variables that presents a high degree of complexity for application in real electric power systems (EPS). This paper addresses an improved Honey Bee Mating Optimization (HBMO) with strength Pareto front to find the feasible optimal solution of the RPP problem with various generator constraints in power systems. For practical generator operation, many nonlinear constraints of the generator, such as ramp rate limits, generation limits, transmission line loss and non-smooth cost functions are all considered using the proposed method. Effectiveness of the proposed method is demonstrated for two different systems, including 6 and 54 unit generating in comparison with the performance of the other recently optimization algorithms reported in the literature in terms of the solution quality and computation efficiency. The results analysis confirms that the proposed approach has an excellent capability to determine optimal solution of the RPP problems over the other existing methods and enhances efficiently the solutions quality of the power systems.
Keywords: HBMO, Pareto front, Optimization, Reactive power planning, Non-linear constrains.
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Type of Study: Research | Subject: Special
Received: 2012/11/28 | Accepted: 2013/03/3 | Published: 2013/03/3

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Solving Reactive power dispatch and planning via multi objective Pareto Honey Bee Mating Optimization based fuzzy theory. ieijqp. 2013; 1 (2) :38-48
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Volume 1, Issue 2 (2-2013) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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