Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2

fuel cost Related Publications

2 Solution Economic Power Dispatch Problems by an Ant Colony Optimization Approach

Authors: Mojtaba Hakimzadeh, Navid Mehdizadeh Afroozi, Khodakhast Isapour, Abdolmohammad Davodi

Abstract:

The objective of the Economic Dispatch(ED) Problems of electric power generation is to schedule the committed generating units outputs so as to meet the required load demand at minimum operating cost while satisfying all units and system equality and inequality constraints. This paper presents a new method of ED problems utilizing the Max-Min Ant System Optimization. Historically, traditional optimizations techniques have been used, such as linear and non-linear programming, but within the past decade the focus has shifted on the utilization of Evolutionary Algorithms, as an example Genetic Algorithms, Simulated Annealing and recently Ant Colony Optimization (ACO). In this paper we introduce the Max-Min Ant System based version of the Ant System. This algorithm encourages local searching around the best solution found in each iteration. To show its efficiency and effectiveness, the proposed Max-Min Ant System is applied to sample ED problems composed of 4 generators. Comparison to conventional genetic algorithms is presented.

Keywords: Algorithm, Ant colony optimization, fuel cost, Economic Dispatch (ED)

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1 Genetic Algorithm for Solving Non-Convex Economic Dispatch Problem

Authors: Mojtaba Hakimzadeh, Navid Javidtash, Abdolmohamad Davodi, Abdolreza Roozbeh

Abstract:

Economic dispatch (ED) is considered to be one of the key functions in electric power system operation. This paper presents a new hybrid approach based genetic algorithm (GA) to economic dispatch problems. GA is most commonly used optimizing algorithm predicated on principal of natural evolution. Utilization of chaotic queue with GA generates several neighborhoods of near optimal solutions to keep solution variation. It could avoid the search process from becoming pre-mature. For the objective of chaotic queue generation, utilization of tent equation as opposed to logistic equation results in improvement of iterative speed. The results of the proposed approach were compared in terms of fuel cost, with existing differential evolution and other methods in literature.

Keywords: Optimization, genetic algorithm (GA), fuel cost, Economic Dispatch(ED)

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