A Honey Bee Foraging approach for optimal location of a biomass power plant

David Vera, Julio Carabias, Francisco Jurado and Nicolás Ruiz-Reyes

Applied Energy, 2010, vol. 87, issue 7, 2119-2127

Abstract: Over eight million hectares of olive trees are cultivated worldwide, especially in Mediterranean countries, where more than 97% of the world's olive oil is produced. The three major olive oil producers worldwide are Spain, Italy, and Greece. Olive tree pruning residues are an autochthonous and important renewable source that, in most of cases, farmers burn through an uncontrolled manner. Besides, industrial uses have not yet been developed. The aim of this paper consists of a new calculation tool based on particles swarm (Binary Honey Bee Foraging, BHBF). Effectively, this approach will make possible to determine the optimal location, biomass supply area and power plant size that offer the best profitability for investor. Moreover, it prevents the accurate method (not feasible from computational viewpoint). In this work, Profitability Index (PI) is set as the fitness function for the BHBF approach. Results are compared with other evolutionary optimization algorithms such as Binary Particle Swarm Optimization (BPSO), and Genetic Algorithms (GA). All the experiments have shown that the optimal plant size is 2 MW, PI = 3.3122, the best location corresponds to coordinate: X = 49, Y = 97 and biomass supply area is 161.33 km2. The simulation times have been reduced to the ninth of time than the greedy (accurate) solution. Matlab® is used to run all simulations.

Keywords: Biomass; Swarm; intelligence; Profitability; index (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (24)

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