Particle Swarm Optimization for Outdoor Lighting Design

Ana Castillo-Martinez, Jose Ramon Almagro, Alberto Gutierrez-Escolar, Antonio Del Corte, José Luis Castillo-Sequera, José Manuel Gómez-Pulido and José-María Gutiérrez-Martínez
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Ana Castillo-Martinez: Department of Computer Sciences, Polytechnic School, University of Alcala, Madrid-Barcelona Road, Km 33.6, 28871 Alcala de Henares, Spain
Jose Ramon Almagro: Airbus Defence and Space, Gunnels Wood Road, Stevenage, Hertfordshire SG12AS, UK
Alberto Gutierrez-Escolar: Department of Computer Sciences, Polytechnic School, University of Alcala, Madrid-Barcelona Road, Km 33.6, 28871 Alcala de Henares, Spain
Antonio Del Corte: Department of Computer Engineering, Polytechnic School, University of Alcala, Madrid-Barcelona Road, Km 33.6, Alcala de Henares 28871, Spain
José Luis Castillo-Sequera: Department of Computer Sciences, Polytechnic School, University of Alcala, Madrid-Barcelona Road, Km 33.6, 28871 Alcala de Henares, Spain
José Manuel Gómez-Pulido: Department of Computer Sciences, Polytechnic School, University of Alcala, Madrid-Barcelona Road, Km 33.6, 28871 Alcala de Henares, Spain
José-María Gutiérrez-Martínez: Department of Computer Sciences, Polytechnic School, University of Alcala, Madrid-Barcelona Road, Km 33.6, 28871 Alcala de Henares, Spain

Energies, 2017, vol. 10, issue 1, 1-11

Abstract: Outdoor lighting is an essential service for modern life. However, the high influence of this type of facility on energy consumption makes it necessary to take extra care in the design phase. Therefore, this manuscript describes an algorithm to help light designers to get, in an easy way, the best configuration parameters and to improve energy efficiency, while ensuring a minimum level of overall uniformity. To make this possible, we used a particle swarm optimization (PSO) algorithm. These algorithms are well established, and are simple and effective to solve optimization problems. To take into account the most influential parameters on lighting and energy efficiency, 500 simulations were performed using DIALux software (4.10.0.2, DIAL, Ludenscheid, Germany). Next, the relation between these parameters was studied using to data mining software. Subsequently, we conducted two experiments for setting parameters that enabled the best configuration algorithm in order to improve efficiency in the proposed process optimization.

Keywords: Energy efficiency; lighting design; lighting optimization; particle swarm optimization (PSO) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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