Energy efficient street lighting framework: An archived multi-objective simulated annealing based approach

Abstract

An archived multi objective simulated annealing based energy efficient street lighting framework is proposed to maximize the energy efficiency and uniformity of the system while minimizing the power requirement of the luminaries. The proposed methodology considers the initial population in terms of the combination of the input parameters, such as the inter-distance between two consecutive street lights, luminary height, road width and average illuminance. The crossover and the clustering are used to check the domination status between the earlier and the new population as well as to reduce an excessive amount of possible solutions generated. The convergence and the diversity of the obtained solution set are evaluated for the proposed work over other alternative multiobjective optimization algorithms by four performance metrics, such as Generational Distance, Inverted Generational Distance, minimal-spacing, and purity, to highlight the energy efficiency in the proposed street lighting framework. The result obtained from the proposed approach amidst others, in terms of convergence and diversity, is validated using DIALux (an open source lighting software) to ensure the standard recommendation. Several improvements, in terms of various facets, resulting from the proposed work over other existing approaches are highlighted.