Battery Sizing Optimization in Power Smoothing Applications

Abstract

The main objective of this work was to determine the worth of installing an electrical battery in order to reduce peak power consumption. The importance of this question resides in the expensive terms of energy bills when using the maximum power level. If maximum power consumption decreases, it affects not only the revenues of maximum power level bills, but also results in important reductions at the source of the power. This way, the power of the transformer decreases, and other electrical elements can be removed from electrical installations. The authors studied the Spanish electrical system, and a particle swarm optimization (PSO) algorithm was used to model battery sizing in peak power smoothing applications for an electrical consumption point. This study proves that, despite not being entirely profitable at present due to current kWh prices, implanting a battery will definitely be an option to consider in the future when these prices come down.

Basque Optimization: a new cost function prediction based optimization algorithm

“…For each solution, a randomized velocity is assigned, and the original solutions, which are called particles, are then own through the problem space. Each particle keeps track of its coordinates in the problem space, which are associated with the best solution ( tness) it has achieved so far, see Eberhart et al [4] and Zulueta et al [5]. In the study of Poli [6], several works that have utilized PSO are investigated.…”

“…In the study of Poli [6], several works that have utilized PSO are investigated. Authors have successfully employed particle swarm optimization algorithms multiple times in Zulueta et al [5], Martinez-Filgueira et al [7] and Uriarte et al [8].…”