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.

Highlights

  • In this work, the authors propose an electrical battery model

  • 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

  • A particle swarm optimization (PSO)-based algorithm is used for battery sizing in peak power smoothing applications for different electrical consumption points

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Summary

Introduction

The authors propose an electrical battery model. the authors have modelled the electrical consumption and the consequent bills with reference to the different penalties that apply when the maximum power level is exceeded. Restrictions are introduced when modifying the loss function with regularization techniques, such as L1 and L2, or batch normalization techniques [11,12,13] These algorithms are able to manage very extensive dimension optimization problems. They need many iterations or epochs of optimization in order to reach an admissible solution. Their convergence decreases heavily when they reach certain local optima, momentum techniques are very common [14] In this gradient descent algorithm, explicit mathematical expressions are needed in order to obtain the gradient components. A particle swarm optimization (PSO)-based algorithm is used for battery sizing in peak power smoothing applications for different electrical consumption points. Loop to the second step until a criterion is met

Electrical Bill Model
Charge and Discharge Dynamic Modelling
Modelling Battery Aging
Modelling Electric Grid Demand
Cost Function
Optimization Process
Consumption Data
Electrical Battery Economical Return Analysis
Findings
Conclusions

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