Title: Swarm and evolutionary algorithms for energy disaggregation: challenges and prospects

Authors: Samira Ghorbanpour; Trinadh Pamulapati; Rammohan Mallipeddi

Addresses: School of Electronics Engineering, Kyungpook National University, Daegu, 702701, South Korea ' School of Electronics Engineering, Kyungpook National University, Daegu, 702701, South Korea ' School of Electronics Engineering, Kyungpook National University, Daegu, 702701, South Korea

Abstract: Energy disaggregation is defined as the process of estimating the individual electrical appliance energy consumption of a set of appliances in a house from the aggregated measurements taken at a single point or limited points. The energy disaggregation problem can be modelled both as pattern recognition problem and as an optimisation problem. Among the two, the pattern recognition problem has been considerably explored while the optimisation problem has not been explored to the potential. In literature, researchers have attempted to solve the problem using various optimisation algorithms including swarm and evolutionary algorithms. However, the focus on optimisation-based methodologies, in general, swarm and evolutionary algorithm-based methodologies in particular is minimal. By considering the different problem formulations in the literature, we propose a framework to solve the energy disaggregation problem with swarm and evolutionary algorithms. With the help of simulation results using the existing problem formulations, we discuss the challenges posed by the energy disaggregation to swarm and evolutionary algorithm-based methodologies and analyse the prospects of these algorithms for the problem of energy disaggregation with some future directions.

Keywords: energy disaggregation; swarm and evolutionary algorithms.

DOI: 10.1504/IJBIC.2021.116548

International Journal of Bio-Inspired Computation, 2021 Vol.17 No.4, pp.215 - 226

Received: 14 Jan 2019
Accepted: 29 Jan 2020
Published online: 28 Jul 2021 *

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