A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems

Document Type

Article

Source of Publication

Sustainable Operations and Computers

Publication Date

1-1-2024

Abstract

This paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerful optimization methods, is adjusted and adapted to address EPP optimally and achieve its objectives efficiently. The GWO is adapted due to its high performance in addressing NP-complex hard problems like the EPP, where it contains efficient and dynamic parameters that enhance its exploration and exploitation capabilities, particularly for large search spaces. In addition, new energy and real-world resources based on solar renewable energy systems (RESs) are combined with the proposed GWO to enhance its performance and ensure the optimisation of EPP objectives. Furthermore, EPP is presented as a multi-objective planning problem to optimize all objectives simultaneously. To efficiently investigate the proposed method performance, the results obtained by the GWO with the RESs are compared in three stages: comparison with original methods without RESs, comparison with methods using RESs, and comparison with state-of-the-art. The obtained results proved the robust performance of the proposed method in handling EPP and optimizing its objectives.

ISSN

2666-4127

Publisher

Elsevier BV

Volume

5

First Page

88

Last Page

101

Disciplines

Computer Sciences

Keywords

Energy Planning Problem, Grey Wolf Optimizer, Multi-objective Optimization, Optimization, Renewable Energy System

Scopus ID

85192684850

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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