Exploring LBWO and BWO Algorithms for Demand Side Optimization and Cost Efficiency: Innovative Approaches to Smart Home Energy Management

• Published in: IEEE Access
• Main Authors: Heba Youssef, Salah Kamel, Mohamed H. Hassan, Ehab Mahmoud Mohamed, Nasreddine Belbachir
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE 2024
• Subjects: Beluga whale optimization; demand side management; leader beluga whale improvement; mini-grid; renewable energy source; storage system; Electrical engineering. Electronics. Nuclear engineering; TK1-9971; Beluga; Beluga whale; Beluga*
• Online Access: https://doi.org/10.1109/ACCESS.2024.3367446; https://doaj.org/article/de55d419eecf436293926b60c6bccaa8

Demand side management (DSM) involves technologies and strategies that allow customers to actively participate in the optimization of their energy usage patterns, ultimately contributing to a more sustainable and efficient energy system. In this paper, leader beluga whale optimization improvement (LBWO) and original beluga whale optimization (BWO) are used to implement a DSM scheme that enables lower peak-to-average ratio (PAR) and decreasing the expenses associated with electricity consumption. In the context of this research, electricity consumers decide to store, buy, or sell the electricity to maximize profits while minimizing its costs and PAR. Electricity consumers make their decisions based on the amount of electricity generated from their mini-grid, electricity prices and demand from the public network. The mini-grid is a combination of a photovoltaic (PV) panel and a wind turbine connected to an energy storage system (ESS). An ESS is used for maintaining power system stability because the power generated from renewable energy source (RES) has intermittent characteristics depending on environmental conditions. The proposed scheme is tested on three different cases from a study, the first case is the traditional house, the second case is the smart house with DSM, and the last case is the smart house with its mini-grid and DSM. Simulation results indicate that in case 2, LBWO and BWO achieved a remarkable reduction in electricity cost by 61% and 51% respectively. In case 3, the reduction was even more significant, with LBWO and BWO lowering the cost by 76% and 64% respectively. Moreover, LBWO generated a revenue of 154 (cents), while BWO generated a revenue of 118 (cents). The results confirm the effectiveness and robustness of the suggested scheme in reducing electricity costs and the PAR (Peak to Average Ratio), while simultaneously increasing profits for electricity consumers.