Lens-oppositional duck pack algorithm based smart home energy management system for demand response in smart grids. (March 2023)

• Record Type: Journal Article
• Authors: Alghtani, Abdulaziz H.; Tirth, Vineet; Algahtani, Ali
• Is Part Of: Sustainable energy technologies and assessments. Volume 56(2023)
• Publication Date: 2023-03
• Subjects: Energy management system -- Smart grid -- Demand response -- Smart Homes -- Duck pack algorithm -- Internet of things; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2023.103112
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: To develop a LODPA-SMEMS for demand response in Smart Grid applications. To optimise the regulation of energy consumption using a scheduling technique. Reduce PAR and energy expenditures while maximising user comfort (UC). LODPA-SMEMS improves the sustainability by decreasing energy usage. Abstract: Smart grid (SG) is one of the emergent technologies providing effective solutions for increased power demand globally. Due to the advances of Internet of Things (IoT), smart devices are integrated with the smart home (SH) environment which actively participates in electricity market through demand response (DR) programs for energy management. DR refers to the modifications in the electricity utilization of the end user from the common utilization pattern in response to the variation in electricity prices. An effective energy management system (EMS) with price-based DR model is essential for IoT enabled SH environment. In this view, this article develops a Lens-Oppositional Duck Pack Algorithm based Smart Home Energy Management System (LODPA-SMEMS) for DR in SGs. The major focus of the LODPA-SMEMS model is to achieve optimal management of energy usage by scheduling process. The LODPA is derived by the incorporation of lens-oppositional based learning (LOBL) with conventional DPA. The LODPA-SMEMS model is mainly derived to reduce peak-to-average ratio (PAR) and electricity price with maximum user comfort (UC). The experimental outcome of the LODPA-SMEMS model outperforms the other methods under several aspects. The results reported that the LODPA-SMEMS model improves overall energy usage and consequently, the sustainability of IoT enabled SH gets enhanced. According to the findings, the LODPA-SMEMS model increases overall energy efficiency, hence increasing the sustainability of IoT-enabled SH. The experimental values demonstrated that the LODPA-SMEMS model has accomplished lower PAPR of 2.10 whereas GA, BPSO, GWDO, GBPSO, and WBFA models have attained higher PAPR of 3.70, 3.10, 3.80, 3.60, and 2.40 respectively. Also, EEC analysis of LODPA-SMEMS on DAPS, RTPS, TUPS: 3.53kWh, 1.81kWh, 1.85kWh. Similarly, LODPA-SMEMS model has achieved superior performance with least ET of 68 s.