Abstract
In literature, proposed approaches mostly focused on household appliances scheduling for reducing consumers’ electricity bills, peak-to-average ratio, electricity usage in peak load hours, and enhancing user comfort level. The scheduling of smart home deployed energy resources recently became a critical issue on demand side due to a higher share of renewable energy sources. In this paper, a new hybrid genetic-based harmony search (HGHS) approach has been proposed for modeling the home energy management system, which contributes to minimizing consumers’ electricity bills and electricity usage during peak load hours by scheduling both household appliances and smart home deployed energy resources. We have comparatively evaluated the optimization results obtained from the proposed HGHS and other approaches. The experimental results confirmed the superiority of HGHS over genetic algorithm (GA) and harmony search algorithm (HSA). The proposed HGHS scheduling approach outperformed more efficiently than HSA and GA. The electricity usage cost for completing one-day operation of household appliances was limited to 1305.7 cents, 953.65 cents, and 569.44 cents in the proposed scheduling approach for case I, case II, and case III, respectively and was observed as lower than other approaches. The electricity consumption cost was reduced upto 23.125%, 43.87% and 66.44% in case I, case II, and case III, respectively using proposed scheduling approach as compared to an unscheduled load scenario. Moreover, the electrical peak load was limited to 3.07 kW, 2.9478 kW, and 1.9 kW during the proposed HGHS scheduling approach and was reported as lower than other approaches.
Highlights
SIMULATIONS RESULTS The simulation based experimental results are explained by making comparisons of results obtained from genetic algorithm (GA), harmony search algorithm (HSA), proposed hybrid genetic-based harmony search (HGHS) scheduling approach and unscheduled load
In the proposed home energy management (HEM) system model, the effects of smart home deployed energy resources (i.e., renewable energy sources (RESs) and energy storage system (ESS)) on electricity consumption patterns, electricity cost, and electrical peak load are discussed
The real-time pricing (RTP) electricity tariff is used for enabling consumers to make beneficial decisions for reducing electricity usage cost and electrical peak load
Summary
The traditional power utility or grid is one-way or unidirectional in nature and utilities have no real-time information of electricity demand from consumers [1]. In order to meet consumers’ electricity demand, a demand response (DR) program is applied to enhance the power system’s operational efficiency and minimize electricity usage during peak load hours in residential areas. A grid utility can directly access and schedule the usage of household appliances by giving monetary benefits to consumers for controlling electricity usage during peak load hours [11], in case of the incentive-based DR programs. Both DR programs play a key role to enhance the operational efficiency of power systems as well as offer financial benefits to consumers by making load demand sensitive to electricity price signals
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