Controlling electricity consumption at home smart home

Abdelwahed, Ahmed; Zekry, Abdelhalim; Zayed, Hossam Labib A.; Sayed, Ahmed M.

doi:10.1109/icces.2015.7393017

Cited by 8 publications

(3 citation statements)

References 4 publications

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“…High PAR puts a strain on the electrical system. As a result, several authors in Ahmad et al, 8 Zhao et al, 13 Abdelwahed et al, 14 include PAR as one of the objectives in a multiobjective issue. In Zhao et al, 13 the author developed a SG-based design for HEMS, which was then followed by an efficient scheduling technique for residential energy usage.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Because these sorts of optimization issues are usually nonlinear in nature, the researchers used a genetic algorithm (GA) to solve them. In Abdelwahed et al, 14 authors have developed a multi-objective optimization problem involving electricity cost and PAR. They used a rulebased algorithm (RBA) to experiment with different weighting coefficient values in order to get the best possible outcome.…”

Section: Literature Reviewmentioning

confidence: 99%

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An optimal home energy management system with integration of renewable energy and energy storage with home to grid capability

Mohammad

Zuhaib

Ashraf

2022

Intl J of Energy Research

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Summary Residential building consumes a significant amount of energy. To address the issue, these structures have been supplied with renewable energy sources (RES), an energy storage system (ESS), and an electric vehicle (EV). In a home, a home energy management system (HEMS) has been implemented to schedule and regulate domestic appliances. Many studies in HEMS have been conducted in order to reduce the cost of power and the peak to average ratio (PAR). However, there is insufficient use of RES, ESS, EV, and excess domestic energy. As a result, this research presents a HEMS architecture that is integrated with RES and ESS and includes home‐to‐grid (H2G) power flow functionality. The RES electricity is initially utilized to power domestic appliances and charge ESS before being transferred back into the main grid to reap economic rewards. During the low‐price period, the ESS and EV are charged and discharged during the high‐price period. The paper built a multi‐objective optimization problem using the provided approach that integrates electricity cost and system PAR. The grey wolf optimization algorithm is used to tackle the multi‐objective optimization problem. The results clearly show that the proposed technique decreases expenditures by 45.80% and PAR by 28.44%, compared to the baseline timetable in 24 h. The H2G power flow feature allows the home to send back excess energy to the grid, cutting electricity expenditures by 70% and achieving additional economic benefits.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

An optimal home energy management system with integration of renewable energy and energy storage with home to grid capability

Mohammad

Zuhaib

Ashraf

2022

Intl J of Energy Research

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“…The load management unit can be used to delay or shift the peaks to another period. It not only reduces the total peak but also helps reduce the loss of the feeder and enhances the load factor [8].…”

Section: The Priority Of the Device Is To Decrease In-line Lossesmentioning

confidence: 99%

Home Energy Management System Based on Priority of devices

Elwahed

Zekry²,

Amer

et al. 2022

Journal of Computing and Communication

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The rising number of home devices, as well as the differences in technology between them (smart and traditional), are the causes of the difficulty in balancing the use of energy in the home. Furthermore, increased demand for energy often leads to pressure on electricity networks and utilities, which leads to interruptions or disruptions of services caused by peak load. All these factors contribute to the adoption of energy management systems to control and reduce usage and automatically monitor the usage of home devices. When consumption is controlled, it is beneficial to customers and electricity companies when demand is reduced at peak times.This research will present a prototype for an energy management system to control and monitor the usage of devices in the home, and automatic control utilizing MATLAB simulation and implementation employing a Microcontroller to assess Demand Response.The suggested algorithm would manage consumption to reach the lowest usage possible to decrease the monthly bill, reduce peak load based on customer priority, and ensure that the consumption does not exceed the specified value. The algorithm's accuracy is demonstrated by several situations of consumption in the home, where the algorithm was able to lower consumption by up to 39.5% when compared to consumption without utilizing the suggested algorithm.

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