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Article

Integrating Internet-of-Things-Based Houses into Demand Response Programs in Smart Grid

Department of Electrical Engineering, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11564, Saudi Arabia
Energies 2023, 16(9), 3699; https://doi.org/10.3390/en16093699
Submission received: 18 March 2023 / Revised: 15 April 2023 / Accepted: 19 April 2023 / Published: 26 April 2023

Abstract

This paper presents a novel framework that mathematically and optimally quantifies demand response (DR) provisions, considering the power availability of Internet of Things (IoT)-based house load management for the provision of flexibility in the smart grid. The proposed framework first models house loads using IoT windows and occupant behavior, and then integrates IoT-based house loads into DR programs based on a novel mathematical optimization model to provide the optimal power flexibility considering the penetration of IoT-based houses in distribution systems. Numerical results that consider a 33-bus distribution system are reported and discussed to demonstrate the effectiveness of flexibility provisions, from integrating IoT-based houses into DR programs, on peak load reduction and system capacity enhancement.
Keywords: Internet of Things; flexibility; load management; mathematical model Internet of Things; flexibility; load management; mathematical model

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MDPI and ACS Style

Alharbi, W. Integrating Internet-of-Things-Based Houses into Demand Response Programs in Smart Grid. Energies 2023, 16, 3699. https://doi.org/10.3390/en16093699

AMA Style

Alharbi W. Integrating Internet-of-Things-Based Houses into Demand Response Programs in Smart Grid. Energies. 2023; 16(9):3699. https://doi.org/10.3390/en16093699

Chicago/Turabian Style

Alharbi, Walied. 2023. "Integrating Internet-of-Things-Based Houses into Demand Response Programs in Smart Grid" Energies 16, no. 9: 3699. https://doi.org/10.3390/en16093699

APA Style

Alharbi, W. (2023). Integrating Internet-of-Things-Based Houses into Demand Response Programs in Smart Grid. Energies, 16(9), 3699. https://doi.org/10.3390/en16093699

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