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Dynamic Price-Based Demand Response through Linear Regression for Microgrids with Renewable Energy Resources

Hassan, Muhammad Arshad Shehzad and Assad, Ussama and Farooq, Umar and Kabir, Asif and Khan, Muhammad Zeeshan and Bukhari, S. Sabahat H. and Jaffri, Zain ul Abidin and Oláh, Judit and Popp, József (2022) Dynamic Price-Based Demand Response through Linear Regression for Microgrids with Renewable Energy Resources. ENERGIES, 15 (4). pp. 1-17. ISSN 1996-1073

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Abstract

The green innovations in the energy sector are smart solutions to meet the excessive power requirements through renewable energy resources (RERs). These resources have forwarded the revolutionary relief in control of carbon dioxide gaseous emissions from traditional energy resources. The use of RERs in a heuristic manner is necessary to meet the demand side management in microgrids (MGs). The pricing scheme limitations hinder the profit maximization of MG and their customers. In addition, recent pricing schemes lack mechanistic underpinning. Therefore, a dynamic electricity pricing scheme through linear regression is designed for RERs to maximize the profit of load customers (changeable and unchangeable) in MG. The demand response optimization problem is solved through the particle swarm optimization (PSO) technique. The proposed dynamic electricity pricing scheme is evaluated under two different scenarios. The simulation results verified that the proposed dynamic electricity pricing scheme sustained the profit margins and comforts for changeable and unchangeable load customers as compared to fixed electricity pricing schemes in both scenarios. Hence, the proposed dynamic electricity pricing scheme can readily be used for real microgrids (MGs) to grasp the goal for cleaner energy production.

Item Type: Article
Uncontrolled Keywords: renewable energy resources; linear regression; dynamic electricity pricing scheme; demand response; particle swarm optimization
Subjects: H Social Sciences / társadalomtudományok > H Social Sciences (General) / társadalomtudomány általában
Depositing User: Enikő Pergéné Szabó
Date Deposited: 30 Nov 2022 13:36
Last Modified: 30 Nov 2022 13:36
URI: http://real.mtak.hu/id/eprint/154155

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