Multi-Objective Optimization for Demand Response Planning in Residential Homes Using Smart Aggregators
Subject Areas : Electrical engineering (electronics, telecommunications, power, control)Gholam-Reza Kamyab 1 * , Mohammad Hossein Erfani Majd 2 , سعید بلوچیان 3
1 - Department of Electrical Engineering, Gonabad Branch, Islamic Azadi University
2 - Department of Electrical Engineering, Gonabad Branch, Islamic Azad University, Gonabad, Iran
3 - Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Keywords: Multi-objective optimization, Demand response, Smart aggregators, NSGA-II, Fuzzy technique, Best compromise solution,
Abstract :
This paper examines multi-objective optimization for demand response planning in residential households using smart aggregators. Smart aggregators play a crucial role as effective tools in optimizing home energy consumption and reducing costs, leveraging advanced algorithms and innovative technologies in energy demand management. The main objective of this research is to reduce energy costs and minimize customer dissatisfaction in the demand response process. To achieve these goals, the multi-objective optimization algorithm NSGA-II is employed, which can provide a set of optimal solutions considering various objectives. This algorithm utilizes natural selection techniques and genetic processes to find a balance between different goals. Subsequently, a multi-objective fuzzy method is used to select the best trade-off solution between conflicting objectives. This method evaluates different solutions based on their degree of alignment with various goals using fuzzy membership functions. The application of the NSGA-II algorithm and fuzzy techniques in optimizing home energy consumption leads to a significant reduction in costs and customer dissatisfaction. Numerical simulation results show that these methods effectively create an optimal balance between cost reduction and improving consumer welfare in smart distribution networks. Finally, this research highlights the importance of using advanced algorithms in optimizing home energy systems and achieving a sustainable and intelligent system.
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