A Multi-Objective Optimization Framework for Peer-to-Peer Energy Trading in South Korea’s Tiered Pricing System
Source abstract
Abstract
This study proposes a multi-objective optimization framework for peer-to-peer (P2P) energy trading in South Korea’s tiered electricity pricing system. The framework employs the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) to optimize three conflicting objectives: minimizing consumer costs, maximizing prosumer benefits, and enhancing energy utilization. Using real microgrid data from a South Korean community, the framework’s performance is validated through simulations. The results highlight that MOEA/D achieved an optimal cost of KRW 32,205.0, a benefit of KRW 32,205.0, and an energy utilization rate of 57.46%, outperforming the widely used NSGA-II algorithm. Pareto front analysis demonstrates MOEA/D’s ability to generate diverse and balanced solutions, making it well suited for regulated energy markets. These findings underline the framework’s potential to improve energy efficiency, lower costs, and foster sustainable energy trading practices. This research offers valuable insights for advancing decentralized energy systems in South Korea and similar environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Smart Grid Energy Management · Energy Efficiency and Management · Energy, Environment, and Transportation Policies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering, Chonnam National University, Gwangju 61186, Republic of Korea
Department of Information Systems Technology and Design, Singapore University of Technology and Design, Singapore 487372, Singapore
Funding
Ministry of Education of the Republic of Korea and the National Research Foundation of Korea
References (23)
Show source-provided references
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