Hybrid P2P Energy Trading using Two-fold Fairness-Driven Enhanced NSGA-II for Optimized Demand Allocation with Dual Pricing in South Korea

This paper explores the performance of a hybrid Peer-to-Peer (P2P) energy trading model in South Korea, designed to optimize demand allocation between community-based P2P trading and the centralized KEPCO grid. To overcome the limitations of surplus-based P2P models that exclude non-surplus prosumers and often lack scalability, we propose a surplus-free hybrid trading framework optimized via the Fairness-Driven Non-dominated Sorting Genetic Algorithm II (NSGA-II). This enhancement specifically developed to co-optimize economic benefits for prosumers and social equity within the community. Real data from the Korea Electric Power Corporation (KEPCO) and Grida Energy C2X project are used to evaluate the model’s effectiveness. Simulation results demonstrate significant economic gains, with average cost reductions of 47.75% for KEPCO and 28.52% for Grida prosumers. More importantly, the fairness mechanism proved highly adaptive, where it successfully improved social equity in the large-scale, heterogeneous KEPCO setting while prioritizing solution quality and transactional efficiency in the smaller-scale Grida environment. These findings validate the proposed model’s adaptability and its intelligent approach to balancing economic efficiency and fairness, offering critical insights for the scalable deployment of equitable P2P energy communities.