Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing

Abstract

Amidst the escalating challenges of global warming and energy crises, the rapid development of distributed renewable energy resources has emerged as a critical strategy. Regional integrated energy systems (RIESs) have garnered significant attention for their potential to integrate and optimize both distributed renewable energy resources and conventional energy facilities. This article presents a bilevel optimization framework for the electricity-storage coupling market in multi-RIES, considering the integration of 6G network slicing technology and battery energy storage (BES) capacity sharing. The upper-level model maximizes the profit of generation units by optimizing their bidding strategies, while the lower-level model aims to maximize social welfare through market clearing. The proposed line search-based global Levenberg–Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. Numerical case studies validate the effectiveness of the proposed framework, demonstrating enhanced BES utilization, increased renewable energy generation, and improved social welfare. The results also highlight the sensitivity of social welfare to communication costs, underscoring the importance of careful cost calibration.