Bi-level collaborative day-ahead optimization scheduling of manufacturing-energy system targeting energy cost reduction

Abstract

Rising energy costs have become a critical factor in production planning and scheduling. This paper proposes a bi-level collaborative optimization scheduling approach to address the challenge of reducing energy cost in flexible manufacturing systems. The model is designed to find an optimal production and energy scheduling scheme that minimizes the total energy cost while respecting day-ahead scheduling constraints. The proposed framework uniquely integrates manufacturing and energy systems through a bi-level structure. Specifically, the outer level reconfigures flexible production schedules to enable load shifting, while the inner level optimizes distributed energy dynamics based on multi-energy complementarity within Virtual Power Plants (VPPs) and Time-of-Use (TOU) pricing. The results demonstrate that this approach achieves significant energy cost savings and exhibits high robustness against load fluctuations and uncertainties in wind power (WP) and photovoltaic (PV) generation. The developed framework provides a robust and practical solution for achieving economic objectives in manufacturing systems.