Towards green manufacturing: Co-optimizing capacity expansion planning of production and renewable energy generation with endogenous uncertainty

The manufacturing industry stands as a significant consumer of electricity, for which the production of renewable energy through integrated distributed generation systems represents a sustainable alternative. However, uncertainty about customer demand and energy generation poses challenges for capacity planning. In this paper, we aim to address the joint decision-making for production capacity and renewable energy-generation capacity. To this end, we first establish a two-stage robust optimization (TRO) framework that considers uncertain product demand and generation rates, with the objective of minimizing the total costs. The TRO encompasses not only strategic decisions on production and electricity-generation capacity, but also tactical decisions on production planning, inventory, and emission targets. To solve this model, we propose a pre-check parametric column and constraint generation (PP-C&CG) algorithm. Subsequent validation with benchmark data and application to two practical cases demonstrate that our proposed joint-decision approach is more efficient than non-robust decisions. Lastly, despite its additional costs, our approach based on robust decisions offers practical utility in addressing worst-case scenarios characterized by considerable uncertainty.