Robust optimization for energy transition planning in manufacturing firms: An integrated model addressing economic and environmental issues

Abstract

Moving away from fossil fuels to cleaner energies is a big challenge in different industries due to its complexities and the huge capital investment needed. Manufacturers therefore need efficient energy transition planning to enhance their energy basket. In this regard, capacity expansion planning models can provide an appropriate context in which operations decisions can be integrated into energy transition planning. To pursue this, we develop an optimization model to integrate capacity planning, energy transition planning, while focusing on economic and environmental issues. Due to the effect of operations and financial decisions on both strategic and tactical planning, we integrate strategic and tactical planning horizons in this paper. Furthermore, to deal with the inherent uncertainty in the proposed model, a robust optimization approach will be developed. This approach is used to handle demand uncertainty while overcoming the over-conservativeness issue. The practicality and the effectiveness of the proposed approach are illustrated by implementing it on a real case study. Additionally, Monte Carlo simulations are utilized to assess the performance of the robust solutions. The results show that robust solutions may lead to a drop in the simulated objective function by 14% in comparison with deterministic solutions when uncertainty level is high.