Energy System Roadmap for Carbon Neutrality via Production Scheduling in Manufacturing

Under the panorama of increasing energy costs and environmental policies, driven by global warming concerns, this research is aimed at creating an energy optimal production schedule model to minimize energy costs and reduce carbon footprint emissions. The proposed model is built under the context of a sequence-dependent single machine scheduling problem. Moreover, the scheduling decisions are assumed to be affected by independent time of use electricity prices and carbon footprint environmental policies forced by either corporate or governmental institutions. To this end, a multi-objective Energy-Carbon Aware Sequence Dependent Job Scheduling optimization model is developed under a Mixed Integer Linear Programming formulation. The value of the model when compared to classical scheduling optimization approaches and job scheduling heuristics. Results show that energy-carbon aware scheduling models have a conflicting nature with production performance metrics (e.g. completion time). However, by leveraging on energy policies, such as net metering which incentivizes on-site power generation, carbon-neutrality is achieved without compromising production performance. These results are further examined under different net-metering compensation structures and dynamics of solar photovoltaic systems with and without energy storage systems. Their cost-savings are contrasted with a baseline scenario of power consumption only from the grid. Research directions and proposed roadmap to energy-carbon neutrality are finally discussed.