LAUSR

The smart grid opens many opportunities for electricity suppliers and customers to maintain grid stability, reduce electricity cost, and promote environmentally sustainable operation. Unfortunately, these benefits cannot be fully realized from industrial energy customers due to inadequate manufacturing decision-making methodology that fails to consider manufacturers and energy suppliers simultaneously. The influence manufacturers have on the grid comes from their large electricity demand contributing to peak power and their large natural gas usage due to the increasing dependency of the electricity sector on gas-fired generation. Nonetheless, the interdependency between manufacturers’ electricity and natural gas demand has not been well studied. In this paper, an electricity and natural gas driven production scheduling model for manufacturers is established. The model considers time-based and event-based electricity and gas demand response. A modified simulated annealing (MSA) algorithm is proposed to solve the problem in reaction to real-time supply notifications to promote the interaction between manufacturers and energy providers. Numerical case studies are implemented and illustrate that 66%–68% in energy cost savings for the manufacturer can be achieved when using the proposed model compared to baseline scenarios. Meanwhile, the MSA algorithm outperforms various solution methods in solving the proposed problem.