Computational approaches for efficient scheduling of steel plants as demand response resource

Demand response is seeing increased popularity worldwide and industrial loads are actively taking part in this trend. As a host of energy-intensive industrial processes, steel plants have both the motivation and potential to provide demand response. However, the scheduling of steel plants is very complex and the involved computations are intense. In this paper, we focus on these difficulties and propose methods such as adding cuts and implementing an application-specific branch and bound algorithm to make the computations more tractable.