LSTN: A Linear Model of Industrial Production Process for Demand Response
Ruike Lyu, Hongye Guo, Yuanjie Zheng, Yunlong Bai, Qixin Chen
Abstract
Industrial production modeling provides operational constraints for industrial users participating in demand response (DR) programs. Conventional modeling of the production process introduces binary variables to model the discrete operating points of industrial equipment, which can be computationally infeasible in large-scale DR applications. To reasonably model industrial users' operational constraints while balancing computational complexity and modeling accuracy, we developed a linear model of the industrial production process for evaluating DR applications. Numerical results verify the accuracy of the proposed model and its great improvement in computational efficiency over competing approaches.
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