A novel approach for steelmaking scheduling with self-generation under real-time and demand charge tariffs

Abstract

It is difficult for energy-intensive enterprises equipped with self-generation to incentivize consumers to shift load to low-demand periods through time-based pricing. This paper addresses a scheduling problem of steel plant equipped with self-generation under real-time electricity prices. Considering the possibility of centralized load shifting resulting in excessive loads for some periods, we also consider the demand charge pricing. A continuous-time mixed-integer linear programming model based on event expression and generalized disjunctive programming is proposed. As industrial scale problems cannot be solved by some commercial solvers in an acceptable time, a SPEA2 algorithm is tailored. Effective encoding based on decomposition-and-offsetting mechanism and decoding based on backward-and-rules are used to generate the initial population and scheduling scheme, respectively. Meanwhile, crossover and mutation operators incorporating conflict resolution strategies can strike a balance between exploring and exploiting to produce high-quality solutions. Numerical experiments indicate that the proposed approach has superiority in performance and efficiency.