Mid-short term industrial demand response strategy-case study for a steel mill

Demand Response (DR), as one of the popular approaches in today's power system, focuses on changing electricity customer behavior to provide ancillary services for load balance and peak shaving for load factor improvement. As the potential it can provide, the industrial customer is one of the best candidates to be encouraged to participate in the DR program. In view of the industrial characteristics, we propose a mid-short term energy management for the industrial customers to join in the DR program to achieve maximum DR profit. The month-ahead maintenance planning and 5-day load arrangement constitute our model. Specifically, on the basis of monthly job planning, mixed integer linear programming (MILP) algorithm is proposed for the short-term DR scheduling via daily optimization within the 5-day moving window. In the optimization process, the opportunity cost, DR execution days, and manufacturing process are considered. The realistic data from a steel company in Taiwan is employed in our case studies. The results illustrate that the economic efficiency of the proposed method achieves the DR profit and, therefore, considerable electricity cost reduction for the consumer. The importance of opportunity cost consideration is demonstrated in the simulation as well.