Intelligent Demand Response for Industrial Energy Management Considering Thermostatically Controlled Loads and EVs

In this paper, an intelligent energy management framework with demand response capability was proposed for industrial facilities. The framework consists of multiple components, including industrial processes modeled by the state task network method, thermostatically controlled loads, like the heating, ventilation, and air conditioning system with chilled water storage, renewable generation, like photovoltaic arrays and electric vehicles. These components are first modeled and their operation is then optimized in time-of-use pricing schemes. Factors that affect several components at the same time, e.g., the number of workers, are considered. The optimization is formulated as a mixed integer linear programming problem. A general tire manufacturing facility was investigated as the case study. Simulation results show that the proposed intelligent industrial energy management with demand response is able to effectively utilize the flexibility contained in all parts of the facility and reduce the electricity costs, as well as the peak demand of the facility, while satisfying all the operating constraints.