Integrated Electricity Strategic Bidding and Job-Shop Scheduling for Industrial Demand Response

It is important for a smart factory with substantial demand to jointly study its electricity strategic bidding and job-shop scheduling. However, the problem is complicated because job schedules constrained by manufacturing operations limit the bidding curves of demand response, which may influence the electricity market prices that, in turn, affect the profit and the job schedules of the factory. To bridge the gap, this letter innovatively integrates and formulates the electricity strategic bidding and job-shop scheduling of a smart factory as a bilevel optimization model. The upper level makes decisions for the factory to maximize its profit, and the lower level clears the electricity market to minimize the total electricity cost. Since the factory scheduling horizon may not be equal to the electricity market horizon, our idea is to distribute the production revenue and tardiness cost of each part into its operations. To solve the bilevel optimization problem, it is transformed into a single level as a mathematical program with equilibrium constraints (MPEC), and nonlinear components are linearized. Numerical results demonstrate the benefits of participating in demand response for the smart factory, the impacts on its manufacturing schedules as well as market prices, and the computational efficiency of our approach.