A day-ahead generation scheduling with demand response considering thermal cycling ramp

While increasing the shares of renewables is necessary for the transition to fossil-free energy provision, new challenges of flexibility are associated therein. Consumer flexibility is crucial to accommodate variable generation and peak loads. This paper proposes a chance-constrained programming (CCP) based day-ahead generation scheduling, including variable wind generation while engaging demand response (DR). Cycling ramp cost is introduced in this paper as a penalty in the objective cost function, to model the operation and maintenance (O&M) costs, which lead to the reduction of the wear and tear of the generator. The cycling of conventional generation and the dispatch of adjustable load are utilized to enhance the load following and net load flattening capabilities. The chance constraint is then converted into an equivalent mixed-integer linear programming (MILP) expression by using the Projected Disjunctive Reformulation (PDR), to speed up the computational performance. Test results on a 6-bus system show the merits of the proposed scheduling model.