A day-ahead generation scheduling with energy storage considering cycling ramp costs

Variability and uncertainty associated with the growth of variable renewable generation, particularly wind power, introduce significant challenges to grid system operators. This paper proposes a day-ahead chance constraint generation scheduling (CCGS) approach, considering variable wind generation and energy storage. 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 leads to the reduction of the wear and tear of the generator. The cycling of conventional generation as well as the dispatch of energy storage is utilized to enhance the load following and flexible ramping support capabilities; thus mitigate the impact of net load ramps. The chance constraint is converted into an equivalent mixed-integer linear programming (MILP) expression by using the Projected Disjunctive Reformulation (PDR), with the aim to maintain compatibility with commercially state-of-the-art optimization solvers. Results show the merits of the proposed scheduling model in controlling the fluctuating characteristics due to high wind penetration levels. The impact of introducing cycling ramp cost and the benefits of energy storage in reducing the respective cost, are also investigated in the test cases.