Generation Scheduling of a Hydrothermal System Considering Multiple Provincial Peak-Shaving Demands

There is a common lack of flexible power to quickly follow peak loads of many coal-dominated provincial power grids (PPGs) in China. A regional power grid (RPG) that covers several provinces is responsible for scheduling the power plants it manages and allocating their power to subordinate PPGs in response to different peak loads. This process is more difficult than conventional peak operations for a single PPG. A methodology for hydrothermal system generation scheduling considering multiple provincial peak-shaving demands is developed. This methodology utilizes a novel load subsection optimization model to smooth local frequent load fluctuations. The model divides the provincial load curve into several subsections to construct an expected residual load profile with the average load of each subsection in advance. Minimizing deviation between the expected and calculated load profiles is then formulated as the optimization objective. Three practical algorithms, named the multistep progressive optimality algorithm, the heuristic algorithm, and an improved load shedding method, are integrated to determine the power generation for hydropower plants, pumped-storage plants, and thermal plants, respectively. Moreover, a variable neighborhood search algorithm is proposed to coordinate the allocation of the power generation among PPGs. This methodology has been implemented for the operations of the East China Grid, which is the largest RPG in China. Comparisons with an existing optimization model and a conventional method are, respectively, given in two cases. The first case shows that the peak-shaving demands in subordinate PPGs are effectively met. The load fluctuations in local hours are smoothed, with an average reduction of 6.3% in allan variance of residual loads. The second case implies that the proposed method deals better with the load differences in multiple power grids. It should also be noted that the operating flexibility of different power plants has a significant effect on smoothing fluctuations in residual loads.