Abstract
AbstractThis paper presents a day‐ahead scheduling for multi‐energy entities. The deep load regulation involving pumped storages, which refers to deep peak regulation, is adopted to address the impact of wind power and photovoltaic (PV) uncertainties, thereby improving the economic efficiencies of day‐ahead dispatching. And the impact of different peak valley electricity price differences on the peak shaving effectiveness of pumped storage energy was studied. Firstly, the multi‐scenario random programming method is applied to solve the prediction uncertainties of wind power and PV output in the day‐ahead. Subsequently, the multi‐scenario set of day‐ahead wind power and PV output and the load forecasting curve are considered. A pumped storage scheduling model is then established integrating the hydropower, thermal power and pumped storage. The optimal generation scheduling of pumped storage and thermal units is determined by minimizing load fluctuations and peak shaving costs. Finally, a local power grid in the Hunan province of China is selected for verification. It is shown that the proposed model can effectively accommodate the fluctuation of renewable energy output, reduce the peak regulating pressure of thermal units, and improve the operational economy of the power system.
Published Version
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