Day-Ahead and Intra-Day Optimal Scheduling Considering Wind Power Forecasting Errors

The aim of this paper is to address the challenges regarding safety and economics power system operation after integration a high proportion wind power. In response limitations literature, which often fails simultaneously consider both aspects, we propose solution based on stochastic optimization scheduling model. Firstly, uncertainty day-ahead forecasting errors establish multi-scenario By balancing reserve capacity economic efficiency in scheduling, obtain optimized unit combinations that are applicable various scenarios. Secondly, account for auxiliary service constraints thermal units participating deep peak shaving, develop an intra-day dynamic dispatch Through inclusion energy storage accommodation further enhanced. Lastly, electricity market environment, increasing can increase profits shaving. However, observe trend initially subsequently decreasing as increases. Considering flexibility curtailed rate, it advisable moderately install grid-connected within system. conclusion, our study demonstrates effectiveness proposed model managing enhancing