Fuzzy-based Reserve Scheduling in Renewable Integrated Power Systems

Power systems require operating reserves to counteract unanticipated operating conditions and maintain load-generation balance. Traditional operating reserves are limited to addressing system’s contingency events. Variability and uncertainty of Renewable Energy Sources (RES) hamper system security in low-carbon grids. Hence, operating reserve allocations must consider renewable intermittency along with unanticipated contingencies. However, securing additional reserves impose higher operating costs. This necessitates the need to devise effective and robust methodologies to characterize renewable uncertainty. In this context, the paper proposes a Fuzzy theory based modeling for renewable uncertainty characterization. The estimated additional reserve requirement based on renewable uncertainty is optimally scheduled along with energy and contingency reserves from thermal generators and RES using a day-ahead scheduling framework. Operating reserves are quantified for various uncertainty deviation levels. Numerical results carried out on Great Britain test system highlight the proficiency of proposed scheduling framework.