A hybrid robust-stochastic approach for strategic scheduling of a multi-energy system as a price-maker player in day-ahead wholesale market

This study investigates the strategic scheduling of a multi-energy system (MES) in day-ahead wholesale market (DWM) as price-maker that can submit offers/bids to purchase/sell energy. In this regard, proposed model presents bi-level optimization problem, wherein upper-level is cost minimization objective MES, while lower-level considered operator (WMO) clears according received from producers/consumers intending maximize public satisfaction. The Karush-Kuhn-Tucker (KKT) conditions are utilized convert nonlinear problem into single level mixed-integer linear (MILP). A combined heat and power (CHP) unit wind turbines (WT) integrated MES production units, various storage technologies, such hydrogen energy (HES), natural gas (GS) thermal (TES), well demand response program (DRP), increase flexibility system. hybrid robust (RO) stochastic programming (SP) method deployed deal with uncertainties MES. results illustrate efficacy manipulating clearing price favor different case studies show privileges utilizing RO-SP method.