OPTIMAL BIDDING AND STOCHASTIC MODEL PREDICTIVE CONTROL BASED OPERATION STRATEGIES FOR WIND ENERGY GENERATION SUPPORTED BY A HYDRO STORAGE SYSTEM
Tarih ve Saat
9 Ekim 2017 - 14:00
YerMühendislik Binası A-511
Title: OPTIMAL BIDDING AND STOCHASTIC MODEL PREDICTIVE CONTROL BASED OPERATION STRATEGIES FOR WIND ENERGY GENERATION SUPPORTED BY A HYDRO STORAGE SYSTEM
Abstract: Consider a generation company (GENCO) operating a system composed a wind farm and a pumped hydro-storage (PHS) system. The company trades energy in day-ahead market and is assumed to have a relatively small generation capacity which renders it a price taker player. There are several studies in the literature that investigates optimal bidding strategies for such GENCOs. However, in most of them a little attention is paid to the real-time operation and usually heuristic methods are employed for this purpose. The primary goal of the present work is to introduce an advanced real-time management strategy that maximizes the profit of the GENCO utilizing the storage device effectively. The algorithm is based on a stochastic model predictive control (SMPC) approach that solves an MILP optimization problem repeatedly. In addition to operation, optimal bidding problem is also solved to find contracts used by SMPC method. Simulation studies show that the proposed approach outperforms the available methods owing to its ability to exploit the most recent information available within the day and ability to take into account contingencies of wind energy production.
Biography: İsmail KAYAHAN graduated from Industrial and Systems Engineering Dept., Yeditepe University in 2009. He is currently a Ph.D. student at Systems Engineering Program, Graduate School of Natural and Applied Sciences at Yeditepe University.