时间：2018年4月16日 星期一 下午2：00 - 3：00
报告人：Denis Sidorov （俄罗斯能源研究院西伯利亚分院研究院）
Denis Sidorov is a Leading Researcher at Energy Systems Institute of Russian Academy of Sciences. He is Distinguished Guest Professor of Hunan University and Professor of Russian Academy of Sciences. His research interests include: nonlinear dynamical systems, power quality, inter-area oscillations, integral and differential equations theory, machine learning methods and forecasting. Dr. Sidorov is the author of more than 120 scientific papers and two monographs.
Development of reliable methods for optimized energy storage and generation is one of the most imminent challenges in modern power systems. In this presentation, an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels is proposed. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. A direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimization in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Markets of Republic of Ireland and Sakhalin island in Russian Far East.