Resilient-Economic Coordinated Robust Operation of Integrated Electric-Gas Systems
Ahmed Rabee Sayed, Cheng Wang, Tianshu Bi
备注：
This document is a Ph.D. Thesis has been prepared for graduation in June 2020 from the School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China. It includes 7 chapters, 255 pages, 49 figures, and 131 tables. The included work has been been published in different archive journals and international conferences
Interactions between power and gas systems, which are both large and complex, have been gradually intensified during the last decades, predominantly due to the propagation of large fleet natural gas-fired power units (GPUs) and the technological developments of power-to-gas (P2G) facilities. These interactions not only bring significant economic benefits to society but also provide additional operating flexibilities, which are essential to handle fluctuations of the large-scale renewable power generation (RPG) and power system contingencies. Moreover, neglecting these interactions in power system operation may not only result in infeasible operation status in the gas systems but also increase the decision-making operation costs of both systems. previous studies suffered from two significant drawbacks, namely (1) they assumed the existence of only one utility that has full control authority over the power system and gas system; (2) the economic interactions between power systems and gas systems have been neglected, which goes against the current industrial practice. This research revisits the day-ahead resilient and economic operations of power systems considering the economic and physical interactions with gas systems, which are characterized by the modeling of bilateral energy purchase contracts and operational constraints of gas systems. This thesis provides a novel perspective and solution for the resilient and economically coordinated robust operation of integrated electric-gas systems (IEGSs) under uncertainties. The proposed robust scheduling decision frameworks are practically compatible with the existing industrial operations of the IEGSs.
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