Review of Optimization Methods for Energy Hub Planning, Operation, Trading, and Control
Tao Ding, Wenhao Jia, Mohammad Shahidehpour, Ouzhu Han, Yuge Sun, Ziyu Zhang
Abstract
The increasing concerns with adverse environmental issues have led to the proliferation of renewable energy resources (RESs), which have been expanded more recently to multi-energy systems (MESs) in various parts of the world. MES can improve energy efficiency and reduce carbon emission by co-optimizing multiple forms of energy, including electricity, natural gas, heating, cooling, etc., which provide a promising approach to carbon neutrality. Energy hub (EH) is an efficient framework for MES modeling and management, where various energy carriers are optimally converted, utilized, and stored for satisfying certain sociopolitical and socioeconomic mandates. This paper presents a comprehensive review of available EH optimization and control studies. First, we introduce basic concepts and EH modeling methods. Then, we conduct a systematic review of optimization methods, as well as state-of-the-art solution algorithms for EH planning, operation, and trading. Furthermore, we analyze an internet of things (IoT) based EH control structure and review the corresponding state estimation, communication, and control methods for managing large EH data sets. Finally, we present and discuss several research topics for future research.