Optimal Operation of Integrated Multi-Energy Systems Under Uncertainty - Tapa blanda

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Qiuwei Wu received the PhD degree in Electrical Engineering from Nanyang Technological University, Singapore, in 2009. He is a professor with the School of Electronics, Electrical Engineering, and Computer Science (EEECS), Queen’s University Belfast, the UK. His research interests are distributed optimal operation and control of low carbon power and energy systems, including distributed optimal control of wind power, optimal operation of active distribution networks, and optimal operation and planning of integrated energy systems.

Jin Tan received her Ph.D. degree in Electrical Engineering from the Technical University of Denmark, Denmark, in 2022, following a MSc at the Department of Electrical Engineering, Wuhan University, China (2018). Her research interests include the optimal operation of integrated electricity and heating system and renewable energy integration.

Menglin Zhang received the B.S. degree in electrical engineering from Southwest Jiaotong University (SWJTU), Chengdu, China, in 2011, and the Ph.D. degree in electrical engineering from Wuhan University (WHU), Wuhan, China, in 2017. She was with the Department of Electrical Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China from 2017 to 2019. Currently, she is a Post-Doctoral Researcher with the Center for Electric Power and Energy, Technical University of Denmark (DTU). Her current research interests include the modeling of temporal-spatial correlation of renewables in stochastic programming and advanced uncertainty set to reduce conservativeness in robust optimization, the modeling of optimal operation of integrated electricity and heat system considering flexibility, and the accelerated solving algorithm for the bulk system.

Xiaolong Jin obtained the Ph.D. degree from the School of Electrical and Information Engineering, Tianjin University, Tianjin, China, in 2019. He is now a Postdoc researcher with Technical University of Denmark (DTU). His research interests include energy management of multi-energy systems and multi-energy buildings. Specifically, his research focuses on improving energy efficiency and reducing operating cost of multi-energy systems and multi-energy buildings with designed energy management frameworks, which uses the flexibilities from three aspects: 1) Use the demand-side flexibility by dispatching the flexible multi-energy loads in smart buildings; 2) Use the network-side flexibility by coordinating the multi-vector energy networks; 3) Use the supply-side flexibility by scheduling the various generations in the energy stations and the distributed energy resources connected with multi-energy systems and multi-energy buildings.

Ana Turk received the B.S. degree from the Faculty of Electrical Engineering and Computer Science at University of Maribor in Slovenia and MSc degree in Energy Engineering from Faculty of Engineering and Science at Aalborg University in Denmark in 2018. She is currently pursuing a Ph.D. at the Center of Electric Power and Energy (CEE) at the Department of Electrical Engineering at the Technical University of Denmark (DTU). Her research interest include integration and modeling of multi-energy systems (district heating, natural gas and electric power system), stochastic programming and optimal operation and scheduling of multi-energy systems. In particular, special focus is on optimal operation and real time control of integrated energy systems by using model predictive control.

De la contraportada

Modeling and Optimal Operation of Integrated Multi-Energy Systems discusses core concepts, advanced modelling, and key operation strategies for integrated multi-energy systems geared for optimal operation. It focuses particularly on reviewing novel operating strategies supported by relevant code in MATLAB and GAMS. The book covers foundational concepts, key challenges and opportunities in operational implementation, followed by discussion of conventional approaches to modeling electricity, heat and gas networks. This modeling is the base for more detailed operation strategies for optimal operation of integrated multi-energy systems under uncertainty covered in the latter part of the work.