Overview

Optimal Operation of Integrated Multi-Energy Systems Under Uncertainty discusses core concepts, advanced modeling and key operation strategies for integrated multi-energy systems geared for use in optimal operation. The book particularly focuses on reviewing novel operating strategies supported by relevant code in MATLAB and GAMS. It covers foundational concepts, key challenges and opportunities in operational implementation, followed by discussions 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.

Full Product Details

Author:   Qiuwei Wu (Chair Professor, School of Electrical and Information Engineering, Tianjin University, China) ,  Jin Tan (Technical University of Denmark, Denmark) ,  Menglin Zhang (Postdoctoral researcher, Technical University of Denmark, Denmark) ,  Xiaolong Jin (Postdoctoral researcher, Technical University of Denmark, Denmark)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Elsevier Science Publishing Co Inc
Weight:   0.450kg
ISBN:  

9780128241141

ISBN 10:   0128241144
Pages:   370
Publication Date:   13 September 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

1. Introduction of integrated multi-energy systems 2. Modeling of integrated multi-energy systems 3. Uncertainty modelling of wind power for stochastic and robust optimization 4. Optimal operation of multi-energy building complex 5. MPC based real-time dispatch of multi-energy building complex 6. Adaptive robust two-stage optimal operation of integrated electricity and heat system 7. Decentralized robust optimal operation of multiple integrated electricity and heat systems 8. Chance constrained energy and reserve scheduling for integrated electricity and heating systems considering wind spatio-temporal correlations 9. Day-ahead stochastic optimal operation of integrated electricity and heat systems considering reserve of flexible devices 10. Two-stage stochastic optimal operation of integrated energy systems 11. MPC based real-time operation of integrated energy systems

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Author Information

Qiuwei Wu is currently a Chair Professor at the School of Electrical and Information Engineering at Tianjin University, China. Prior to this he was a tenured Associate Professor at the Tsinghua-Berkeley Shenzhen Institute of Tsinghua University, China. His research interests are in decentralized/distributed optimal operation and control of power systems with high penetration of renewables, including distributed wind power modelling and control, decentralized/distributed congestion management, voltage control and load restoration of active distribution networks, and decentralized/distributed optimal operation of integrated energy systems. Dr. Wu is an Associate Editor of IEEE Transactions on Power Systems and IEEE Power Engineering Letters, Deputy Editor-in-Chief and Associate Editor of the International Journal of Electrical Power and Energy Systems and the Journal of Modern Power Systems and Clean Energy, and a subject editor for IET Generation, Transmission & Distribution and IET Renewable Power Generation. 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.

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