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A01=Cuo Zhang
A01=Yan Xu
A01=Yu Wang
A01=Zhengmao Li
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Age Group_Uncategorized
Author_Cuo Zhang
Author_Yan Xu
Author_Yu Wang
Author_Zhengmao Li
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Category1=Non-Fiction
Category=THRB
Category=THRD
COP=United Kingdom
Delivery_Delivery within 10-20 working days
Language_English
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Coordination of Distributed Energy Resources in Microgrids: Optimisation, control, and hardware-in-the-loop validation

English

By (author): Cuo Zhang Yan Xu Yu Wang Zhengmao Li

Coordination of Distributed Energy Resources in Microgrids: Optimisation, control, and hardware-in-the-loop validation provides a structured overview of research into techniques for managing microgrids with distributed energy resources (DERs). The DERs including distributed generators, energy storage systems, and flexible loads are posing both challenges and opportunities to microgrids' security, planning, operation, and control. Advanced operation and control techniques are needed to coordinate these components in the microgrids and maintain power quality, as well as keeping the system economically feasible.

This book is for researchers and students in the area of smart grids, power engineering, and control engineering, as well as for advanced students, transmission network and grid operators. It focuses on cutting-edge techniques for secure, economic, and robust operation and control of microgrids. Effective coordination of DERs on both temporal and spatial scales are introduced in detail. Topics covered include comprehensive mathematical models of DERs and microgrids, sizing and siting of DERs under uncertainties, stochastic and robust optimisation for active and reactive power dispatch of DERs in microgrids, distributed coordinated control, and hardware-in-the-loop tests for validation of control algorithms.

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A01=Cuo ZhangA01=Yan XuA01=Yu WangA01=Zhengmao LiAge Group_UncategorizedAuthor_Cuo ZhangAuthor_Yan XuAuthor_Yu WangAuthor_Zhengmao Liautomatic-updateCategory1=Non-FictionCategory=THRBCategory=THRDCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=AvailablePrice_€100 and abovePS=Activesoftlaunch
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Product Details
  • Dimensions: 156 x 234mm
  • Publication Date: 07 Feb 2022
  • Publisher: Institution of Engineering and Technology
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781839532689

About Cuo ZhangYan XuYu WangZhengmao Li

Yan Xu is an associate professor at School of Electrical and Electronic Engineering and a cluster director at Energy Research Institute at NTU (ERI@N). Dr Xu has published 1 book 86 IEEE Transactions papers and 30 IET journal papers. He has 13 'Web-of-Science highly cited papers' and received 10 IEEE/IET best paper awards. Dr Xu is serving as an editor for IEEE Transactions (TSG and TPWRS) and IET journals (GTD and ECE). Yu Wang is a research fellow in the Rolls-Royce-NTU Corporate Lab Nanyang Technological University Singapore. He was a recipient of the EU Marie Skodowska-Curie Action Individual Fellowship 2020. His research interests include distributed control and optimisation of energy storage systems microgrids and cyber-physical power systems. He has published 50 peer-reviewed journal and conference papers including 3 'web-of-science highly cited papers.' Cuo Zhang is a research fellow with the University of New South Wales Australia. He is also a chief investigator of ARC Research Hub for Integrated Energy Storage Solutions. His research interests include power system planning and operation voltage stability and control microgrids multi-energy systems and applications of optimisation theory in these areas. He has published 10 IEEE Transactions journal papers including 2 'web-of-science highly cited papers' and awarded 3 IEEE/IET conference best papers. Zhengmao Li is a research fellow at Nanyang Technological University under the NTU-ETH future resilience system project. He was previously a research fellow with the Stevens Institute of Technology Hoboken NJ USA. His research interests include renewable energy integration multi-energy systems such as multi-energy microgrid multi-energy ship optimisation and reinforcement learning techniques such as approximate dynamic programming robust and stochastic optimisation method resilience of multi-energy systems.

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