Intelligent Microgrid Management and EV Control Under Uncertainties in Smart Grid [electronic resource] / by Ran Wang, Ping Wang, Gaoxi Xiao.
By: Wang, Ran [author.]
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Contributor(s): Wang, Ping [author.] | Xiao, Gaoxi [author.] | SpringerLink (Online service).
Material type: 
BookPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVIII, 140 p. 40 illus., 37 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811042508.Subject(s): Electric power production | Renewable energy sources | Operations research | Management science | Electrical Power Engineering | Renewable Energy | Operations Research, Management ScienceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.31 Online resources: Click here to access online
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Springer Nature eBookSummary: This book, discusses the latest research on the intelligent control of two important components in smart grids, namely microgrids (MGs) and electric vehicles (EVs). It focuses on developing theoretical frameworks and proposing corresponding algorithms, to optimally schedule virtualized elements under different uncertainties so that the total cost of operating the microgrid or the EV charging system can be minimized and the systems maintain stabilized. With random factors in the problem formulation and corresponding designed algorithms, it provides insights into how to handle uncertainties and develop rational strategies in the operation of smart grid systems. Written by leading experts, it is a valuable resource for researchers, scientists and engineers in the field of intelligent management of future power grids.
This book, discusses the latest research on the intelligent control of two important components in smart grids, namely microgrids (MGs) and electric vehicles (EVs). It focuses on developing theoretical frameworks and proposing corresponding algorithms, to optimally schedule virtualized elements under different uncertainties so that the total cost of operating the microgrid or the EV charging system can be minimized and the systems maintain stabilized. With random factors in the problem formulation and corresponding designed algorithms, it provides insights into how to handle uncertainties and develop rational strategies in the operation of smart grid systems. Written by leading experts, it is a valuable resource for researchers, scientists and engineers in the field of intelligent management of future power grids.
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