Electric Distribution Grid with Inverter-based Resources : Modelling, Management, Optimization, and Control Approaches

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Electric Distribution Grid with Inverter-based Resources : Modelling, Management, Optimization, and Control Approaches

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  • 製本 Hardcover:ハードカバー版/ページ数 496 p.
  • 言語 ENG
  • 商品コード 9781394334179

Full Description

An expert discussion of the modeling, optimization, control, and management of electric distribution systems and inverter-based resources

In Electric Distribution Grid with Inverter-based Resources: Modelling, Management, Optimization, and Control Approaches, a pair of distinguished engineering professors delivers an expert discussion of how to understand, analyze, model, and evaluate the electric distribution grid with inverter-based resources (IBRs).

The book provides approaches for management optimization and control that are consistent with up-to-date research and data. The authors explain real-life implementation strategies and offer an in-depth experience for readers that includes illustrative examples and models used in the industry. Later chapters provide forward-looking management and control approaches that incorporate the most likely advances and changes coming to the industry.

Additional topics include:

A thorough introduction to IBR modeling, including utility-scale PV farms, behind-the-meter PV units and energy storage systems, energy-efficient buildings and load models, and electric vehicle models
Comprehensive explorations of electric grid level optimization and control incorporating advanced distribution system power flow models with IBRs
Practical discussions of the management of electric distribution grids
Complete treatments of the devices, interfaces, and communication methods that make electric distribution systems with IBRs function

Perfect for undergraduate and graduate students of electrical engineering with an interest in power systems, Electric Distribution Grid with Inverter-based Resources will also aid consultants, researchers, industry practitioners, and cross-disciplinary learners.

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