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E-grāmata: Renewable Energy Integration for Bulk Power Systems: ERCOT and the Texas Interconnection

  • Formāts: PDF+DRM
  • Sērija : Power Electronics and Power Systems
  • Izdošanas datums: 12-May-2023
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783031286391
  • Formāts - PDF+DRM
  • Cena: 83,27 €*
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  • Formāts: PDF+DRM
  • Sērija : Power Electronics and Power Systems
  • Izdošanas datums: 12-May-2023
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783031286391

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Renewable Energy Integration for Bulk Power Systems: ERCOT and the Texas Interconnection looks at the practices and changes introduced in the Texas electric grid to facilitate renewable energy integration. It offers an informed perspective on solutions that have been successfully demonstrated, tested, and validated by the Electric Reliability Council of Texas (ERCOT) to meet the key challenges which engineers face in integrating increased levels of renewable resources into existing electric grids while maintaining reliability. Coverage includes renewable forecasting, ancillary services, and grid and market operations. Proved methods and their particular use scenarios, including wind, solar, and other resources like batteries and demand response, are also covered. The book focuses on a real-world context that will help practicing engineers, utility providers, and researchers understand the practical considerations for developing renewable integration solutions and inspire the future development of more innovative strategies and theoretical underpinnings.
Chapter 1 Renewable Integration at ERCOT.
Chapter 2 Overview of Market
Operation at ERCOT.
Chapter 3 Market Designs to Integrate Renewable
Resources.
Chapter 4 Ancillary Services (AS) at ERCOT.
Chapter 5 Design of
New Primary Frequency Control Market for Hosting Frequency Response Reserve
Offers from both Generators and Loads.
Chapter 6 New Ancillary Service
Market for ERCOT - Fast Frequency Response (FFR).
Chapter 7 System Inertia
Trend and Critical Inertia.
Chapter 8 Multiple-Period Reactive Power
Coordination for Renewable Integration.
Chapter 9 Renewable Forecast.-
Chapter 10 Ensemble Machine Learning Based Wind Forecasting to Combine NWP
Output with Data from Weather Stations. 
Dr. Pengwei Du is with the Electric Reliability Council of Texas (ERCOT). Before that, he was a senior research engineer with Pacific Northwest National Laboratory (PNNL). Dr. Du has extensive experience in simulation, modelling, protection, and control of power systems, renewable energy integration, and grid operations. He has been Chair of the IEEE Power & Energy Societys (PES) Bulk Power System Planning Subcommittee. He has been a subject editor for IET Generation Transmission & Distribution and an editor for IEEE Transactions on Power Systems and IEEE Transactions on Energy Markets, Policy and Regulation. Dr. Du is the recipient of the IEEE PES Power System Dynamic Performance Committee Best Paper Prize in 2016 and the IEEE PES Prize Paper Award in 2020. He graduated from Rensselaer Polytechnic Institute with a Ph.D. in electric power engineering. He is a Fellow of the IET.