Description: Data Analytics in Power Markets by Qixin Chen, Hongye Guo, Kedi Zheng, Yi Wang Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches. These methods are especially useful for market organizers to understand the bidding behaviors of market participants and make essential policies. Publisher Description This book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches. It begins with an overview of the power market data and analyzes on their characteristics and importance for market clearing. Then, the first part of the book discusses the essential problem of bus load forecasting from the perspective of market organizers. The related works include load uncertainty modeling, bus load bad data correction, and monthly load forecasting. The following part of the book answers how much information can be obtained from public data in locational marginal price (LMP)-based markets. It introduces topics such as congestion identification, componential price forecasting, quantifying the impact of forecasting error, and financial transmission right investment. The final part of the book answers how to model the complex market bidding behaviors. Specific works include pattern extraction, aggregated supply curve forecasting, market simulation, and reward function identification in bidding. These methods are especially useful for market organizers to understand the bidding behaviors of market participants and make essential policies. It will benefit and inspire researchers, graduate students, and engineers in the related fields. Author Biography Qixin Chen, IEEE Senior Member, Tenured Associate Professor of Department of Electrical Engineering in Tsinghua University, Chair of IEEE working group on load aggregation; Associate Director for Energy Internet Research Institute, Tsinghua University Research interests: Power market, low carbon electricity technology, power system. Honors:- National Youth Top-notch Talent Support Program, Ministry of Science and Technology, China (2018)- National Science Fund for Distinguished Young Scholars (2016);- Research Fund for Distinguished Young Scholars, Fok Ying-Tong Education Foundation (2015);- Beijing New-Star Plan for Young Scholars, Scientific Committee of Beijing City Government (2015);-Young Scientist Honor (40 under the Age of 40), by World Economic Forum Summer Davos (2013);-Top 35 Young Innovator under the Age of 35 (TR 35), by MIT Technology Review (2012);-FirstRunner-up, Young Scientist Award, by ProSper.Net, Scopus and Elsevier (2011);-Nominee Honor, National Excellent 100 Doctoral Dissertation, Ministry of Education, China (2013);-Paper Author, Chinas top 5000 scientific journal papers (F5000) (2012/2013/2016);-Annual Award for Publishing a One-Hundred Most Influential Chinese Scholar Paper (2012). Hongye Guo, postdoc research fellow at Department of Electrical Engineering in Tsinghua University. Visiting scholar of Stanford University in 2018. Visiting scholar of Illinois Institute of Technology in 2019. Research interests: Power market, game theory, energy economics, machine learning. Honors:- "Shuimu" Tsinghua Scholar (2020);- Best PhD Dissertation of Tsinghua University (2020);- Outstanding Young Researcher, Department of Electrical Engineering, Tsinghua University (2020);- Doctoral National Scholarship (2019);- Integrated Excellence Scholarships, Tsinghua University (2018); Kedi Zheng, PhD student of Department of Electrical Engineering in Tsinghua University. Research interests: Power market, locational marginal price (LMP) theory, electricity forecasting. Honors:- Integrated Excellence Scholarships, Tsinghua University (2018/2020)- Outstanding Graduate Award, City of Beijing (2017);- Excellent Graduate Award, Tsinghua University (2017); Yi Wang, Assistant Professor of Department of Electrical and Electronic Engineering in the University of Hong Kong, Editor of International Transactions on Electrical Energy Systems, Youth Associate Editor of CSEE Journal of Power & Energy Systems, Secretary of IEEE working group on load aggregation. Research interests: Load forecasting, demand response, machine learning for smart grid, multiple energy systems. Honors:-Siebel Scholar Award;-IEEE Transactions on Smart Grid Best Reviewer (2018/2017);-IEEE Transactions on Power Systems Outstanding Reviewer (2018/2016);-Fellowships for Future Scholars, Tsinghua University (2014);-Tsinghua Science & Technology Best Paper Awards;-Doctoral National Scholarship (2016/2017/2018). Details ISBN 981164974X ISBN-13 9789811649745 Title Data Analytics in Power Markets Author Qixin Chen, Hongye Guo, Kedi Zheng, Yi Wang Format Hardcover Year 2021 Pages 273 Edition 1st Publisher Springer Verlag, Singapore GE_Item_ID:140303367; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. 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Price: 176.3 USD
Location: Fairfield, Ohio
End Time: 2024-09-19T02:21:24.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9789811649745
Type: NA
Publication Name: NA
Book Title: Data Driven Analysis and Forecasting in Power Markets
Number of Pages: Xix, 273 Pages
Language: English
Publisher: Springer
Topic: Intelligence (Ai) & Semantics, Probability & Statistics / General, Industries / Energy
Publication Year: 2021
Illustrator: Yes
Genre: Mathematics, Computers, Business & Economics
Item Weight: 22.2 Oz
Author: Yi Wang, Qixin Chen, Kedi Zheng, Hongye Guo
Item Length: 9.3 in
Item Width: 6.1 in
Format: Hardcover