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Image of Data Analytics in Power Markets

Electronic Resource

Data Analytics in Power Markets

Chen, Qixin - Personal Name; Guo, Hongye - Personal Name; Zheng, Kedi - Personal Name; Wang, Yi - Personal Name;

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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.


Availability
Inventory Code Barcode Call Number Location Status
2108000074EB0005325658.81 DatCentral Library (OPAC)Available
Detail Information
Series Title
-
Call Number
658.81 Dat
Publisher
Singapore : Springer Singapore., 2021
Collation
xix, 273p.:ill
Language
English
ISBN/ISSN
978-981-16-4975-2
Classification
658.81
Content Type
Ebook
Media Type
-
Carrier Type
online resource
Edition
1
Subject(s)
Management--Market
Specific Detail Info
-
Statement of Responsibility
BRF
Other version/related

No other version available

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  • Data Analytics in Power Markets
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