Data analytics in power markets

Data analytics in power markets / Qixin Chen, Hongye Guo, Kedi Zheng, Yi Wang.

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 p...

Full description

Saved in:
Bibliographic Details
Main Authors: Chen, Qixin (Electrical engineer) (Author), Guo, Hongye (Author), Zheng, Kedi (Author), Wang, Yi (Author)
Format: eBook
Language:English
Published: Singapore : Springer, 2021.
Subjects:
Electric utilities > Statistical methods.
Electric utilities > Data processing.
Electric utilities > Data processing
Online Access:Click for online access
Table of Contents:
  • Introduction to power market data and their characteristics
  • Modeling load forecasting uncertainty using deep learning models
  • Data-driven load data cleaning and its impacts on forecasting performance
  • Generalized cost-oriented load forecasting in economic dispatch
  • A monthly electricity consumption forecasting method
  • Data-driven pattern extraction for analyzing market bidding behaviors
  • Stochastic optimal offering based on probabilistic forecast on aggregated supply curves
  • Power market simulation framework based on learning from individual offering strategy
  • Deep inverse reinforcement learning for reward function identification in bidding models
  • The subspace characteristics and congestion identification of LMP data
  • Online transmission topology identification in LMP-based markets
  • Day-ahead componential electricity price forecasting
  • Quantifying the impact of price forecasting error on market bidding
  • Virtual bidding and FTR speculation based on probabilistic LMP forecasting
  • Abnormal detection of LMP scenario and data with deep neural networks.

Similar Items