Share
Data Analytics in Power Markets
Qixin Chen
(Author)
·
Hongye Guo
(Author)
·
Kedi Zheng
(Author)
·
Springer
· Paperback
Data Analytics in Power Markets - Chen, Qixin ; Guo, Hongye ; Zheng, Kedi
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: U.S.A.
(Import costs included in the price)
It will be shipped from our warehouse between
Tuesday, July 16 and
Tuesday, July 23.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "Data Analytics in Power Markets"
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.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.
