University of Illinois Urbana-Champaign

A MARKOVIAN APPROACH FOR WIND POWER FORECASTING TO SUPPORT OPTIMIZATION ALGORITHMS FOR RISK-SENSITIVE, MULTI-TIME STAGE FORWARD ENERGY PROCUREMENT PROBLEMS IN POWER GRIDS

Khandelwal, Divyam

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https://hdl.handle.net/2142/106021

Description

Title
A MARKOVIAN APPROACH FOR WIND POWER FORECASTING TO SUPPORT OPTIMIZATION ALGORITHMS FOR RISK-SENSITIVE, MULTI-TIME STAGE FORWARD ENERGY PROCUREMENT PROBLEMS IN POWER GRIDS
Author(s)
Khandelwal, Divyam
Contributor(s)
Bose, Subhonmesh
Issue Date
2019-12
Keyword(s)
  • Wind-power forecasting
  • Energy Procurement
  • Economic Dispatch
  • Power Grids
Abstract
In this paper, a data-driven Markov chain model is used to provide short-term forecasts of power generation in wind farms. The probabilistic distributions generated from the model are then integrated in a risk-sensitive, forward energy procurement problem with the incorporation of uncertain wind generation that penalizes costs and constraint violations, forming the basis for performing risk-sensitive economic dispatch on power networks. This allows a system operator to model her tolerance to high uncertain costs and constraint violations.
Type of Resource
text
Language
en
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http://hdl.handle.net/2142/106021

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