TY - JOUR
T1 - An Investigation on the Impacts of Low Probability and High Intensity Events on Wind Power Generator's Market Participation
AU - Mallahi, Abdolaziz
AU - Abdollahi, Amir
AU - Rashidinejad, Masoud
AU - Heydarian-Forushani, Ehsan
AU - Al-Sumaiti, Ameena Saad
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper presents an extensive decision-making model for Wind Power Generators (WPGs) for profit maximization in an electricity market environment. This model has been presented at the intraday market stage due to the fact that WPGs can react according to the latest information and also they have less forecast errors in comparison to Day-ahead (DA) market. In addition, the Intraday Demand Response Exchange (IDRX) market is modelled with the aim of covering wind generation volatility so that the WPG can participate in it as a buyer. Note that, Demand Response (DR) uncertainty is modelled through Information Gap Decision Theory (IGDT) method so that the amount of financial resistance to the possible increase of the load is considered. In this article, the profitability of WPG in the event of High-Intensity and Low-Probability (HILP) events such as the hurricane, is also examined. In fact, the effects of hurricane on failure rate, reliability and aging of wind units are investigated. The Conditional Value at Risk (CVaR) is utilized to quantify the WPG risk as well. Several numerical analysis are conducted to show evidence of the approach efficacy.
AB - This paper presents an extensive decision-making model for Wind Power Generators (WPGs) for profit maximization in an electricity market environment. This model has been presented at the intraday market stage due to the fact that WPGs can react according to the latest information and also they have less forecast errors in comparison to Day-ahead (DA) market. In addition, the Intraday Demand Response Exchange (IDRX) market is modelled with the aim of covering wind generation volatility so that the WPG can participate in it as a buyer. Note that, Demand Response (DR) uncertainty is modelled through Information Gap Decision Theory (IGDT) method so that the amount of financial resistance to the possible increase of the load is considered. In this article, the profitability of WPG in the event of High-Intensity and Low-Probability (HILP) events such as the hurricane, is also examined. In fact, the effects of hurricane on failure rate, reliability and aging of wind units are investigated. The Conditional Value at Risk (CVaR) is utilized to quantify the WPG risk as well. Several numerical analysis are conducted to show evidence of the approach efficacy.
KW - Bidding strategy
KW - demand response
KW - HILP events
KW - uncertainty modelling
KW - wind power generators
UR - http://www.scopus.com/inward/record.url?scp=85124230971&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2022.3149035
DO - 10.1109/ACCESS.2022.3149035
M3 - Article
AN - SCOPUS:85124230971
SN - 2169-3536
VL - 10
SP - 18093
EP - 18104
JO - IEEE Access
JF - IEEE Access
ER -