Coordinated trading of wind and thermal energy

Ali T. Al-Awami; Mohamed A. El-Sharkawi

doi:10.1109/TSTE.2011.2111467

Coordinated trading of wind and thermal energy

Ali T. Al-Awami
, Mohamed A. El-Sharkawi

Research output: Contribution to journal › Article › peer-review

120 Scopus citations

Abstract

Trading wind energy in short-term electricity markets has high associated risks due to the uncertainties in hourly available wind, energy prices, and imbalance penalties. Coordinated trading of wind and thermal energy is proposed to mitigate risks due to those uncertainties. The problem of wind-thermal coordinated trading is formulated as a mixed-integer stochastic linear program. The objective is to obtain the optimal trade-off bidding strategy that maximizes the total expected profits while controlling trading risks. For risk control, a weighted term of the conditional value at risk (CVaR) is included in the objective function. The CVaR aims to maximize the expected profits of the least profitable scenarios, thus improving trading risk control. A case study comparing coordinated with uncoordinated bidding strategies depending on the trader's risk attitude is included. Simulation results show that coordinated bidding can improve the expected profits while significantly improving the CVaR.

Original language	English
Article number	5709999
Pages (from-to)	277-287
Number of pages	11
Journal	IEEE Transactions on Sustainable Energy
Volume	2
Issue number	3
DOIs	https://doi.org/10.1109/TSTE.2011.2111467
State	Published - Jul 2011
Externally published	Yes

Bibliographical note

Funding Information:
Manuscript received August 06, 2010; revised December 15, 2010; accepted January 27, 2011. Date of publication February 04, 2011; date of current version June 22, 2011. The work of A. T. Al-Awami was supported by King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Coordinated bidding strategy
mixed integer stochastic programming (SP)
risk
thermal power production
wind power production

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment

Access to Document

10.1109/TSTE.2011.2111467

Cite this

@article{33ed7fefd1b4416eae3817f5925f461d,

title = "Coordinated trading of wind and thermal energy",

abstract = "Trading wind energy in short-term electricity markets has high associated risks due to the uncertainties in hourly available wind, energy prices, and imbalance penalties. Coordinated trading of wind and thermal energy is proposed to mitigate risks due to those uncertainties. The problem of wind-thermal coordinated trading is formulated as a mixed-integer stochastic linear program. The objective is to obtain the optimal trade-off bidding strategy that maximizes the total expected profits while controlling trading risks. For risk control, a weighted term of the conditional value at risk (CVaR) is included in the objective function. The CVaR aims to maximize the expected profits of the least profitable scenarios, thus improving trading risk control. A case study comparing coordinated with uncoordinated bidding strategies depending on the trader's risk attitude is included. Simulation results show that coordinated bidding can improve the expected profits while significantly improving the CVaR.",

keywords = "Coordinated bidding strategy, mixed integer stochastic programming (SP), risk, thermal power production, wind power production",

author = "Al-Awami, \{Ali T.\} and El-Sharkawi, \{Mohamed A.\}",

note = "Funding Information: Manuscript received August 06, 2010; revised December 15, 2010; accepted January 27, 2011. Date of publication February 04, 2011; date of current version June 22, 2011. The work of A. T. Al-Awami was supported by King Fahd University of Petroleum \& Minerals (KFUPM), Dhahran, Saudi Arabia.",

year = "2011",

month = jul,

doi = "10.1109/TSTE.2011.2111467",

language = "English",

volume = "2",

pages = "277--287",

journal = "IEEE Transactions on Sustainable Energy",

issn = "1949-3029",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "3",

}

TY - JOUR

T1 - Coordinated trading of wind and thermal energy

AU - Al-Awami, Ali T.

AU - El-Sharkawi, Mohamed A.

N1 - Funding Information: Manuscript received August 06, 2010; revised December 15, 2010; accepted January 27, 2011. Date of publication February 04, 2011; date of current version June 22, 2011. The work of A. T. Al-Awami was supported by King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia.

PY - 2011/7

Y1 - 2011/7

N2 - Trading wind energy in short-term electricity markets has high associated risks due to the uncertainties in hourly available wind, energy prices, and imbalance penalties. Coordinated trading of wind and thermal energy is proposed to mitigate risks due to those uncertainties. The problem of wind-thermal coordinated trading is formulated as a mixed-integer stochastic linear program. The objective is to obtain the optimal trade-off bidding strategy that maximizes the total expected profits while controlling trading risks. For risk control, a weighted term of the conditional value at risk (CVaR) is included in the objective function. The CVaR aims to maximize the expected profits of the least profitable scenarios, thus improving trading risk control. A case study comparing coordinated with uncoordinated bidding strategies depending on the trader's risk attitude is included. Simulation results show that coordinated bidding can improve the expected profits while significantly improving the CVaR.

AB - Trading wind energy in short-term electricity markets has high associated risks due to the uncertainties in hourly available wind, energy prices, and imbalance penalties. Coordinated trading of wind and thermal energy is proposed to mitigate risks due to those uncertainties. The problem of wind-thermal coordinated trading is formulated as a mixed-integer stochastic linear program. The objective is to obtain the optimal trade-off bidding strategy that maximizes the total expected profits while controlling trading risks. For risk control, a weighted term of the conditional value at risk (CVaR) is included in the objective function. The CVaR aims to maximize the expected profits of the least profitable scenarios, thus improving trading risk control. A case study comparing coordinated with uncoordinated bidding strategies depending on the trader's risk attitude is included. Simulation results show that coordinated bidding can improve the expected profits while significantly improving the CVaR.

KW - Coordinated bidding strategy

KW - mixed integer stochastic programming (SP)

KW - risk

KW - thermal power production

KW - wind power production

UR - https://www.scopus.com/pages/publications/79959571592

U2 - 10.1109/TSTE.2011.2111467

DO - 10.1109/TSTE.2011.2111467

M3 - Article

AN - SCOPUS:79959571592

SN - 1949-3029

VL - 2

SP - 277

EP - 287

JO - IEEE Transactions on Sustainable Energy

JF - IEEE Transactions on Sustainable Energy

IS - 3

M1 - 5709999

ER -

Coordinated trading of wind and thermal energy

Abstract

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this