TY - JOUR
T1 - Power Congestion Management in Integrated Electricity and Gas Distribution Grids
AU - Khani, Hadi
AU - El-Taweel, Nader
AU - Farag, Hany E.Z.
N1 - Funding Information:
Manuscript received December 26, 2017; revised May 13, 2018; accepted June 23, 2018. Date of publication July 13, 2018; date of current version May 31, 2019. This work was supported by the Natural Sciences and Engineering Research Council of Canada. (Corresponding author: Hadi Khani.) The authors are with the Department of Electrical Engineering and Computer Science, York University, Toronto, ON M3J 1P3, Canada (e-mail:, [email protected]; [email protected]; [email protected]). Digital Object Identifier 10.1109/JSYST.2018.2850882
Publisher Copyright:
© 2007-2012 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - The proliferation of gas-fired generation (GfG) units and emerging power-to-gas (PtG) technology can set the stage for an integrated natural gas and power distribution system. PtG and gas-fired units have the potential to mitigate several existing and imminent issues of power distribution systems. This paper investigates how PtG and GfG facilities can be added to the portfolio of conventional resolutions when the motivation is (partly) congestion management in power distribution systems. It demonstrates how PtG and GfG units as merchant investments can change the operation philosophy from the traditional preventive to the novel corrective mode. To that end, a new real-time optimal scheduling algorithm is proposed to enable a PtG-GfG unit to optimally contribute to the congestion management. Merchandise operators profit, in addition to the arbitrage benefit, by relieving the distribution grid's congestion, thereby achieving a more stable return on investments. Slack variables are incorporated into the optimization problem to measure the contribution of the PtG-GfG unit to the congestion management. A new mechanism is proposed through which the merchandise operator is financially compensated by the power system operator, due to its contribution to the congestion management. Numerical studies using real-world data on a test system validate the efficacy and feasibility of the algorithm.
AB - The proliferation of gas-fired generation (GfG) units and emerging power-to-gas (PtG) technology can set the stage for an integrated natural gas and power distribution system. PtG and gas-fired units have the potential to mitigate several existing and imminent issues of power distribution systems. This paper investigates how PtG and GfG facilities can be added to the portfolio of conventional resolutions when the motivation is (partly) congestion management in power distribution systems. It demonstrates how PtG and GfG units as merchant investments can change the operation philosophy from the traditional preventive to the novel corrective mode. To that end, a new real-time optimal scheduling algorithm is proposed to enable a PtG-GfG unit to optimally contribute to the congestion management. Merchandise operators profit, in addition to the arbitrage benefit, by relieving the distribution grid's congestion, thereby achieving a more stable return on investments. Slack variables are incorporated into the optimization problem to measure the contribution of the PtG-GfG unit to the congestion management. A new mechanism is proposed through which the merchandise operator is financially compensated by the power system operator, due to its contribution to the congestion management. Numerical studies using real-world data on a test system validate the efficacy and feasibility of the algorithm.
KW - Arbitrage
KW - congestion management
KW - financial compensation
KW - gas distribution grid
KW - gas-fired generation (GfG) unit
KW - optimal scheduling
KW - power distribution system
KW - power-to-gas unit
UR - http://www.scopus.com/inward/record.url?scp=85049947127&partnerID=8YFLogxK
U2 - 10.1109/JSYST.2018.2850882
DO - 10.1109/JSYST.2018.2850882
M3 - Article
AN - SCOPUS:85049947127
SN - 1932-8184
VL - 13
SP - 1883
EP - 1894
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 2
M1 - 8410675
ER -