TY - GEN
T1 - Optimal scheduling of energy storage to mitigate power quality issues in power systems
AU - Khani, Hadi
AU - Farag, Hany E.Z.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/29
Y1 - 2018/1/29
N2 - In this paper, a new optimal scheduling algorithm is proposed to enhance the economic feasibility of integrating energy storage systems (ESSs) in power grids. In addition to the profit gained by ESS owners from arbitrage, ESSs can contribute to mitigate power quality (PQ) issues in power systems. Toward that end, using a mixed-integer linear programming optimization problem, an adaptive reserve margin is created in the ESS reservoir; this enables an ESS to accept and follow the PQ external signals received from the grid operator. A new index is proposed to measure the ESS contribution to mitigation of PQ issues. Due to its contribution to mitigate PQ issues, the ESS owner is financially compensated by the grid operator. This financial benefit can be added to the regular profit resulted from exploiting arbitrage, thereby increasing the profitability of investment in ESSs. Numerical studies are conducted using actual data adopted from Ontario's electricity market.
AB - In this paper, a new optimal scheduling algorithm is proposed to enhance the economic feasibility of integrating energy storage systems (ESSs) in power grids. In addition to the profit gained by ESS owners from arbitrage, ESSs can contribute to mitigate power quality (PQ) issues in power systems. Toward that end, using a mixed-integer linear programming optimization problem, an adaptive reserve margin is created in the ESS reservoir; this enables an ESS to accept and follow the PQ external signals received from the grid operator. A new index is proposed to measure the ESS contribution to mitigation of PQ issues. Due to its contribution to mitigate PQ issues, the ESS owner is financially compensated by the grid operator. This financial benefit can be added to the regular profit resulted from exploiting arbitrage, thereby increasing the profitability of investment in ESSs. Numerical studies are conducted using actual data adopted from Ontario's electricity market.
UR - http://www.scopus.com/inward/record.url?scp=85046338602&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2017.8274600
DO - 10.1109/PESGM.2017.8274600
M3 - Conference contribution
AN - SCOPUS:85046338602
T3 - IEEE Power and Energy Society General Meeting
SP - 1
EP - 5
BT - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017
PB - IEEE Computer Society
T2 - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Y2 - 16 July 2017 through 20 July 2017
ER -
