TY - GEN
T1 - Optimal Participation of Price-Maker Battery Energy Storage Systems in Energy, Reserve and Pay as Performance Regulation Markets
AU - Khalilisenobari, Reza
AU - Wu, Meng
PY - 2019/10
Y1 - 2019/10
N2 - Motivated by the need of assessing the optimal allocation of battery energy storage services across various markets and the corresponding impact on market operations, an optimization framework is proposed in this work to coordinate the operation of an independent utility-scale price-maker battery energy storage system (BESS) in the energy, spinning reserve and performance-based regulation markets. The entire problem is formulated as a bi-level optimization process, where the structure of all markets is modeled considering the joint operation limits. The strategic bidding behavior of a price-maker BESS in a pay as performance regulation market is investigated. Additionally, a specific approach is introduced for modeling automatic generation control (AGC) signals in the optimization. Although the formulated problem is non-linear, it is converted to mixed-integer linear programming (MILP) to find the optimum solution. The proposed framework is evaluated using test case scenarios created from real-world market data. Case study results show the impact of BESS's price-making behavior on the joint operation of energy, reserve, and regulation markets.
AB - Motivated by the need of assessing the optimal allocation of battery energy storage services across various markets and the corresponding impact on market operations, an optimization framework is proposed in this work to coordinate the operation of an independent utility-scale price-maker battery energy storage system (BESS) in the energy, spinning reserve and performance-based regulation markets. The entire problem is formulated as a bi-level optimization process, where the structure of all markets is modeled considering the joint operation limits. The strategic bidding behavior of a price-maker BESS in a pay as performance regulation market is investigated. Additionally, a specific approach is introduced for modeling automatic generation control (AGC) signals in the optimization. Although the formulated problem is non-linear, it is converted to mixed-integer linear programming (MILP) to find the optimum solution. The proposed framework is evaluated using test case scenarios created from real-world market data. Case study results show the impact of BESS's price-making behavior on the joint operation of energy, reserve, and regulation markets.
KW - Battery energy storage system (BESS)
KW - bidding strategy
KW - bilevel optimization
KW - mixed integer linear programming
KW - performance-based regulation market
KW - price-maker
UR - http://www.scopus.com/inward/record.url?scp=85080931706&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85080931706&partnerID=8YFLogxK
U2 - 10.1109/NAPS46351.2019.9000230
DO - 10.1109/NAPS46351.2019.9000230
M3 - Conference contribution
T3 - 51st North American Power Symposium, NAPS 2019
BT - 51st North American Power Symposium, NAPS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 51st North American Power Symposium, NAPS 2019
Y2 - 13 October 2019 through 15 October 2019
ER -