TY - JOUR
T1 - A Reserve Response Set Model for Systems with Stochastic Resources
AU - Singhal, Nikita G.
AU - Li, Nan
AU - Hedman, Kory
N1 - Funding Information: This work was supported in part by the Consortium for Electric Reliability Technology Solutions with the U.S. Department of Energy (DOE) and in part by the Advanced Research Projects Agency - Energy with the U.S. DOE Funding Information: Manuscript received April 8, 2017; revised August 15, 2017 and October 26, 2017; accepted November 17, 2017. Date of publication November 24, 2017; date of current version June 18, 2018. This work was supported in part by the Consortium for Electric Reliability Technology Solutions with the U.S. Department of Energy (DOE) and in part by the Advanced Research Projects Agency – Energy with the U.S. DOE. Paper no. TPWRS-00514-2017. (Corresponding author: Nikita G. Singhal.) The authors are with the School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287 USA (e-mail: nsinghal@ asu.edu; [email protected]; [email protected]). Digital Object Identifier 10.1109/TPWRS.2017.2776202 Publisher Copyright: © 1969-2012 IEEE.
PY - 2018/7
Y1 - 2018/7
N2 - The uncertainty and variability associated with stochastic resources coupled with the constantly changing system operating conditions introduce new challenges to power systems. Smart, well-designed reserve policies are needed to assist the operators in maintaining system reliability. This paper presents a reserve response set model, which improves upon existing deterministic models. The proposed model aims to address the allocation and deliverability issues associated with reserves by using reserve response set policies and by modeling the predicted post-contingency effects of nodal reserve deployment on critical transmission elements. The performance of the proposed reserve model is compared against contemporary deterministic programs and an extensive-form stochastic program. The results show that the proposed reserve model outperforms the contemporary models and improves the deliverability of reserves post-contingency at reduced costs. All numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems.
AB - The uncertainty and variability associated with stochastic resources coupled with the constantly changing system operating conditions introduce new challenges to power systems. Smart, well-designed reserve policies are needed to assist the operators in maintaining system reliability. This paper presents a reserve response set model, which improves upon existing deterministic models. The proposed model aims to address the allocation and deliverability issues associated with reserves by using reserve response set policies and by modeling the predicted post-contingency effects of nodal reserve deployment on critical transmission elements. The performance of the proposed reserve model is compared against contemporary deterministic programs and an extensive-form stochastic program. The results show that the proposed reserve model outperforms the contemporary models and improves the deliverability of reserves post-contingency at reduced costs. All numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems.
KW - Ancillary services
KW - electricity market design
KW - power generation scheduling
KW - reliability
KW - stochastic resources
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U2 - 10.1109/TPWRS.2017.2776202
DO - 10.1109/TPWRS.2017.2776202
M3 - Article
SN - 0885-8950
VL - 33
SP - 4038
EP - 4049
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 4
ER -