TY - GEN
T1 - Reserve zone determination based on statistical clustering methods
AU - Wang, Fengyu
AU - Hedman, Kory
PY - 2012
Y1 - 2012
N2 - Due to contingencies, uncertainties, and congestion both the amount and the location of operating reserve (spinning and non-spinning) are essential to ensure system reliability and market efficiency. Today's reserve zone determination methods are mainly based on ad-hoc rules, such as utilities ownership, geographical boundaries, or key transmission lines. Thus, there is a need for more systematic, theoretical ways to determine reserve zones. The mathematical representation of reserves within day-ahead unit commitment models does not account for congestion, which is why reserve zones are important: to ensure the deliverability of reserve. Even with reserve zones, reserves within a zone are assumed to have no deliverability problem, i.e., it is assumed that congestion will not prevent reserve to be delivered where needed within that zone. With the advent of variable renewable resources and other causes of uncertainty (load, electric vehicles), there is a need to improve the determination of reserve zones in order to ensure a reliable system. Statistical clustering techniques are employed to determine the reserve zones based on the power transfer distribution factors (PTDF) and electrical distances (ED).
AB - Due to contingencies, uncertainties, and congestion both the amount and the location of operating reserve (spinning and non-spinning) are essential to ensure system reliability and market efficiency. Today's reserve zone determination methods are mainly based on ad-hoc rules, such as utilities ownership, geographical boundaries, or key transmission lines. Thus, there is a need for more systematic, theoretical ways to determine reserve zones. The mathematical representation of reserves within day-ahead unit commitment models does not account for congestion, which is why reserve zones are important: to ensure the deliverability of reserve. Even with reserve zones, reserves within a zone are assumed to have no deliverability problem, i.e., it is assumed that congestion will not prevent reserve to be delivered where needed within that zone. With the advent of variable renewable resources and other causes of uncertainty (load, electric vehicles), there is a need to improve the determination of reserve zones in order to ensure a reliable system. Statistical clustering techniques are employed to determine the reserve zones based on the power transfer distribution factors (PTDF) and electrical distances (ED).
KW - Expected load not served
KW - K-means
KW - electrical distance
KW - power transfer distribution factors
KW - reserve requirements
KW - reserve zones
KW - unit commitment
KW - value of lost load
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U2 - 10.1109/NAPS.2012.6336318
DO - 10.1109/NAPS.2012.6336318
M3 - Conference contribution
AN - SCOPUS:84870536349
SN - 9781467323086
T3 - 2012 North American Power Symposium, NAPS 2012
BT - 2012 North American Power Symposium, NAPS 2012
T2 - 2012 North American Power Symposium, NAPS 2012
Y2 - 9 September 2012 through 11 September 2012
ER -