Location

Hilton Waikoloa Village, Hawaii

Event Website

http://www.hicss.hawaii.edu

Start Date

1-4-2017

End Date

1-7-2017

Description

Security-constrained unit commitment (SCUC) is a classical problem used for day-ahead commitment, dispatch, and reserve scheduling. Even though SCUC models acquire reserves, N-1 reliability is not guaranteed. This paper presents an enhanced security-constrained unit commitment formulation that facilitates the integration of stochastic resources and accounts for reserve deliverability issues. In this formulation, the SCUC is modified to incorporate a reserve response set model. The enhanced reserve model aims to predict the effects of nodal reserve deployment on critical transmission lines so as to improve the deliverability of reserves post-contingency. The enhanced reserve policies are developed using a knowledge discovery process as a means to predict reserve activation. The approach, thus, aims to acquire reserve at prime locations that face fewer reserve deliverability issues. The results show that the proposed approach consistently outperforms contemporary approaches. All numerical results are based on the IEEE 73-bus test case.

Share

COinS
 
Jan 4th, 12:00 AM Jan 7th, 12:00 AM

An Enhanced Security-Constrained Unit Commitment Model with Reserve Response Set Policies

Hilton Waikoloa Village, Hawaii

Security-constrained unit commitment (SCUC) is a classical problem used for day-ahead commitment, dispatch, and reserve scheduling. Even though SCUC models acquire reserves, N-1 reliability is not guaranteed. This paper presents an enhanced security-constrained unit commitment formulation that facilitates the integration of stochastic resources and accounts for reserve deliverability issues. In this formulation, the SCUC is modified to incorporate a reserve response set model. The enhanced reserve model aims to predict the effects of nodal reserve deployment on critical transmission lines so as to improve the deliverability of reserves post-contingency. The enhanced reserve policies are developed using a knowledge discovery process as a means to predict reserve activation. The approach, thus, aims to acquire reserve at prime locations that face fewer reserve deliverability issues. The results show that the proposed approach consistently outperforms contemporary approaches. All numerical results are based on the IEEE 73-bus test case.

http://aisel.aisnet.org/hicss-50/es/markets/4