TY - JOUR
T1 - Risk Assessment Based Long-Term Transmission System Hardening under Prior Probabilistic Information
AU - Ding, Tao
AU - Li, Cheng
AU - Chen, Chen
AU - Chen, Bo
AU - Yang, Yongheng
PY - 2019/1
Y1 - 2019/1
N2 - In the long-term transmission system hardening, critical components in transmission infrastructure should be identified and hardened to reduce the load loss risk in the presence of scheduled and unscheduled outages. Generally, the probabilistic information of assets in power systems can be evaluated via historical statistics. On the basis of the prior probabilistic information, this study proposed a tri-level optimisation model to deal with the problem of long-term transmission system hardening, in which the risk assessment is taken into account in the objective function. Furthermore, the problem is formulated as a two-stage robust optimisation model. To address the non-linear problem in the inner model, logarithmic transformation and piecewise linearisation are utilised to exactly linearise the non-linear terms in the model. Finally, the standard column-and-constraints generation algorithm is employed to solve the proposed model with a master-sub-problem framework. The test results on a standard IEEE RTS-96 system show the effectiveness of the proposed model.
AB - In the long-term transmission system hardening, critical components in transmission infrastructure should be identified and hardened to reduce the load loss risk in the presence of scheduled and unscheduled outages. Generally, the probabilistic information of assets in power systems can be evaluated via historical statistics. On the basis of the prior probabilistic information, this study proposed a tri-level optimisation model to deal with the problem of long-term transmission system hardening, in which the risk assessment is taken into account in the objective function. Furthermore, the problem is formulated as a two-stage robust optimisation model. To address the non-linear problem in the inner model, logarithmic transformation and piecewise linearisation are utilised to exactly linearise the non-linear terms in the model. Finally, the standard column-and-constraints generation algorithm is employed to solve the proposed model with a master-sub-problem framework. The test results on a standard IEEE RTS-96 system show the effectiveness of the proposed model.
UR - http://www.scopus.com/inward/record.url?scp=85059978343&partnerID=8YFLogxK
U2 - 10.1049/iet-gtd.2018.6278
DO - 10.1049/iet-gtd.2018.6278
M3 - Journal article
SN - 1751-8687
VL - 13
SP - 108
EP - 115
JO - IET Generation, Transmission & Distribution
JF - IET Generation, Transmission & Distribution
IS - 1
ER -