Open AccessOptimal wind turbine allocation and network reconfiguration for enhancing resiliency of system after major faults caused by natural disaster considering uncertainty
Author(s) -
Nikkhah Saman,
Jalilpoor Kamran,
Kianmehr Ehsan,
Gharehpetian Gevork B.
Publication year - 2018
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2018.5237
Subject(s) - turbine , control reconfiguration , reliability engineering , computer science , electric power system , load shedding , wind power , interconnection , natural disaster , fault (geology) , mathematical optimization , operations research , power (physics) , engineering , mathematics , computer network , physics , mechanical engineering , electrical engineering , quantum mechanics , seismology , embedded system , geology , meteorology
This study proposes a two‐stage stochastic optimisation model for jointly wind turbine (WT) allocation and network reconfiguration (NR) so as to increase the resiliency of distribution system in face of natural disasters. In this regard, in the first level, a possibilistic‐scenario method is proposed to select the line outage scenarios. The proposed model is capable with distribution systems and considers different failure probabilities for system components subject to the intensity of natural disaster in its associated zone. After selecting the line outage scenarios, in the second level, a multi‐stage optimisation framework is proposed for jointly NR and WT allocation in a multi‐zone and multi‐fault system, considering the uncertainty of system load and wind power generation. This strategy makes an interconnection between NR and islanded WTs to increase the resiliency of system and decreases the load shedding. Different economic objectives including, costs of load shedding and power generation are considered in the model. In addition, hardening budget is taken into consideration for the transmission lines, which is minimised during the optimisation process. The simulation results demonstrate the capability and necessity of proposed resiliency‐oriented method and prove the importance of hardening budgets.