Open AccessIslanding strategy for restoring electric power supply by means of electric vehicle idle power against cold load pickup
Author(s) -
Wang Yue,
Yao Meng,
Chen Lu,
Li Xinyu
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6296
Subject(s) - islanding , idle , power (physics) , automotive engineering , energy (signal processing) , engineering , electric vehicle , electric power , computer science , reliability engineering , electrical engineering , distributed generation , mathematics , physics , quantum mechanics , operating system , statistics , renewable energy
This study presents a new method of forming emergency‐responsive autonomous islands for restoring electric power supply using an electric vehicle (EV) idle power against the so‐called cold load pickup (CLPU). Two stepwise discretisation methodologies are firstly proposed, which are used to discretise arbitrarily given cold‐load models and aggregate discretised EV discharge models, respectively. Then, under the framework of mixed‐integer linear programming, a methodology of forming particular responsive restoration islands is built, which aims to maximise the recovered energy of interrupted end‐users given discretised CLPU and EV discharge models. Comparative analyses via the proposed method against existing algorithms are conducted on both a partial IEEE RBTS‐BUS6 test feeder and a practical feeder. Specifically, the conducted analyses investigate the impacts of the CLPU on energy restoration and the assistance performance of discharge power from EV's on boosting the capability of responsive restoration islands to restore the interruption. Moreover, an especial relationship is studied, between the utilisation rate of total discharge power of an EV parking lot and the rate of restored energy concerning the total lost energy.