Open AccessBattery and backup generator sizing for a resilient microgrid under stochastic extreme events
Author(s) -
Dong Jiaojiao,
Zhu Lin,
Su Yu,
Ma Yiwei,
Liu Yilu,
Wang Fred,
Tolbert Leon M.,
Glass Jim,
Bruce Lilian
Publication year - 2018
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.2018.5883
Subject(s) - microgrid , backup , reliability engineering , islanding , battery (electricity) , reliability (semiconductor) , computer science , stochastic programming , generator (circuit theory) , grid , duration (music) , sizing , stochastic modelling , mathematical optimization , installation , engineering , power (physics) , distributed generation , electrical engineering , mathematics , renewable energy , art , physics , quantum mechanics , visual arts , operating system , geometry , literature , statistics , database
Owing to the recent power outages caused by extreme events, installing battery energy storage and backup generators is important to improve resiliency for a grid‐tied microgrid. In the design stage, the event occurrence time and duration, which are highly uncertain and cannot be effectively predicted, may affect the needed battery and backup generator capacity but are usually assumed to be pre‐determined in utility planning tools. This study investigates the optimal battery and backup generator sizing problem considering the stochastic event occurrence time and duration for the grid‐tied microgrid under islanded operation. The reliability requirement is quantified by the mean value of the critical customer interruption time in each stochastic islanding time window (ITW), whose length is the duration and the centre is the occurrence time. The stochastic ITW constraint is then transformed to a probability‐weighted expression to derive an equivalent Mixed Integer Linear Programming model. Numerical simulations on a realistic grid‐tied PV‐based microgrid demonstrate that the total cost is reduced by 11.5% considering the stochastic ITW, compared with the deterministic ITW under the same reliability requirement.