TY - JOUR
T1 - Optimal Sizing of Energy Storage Devices in Isolated Wind-Diesel Systems Considering Load Growth Uncertainty
AU - Nguyen-Hong, Nhung
AU - Nguyen-Duc, Huy
AU - Nakanishi, Yosuke
N1 - Publisher Copyright:
© 1972-2012 IEEE.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - The development of wind power plants is an economical solution to provide energy to remote communities. For these isolated systems, the cogeneration of diesel generators and wind turbines is a typical configuration, but also poses several technical challenges regarding load balancing and frequency control. Auxiliary devices such as battery storages, flywheels, and dump loads are often needed to ensure a more stable operation and a higher penetration level of wind energy. However, the cost of these auxiliary devices can be substantial. This paper proposes a two-stage stochastic optimization framework to determine the optimal size of energy storage devices in a hybrid wind-diesel system. The optimization problem considers two main uncertain factors, namely the wind speed and the load growth rate. An efficient scenario reduction method is also proposed to reduce the computational burden. The optimization framework is tested with a realistic case study.
AB - The development of wind power plants is an economical solution to provide energy to remote communities. For these isolated systems, the cogeneration of diesel generators and wind turbines is a typical configuration, but also poses several technical challenges regarding load balancing and frequency control. Auxiliary devices such as battery storages, flywheels, and dump loads are often needed to ensure a more stable operation and a higher penetration level of wind energy. However, the cost of these auxiliary devices can be substantial. This paper proposes a two-stage stochastic optimization framework to determine the optimal size of energy storage devices in a hybrid wind-diesel system. The optimization problem considers two main uncertain factors, namely the wind speed and the load growth rate. An efficient scenario reduction method is also proposed to reduce the computational burden. The optimization framework is tested with a realistic case study.
KW - Energy storage
KW - stochastic optimization
KW - wind energy
UR - http://www.scopus.com/inward/record.url?scp=85041547515&partnerID=8YFLogxK
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U2 - 10.1109/TIA.2018.2802940
DO - 10.1109/TIA.2018.2802940
M3 - Article
AN - SCOPUS:85041547515
SN - 0093-9994
VL - 54
SP - 1983
EP - 1991
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 3
ER -