TY - JOUR
T1 - Expected wind speed estimation considering spatio-temporal anisotropy for generating synthetic wind power profiles
AU - Hama, Kouki
AU - Fujimoto, Yu
AU - Hayashi, Yasuhiro
N1 - Publisher Copyright:
© 2018 The Authors. Published by Elsevier Ltd.
PY - 2018
Y1 - 2018
N2 - Wind power generation is one of renewable energies which are expected to introduce to power grid in the future. However, unexpected fluctuations of wind power output will cause serious problems such as the lack of frequency adjustment. One of the countermeasures is utilization of battery systems for mitigating short-term fluctuations. However, in general, time series data of wind power which will be generated at the wind farm built in the future is required for estimating appropriate specification of the battery system. Therefore, we have been developed a framework generating synthetic wind power profiles of a target point for any target points where the wind turbine will be built. In this paper, we propose a statistical approach for reproducing temporally plausible wind speed sequence for generating synthetic wind power profiles. We show the result of numerical experience using real-world dataset.
AB - Wind power generation is one of renewable energies which are expected to introduce to power grid in the future. However, unexpected fluctuations of wind power output will cause serious problems such as the lack of frequency adjustment. One of the countermeasures is utilization of battery systems for mitigating short-term fluctuations. However, in general, time series data of wind power which will be generated at the wind farm built in the future is required for estimating appropriate specification of the battery system. Therefore, we have been developed a framework generating synthetic wind power profiles of a target point for any target points where the wind turbine will be built. In this paper, we propose a statistical approach for reproducing temporally plausible wind speed sequence for generating synthetic wind power profiles. We show the result of numerical experience using real-world dataset.
KW - Spatio-temporal anisotorpy
KW - Spatio-temporal kriging
KW - Synthetic wind power profiles
KW - Wind speed estimation
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U2 - 10.1016/j.egypro.2018.11.047
DO - 10.1016/j.egypro.2018.11.047
M3 - Conference article
AN - SCOPUS:85058211191
SN - 1876-6102
VL - 155
SP - 309
EP - 319
JO - Energy Procedia
JF - Energy Procedia
T2 - 12th International Renewable Energy Storage Conference, IRES 2018
Y2 - 13 March 2018 through 15 March 2018
ER -