Weather impacts on electric power load: partial phase synchronization analysis
作者： Jinkyu Hong , Won Sup Kim
DOI: 10.1002/MET.1535
关键词:
摘要: Electricity demand is influenced by atmospheric conditions, and, therefore it important to quantify their relationships suitably for accurate electricity forecasting and the implementation of power-saving policies. However, interdependencies characteristics covariance among meteorological variables within same periodicities hinder quantification direct indirect impacts on electric power load. To investigate strength correlation between conditions load, this study harnessed a new partialization analysis method based partial phase synchronization index combined with wavelet transformation. The advantage proposed that can be used evaluate degree independent contribution over different spatiotemporal scales. Compared traditional statistical analyses, shows air temperature principal variable associated directly demand, but relationship varies season time scale. Relative humidity wind speed have strong correlations in summer winter, respectively. Insolation coupled load only sub-diurnal This investigation indicates changes coupling strengths should incorporated into process. index, transformation, useful tool could other studies assess complex interacting oscillations cannot assessed properly approaches.
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sci-hub.se 参考文章(24)
Zi Y. Zhang, Dao Y. Gong, Jing J. Ma, A study on the electric power load of Beijing and its relationships with meteorological factors during summer and winter Meteorological Applications. ,vol. 21, pp. 141- 148 ,(2014) , 10.1002/MET.1313
Andrew Henley, John Peirson, Non‐Linearities in Electricity Demand and Temperature: Parametric Versus Non‐Parametric Methods Oxford Bulletin of Economics and Statistics. ,vol. 59, pp. 149- 162 ,(1997) , 10.1111/1468-0084.00054
Won Sup Kim, Xue-Mei Cui, Chang No Yoon, Hung Xuan Ta, Seung Kee Han, Estimating network link weights from inverse phase synchronization indices EPL. ,vol. 96, pp. 20006- ,(2011) , 10.1209/0295-5075/96/20006
Woo-Joo Lee, Jinkyu Hong, A hybrid dynamic and fuzzy time series model for mid-term power load forecasting International Journal of Electrical Power & Energy Systems. ,vol. 64, pp. 1057- 1062 ,(2015) , 10.1016/J.IJEPES.2014.08.006
H.M. Al-Hamadi, S.A. Soliman, Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model Electric Power Systems Research. ,vol. 68, pp. 47- 59 ,(2004) , 10.1016/S0378-7796(03)00150-0
S. Ruzic, A. Vuckovic, N. Nikolic, Weather sensitive method for short term load forecasting in Electric Power Utility of Serbia IEEE Transactions on Power Systems. ,vol. 18, pp. 1581- 1586 ,(2003) , 10.1109/TPWRS.2003.811172
Björn Schelter, Matthias Winterhalder, Rainer Dahlhaus, Jürgen Kurths, Jens Timmer, Partial phase synchronization for multivariate synchronizing systems. Physical Review Letters. ,vol. 96, pp. 208103- 208300 ,(2006) , 10.1103/PHYSREVLETT.96.208103
S.A. Soliman, S. Persaud, K. El-Nagar, M.E. El-Hawary, Application of least absolute value parameter estimation based on linear programming to short-term load forecasting International Journal of Electrical Power & Energy Systems. ,vol. 19, pp. 209- 216 ,(1997) , 10.1016/S0142-0615(96)00048-8
Dongxiao Niu, Yongli Wang, Desheng Dash Wu, Power load forecasting using support vector machine and ant colony optimization Expert Systems With Applications. ,vol. 37, pp. 2531- 2539 ,(2010) , 10.1016/J.ESWA.2009.08.019
S MIRASGEDIS, Y SARAFIDIS, E GEORGOPOULOU, D LALAS, M MOSCHOVITS, F KARAGIANNIS, D PAPAKONSTANTINOU, Models for mid-term electricity demand forecasting incorporating weather influences Energy. ,vol. 31, pp. 208- 227 ,(2006) , 10.1016/J.ENERGY.2005.02.016