Abstract
The wind power and load are both affected by the meteorological factors. Studying on the correlation between wind power and load in different weather conditions is beneficial to reduce the double uncertainties on the sides of source and load, and significant to the planning, dispatching, safe and stable operation of the electric power system. First, the improved algorithm of traditional K-means clustering algorithm—X-means is adopted to divide the daily meteorological factors of wind speed and temperature, which mainly affect the wind power and load. Then, the Pearson, Kendall and Spearman correlation coefficients are used to analyze the correlation between wind power and load variables in different weather conditions. Finally, the optimal Copula function is selected from four commonly-used Copula functions to describe the joint distribution of wind power and load in each weather condition. Furthermore, the data in another place is used to verify the correlation between wind power and load with the weather condition. The conclusions are as follows: (1) the X-means algorithm can realize the effective classification of weather conditions. (2) The positive correlation between wind power and load is mainly concentrated in summer or near summer, the negative correlation between them is mainly concentrated in winter or near winter. (3) The correlation between wind power and load is quite varying in different weather conditions, but the joint distributions are basically consistent with the Archimedes Copula functions, and the tail correlation coefficients of their distribution are zero under most weather conditions. (4) There is a repeated rule between wind power and load with the weather condition.
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Acknowledgements
This work was supported in part by the project of the National Natural Science Foundation of China funded project (51707063), and the project of China Datang Corporation Ltd.
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Chen, Z., Wang, H., Yan, J., Liu, Y., Han, S., Li, L. (2020). Research on Correlation Between Wind Power and Load in Different Weather Conditions. In: Xue, Y., Zheng, Y., Rahman, S. (eds) Proceedings of PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control. Lecture Notes in Electrical Engineering, vol 585. Springer, Singapore. https://doi.org/10.1007/978-981-13-9783-7_3
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DOI: https://doi.org/10.1007/978-981-13-9783-7_3
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