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The Short-term Load Forecasting of Electric System

Zhaoyuan Wang
2016 Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications   unpublished

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This thesis firstly analyzes some indexes as daily maximum load, daily minimum load, daily difference between peak and valley and daily load rate in two different regions. And then it makes a stepwise regression analysis on the relationship between the above indexes and various climate factors, so as to obtain equations of linear regression and regression errors in the two regions. After that, the thesis selects some key impacting indexes to analyze the influence of climate on the electric load
more » ... forecasting. Finally, it makes short-term forecasting on the load of the two regions by the grey predication way, the data of which are compared with the real ones to judge the feasibility of the forecasting methods.
doi:10.2991/icmmita-16.2016.80 fatcat:sop7meguirfzjmg63jjlyj3sl4
Citation

Zhaoyuan Wang. "The Short-term Load Forecasting of Electric System." Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications (2016)