Abstract
Abstract
Electric power has become one of the most important energy sources in today’s society. It is of great significance for power grid enterprises and people’s livelihood to accurately grasp the historical data of power load and to mine the potential value of data. In this paper, by making using of the multi-variable grey model, the power load forecasting is studied. Firstly, this paper establishes the multi-variable grey model with grey system theory. Secondly, the correlation between four temperature factors and load is analyzed, which shows that four temperature factors should be considered as the influencing factors of load. Finally, multi-variable grey model is applied to forecast the summer load of some region in Ningbo. The results show that the prediction has better fitting and prediction accuracy.
Subject
General Physics and Astronomy
Reference14 articles.
1. Review of power system load forecasting and its development[J];Kang;Automation of Electric Power Systems,2004
2. Neural networks for short-term load forecasting: a review and evaluation[J];Hippert;IEEE Transactions on Power Systems,2001
3. Short-term load forecasting for the holidays using fuzzy linear regression method[J];Song;IEEE Transactions on Power Systems,2005
4. A load curve based fuzzy modeling technique for short-term load forecasting[J];Papadakis;Fuzzy Sets & Systems,2003
5. Adaptive online load forecasting via time series modeling[J];Parrmann;Electric Power Systems Research,1995
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Dynamic Forecasting of Power System Load Based on Kalman Filter;2022 2nd International Conference on Electrical Engineering and Mechatronics Technology (ICEEMT);2022-07-01