The price prediction for the energy market based on a new method 论文
详细信息
- 发表期刊/会议
- Economic Research-Ekonomska Istraživanja
- 发表日期
- 2018-01-01
- 发表年份
- 2018
关键词
摘要
Regarding the complex behaviour of price signalling, its prediction is difficult, where an accurate forecasting can play an important role in electricity markets. In this paper, a feature selection based on mutual information is implemented for day ahead prediction of electricity prices, which are so valuable for determining the redundancy and relevancy of selected features. A combination of wavelet transform (WT) and a hybrid forecast method is presented based on a neural network (NN). Furthermore, an intelligent algorithm is considered for a prediction process to set the proposed forecast engine free parameters based NN. This optimisation process improved the accuracy of the proposed model. To demonstrate the validity of this model, the Pennsylvania-New Jersey-Maryland (PJM) electricity market is considered as a test case and compared with some of the most recent price forecast methods. These comparisons illustrate the effectiveness of the proposed strategy.