Next Article in Journal
Reschedule of Distributed Energy Resources by an Aggregator for Market Participation
Previous Article in Journal
State-of-Charge Estimation of Battery Pack under Varying Ambient Temperature Using an Adaptive Sequential Extreme Learning Machine
Open AccessArticle

A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting

School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China
Author to whom correspondence should be addressed.
Energies 2018, 11(4), 712;
Received: 27 February 2018 / Revised: 16 March 2018 / Accepted: 19 March 2018 / Published: 22 March 2018
(This article belongs to the Section Electrical Power and Energy System)
Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module) is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is successfully developed in this system, which further improves the effectiveness of data pre-processing and then enhances the final forecasting performance. Furthermore, the modified support vector machine is developed to integrate all the individual predictors and obtain the final prediction, which successfully overcomes the upper drawbacks of the linear combined model. Moreover, the evaluation module is incorporated to perform a scientific evaluation for the developed system. The half-hourly electrical load data from New South Wales are employed to verify the effectiveness of the developed forecasting system, and the results reveal that the developed nonlinear forecasting system can be employed in the dispatching and planning for smart grids. View Full-Text
Keywords: short-term load forecasting; nonlinear forecasting; forecasting performance; combined model short-term load forecasting; nonlinear forecasting; forecasting performance; combined model
Show Figures

Figure 1

MDPI and ACS Style

Tian, C.; Hao, Y. A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting. Energies 2018, 11, 712.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop