| Title |
Non-linear autoregressive neural network (NARNET) with SSA filtering for a university energy consumption forecast |
| ID_Doc |
17581 |
| Authors |
Adedeji, PA; Akinlabi, S; Ajayi, O; Madushele, N |
| Title |
Non-linear autoregressive neural network (NARNET) with SSA filtering for a university energy consumption forecast |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.promfg.2019.04.022 |
| Abstract |
Energy consumption forecast is essential for strategic planning in achieving a sustainable energy system. The hemispherical seasonal dependency of energy consumption requires intelligent forecast. This paper uses a non-linear autoregressive neural network (NARNET) for energy consumption forecast in a South African University with four campuses, using three-year daily energy consumption data. Singular Spectrum Analysis (SSA) technique was used for the data filtering. Three window lengths (L=54, 103 and 155) were obtained using periodogram analysis and R-values of network training at these window lengths were compared. Filtered data at L=103 gave the best R-values of 0.951, 0.983, 0.945 and 0.940 for campus A, B, C, and D respectively. The network validation and a short-term forecast were performed. Forecast accuracies of 85.87%, 75.62%, 85.02% and 76.83% were obtained for campus A, B, C and D respectively. The study demonstrates the significance of data filtering in forecasting univariate autoregressive series. (C) 2019 The Authors. Published by Elsevier B.V. |
| Author Keywords |
Non-linear Autoregressive Neural Network; Singular Spectrum Analysis; Energy Forecast |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000560232900022 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Manufacturing |
| Research Area |
Science & Technology - Other Topics; Engineering |
| PDF |
https://doi.org/10.1016/j.promfg.2019.04.022
|