A hybrid optimized grey seasonal variation index model improved by whale optimization algorithm for forecasting the residential electricity consumption

Xin Xiong, Xi Hu and Huan Guo

Energy, 2021, vol. 234, issue C

Abstract: Forecasting the residential electricity consumption can provide an effective and sustainable electricity supply in the rapid development of urbanization and industrialization. However, it is a challenging task to establish an efficient forecasting model for enhancing the forecasting accuracy, accelerating the forecasting speed, minimizing the electricity consumption and reducing the environmental pollution. Most existing works on the residential electricity consumption focus on improving the forecasting accuracy while the improvement is insufficient. And few of them have considered the forecasting speed. To overcome these limitations, this paper firstly proposes a hybrid Improved Whale Optimization Algorithm - Optimized Grey Seasonal Variation Index (IWOA-OGSVI) model for best solutions of satisfactory forecasting results with high accuracy and fast-convergence. Next, for evaluating the forecasting performance, two case studies are carried out to estimate the effectiveness of our proposed model compared with a range of benchmark models. Finally, the empirical results present that the MAPE values in our proposed model are smallest at the “Excellent” level of the forecasting power and all of them have converged before 30 iterations, which demonstrate the superiority of our proposed model over the others on the forecasting accuracy and speed among the five selected regions.

Keywords: Forecasting accuracy and speed; Improved whale optimization algorithm (IWOA); Optimized grey seasonal variation index (OGSVI) model; Residential electricity consumption (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422101375X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:234:y:2021:i:c:s036054422101375x

DOI: 10.1016/j.energy.2021.121127

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().