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Intelligent Swarm Firefly Algorithm for the Prediction of China's National Electricity Consumption

Zhang, Guangfeng, Chen, Yi, Yu, Yongnian, Hu, Huosheng, Wu, Shaomin (2019) Intelligent Swarm Firefly Algorithm for the Prediction of China's National Electricity Consumption. International Journal of Bio-Inspired Computation, 13 (2). pp. 111-118. ISSN 1758-0366. E-ISSN 1758-0374. (doi:10.1504/IJBIC.2019.098407) (KAR id:61890)

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Official URL:
https://doi.org/10.1504/IJBIC.2019.098407

Abstract

China’s energy consumption is the world’s largest and is still rising, leading to concerns of energy shortage and environmental issues. It is, therefore, necessary to estimate the energy demand and to examine the dynamic nature of the electricity consumption. In this paper, we develop a nonlinear model of energy consumption and utilise a computational intelligence approach, specifically a swarm firefly algorithm with a variable population, to examine China’s electricity consumption with historical statistical data from 1980 to 2012. Prediction based on these data using the model and the examination is verified with a bi-variate sensitivity analysis, a bias analysis and a forecasting exercise, which all suggest that the national macroeconomic performance, the electricity price, the electricity consumption efficiency and the economic structure are four critical factors determining national electricity consumption. Actuate prediction of the consumption is important as it has explicit policy implications on the electricity sector development and planning for power plants.

Item Type: Article
DOI/Identification number: 10.1504/IJBIC.2019.098407
Uncontrolled keywords: energy consumption, nonlinear modelling, swarm firefly algorithm, parameters determination
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 30 May 2017 15:17 UTC
Last Modified: 08 Oct 2021 12:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/61890 (The current URI for this page, for reference purposes)
Wu, Shaomin: https://orcid.org/0000-0001-9786-3213
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