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 bivariate 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.
| Original language | English |
|---|---|
| Pages (from-to) | 111-118 |
| Number of pages | 8 |
| Journal | International Journal of Bio-Inspired Computation |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2019 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© Copyright 2019 Inderscience Enterprises Ltd.
Keywords
- Energy consumption
- Nonlinear modelling
- Parameters determination
- Swarm firefly algorithm
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science
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