Abstract
Electricity demand will be affected by national policies and other factors. There are many semi-structure problems in the electricity demand forecasting, which are very difficult to be solved by the use of traditional methods. In this paper, intelligent engineering is developed. It adopts theory and technique of artificial intelligent, soft computing, uncertain theory, and multi-agent system. Three fundamental problems and generalized model are proposed in intelligent space. As a case, inspired by the physical experiment, the laboratory of policy study is built based on intelligent engineering to simulate the impact of the national policy on electricity demand forecasting. A case study in China has been shown in the paper.
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Hu, Z., Xu, M., Shan, B., Tan, X. (2008). Laboratory of Policy Study on Electricity Demand Forecasting by Intelligent Engineering. In: Fyfe, C., Kim, D., Lee, SY., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2008. IDEAL 2008. Lecture Notes in Computer Science, vol 5326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88906-9_53
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DOI: https://doi.org/10.1007/978-3-540-88906-9_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88905-2
Online ISBN: 978-3-540-88906-9
eBook Packages: Computer ScienceComputer Science (R0)