Laboratory of Policy Study on Electricity Demand Forecasting by Intelligent Engineering

  • Authors:

  • Zhaoguang Hu;Minjie Xu;Baoguo Shan;Xiandong Tan

  • Affiliations:

  • State Power Economic Research Institute of China, Beijing, China 100761;State Power Economic Research Institute of China, Beijing, China 100761;State Power Economic Research Institute of China, Beijing, China 100761;State Power Economic Research Institute of China, Beijing, China 100761

  • Venue:
  • IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
  • Year:
  • 2008

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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.