Power Load Forecasting Based on Wireless Sensor Networks

Authors

  • Xingping Liu College of Electrical & Information Engineering, Hunan Institute of Engineering
  • Weidong Li Powerchina Zhongnan Engineering Co Ltd.

DOI:

https://doi.org/10.3991/ijoe.v13i03.6861

Keywords:

LSSVM, WSN, power data

Abstract


At present, wireless sensor networks (WSN) technology is a field of much research interest in the area of information technology. The application of wireless sensor networks is expected to be very broad. With the development of communication protocol and their corresponding components, wireless sensor networks technology plays an increasingly important role in the power industry. The analysis and forecast of electric power data is essential to the construction and operation of the power network. Through the wireless sensor networks, we can obtain comprehensive power data. Then we can better forecast the power load through the data we obtain from the wireless sensor networks. In this paper, we propose an improved LSSVM method. We collect the power data by the wireless sensor networks and use the improved LSSVM method to forecast the power load. Experimental results demonstrate the effectiveness of the proposed method.

Author Biographies

Xingping Liu, College of Electrical & Information Engineering, Hunan Institute of Engineering

Xingping Liu is an associate professor with College of Electrical & Information Engineering, Hunan Institute of Engineering. He is mainly engaged in the study of communication control.

Weidong Li, Powerchina Zhongnan Engineering Co Ltd.

Weidong Li is a master of Power china Zhongnan Engineering Co Ltd., He is mainly engaged in communication technology research.

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Published

2017-03-28

How to Cite

Liu, X., & Li, W. (2017). Power Load Forecasting Based on Wireless Sensor Networks. International Journal of Online and Biomedical Engineering (iJOE), 13(03), pp. 86–99. https://doi.org/10.3991/ijoe.v13i03.6861

Issue

Vol. 13 No. 03 (2017)

Section

Papers

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