Earticle

초록

영어

Short-term load forecast plays an important role in the safe and economic operation of power system. Its prediction accuracy affects the power system's security, profit and quality directly. And meteorological factor is one of the key factors that affect the accuracy of load forecasting. In this paper, we put forward enterprise electric load forecasting method combined with grey relational degree algorithm and multivariate linear regression forecasting method. The example shows that this method can get better prediction accuracy.

목차

Abstract
 1. Introduction
 2. Descriptive Analysis of Sample Load
 3. Study of Load Forecasting Method Based on Meteorological and Product Information
  3.1. The Preprocessing of the Load Data with Grey Relational Algorithm
  3.2. Multiple Linear Regression Analysis Model and Prediction
 3. Analysis of Examples
 4. Conclusion
 References

키워드

저자

• Hu Bo [ North China Electric Power University, Beijing China, State Grid Anshan Electric Power Supply Company, Anshan China ]
• Wang Nan [ Electric Power Research Institute of State Grid Liaoning Electric Power Co.Ltd, Shenyang China ]
• Di Feng [ College of Information Science and Engineering Northeastern University, Shenyang China ]
• Song Yundong [ Electric Power Research Institute of State Grid Liaoning Electric Power Co.Ltd, Shenyang China ]
• Zhang Junyang [ Electric Power Research Institute of State Grid Liaoning Electric Power Co.Ltd, Shenyang China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605