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Medium- and Long-Term Load Forecasting Based on GLRM and MC Error Correction

  • CUI Qiong ,
  • SHU Jie ,
  • WU Zhi-feng ,
  • HUANG Lei ,
  • YAO Wen-ming ,
  • SONG Xiang-rong
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  • 1. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China;
    2. CAS Key Laboratory of Renewable Energy, Guangzhou 510640, China;
    3. Mianyang Anzhou power supply branch, State Grid Sichuan electric power company, Sichuan Mianyang 622650, China;
    4. Shaoguan Research Institute,Jinan University, Guangdong Shaoguan 512000, China

Received date: 2017-11-10

  Revised date: 2017-12-05

  Online published: 2017-12-29

Abstract

To remedy the defects of traditional grey model (GM) for ignoring linear factors and having large errors when forecasting the sequences with large random fluctuation in medium- and long-term load forecasting, a model which is based on grey linear regression model (GLRM) and Markov chain (MC) is proposed. In this work, the GLRM prediction model is built. A quantitative prediction error estimation method is proposed through analyzing the transfer rule of the model fitting error, a correction model is established consequently for the predicted values of the GLRM model, and then the GLRM-MC model is created. Comparing with GM (1,1) and GLRM, simulation results demonstrate that the proposed model can better grasp the inherent regularity of the actual load, and improve the prediction accuracy of the model, meanwhile, enhance the stability of fitting and forecasting effect.

Cite this article

CUI Qiong , SHU Jie , WU Zhi-feng , HUANG Lei , YAO Wen-ming , SONG Xiang-rong . Medium- and Long-Term Load Forecasting Based on GLRM and MC Error Correction[J]. Advances in New and Renewable Energy, 2017 , 5(6) : 472 -477 . DOI: 10.3969/j.issn.2095-560X.2017.06.009

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