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Modeling of Photovoltaic Power Systems using Clustering Algorithm and Modular Networks

군집화 알고리즘 및 모듈라 네트워크를 이용한 태양광 발전 시스템 모델링

  • Received : 2016.04.18
  • Accepted : 2016.05.17
  • Published : 2016.06.01

Abstract

The real-world problems usually show nonlinear and multi-variate characteristics, so it is difficult to establish concrete mathematical models for them. Thus, it is common to practice data-driven modeling techniques in these cases. Among them, most widely adopted techniques are regression model and intelligent model such as neural networks. Regression model has drawback showing lower performance when much non-linearity exists between input and output data. Intelligent model has been shown its superiority to the linear model due to ability capable of effectively estimate desired output in cases of both linear and nonlinear problem. This paper proposes modeling method of daily photovoltaic power systems using ELM(Extreme Learning Machine) based modular networks. The proposed method uses sub-model by fuzzy clustering rather than using a single model. Each sub-model is implemented by ELM. To show the effectiveness of the proposed method, we performed various experiments by dataset acquired during 2014 in real-plant.

Keywords

ELM;Modular networks;Photovoltaic power system

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Acknowledgement

Supported by : 중소기업청