Artificial Neural Network Based Power Flow Analysis for Micro Grids

Serhat Berat EFE; Mehmet CEBECİ

doi:https://doi.org/10.17678/beujst.75539

Article Details

Artificial Neural Network Based Power Flow Analysis for Micro Grids

Authors:

Serhat Berat EFE | Mehmet CEBECİ

Publisher:

Bitlis Eren University

Journal:

Bitlis Eren University Journal of Science and Technology 2015 Vol.5 Issue 1, pp.42-47

Document Type:

Article

Publication Date:

6/2015

Document Language:

English

Document ID (Org No.):

2000888101

Frequency:

Bi-Annual

eISSN:

2146-7706

DOI:

https://doi.org/10.17678/beujst.75539

Abstract:

 

This paper proposes a neural network based power flow analysis method that applied on a grid connected and ring-shaped micro grid. As the use of micro grids increasing rapidly, it becomes necessary to analyze them for different operating and loading conditions as large power systems. At the outset, a MG is designed and simulated under MATLAB / Simulink platform. Normal operation data collected and stored. Then, different loading scenarios performed, operational data collected and stored to use for proposed method. Intelligent systems are used to process these data and also for training. After training a fully different scenario is created and the effectiveness of the proposed method is verified through simulation study.

Article Details

Artificial Neural Network Based Power Flow Analysis for Micro Grids

Authors: Serhat Berat EFE | Mehmet CEBECİ

Publisher: Bitlis Eren University

Journal: Bitlis Eren University Journal of Science and Technology 2015 Vol.5 Issue 1, pp.42-47

Document Type: Article

Publication Date: 6/2015

Document Language: English

Document ID (Org No.): 2000888101

Frequency: Bi-Annual

eISSN: 2146-7706

DOI: https://doi.org/10.17678/beujst.75539

Issues

Authors:

Serhat Berat EFE | Mehmet CEBECİ

Publisher:

Bitlis Eren University

Journal:

Bitlis Eren University Journal of Science and Technology 2015 Vol.5 Issue 1, pp.42-47

Document Type:

Article

Publication Date:

6/2015

Document Language:

English

Document ID (Org No.):

2000888101

Frequency:

Bi-Annual

eISSN:

2146-7706

DOI:

https://doi.org/10.17678/beujst.75539