Multi-layered feed-forward back propagation neural network approach for solving short-term thermal unit commitment

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Published Jun 2, 2015
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Volume 11, Issue 2, June 2015

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V. Pavan Kumar
PG Student, Department of Electrical Engineering, VNIT, Nagpur
P. S. Kulkarni
Associate Professor, Department of Electrical Engineering, VNIT, Nagpur

Abstract

This paper presents an approach for solving the short-term thermal unit commitment (UC) problem using a multi-layered Feed-forward Back propagation Neural Network (FF-BPNN). The main focus of the paper is on finding the schedule of committed thermal units within a short computational timesuch that the total operating cost is minimized. The proposed method is implemented and tested on a 3-unit and 10-unit systems for a scheduling period of 4-hours and 24-hours respectively in MATLABTM software using the Neural Network toolbox. Comparison of simulation results of the proposed method with the results of previous published methods shows that the proposed FF-BPNN method provides better solution with less computational time.

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How to Cite
Pavan Kumar, V., & Kulkarni, P. S. (2015). Multi-layered feed-forward back propagation neural network approach for solving short-term thermal unit commitment. Power Research - A Journal of CPRI, 277–286. Retrieved from https://cprijournal.in/index.php/pr/article/view/723

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