Artificial Neural Network Based Short-Term Hydrothermal Scheduling

Journal Title: RECENT - Year 2013, Vol 14, Issue 39

Abstract

A worldwide trend in the development of power systems is to build interconnections with the goal to achieve economic benefits. Interconnections of power systems may offer significant technical, economic and environmental advantages. A modern power system consists of a large number of Thermal and Hydal Power plants connected at various load centres through a transmission network. An important objective in the operation of such a power system is to generate and transmit power to meet the system load demand at minimum fuel cost by an optimal mix of various types of plant. In this paper Kirchmayer’s method is used for hydrothermal scheduling which is a conventional method and slow. In order to overcome the disadvantage in the Kirchmayer’s method, Back Propagation Neural Network (BPNN) is proposed for scheduling of Hydro-Thermal system. The result shows the effectiveness of the proposed method compared to the conventional in terms of speed and accuracy.

Authors and Affiliations

M. SUMAN, M. VENU RAO

Keywords

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  • EP ID EP104558
  • DOI -
  • Views 106
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How To Cite

M. SUMAN, M. VENU RAO (2013). Artificial Neural Network Based Short-Term Hydrothermal Scheduling. RECENT, 14(39), 191-195. https://europub.co.uk/articles/-A-104558