Optimising Multi-Objective Taguchi-Based Energy Management Systems for Reduced Power Consumption

Authors

  • Mohan T Patel
  • Nikhil J. Rathod

DOI:

https://doi.org/10.63682/jns.v13i1.9939

Keywords:

Energy Management System, Electricity Demand Optimization, Taguchi Method, Signal-to-Noise Ratio, Analysis of Variance (ANOVA), Mean Squared Deviation, Energy Efficiency, Experiment Design, Robust Optimization

Abstract

 To boost system efficiency, reduce operating costs, and enhance reliability, modern energy management systems (EMS) must efficiently control power demand. This work use the Taguchi design of experiments approach to systematically optimize electricity demand. Three control parameters, each at three levels, were investigated in order to optimize system efficiency while reducing power consumption and mean squared deviation (MSD). Response tables, analysis of variance (ANOVA), and signal-to-noise (S/N) ratio analysis were used to identify the most critical parameters and their optimal values.

The results demonstrate that factor B has the most impact on power demand and MSD, accounting for more than 90% of the total fluctuation, whereas factor C is mainly in charge of boosting system efficiency. The optimal parameter combination for lowering power consumption and MSD was found to be A₁B₁C₂.₃, even though maximum efficiency was reached at A₃B₂C. The produced models show excellent prediction accuracy with R2 values exceeding 96%..
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Published

2024-12-24

How to Cite

1.
T Patel M, J. Rathod N. Optimising Multi-Objective Taguchi-Based Energy Management Systems for Reduced Power Consumption. J Neonatal Surg [Internet]. 2024 Dec. 24 [cited 2026 Feb. 3];13(1):2042-5. Available from: https://jneonatalsurg.com/index.php/jns/article/view/9939

Issue

Vol. 13 (2024): Journal of Neonatal Surgery

Section

Original Article

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