Optimization Pump as Turbine Coupled to a Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm

Authors

  • Emanuel Nyirenda Phd Student
  • Dr Kihedu University of Dar es Salaam
  • Cuthbert Kimambo University of Dar es Salaam
  • Torbjorn Nielsen University of Dar es Salaam

DOI:

https://doi.org/10.52339/tjet.v43i1.983

Keywords:

Pump as Turbine, SEIG, Energy Recovery, Energy Sources, Genetic Algorithm, Optimization

Abstract

As a way of accelerating the deployment of affordable and clean renewable energy generation technologies, applying a pump working as a turbine coupled to a self-excited induction generator is gaining popularity in various areas including energy recovery and micro hydro systems. However, it is currently challenging to predict the performance of the PAT-SEIG system and there is no agreed-upon rule on the selection of the appropriate system to be installed at a particular site. This paper has presented multi-objective optimization to select the best operating point of the PAT-SEIG system. The results show that the peak efficiencies for the PAT fall between 39.9% and 40.08% and for SEIG they fall between 69.78% and 69.84% and are not coincident. Thus, when selecting the operating point, a trade off on one element is necessary. Gamultobj optimization outputs the Pareto solutions and FMINCON locates the BEP within the Pareto solutions.

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Author Biography

Dr Kihedu, University of Dar es Salaam

Senior Lecturer

Additional Files

Published

2024-06-28

How to Cite

Nyirenda, E., Kihedu, J., Kimambo, C., & Nielsen, T. (2024). Optimization Pump as Turbine Coupled to a Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm. Tanzania Journal of Engineering and Technology, 43(1), 133-143. https://doi.org/10.52339/tjet.v43i1.983
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