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Comparative Between Neuro–Fuzzy and PI Controller Temperature of Condenser in Thermal Power Plant (160 MW)


Affiliations
1 Department of Electrical and Electronic Engineering, University of Technology, Baghdad, Iraq
 

Objectives: The temperature in the condenser is one of the serious and necessary parameters that should be maintained to harness the fullest efficiency power plant (160 MW) operations. For this reason, the regulation can be achieved by Artificial Intelligence (AI) technology, containing (Hybrid) the neuro–fuzzy system. Methods/Statistical Analysis: ANFIS theory compares with the conventional PID method by using MATLAB/ Simulink program which tracks the temperature levels. Findings: The comparison was made using various parameters (settling time, overshoot, rise time, peak time) and used to excess the thermal efficiency of the condenser by tracking the temperature and to reach the degree of 80°C in less time with accuracy, which also lead to maintain the condenser as shown in the results. Application/Improvements: Neuro– fuzzy was the more accurate, superiority and reach the steady state in the short time, while PI represented the being of an overshoot where it causes system malfunction, leading to the driving off operation.
User

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  • Comparative Between Neuro–Fuzzy and PI Controller Temperature of Condenser in Thermal Power Plant (160 MW)

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Authors

Hosham Salim Anead
Department of Electrical and Electronic Engineering, University of Technology, Baghdad, Iraq
Khalid Faisal Sultan
Department of Electrical and Electronic Engineering, University of Technology, Baghdad, Iraq
Malak Moneeryounis
Department of Electrical and Electronic Engineering, University of Technology, Baghdad, Iraq

Abstract


Objectives: The temperature in the condenser is one of the serious and necessary parameters that should be maintained to harness the fullest efficiency power plant (160 MW) operations. For this reason, the regulation can be achieved by Artificial Intelligence (AI) technology, containing (Hybrid) the neuro–fuzzy system. Methods/Statistical Analysis: ANFIS theory compares with the conventional PID method by using MATLAB/ Simulink program which tracks the temperature levels. Findings: The comparison was made using various parameters (settling time, overshoot, rise time, peak time) and used to excess the thermal efficiency of the condenser by tracking the temperature and to reach the degree of 80°C in less time with accuracy, which also lead to maintain the condenser as shown in the results. Application/Improvements: Neuro– fuzzy was the more accurate, superiority and reach the steady state in the short time, while PI represented the being of an overshoot where it causes system malfunction, leading to the driving off operation.

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DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i29%2F129061