Firas Basim Ismail1*, Ammar Al-Bazi2, Rami Hikmat Al-Hadeethi3, Deshvin Singh1

Author affiliation

1Power Generation Unit, Institute of Power Engineering (IPE), Universiti Tenaga Nasional (UNITEN), 43000 Kajang, Malaysia

2Faculty of Engineering, Environment and Computing, Coventry University, Coventry CV1 2JH, UK

3School of Engineering, Department of Industrial Engineering, The University of Jordan, Amman 11942, Jordan


Growing worldwide demand for energy leads to increasing the levels of challenge in power plants management. These challenges include but are not limited to complex equipment maintenance, power estimation under uncertainty, and energy optimisation. Therefore, efficient power plant management is required to increase the power plant’s operational efficiency. Conventional optimisation tools in power plants are not reliable as it is challenging to monitor, model and analyse individual and combined components within power systems in a plant. However, intelligent computational tools such as artificial neural networks (ANN), nature-inspired computations and meta-heuristics are becoming more reliable, offering a better understanding of the behaviour of the power systems, which eventually leads to better energy efficiency. This paper aims to provide an overview of the development and application of intelligent computational tools such as ANN in managing power plants. Also, to present several applications of intelligent computational tools in power plants operations management. The literature review technique is used to demonstrate intelligent computational tools in various power plants applications. The reviewed literature shows that ANN has the greatest potential to be the most reliable power plant management tool.


Intelligent Computational Tools, Power Plant, Energy Efficiency, Artificial Neural Networks, Genetic Algorithms, Hybrid Intelligent Systems.