Markov modelling and adaptive neuro fuzzy inference system computing of hydroelectric power plant

The main objective of present study is to develop a mathematical model for renewable energy sources like hydroelectric power plant (HPP). The availability of the hydroelectric power plant is predicted using Adaptive Neuro Fuzzy Inference System (ANFIS). The considered HPP systems is configured using four components viz. turbine, turbine governor, generator and generator converter. All these components connected in series structure and the availability of the system also influenced by non-availability of water and human failure. The Chapman–Kolmogorov differential difference equations developed corresponding to proposed model by using Markov birth–death process. All the failure and repair rates are considered as exponentially distributed. The numerical results of steady state availability derived to investigate the influence of various failure rates on the system performance. The ANFIS methodology is used to predict the availability of the HPP. It is observed that predicted and experimental results are closely related. The regression curve is fitted between predicted and experimental values by using neural net fitting (nftool) in MATLAB software. The results are beneficial for the engineers and researchers to improve the reliability of the HPPs and other energy production plants like solar energy production plants, wind energy production plants, nuclear power plants, etc.