Energetic and exergetic performance computation of coal-fired steam power plant using IAPWS IF-97 formulation for target variable datasets generation in machine learning based performance prediction

Abstract

More than 50% of power plants in Indonesia are Coal-Fired Steam Power Plants. According to the Ministry of Energy and Mineral Resources of Indonesia, coal reserves in Indonesia will run out in 67 years. Fuel saving can be done by operating the system at the highest efficiency operating conditions. These conditions can be determined by analysing the operating history of the system along with the energetic and exergetic performance produced using machine learning algorithm. Unfortunately, energetic and exergetic performance calculation of the Coal-Fired Steam Power Plants system that is not easy results in lack of system performance target datasets generated from the history of the Coal-Fired Steam Power Plants operation, so that the Steam Powerplant performance data generation software written using the Python programming language is created in this paper to calculate the Coal-Fired Steam Power Plants energetic and exergetic performance using IAPWS IF-97 formulation quickly and accurately. Accuracy of the software written in this paper was tested using the Coal-Fired Steam Power Plants performance values calculated manually as a comparison and result difference between the two types of calculations below 1% and able to cut manual calculation time from 142.46 minutes to 14.34 minutes using the software which is feasible to generate target variable datasets needed for performance prediction using machine learning algorithm.