A review of current prediction methods for slagging and fouling in Malaysian coal fired power plants

• Main Authors: Anhar, Zaki, Musa, Muktaruddin, Illias, Suhaimi, Ani, Mohd Hanafi
• Format: Article
• Language: English
• Published: TEST Engineering & Management 2020
• Subjects: TA Engineering (General). Civil engineering (General); TA401 Materials of engineering and construction
• Online Access: http://irep.iium.edu.my/81019/1/81019_A%20Review%20of%20Current%20Prediction.pdf; http://irep.iium.edu.my/81019/; https://www.testmagzine.biz/index.php/testmagzine/article/view/7427/5645

Coal is a very important source of Energy worldwide. Current statistics show a strong indication that coal continues to contribute be one of the main sources of energy. Since coal fired power plants supply a large portion of Malaysia’s electricity, outages at these plants tend to cause serious problems within the country’s National Grid. Any shortcomings from coal fired generation would have to be replaced by more expensive Natural Gas based generation, especially if a sudden dip in power generation is experienced. Thus, it is important to both national security and economic considerations that the coal power plants be run as reliably as possible. In Malaysia, the impact of deposits on coal fired plant operation is varied, with some cases known to have caused Forced Outages, Forced Deration and also secondary damage to other plant equipment, such as Boiler Tubes, Burners and Bottom Ash Handling Equipment. Deposits continue to be a leading issue related to coal firing, and such is an ongoing concern for power plant operators. It is therefore important for power plants to be able to predict the potential impact of the coal to the plants, especially relating to the deposits. There are several methods utilised by the power industry, namely predictive indices, model based predictions and scale up from laboratory tests. This study will compare the available prediction methods widely used in Malaysia against actual plant observations. Comparisons will be made based on a sample of 30 full scale coal trial burns at 6 different power plants, with each test having its deposit risk assessed by both predictive indices and model based predictions. The results show the model based predictions being more reliable especially when dealing with sub bituminous coals.