Abstract:
Analyzing the reliability of a newly built coal fired power station is important when the expected reliability is not proved by the power station. The guaranteed minimum availability of the Lakvijaya coal power station by the contractor is 85%. But the actual is fur below than that during first two years. Turbine side is the main contributor for poor reliability. It contributed to a 56% of forced outages and 57% of energy loss causes by forced outages. The major systems of the turbine side as well as related auxiliary systems contributed in various scales to the poor reliability of the power plant. The study focuses on identifications and analysis the reliability issues of turbine side of Lakvijaya power station. Then find out the reasons behind the reliability issues and propose methods to improve the reliability. The existing reliability is analyzed based on the historical data of failures. The reliability measures as MTBF, MTTR, FOR, availability and failure rate are used to analyze the reliability. The actual results obtained are compared with the standard values. It can be seen that design issues of systems, lack of attention given to commissioning, poor workmanship and lack of preventive maintenance causes poor reliability of turbine side. A minimum of 1.8 billion rupees could have been saved to CEB if the reliability issues in turbine side didn't anse. The reliability improvement methods are proposed to improve the reliability. Design changes and improvements to the existing systems are proposed for improve lack of reliability. A minimum of 3.3 billion rupees can be saved within three years period by implementing these improvements. A short term reliability analysis is helpful to understand the behavior of generating unit. In short term, based on the state where the unit is operating when the fault occurs FOR, EENS and state probabilities are illustrated. It provides a guideline to decide the most reliable generating capacity among the available capacities after a fault. It is recommended updating the database of failures of the power plant and develops a more precise guideline for operating decision making.
