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.
