Maximizing Steam Turbine Efficiency in Coal Fired Power Plant Through Artificial Intelligence-Based Digital Turbine Optimization (D-TOP)

Optimizing steam turbine operating parameters is crucial for improving the performance of coal-fired power plants, as even minor adjustments can significantly impact the net plant heat rate. However, manual parameter optimization becomes ineffective due to the intricate nature of the steam turbine system and the complex interactions among various operating patterns. An artificial intelligence-based Digital Turbine Optimization (D-TOP) application will determine the best operating parameters to address this challenge. D-TOP involves the analysis of turbine operational data, functional simulation, integration of PI communication with Python, and an artificial intelligence program model, incorporating fuzzy logic for root cause analysis of heat rate discrepancies. Utilizing D-TOP, optimal values for controllable operating parameters, including steam pressure, temperature, water heater level, and others, are provided in real-time at each alteration in electricity production and fuel usage, ensuring the most efficient turbine heat rate. Consequently, D-TOP significantly reduced the turbine heat rate to 79 kcal/kWh, equivalent to a commendable net plant heat rate of 36.55 kcal/kWh, resulting in remarkable energy cost savings of $1,392,552.47 annually. These substantial energy savings correspond to a reduction of 0.0208 cents/kWh and a notable decrease in carbon emissions by an average of 298,14 tons of CO2eq.