Statistical Optimisation Of Operational Parameters In A Thermal Power Station (A Case Study Of Hwange Power Station)
- Author
- Emmanuel Mucheri
- Title
- Statistical Optimisation Of Operational Parameters In A Thermal Power Station (A Case Study Of Hwange Power Station)
- Abstract
- This research investigates the potential of statistical optimization techniques to improve the operational performance of Hwange Power Station, Zimbabwe's largest coal-fired power plant. Real-time operational data is collected and analyzed to identify relationships between key operational parameters (e.g., boiler temperature, turbine inlet pressure) and performance metrics (e.g., plant efficiency, emissions). Statistical optimization techniques like regression analysis or machine learning algorithms are employed to develop a data-driven model that recommends optimal settings for these parameters. The model is validated to ensure its effectiveness and generalizability. The research findings explore the impact of optimized parameters on plant efficiency, emission reduction, and potentially, cost control. The successful implementation of this statistical optimization model at Hwange Power Station can lead to significant benefits. Improved efficiency translates to fuel savings and reduced energy production costs. Lower emissions contribute to a cleaner environment and compliance with regulations. Additionally, the developed model can serve as a valuable tool for other thermal power plants seeking to optimize their performance. This research acknowledges limitations related to data availability and model complexity. Future work can explore integrating the model with existing control systems and adapting the approach for broader application to other power plants.
- Date
- June 2024
- Publisher
- BUSE
- Keywords
- Statistical Optimisation
- Operational Parameters
- Thermal Power Station
- Supervisor
- DR T.W. Mapuwei
