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Optimal operation and control for a hybrid hfo-dlco gas turbine power generating plant

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dc.contributor.advisor Markus, ED
dc.contributor.advisor Kusakana, K
dc.contributor.author Kulor, Frank
dc.date.accessioned 2024-08-30T03:51:47Z
dc.date.available 2024-08-30T03:51:47Z
dc.date.issued 2022
dc.identifier.uri http://hdl.handle.net/11462/2596
dc.description Thesis (Doctor: Engineering: Electrical Engineering)--Central University of Technology en_US
dc.description.abstract Gas turbines (GT) are a critical and reliable part of modern power generation plants. They are required in aircraft engine propulsion and power generation for industrial and commercial applications where they serve as the primary mechanical power source for large pumps and compressors. These turbines typically comprise of dual nozzle gas/Heavy fuel oil – diesel light crude oil (HFO-DLCO) generators. Therefore, optimisation and control of their operation is crucial in maximising their performance and cost scaling. Significant research has been conducted, and a plethora of analytical and experimental models have been developed, to better understand that gas turbine systems exhibit nonlinear behaviour and complex dynamics. However, the requirement for accurate and reliable models of gas turbines for a variety of hybrid fuel applications, as well as for cost savings while minimising environmental impact, has been a strong incentive for researchers to continue working in this fascinating field of study. This thesis developed an intelligent control system for a hybrid dual nozzle fuel power plant to increase its energy conversion efficiency and reliability. To accomplish this, the study developed and integrated a dual nozzle power plant model and an optimal cost-effective fuel transition management into a comprehensive control system. The hybrid plant model is a novel modelling technique that combines the algorithms of PID and Model Predictive Controllers to extract plant parameters and uncertainties from operational data and to significantly improve the model's accuracy for subsequent and future analysis and research. To optimise plant efficiency, the MPC state estimator is used to generate optimal set points and PID control provides the final loop control action. By integrating heuristic MPC and PID, technologies, a nonlinear optimal control operation framework is developed. Finally, the individual control systems are integrated into a comprehensive system that manages the dual nozzle fuel GT power plant as a whole. The integrated control system enabled the power plant to operate at normal fuel switching providing a smooth wellregulated system during low fuel pressure. As a result, an intelligent autonomous control system that can perform high-quality plant-wide control is achieved, ensuring efficiency, cost-effectiveness, and reliability. As a result, the hybrid dual nozzle GT power plant achieves an intelligent autonomous control system, allowing for high-quality plant-wide fuel transition management that ensures fuel flow accuracy, efficiency, and reliability in fuel switching operation. en_US
dc.publisher Central University of Technology en_US
dc.subject Gas Turbines en_US
dc.subject (HFO-DLCO) generators en_US
dc.subject Intelligent control system en_US
dc.subject Hybrid plant model en_US
dc.title Optimal operation and control for a hybrid hfo-dlco gas turbine power generating plant en_US
dc.type Thesis en_US


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