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Browsing by Author "Xue, Jie"
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Item Optimal Power Control of a Wind Turbine Power Generation System(2012-09-27) Xue, Jie; Chen, Yaobin; Li, Lingxi; Rovnyak, StevenThis thesis focuses on optimization of wind power tracking control systems in order to capture maximum wind power for the generation system. In this work, a mathematical simulation model is developed for a variable speed wind turbine power generation system. The system consists a wind turbine with necessary transmission system, and a permanent magnet synchronous generator and its vector control system. A new fuzzy based hill climbing method for power tracking control is proposed and implemented to optimize the wind power for the system under various conditions. Two existing power tracking control methods, the tip speed ratio (TSR) control method and the speed sensorless control method are also implemented with the wind power system. The computer simulations with a 5 KW wind power generation system are performed. The results from the proposed control method are compared with those obtained using the two existing methods. It is illustrated that the proposed method generally outperforms the two existing methods, especially when the operating point is far away from the maximum point. The proposed control method also has similar stable characteristic when the operating point is close to the peak point in comparison with the existing methods. The proposed fuzzy control method is computationally efficient and can be easily implemented in real-time.Item Two-Stage Method for Optimal Operation of a Distributed Energy System(IEEE, 2016-11) Xue, Jie; Zhou, Jue; Chen, Yaobin; Department of Electrical and Computer Engineering, School of Engineering and TechnologyIn this paper, a gas turbine-based distributed energy system (DES) model is developed for the design of operation planning. An operation mode aimed to optimize the operation of this DES is proposed. A multi-objective cost function considering the total system efficiency and operational cost is formulated for the optimal design of DES operation and control. A two-stage approach combining the particle swarm algorithm (PSO) with the sequential quadratic programming (SQP) method is employed to solve the nonlinear programming problem. Optimal operation strategies for the DES are investigated using the proposed two-stage method under three different demand loads in terms of weather conditions. The simulation results are compared with those using traditional rule-based operation methods. It is found that under the proposed operation mode, the DES is capable of achieving an improved performance in terms of thermal efficiency and operational cost.