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題名 | Developing a Turbine Cycle Model Using Adaptive Neuro-Fuzzy Inference System for Kuosheng Nuclear Power Plant |
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作者 | Chan, Yea-kuang; Gu, Jyh-cherng; | 書刊名 | Journal of The Chinese Institute of Engineers |
卷期 | 36:5 2013.07[民102.07] |
頁次 | 頁577-588 |
分類號 | 448.2 |
關鍵詞 | Adaptive neural-fuzzy inference system; Turbine cycle model; Turbine-generator; Nuclear power plant; |
語文 | 英文(English) |
英文摘要 | The objective of this study is to develop a turbine cycle model using adaptive neural-fuzzy inference system (ANFIS) for the Kuosheng Nuclear Power Plant (NPP) in Taiwan. This ANFIS based turbine cycle model is used to estimate the turbine-generator output. The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the neuro-fuzzy based turbine cycle model. After training and validating with key parameters, including turbine throttle pressure, condenser backpressure, feedwater flow rate, and final feedwater temperature, the proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed neuro-fuzzy based turbine cycle model is demonstrated using plant operating data obtained from Unit 1 of the Kuosheng NPP owned by Taiwan Power Company. The results show that this neuro-fuzzy based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, a thermodynamics turbine cycle model was developed using commercial software in order to compare the performance of the ANFIS based turbine cycle model. The results of this study provide an alternative approach to evaluate thermal performance in nuclear power plants. |
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