Modeling and optimization of a utility system containing multiple extractions steam turbines

被引:100
作者
Luo, Xianglong [1 ]
Zhang, Bingjian [2 ]
Chen, Ying [1 ]
Mo, Songping [1 ]
机构
[1] Guangdong Univ Technol, Sch Mat & Energy, Guangzhou 510006, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Sch Chenistry & Chem Engn, Guangzhou 510275, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Utility system; Multiple extractions; Steam turbine; Optimization; Mathematical modeling; POWER-PLANT; PART; SIMULATION; OPERATION; NETWORK; DESIGN;
D O I
10.1016/j.energy.2011.03.056
中图分类号
O414.1 [热力学];
学科分类号
070201 [理论物理];
摘要
Complex turbines with multiple controlled and/or uncontrolled extractions are popularly used in the processing industry and cogeneration plants to provide steam of different levels, electric power, and driving power. To characterize thermodynamic behavior under varying conditions, nonlinear mathematical models are developed based on energy balance, thermodynamic principles, and semi-empirical equations. First, the complex turbine is decomposed into several simple turbines from the controlled extraction stages and modeled in series. THM (The turbine hardware model) developing concept is applied to predict the isentropic efficiency of the decomposed simple turbines. Stodola's formulation is also used to simulate the uncontrolled extraction steam parameters. The thermodynamic properties of steam and water are regressed through linearization or piece-wise linearization. Second, comparison between the simulated results using the proposed model and the data in the working condition diagram provided by the manufacturer is conducted over a wide range of operations. The simulation results yield small devizition from the data in the working condition diagram where the maximum modeling error is 0.87% among the compared seven operation conditions. Last, the optimization model of a utility system containing multiple extraction turbines is established and a detailed case is analyzed. Compared with the conventional operation strategy, a maximum of 5.47% of the total operation cost is saved using the proposed optimization model. (C) 2011 Published by Elsevier Ltd.
引用
收藏
页码:3501 / 3512
页数:12
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