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The study of dynamic process of ORC variable conditions based on control characteristics analysis
Author(s) -
Yunli Jin,
Naiping Gao,
Tong Zhu
Publication year - 2017
Publication title -
energy procedia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.474
H-Index - 81
ISSN - 1876-6102
DOI - 10.1016/j.egypro.2017.09.133
Subject(s) - process (computing) , control (management) , control theory (sociology) , variable (mathematics) , control variable , mode (computer interface) , control engineering , state variable , engineering , control system , state (computer science) , process control , selection (genetic algorithm) , computer science , mathematics , algorithm , mathematical analysis , artificial intelligence , operating system , physics , electrical engineering , machine learning , thermodynamics
The effect of the characteristics of the ORC components including equipment and parameters on system performance has been explored deeply in previous studies. The fluctuation of heat source and load demand in practical application, leads to the change of ORC operation environment. Operation condition variation of ORC system responding to this change should be done, which is realized by certain control strategy. The way that control strategies impose influence on ORC system has not been investigated. The purpose of this paper is to study the impact of control strategy on ORC performance. The control characteristic analysis is introduced which means the dynamic characteristic of ORC system under certain control strategy. Four different control strategies based on different regulated variables, control variables, control algorithm and operation mode are proposed and compared. The dynamic process model is built and simulated. The results show that the selection of regulated variables, control variables and control algorithm directly influences the dynamic behavior of variable conditions, but not the final steady state. The operation mode selection of fixed or slide pressure has the effect on both ORC dynamic process and final steady state.

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