Multi-objective Optimal Temperature Control for Organic Rankine Cycle Systems
被引:0
作者:
Zhang, Jianhua
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机构:
North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R ChinaNorth China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China
Zhang, Jianhua
[1
]
Ren, Mifeng
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机构:
North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R ChinaNorth China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China
Ren, Mifeng
[2
]
Xiong, Jing
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机构:
North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R ChinaNorth China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China
Xiong, Jing
[2
]
Lin, Mingming
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h-index: 0
机构:
North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R ChinaNorth China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China
Lin, Mingming
[2
]
机构:
[1] North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China
[2] North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China
来源:
2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA)
|
2014年
基金:
美国国家科学基金会;
关键词:
Organic Rankine Cycle (ORC) systems;
non-Gaussian disturbances;
multi-objective optimized problem;
multi-objective estimation of distribution algorithm (MOEDA);
MINIMUM ENTROPY CONTROL;
PERFORMANCE ANALYSIS;
PARAMETRIC OPTIMIZATION;
WORKING FLUIDS;
ORC;
SELECTION;
D O I:
暂无
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
The Organic Rankine Cycle (ORC) has attracted a lot of interests for its ability to recover low-grade heat and the possibility to be implemented in decentralized low-capacity power plants. In this paper, a new optimal temperature control method is proposed for ORC systems with non-Gaussian disturbances which influence the quality of exhaust gas. The objective here is to control the speed of the pump so that the superheated vapor temperature follows a target one. It means that the error between those two temperatures is minimized both in magnitude and randomness, which are characterized by mean value and entropy, respectively. Therefore, the proposed control strategy is regarded as a multi-objective optimization problem. To solve this problem, a Multi-Objective Estimation of Distribution Algorithm (MOEDA) is adopted to obtain all the possible optimal control inputs. Simulation results show the effectiveness of the proposed technique.