Modeling and constrained multivariable predictive control for ORC (Organic Rankine Cycle) based waste heat energy conversion systems-Reference-Cited by-同舟云学术

Modeling and constrained multivariable predictive control for ORC (Organic Rankine Cycle) based waste heat energy conversion systems

Published:2014-03 Issue: Volume:66 Page:128-138
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Zhang Jianhua^ORCID,Zhou Yeli,Wang Rui,Xu Jinliang,Fang Fang

Funder

National Basic Research Program of China

Natural Science Foundation of China of International Cooperation Project

Natural Science Foundation of China

Beijing

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference35 articles.

1. Parametric optimization and performance analysis of a waste heat recovery system using organic Rankine cycle;Roy;Energy,2010

2. Performance analysis and optimization of organic Rankine cycle (ORC) for waste heat recovery;Wei;Energy Convers Manag,2007

3. Performance comparison and parametric optimization of subcritical organic Rankine cycle (ORC) and transcritical power cycle system for low-temperature geothermal power generation;Zhang;Appl Energy,2011

4. Performance analysis of an organic Rankine cycle with superheating under different heat source temperature conditions;Roy;Appl Energy,2011

5. Thermo-economic optimization of waste heat recovery organic Rankine cycles;Quoilin;Appl Therm Eng,2011

Cited by 76 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comprehensive assumption-free dynamic simulation of an organic Rankine cycle using moving-boundary method;Energy;2024-10

2. Fast two-layer nonlinear economic predictive control using machine learning for ORC systems with non-Gaussian disturbances;Chemical Engineering Science;2024-03

3. Surrogate empowered Sim2Real transfer of deep reinforcement learning for ORC superheat control;Applied Energy;2024-02

4. On the applicability of advanced model-based strategies to control of electrified vehicle thermal systems;Energy;2023-11

5. Integrating machine learning and mathematical programming for efficient optimization of operating conditions in organic Rankine cycle (ORC) based combined systems;Energy;2023-10