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Machine learning for design and optimization of organic Rankine cycle plants: A review of current status and future perspectives

https://doi.org/10.1002/wene.474
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ep.12901openalex-snapshot
Alternative approach in performance analysis of organic rankine cycle (ORC)
inferredcites →https://doi.org/10.1007/s10957-018-1396-0openalex-snapshot
Deterministic Global Optimization with Artificial Neural Networks Embedded
inferredcites →https://doi.org/10.1007/s11081-019-09454-1openalex-snapshot
Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation
inferredcites →https://doi.org/10.1016/b978-0-12-818597-1.50068-0openalex-snapshot
Impact of Accurate Working Fluid Properties on the Globally Optimal Design of an Organic Rankine Cycle
inferredcites →https://doi.org/10.1016/b978-0-12-823377-1.50295-0openalex-snapshot
Hybrid Mechanistic Data-Driven Modeling for the Deterministic Global Optimization of a Transcritical Organic Rankine Cycle
inferredcites →https://doi.org/10.1016/j.apenergy.2018.05.057openalex-snapshot
Design and optimization of a Tesla turbine for ORC applications
inferredcites →https://doi.org/10.1016/j.apenergy.2019.01.035openalex-snapshot
A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications
inferredcites →https://doi.org/10.1016/j.apenergy.2022.118609openalex-snapshot
Design, improvements and applications of dual-pressure evaporation organic Rankine cycles: A review
inferredcites →https://doi.org/10.1016/j.applthermaleng.2011.07.041openalex-snapshot
ANN based optimization of supercritical ORC-Binary geothermal power plant: Simav case study
inferredcites →https://doi.org/10.1016/j.applthermaleng.2014.11.031openalex-snapshot
Transcritical pressure Organic Rankine Cycle (ORC) analysis based on the integrated-average temperature difference in evaporators
inferredcites →https://doi.org/10.1016/j.applthermaleng.2017.10.019openalex-snapshot
Design methodology of organic Rankine cycle for waste heat recovery in cement plants
inferredcites →https://doi.org/10.1016/j.applthermaleng.2018.07.136openalex-snapshot
A recent review of waste heat recovery by Organic Rankine Cycle
inferredcites →https://doi.org/10.1016/j.applthermaleng.2018.12.112openalex-snapshot
Working fluid selection for organic Rankine cycle power generation using hot produced supercritical CO2 from a geothermal reservoir
inferredcites →https://doi.org/10.1016/j.applthermaleng.2019.114861openalex-snapshot
A quadruple power generation system for very high efficiency and its performance optimization using an artificial intelligence method
inferredcites →https://doi.org/10.1016/j.applthermaleng.2021.117184openalex-snapshot
Machine learning prediction of ORC performance based on properties of working fluid
inferredcites →https://doi.org/10.1016/j.biteb.2022.100976openalex-snapshot
Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review
inferredcites →https://doi.org/10.1016/j.compchemeng.2020.106996openalex-snapshot
Deterministic global superstructure-based optimization of an organic Rankine cycle
inferredcites →https://doi.org/10.1016/j.egyai.2020.100011openalex-snapshot
Overview on artificial intelligence in design of Organic Rankine Cycle
inferredcites →https://doi.org/10.1016/j.egyai.2022.100153openalex-snapshot
Perspective: Predicting and optimizing thermal transport properties with machine learning methods
inferredcites →https://doi.org/10.1016/j.egypro.2017.09.159openalex-snapshot
A World Overview of the Organic Rankine Cycle Market
inferredcites →https://doi.org/10.1016/j.egypro.2017.09.174openalex-snapshot
Neural networks for small scale ORC optimization
inferredcites →https://doi.org/10.1016/j.egyr.2019.10.032openalex-snapshot
Multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle power plant based on NSGA-II
inferredcites →https://doi.org/10.1016/j.egyr.2021.08.133openalex-snapshot
A comprehensive review: Machine learning and its application in integrated power system
inferredcites →https://doi.org/10.1016/j.enconman.2013.07.041openalex-snapshot
ORC waste heat recovery in European energy intensive industries: Energy and GHG savings
inferredcites →https://doi.org/10.1016/j.enconman.2014.08.048openalex-snapshot
On the potential of zeotropic mixtures in supercritical ORC powered by geothermal energy source
inferredcites →https://doi.org/10.1016/j.enconman.2016.12.023openalex-snapshot
Review of organic Rankine cycle for small-scale applications
inferredcites →https://doi.org/10.1016/j.enconman.2017.01.056openalex-snapshot
A novel cascade organic Rankine cycle (ORC) system for waste heat recovery of truck diesel engines
inferredcites →https://doi.org/10.1016/j.enconman.2017.05.077openalex-snapshot
Thermo- economical consideration of Regenerative organic Rankine cycle coupling with the absorption chiller systems incorporated in the trigeneration system
inferredcites →https://doi.org/10.1016/j.enconman.2018.02.062openalex-snapshot
Artificial neural network (ANN) based prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery
inferredcites →https://doi.org/10.1016/j.enconman.2018.04.027openalex-snapshot
Thermodynamic analysis of dual-loop organic Rankine cycle using zeotropic mixtures for internal combustion engine waste heat recovery
inferredcites →https://doi.org/10.1016/j.enconman.2018.04.058openalex-snapshot
Issues, comparisons, turbine selections and applications – An overview in organic Rankine cycle
inferredcites →https://doi.org/10.1016/j.enconman.2018.05.053openalex-snapshot
Influence of superheat and expansion ratio on performance of organic Rankine cycle-based combined heat and power (CHP) system
inferredcites →https://doi.org/10.1016/j.enconman.2018.10.086openalex-snapshot
Multiple parametric analysis, optimization and efficiency prediction of transcritical organic Rankine cycle using trans-1,3,3,3-tetrafluoropropene (R1234ze(E)) for low grade waste heat recovery
inferredcites →https://doi.org/10.1016/j.enconman.2019.03.086openalex-snapshot
Modeling and thermo-economic optimization of a new multi-generation system with geothermal heat source and LNG heat sink
inferredcites →https://doi.org/10.1016/j.enconman.2019.06.064openalex-snapshot
Biomass retrofit for existing solar organic Rankine cycle power plants: Conceptual hybridization strategy and techno-economic assessment
inferredcites →https://doi.org/10.1016/j.enconman.2020.113738openalex-snapshot
Thermo-economic optimization of the hybrid geothermal-solar power system: A data-driven method based on lifetime off-design operation
inferredcites →https://doi.org/10.1016/j.enconman.2021.114996openalex-snapshot
A Four-Hierarchy method for the design of organic Rankine cycle (ORC) power plants
inferredcites →https://doi.org/10.1016/j.energy.2011.06.036openalex-snapshot
Parametric analysis and optimization of regenerative Clausius and organic Rankine cycles with two feedwater heaters using artificial bees colony and artificial neural network
inferredcites →https://doi.org/10.1016/j.energy.2016.05.022openalex-snapshot
Thermodynamic analysis and multi-objective optimization of various ORC (organic Rankine cycle) configurations using zeotropic mixtures
inferredcites →https://doi.org/10.1016/j.energy.2017.12.094openalex-snapshot
Investigation of Support Vector Machine and Back Propagation Artificial Neural Network for performance prediction of the organic Rankine cycle system
inferredcites →https://doi.org/10.1016/j.energy.2018.05.181openalex-snapshot
An upgraded Tesla turbine concept for ORC applications
inferredcites →https://doi.org/10.1016/j.energy.2018.07.074openalex-snapshot
Multi-objective optimization and exergoeconomic analysis of waste heat recovery from Tehran's waste-to-energy plant integrated with an ORC unit
inferredcites →https://doi.org/10.1016/j.energy.2018.10.059openalex-snapshot
Machine Learning for the prediction of the dynamic behavior of a small scale ORC system
inferredcites →https://doi.org/10.1016/j.energy.2018.11.002openalex-snapshot
Thermodynamic selection criteria of zeotropic mixtures for subcritical organic Rankine cycle
inferredcites →https://doi.org/10.1016/j.energy.2019.02.124openalex-snapshot
Improved correlations for working fluid properties prediction and their application in performance evaluation of sub-critical Organic Rankine Cycle
inferredcites →https://doi.org/10.1016/j.energy.2019.03.016openalex-snapshot
How to approach optimal practical Organic Rankine cycle (OP-ORC) by configuration modification for diesel engine waste heat recovery
inferredcites →https://doi.org/10.1016/j.energy.2020.118912openalex-snapshot
Making the case for cascaded organic Rankine cycles for waste-heat recovery
inferredcites →https://doi.org/10.1016/j.energy.2021.120278openalex-snapshot
Efficiency maximization of a quadruple power generation system with zero carbon emission
inferredcites →https://doi.org/10.1016/j.engfailanal.2021.105810openalex-snapshot
Integrity assessment of corroded oil and gas pipelines using machine learning: A systematic review
inferredcites →https://doi.org/10.1016/j.esd.2011.06.002openalex-snapshot
Power production from a moderate temperature geothermal resource with regenerative Organic Rankine Cycles
inferredcites →https://doi.org/10.1016/j.esd.2015.11.004openalex-snapshot
Integrated design and construction of a micro-central tower power plant
inferredcites →https://doi.org/10.1016/j.esd.2020.10.011openalex-snapshot
Assessment of renewable energy transition pathways for a fossil fuel-dependent electricity-producing jurisdiction
inferredcites →https://doi.org/10.1016/j.esd.2021.10.011openalex-snapshot
Perceptions of problems and preferences for solutions: The case of poor air quality in central-southern Chile
inferredcites →https://doi.org/10.1016/j.geothermics.2019.03.003openalex-snapshot
An artificial intelligence approach for thermodynamic modeling of geothermal based-organic Rankine cycle equipped with solar system
inferredcites →https://doi.org/10.1016/j.geothermics.2022.102401openalex-snapshot
Machine learning in subsurface geothermal energy: Two decades in review
inferredcites →https://doi.org/10.1016/j.jbusres.2022.01.076openalex-snapshot
Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods
inferredcites →https://doi.org/10.1016/j.jclepro.2021.125834openalex-snapshot
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
inferredcites →https://doi.org/10.1016/j.jisa.2022.103121openalex-snapshot
Towards a robust and trustworthy machine learning system development: An engineering perspective
inferredcites →https://doi.org/10.1016/j.renene.2018.07.013openalex-snapshot
The Ottana solar facility: dispatchable power from small-scale CSP plants based on ORC systems
inferredcites →https://doi.org/10.1016/j.rser.2011.07.024openalex-snapshot
Low-grade heat conversion into power using organic Rankine cycles – A review of various applications
inferredcites →https://doi.org/10.1016/j.rser.2013.02.019openalex-snapshot
A review on development of industrial processes and emerging techniques for production of hydrogen from renewable and sustainable sources
inferredcites →https://doi.org/10.1016/j.rser.2014.07.113openalex-snapshot
Renewable energy resources: Current status, future prospects and their enabling technology
inferredcites →https://doi.org/10.1016/j.rser.2018.04.039openalex-snapshot
ORC based micro-cogeneration systems for residential application – A state of the art review and current challenges
inferredcites →https://doi.org/10.1016/j.rser.2018.04.097openalex-snapshot
A comprehensive review of state-of-the-art concentrating solar power (CSP) technologies: Current status and research trends
inferredcites →https://doi.org/10.1016/j.rser.2019.109395openalex-snapshot
Biomass torrefaction: properties, applications, challenges, and economy
inferredcites →https://doi.org/10.1016/j.rser.2021.110929openalex-snapshot
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
inferredcites →https://doi.org/10.1016/j.rser.2022.112128openalex-snapshot
Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm
inferredcites →https://doi.org/10.1016/j.seta.2019.05.013openalex-snapshot
Solar energy and wind power supply supported by storage technology: A review
inferredcites →https://doi.org/10.1109/ssci.2016.7849996openalex-snapshot
Modeling of Organic Rankine Cycle for waste heat recovery using RBF neural networks
inferredcites →https://doi.org/10.1146/annurev-environ-020220-061831openalex-snapshot
Machine Learning for Sustainable Energy Systems
inferredcites →https://doi.org/10.18434/t4js3copenalex-snapshot
NIST Reference Fluid Thermodynamic and Transport Properties Database: Version 9.0, NIST Standard Reference Database 23

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4803564openalex-extracted
Reining in the Varieties of Technological Review Methods: A Scoping Review with Transdisciplinary Recommendations for an Uncertain Future
inferred← citeshttps://doi.org/10.1016/j.applthermaleng.2026.131828openalex-snapshot
A hybrid machine learning-mechanistic modeling framework for zeotropic ORC systems: Unraveling composition-property-heat transfer-performance pathways
inferred← citeshttps://doi.org/10.1016/j.energy.2026.142357openalex-snapshot
Safety, not global-warming potential, is the binding constraint on organic Rankine cycle efficiency in the 140–180 °C waste-heat band: A 222-million-candidate reachability analysis anchored by 590 multi-scale measurements
inferred← citeshttps://doi.org/10.1016/j.rser.2024.115150openalex-snapshot
Multi-objective optimization of medium-enthalpy geothermal Organic Rankine Cycle plants
inferred← citeshttps://doi.org/10.3390/a17060234openalex-snapshot
Unleashing the Power of Tweets and News in Stock-Price Prediction Using Machine-Learning Techniques
inferred← citeshttps://doi.org/10.3390/en16165948openalex-snapshot
Design, Integration, and Control of Organic Rankine Cycles with Thermal Energy Storage and Two-Phase Expansion System Utilizing Intermittent and Fluctuating Heat Sources—A Review
inferred← citeshttps://doi.org/10.3934/energy.2026024openalex-snapshot
Deep learning prediction and optimization of biomass-powered organic Rankine cycle
inferred← citeshttps://doi.org/10.62638/zasmat1329openalex-snapshot
Modelling and optimisation of geothermal binary ORC systems using response surface methodology and artificial neural networks
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