Validated dynamic model of an organic Rankine cycle (ORC) for waste heat recovery in a diesel truck

Huster, Wolfgang R.; Vaupel, Yannic; Mhamdi, Adel; Mitsos, Alexander

doi:10.1016/j.energy.2018.03.058

Cited by 47 publications

(18 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Likewise, the transition towards bio-based process routes causes a need for integrated separation techniques by combining, e.g., distillation and extraction [58]. Finally, flexible energy processes are designed to cope with fluctuating sources, e.g., organic Rankine cycles for waste heat recovery in vehicles [59]. Note that all of these examples are governed by strong nonlinearities and/or transient behavior, motivating the development of advanced control methods that in turn require accurate, but not too complex nonlinear models.…”

Section: Generalization To Spatially Distributed Systems and Possiblementioning

confidence: 99%

The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns

Schäfer

Caspari

Schweidtmann

et al. 2020

Chemie Ingenieur Technik

Self Cite

View full text Add to dashboard Cite

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Extensive literature has considered reduced, but still highly accurate, nonlinear dynamic process models, particularly for distillation columns. Nevertheless, there is a need for continuing research in this field. Herein, opportunities from the integration of machine learning into existing reduction approaches are discussed. First, key concepts for dynamic model reduction and their limitations are briefly reviewed. Afterwards, promising model structures for reduced hybrid mechanistic/data-driven models are outlined. Finally, crucial future challenges as well as promising research perspectives are presented.

show abstract

Section: Generalization To Spatially Distributed Systems and Possiblementioning

confidence: 99%

The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns

Schäfer

Caspari

Schweidtmann

et al. 2020

Chemie Ingenieur Technik

Self Cite

View full text Add to dashboard Cite

show abstract

“…ORC is considered to be flexible in terms of the type and temperature of the heat source, and requires low maintenance. The versatility of the heat source and its modular design make ORC an attractive option, especially when waste heat is used for power generation [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Diesel Engine Waste Heat Harnessing ORC

Taylor¹,

Bull²,

Buick³

et al. 2020

SSRG-IJTE

View full text Add to dashboard Cite

Use of ORCs in waste heat recovery is widely seen as a viable and promising solution for increasing energy efficiency and emission reduction efforts, with "on-board" vehicular concepts becoming increasingly popular. In this study, the potential of an ORC harnessing exhaust energy from a diesel generator is considered. Preliminary fluid selection was based on satisfactory thermodynamic performance, and expander size requirement as the limiting parameter. Both simple and recuperative ORC systems were modelled. The effect of the exhaust temperature and the high operational pressure of the ORC model were evaluated in terms of energetic and exergetic performance. For the toluene ORC, moderate pressure values were dictated by the expander size limitation, yet this can be alleviated by high exhaust temperatures. Simple ORCs required a larger heat input and had lower exergetic efficiency. Recuperative ORCs showed better thermal efficiency and lower overall exergy destruction. The expander efficiency was identified as a vital parameter for cycle design and thermodynamic performance.

show abstract

“…In literature, dynamic models of ORC are mainly developed for waste heat recovery applications in vehicles and diesel engines. Huster et al [4] present a dynamic model of a basic ORC for waste heat recovery in a diesel truck. For modelling, the commercial software gPROMS is used and the model is validated by a transient measurement data set.…”

Section: Introductionmentioning

confidence: 99%

Transient Simulation of Geothermal Combined Heat and Power Generation for a Resilient Energetic and Economic Evaluation

2019

View full text Add to dashboard Cite

Geothermal power plants based on the organic Rankine cycle (ORC) are used to convert the thermal power of brine into electricity. The efficiency and profitability of these power plants can be increased by an additional heat supply. The purpose of this study is to evaluate different combined heat and power (CHP) concepts for geothermal applications by thermodynamic and economic considerations. Therefore, a dynamic simulation model of a double-stage ORC is developed to perform annual return simulations. The transient ORC model is validated in a wide range by operational data of an existing power plant in the German Molasse Basin. A district heating system is considered and the corresponding heat load profiles are derived from a real geothermal driven heating network. For CHP, parallel and combined configurations are considered. The validation of the transient model is satisfying with a correlation coefficient of 0.99 between the simulation and real power plant data. The results show that additional heat extraction leads to a higher exergetic efficiency and a higher profitability. The exergetic efficiency and the profitability are increased by up to 7.9% and 16.1%, respectively. The combined concept shows a slightly better performance than the parallel configuration. The efficiency can be increased by up to 1.3%. In economic terms, for CHP the annual return can be increased by at least 2,500,000 €. In principle, the dynamic model shows reliable results for high power gradients. This enables an investigation of geothermal ORC models for the reserve market in future works.

show abstract

Validated dynamic model of an organic Rankine cycle (ORC) for waste heat recovery in a diesel truck

Cited by 47 publications

References 37 publications

The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns

The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns

Diesel Engine Waste Heat Harnessing ORC

Transient Simulation of Geothermal Combined Heat and Power Generation for a Resilient Energetic and Economic Evaluation

Contact Info

Product

Resources

About