A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications

Palagi, Laura; Sciubba, Enrico

doi:10.1016/j.apenergy.2019.01.035

Cited by 40 publications

(14 citation statements)

References 21 publications

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“…The trend can be explained by observing the effect of ∆T pp on the . W net (Figure 16), and considering Equations (5) and (9). In this section, the effect of on system performance was studied.…”

Section: Effect Of Pinch-point Temperature Difference (∆T Pp )mentioning

confidence: 99%

“…A descending trend is observed for both the first and second law efficiencies with increasing pinch-point temperature difference, as seen in Figures 14 and 15. The trend can be explained by observing the effect of on the net W  (Figure 16), and considering Equations (5) and (9).…”

Section: Effect Of Pinch-point Temperature Difference (∆T Pp )mentioning

confidence: 99%

“…Effect of varying TIP on exergy efficiency for several working fluids.The trends depicted inFigures 5 and 6can be justified by considering Equations(5)and(9). For constant values of .…”

mentioning

confidence: 95%

“…11, x; doi: FOR PEER REVIEW www.mdpi.com/journal/sustainability difference, as seen in Figures 14 and 15. The trend can be explained by observing the effect of on the net W (Figure 16), and considering Equations (5) and(9).…”

mentioning

confidence: 99%

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Thermodynamic and Exergoeconomic Analyses of a Novel Combined Cycle Comprised of Vapor-Compression Refrigeration and Organic Rankine Cycles

2019

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In this study, a cooling/power cogeneration cycle consisting of vapor-compression refrigeration and organic Rankine cycles is proposed and investigated. Utilizing geothermal water as a low-temperature heat source, various operating fluids, including R134a, R22, and R143a, are considered for the system to study their effects on cycle performance. The proposed cycle is modeled and evaluated from thermodynamic and thermoeconomic viewpoints by the Engineering Equation Solver (EES) software. Thermodynamic properties as well as exergy cost rates for each stream are found separately. Using R143a as the working fluid, thermal and exergy efficiencies of 27.2% and 57.9%, respectively, are obtained for the cycle. Additionally, the total product unit cost is found to be 60.7 $/GJ. A parametric study is carried out to determine the effects of several parameters, such as turbine inlet pressure, condenser temperature and pressure, boiler inlet air temperature, and pinch-point temperature difference, on the cycle performance. The latter is characterized by such parameters as thermal and exergy efficiencies, refrigeration capacity, produced net power rate, exergy destruction rate, and the production unit cost rates. The results indicate that the system using R134a exhibits the lowest thermal and exergy efficiencies among other working fluids, while the systems using R22 and R143a exhibit the highest energy and exergy efficiencies, respectively. The boiler and turbine contribute the most to the total exergy destruction rate.Sustainability 2019, 11, 3374 2 of 20 algorithm, operating on a set of variable configuration parameters on the basis of a time-running calculation for minimum entropy. Numerous cycles have been introduced and analyzed that use low-temperature energy sources [5,6]. Amongst these, the organic Rankine cycle (ORC) and its various configurations have been broadly used in geothermal power plants. The ORC can also be combined with the vapor-compression refrigeration cycle (VCC) to produce cooling [7]. The VCC, because of its high cooling capacity and smaller size compared to absorption refrigeration systems of the same cooling capacity, has been widely used in cooling systems [8]. Based on machine learning techniques, Palagi and Sciubba [9] proposed a methodology for optimizing the thermodynamic cycle as well as the radial in-flow turbine employed in a small-scale ORC. In this method the physical model of the thermodynamic cycle is converted into a set of continuous and differentiable functions. They reported that the approach had a higher accuracy and a lower computational time. Kim and Perez-Blanco [10] conducted a functional study of a cogeneration system combining an ORC and a VCC. The effects of decision parameters, such as turbine inlet temperature (TIT) and pressure and mass flow split ratio, on the system performance including the amount of produced power, cooling, thermal, and exergy efficiencies were studied. The results indicated that the system has good potential for effective use of low-temperature therm...

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Section: Effect Of Pinch-point Temperature Difference (∆T Pp )mentioning

confidence: 99%

Section: Effect Of Pinch-point Temperature Difference (∆T Pp )mentioning

confidence: 99%

“…Effect of varying TIP on exergy efficiency for several working fluids.The trends depicted inFigures 5 and 6can be justified by considering Equations(5)and(9). For constant values of .…”

mentioning

confidence: 95%

mentioning

confidence: 99%

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Thermodynamic and Exergoeconomic Analyses of a Novel Combined Cycle Comprised of Vapor-Compression Refrigeration and Organic Rankine Cycles

2019

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“…Lastly, Palagi et al [22] developed surrogate models based on a neural network approach to carry out multi-objective optimization of a small-scale ORC unit, showing that the computational time could be reduced by two orders of magnitude in comparison with the traditional optimization approach.…”

Section: Introductionmentioning

confidence: 99%

Regression Models for the Evaluation of the Techno-Economic Potential of Organic Rankine Cycle-Based Waste Heat Recovery Systems on Board Ships Using Low Sulfur Fuels

Baldasso

Mondéjar

Larsen³

et al. 2020

Energies

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When considering waste heat recovery systems for marine applications, which are estimated to be suitable to reduce the carbon dioxide emissions up to 20%, the use of organic Rankine cycle power systems has been proven to lead to higher savings compared to the traditional steam Rankine cycle. However, current methods to estimate the techno-economic feasibility of such a system are complex, computationally expensive and require significant specialized knowledge. This is the first article that presents a simplified method to carry out feasibility analyses for the implementation of organic Rankine cycle waste heat recovery units on board vessels using low-sulfur fuels. The method consists of a set of regression curves derived from a synthetic dataset obtained by evaluating the performance of organic Rankine cycle systems over a wide range of design and operating conditions. The accuracy of the proposed method is validated by comparing its estimations with the ones attained using thermodynamic models. The results of the validation procedure indicate that the proposed approach is capable of predicting the organic Rankine cycle annual energy production and levelized cost of electricity with an average accuracy within 4.5% and 2.5%, respectively. In addition, the results suggest that units optimized to minimize the levelized cost of electricity are designed for lower engine loads, compared to units optimized to maximize the overall energy production. The reliability and low computational time that characterize the proposed method, make it suitable to be used in the context of complex optimizations of the whole ship’s machinery system.

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An integrated dimensionality reduction and surrogate optimization approach for plant‐wide chemical process operation

Savage

Almeida‐Trasvina

Chanona³

et al. 2021

AIChE Journal

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With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.

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A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications

Cited by 40 publications

References 21 publications

Thermodynamic and Exergoeconomic Analyses of a Novel Combined Cycle Comprised of Vapor-Compression Refrigeration and Organic Rankine Cycles

Thermodynamic and Exergoeconomic Analyses of a Novel Combined Cycle Comprised of Vapor-Compression Refrigeration and Organic Rankine Cycles

Regression Models for the Evaluation of the Techno-Economic Potential of Organic Rankine Cycle-Based Waste Heat Recovery Systems on Board Ships Using Low Sulfur Fuels

An integrated dimensionality reduction and surrogate optimization approach for plant‐wide chemical process operation

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