scholarly journals Small Scale ORC Plant Modeling with the AMESim Simulation Tool: Analysis of Working Fluid and Thermodynamic Cycle Parameters Influence

2015 ◽  
Vol 81 ◽  
pp. 440-449 ◽  
Author(s):  
M. Antonelli ◽  
A. Baccioli ◽  
M. Francesconi ◽  
P. Psaroudakis ◽  
L. Martorano
Keyword(s):  
Thermodynamic Cycle ◽  
Working Fluid ◽  
Small Scale ◽  
Simulation Tool ◽  
Plant Modeling ◽  
Amesim Simulation

Performance Evaluation of a Small Scale High Efficiency Cogeneration System

2006 ◽  
Author(s):  
Mauro Reini
Keyword(s):  
High Efficiency ◽  
Pressure Ratio ◽  
Organic Rankine Cycle ◽  
Thermodynamic Cycle ◽  
Rankine Cycle ◽  
Combined Cycle ◽  
Working Fluid ◽  
Small Scale ◽  
Performance Parameters ◽  
Cogeneration System

In recent years, a big effort has been made to improve microturbines thermal efficiency, in order to approach 40%. Two main options may be considered: i) a wide usage of advanced materials for hot ends components, like impeller and recuperator; ii) implementing more complicated thermodynamic cycle, like combined cycle. In the frame of the second option, the paper deals with the hypothesis of bottoming a low pressure ratio, recuperated gas cycle, typically realized in actual microturbines, with an Organic Rankine Cycle (ORC). The object is to evaluate the expected nominal performance parameters of the integrated-combined cycle cogeneration system, taking account of different options for working fluid, vapor pressure and component’s performance parameters. Both options of recuperated and not recuperated bottom cycles are discussed, in relation with ORC working fluid nature and possible stack temperature for microturbine exhaust gases. Finally, some preliminary consideration about the arrangement of the combined cycle unit, and the effects of possible future progress of gas cycle microturbines are presented.

Toward the Integrated Design of Organic Rankine Cycle Power Plants: A Method for the Simultaneous Optimization of Working Fluid, Thermodynamic Cycle, and Turbine

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Matthias Lampe ◽  
Carlo De Servi ◽  
Johannes Schilling ◽  
André Bardow ◽  
Piero Colonna
Keyword(s):  
Integrated Design ◽  
Organic Rankine Cycle ◽  
Design Procedure ◽  
Thermodynamic Cycle ◽  
Rankine Cycle ◽  
Operating Conditions ◽  
Working Fluid ◽  
Small Scale ◽  
Iterative Design ◽  
Selection Of

Abstract The conventional design of organic Rankine cycle (ORC) power systems starts with the selection of the working fluid and the subsequent optimization of the corresponding thermodynamic cycle. More recently, systematic methods have been proposed integrating the selection of the working fluid into the optimization of the thermodynamic cycle. However, in both cases, the turbine is designed subsequently. This procedure can lead to a suboptimal design, especially in the case of mini- and small-scale ORC systems, since the preselected combination of working fluid and operating conditions may lead to infeasible turbine designs. The resulting iterative design procedure may end in conservative solutions after multiple trial-and-error attempts due to the strong interdependence of the many design variables and constraints involved. In this work, we therefore present a new design and optimization method integrating working fluid selection, thermodynamic cycle design, and preliminary turbine design. To this purpose, our recent 1-stage continuous-molecular targeting (CoMT)-computer-aided molecular design (CAMD) method for the integrated design of the ORC process and working fluid is expanded by a turbine meanline design procedure. Thereby, the search space of the optimization is bounded to regions where the design of the turbine is feasible. The resulting method has been tested for the design of a small-scale high-temperature ORC unit adopting a radial-inflow turbo-expander. The results confirm the potential of the proposed method over the conventional iterative design practice for the design of small-scale ORC turbogenerators.

Model, simulation and experiments for a Buoyancy Organic Rankine Cycle

2020 ◽  
Vol 92 (1) ◽  
pp. 10906
Author(s):  
Jeroen Schoenmaker ◽  
Pâmella Gonçalves Martins ◽  
Guilherme Corsi Miranda da Silva ◽  
Julio Carlos Teixeira
Keyword(s):  
Model Simulation ◽  
Organic Rankine Cycle ◽  
Thermodynamic Cycle ◽  
Rankine Cycle ◽  
Test Body ◽  
Working Fluid ◽  
Proof Of Concept ◽  
Energy Scenario ◽  
New Type ◽  
Fluid Reservoir

Organic Rankine Cycle (ORC) systems are increasingly gaining relevance in the renewable and sustainable energy scenario. Recently our research group published a manuscript identifying a new type of thermodynamic cycle entitled Buoyancy Organic Rankine Cycle (BORC) [J. Schoenmaker, J.F.Q. Rey, K.R. Pirota, Renew. Energy 36, 999 (2011)]. In this work we present two main contributions. First, we propose a refined thermodynamic model for BORC systems accounting for the specific heat of the working fluid. Considering the refined model, the efficiencies for Pentane and Dichloromethane at temperatures up to 100 °C were estimated to be 17.2%. Second, we show a proof of concept BORC system using a 3 m tall, 0.062 m diameter polycarbonate tube as a column-fluid reservoir. We used water as a column fluid. The thermal stability and uniformity throughout the tube has been carefully simulated and verified experimentally. After the thermal parameters of the water column have been fully characterized, we developed a test body to allow an adequate assessment of the BORC-system's efficiency. We obtained 0.84% efficiency for 43.8 °C working temperature. This corresponds to 35% of the Carnot efficiency calculated for the same temperature difference. Limitations of the model and the apparatus are put into perspective, pointing directions for further developments of BORC systems.

Multi-Fluid Gas Turbine Components Scaling for a Generation IV Nuclear Power Plant Performance Simulation

2018 ◽  
Author(s):  
Emmanuel O. Osigwe ◽  
Arnold Gad-Briggs ◽  
Theoklis Nikolaidis ◽  
Pericles Pilidis ◽  
Suresh Sampath
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Gas Turbine ◽  
Nuclear Power ◽  
Working Fluid ◽  
Simulation Tool ◽  
Closed Cycle ◽  
Performance Simulation ◽  
Working Fluids ◽  
Component Map

One major challenge to the accurate development of performance simulation tool for component-based nuclear power plant engine models is the difficulty in accessing component performance maps; hence, researchers or engineers often rely on estimation approach using various scaling techniques. This paper describes a multi-fluid scaling approach used to determine the component characteristics of a closed-cycle gas turbine plant from an existing component map with their design data, which can be applied for different working fluids as may be required in closed-cycle gas turbine operations to adapt data from one component map into a new component map. Each component operation is defined by an appropriate change of state equations which describes its thermodynamic behavior, thus, a consideration of the working fluid properties is of high relevance to the scaling approach. The multi-fluid scaling technique described in this paper was used to develop a computer simulation tool called GT-ACYSS, which can be valuable for analyzing the performance of closed-cycle gas turbine operations with different working fluids. This approach makes it easy to theoretically scale existing map using similar or different working fluids without carrying out a full experimental test or repeating the whole design and development process. The results of selected case studies show a reasonable agreement with available data.

Optimization of a Novel Combined Power/Refrigeration Thermodynamic Cycle

Solar Energy ◽  
2002 ◽  
Author(s):  
Shaoguang Lu ◽  
D. Yogi Goswami
Keyword(s):  
Waste Heat ◽  
Thermodynamic Cycle ◽  
Cycle Performance ◽  
Working Fluid ◽  
Second Law ◽  
Optimum Conditions ◽  
Ambient Temperatures ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient ◽  
Performance Conditions

A novel combined power/refrigeration thermodynamic cycle is optimized for thermal performance in this paper. The cycle uses ammonia-water binary mixture as a working fluid and can be driven by various heat sources, such as solar, geothermal and low temperature waste heat. It could produce power as well as refrigeration with power output as a primary goal. The optimization program, which is based on the Generalized Reduced Gradient (GRG) algorithm, can be used to optimize for different objective functions. Examples that maximize second law efficiency, work output and refrigeration output are presented, showing the cycle may be optimized for any desired performance parameter. In addition, cycle performance over a range of ambient temperatures was investigated. It was found that for a source temperature of 360K, which is in the range of flat plate solar collectors, both power and refrigeration outputs are achieved under optimum conditions. All performance parameters, including first and second law efficiencies, power and refrigeration output decrease as the ambient temperature goes up. On the other hand, for a source of 440K, optimum conditions do not provide any refrigeration. However, refrigeration can be obtained even for this temperature under non-optimum performance conditions.

Novel Combined Power and Cooling Thermodynamic Cycle for Low Temperature Heat Sources, Part II: Experimental Investigation

2003 ◽  
Vol 125 (2) ◽  
pp. 223-229 ◽  
Author(s):  
Gunnar Tamm ◽  
D. Yogi Goswami
Keyword(s):  
Low Temperature ◽  
System Analysis ◽  
Waste Heat ◽  
Thermal Power ◽  
Experimental System ◽  
Thermodynamic Cycle ◽  
Operating Conditions ◽  
Working Fluid ◽  
Water Mixture ◽  
Theoretical Simulation

A combined thermal power and cooling cycle proposed by Goswami is under intensive investigation, both theoretically and experimentally. The proposed cycle combines the Rankine and absorption refrigeration cycles, producing refrigeration while power is the primary goal. A binary ammonia-water mixture is used as the working fluid. This cycle can be used as a bottoming cycle using waste heat from a conventional power cycle or as an independent cycle using low temperature sources such as geothermal and solar energy. An experimental system was constructed to demonstrate the feasibility of the cycle and to compare the experimental results with the theoretical simulation. Results showed that the vapor generation and absorption condensation processes work experimentally, exhibiting expected trends, but with deviations from ideal and equilibrium modeling. The potential for combined turbine work and refrigeration output was evidenced in operating the system. Analysis of losses showed where improvements could be made, in preparation for further testing over a broader range of operating conditions.

1-D Model Analysis of Tesla Turbine for Small Scale Organic Rankine Cycle (ORC) System

2017 ◽  
Author(s):  
Jian Song ◽  
Chun-wei Gu
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Organic Rankine Cycle ◽  
Axial Flow ◽  
Rankine Cycle ◽  
Expansion Ratio ◽  
Working Fluid ◽  
Small Scale ◽  
Low Grade ◽  
D Model

Energy shortage and environmental deterioration are two crucial issues that the developing world has to face. In order to solve these problems, conversion of low grade energy is attracting broad attention. Among all of the existing technologies, Organic Rankine Cycle (ORC) has been proven to be one of the most effective methods for the utilization of low grade heat sources. Turbine is a key component in ORC system and it plays an important role in system performance. Traditional turbine expanders, the axial flow turbine and the radial inflow turbine are typically selected in large scale ORC systems. However, in small and micro scale systems, traditional turbine expanders are not suitable due to large flow loss and high rotation speed. In this case, Tesla turbine allows a low-cost and reliable design for the organic expander that could be an attractive option for small scale ORC systems. A 1-D model of Tesla turbine is presented in this paper, which mainly focuses on the flow characteristics and the momentum transfer. This study improves the 1-D model, taking the nozzle limit expansion ratio into consideration, which is related to the installation angle of the nozzle and the specific heat ratio of the working fluid. The improved model is used to analyze Tesla turbine performance and predict turbine efficiency. Thermodynamic analysis is conducted for a small scale ORC system. The simulation results reveal that the ORC system can generate a considerable net power output. Therefore, Tesla turbine can be regarded as a potential choice to be applied in small scale ORC systems.

Multi-Objective Optimization of a Combined Power and Cooling Cycle for Low-Grade and Midgrade Heat Sources

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
Gokmen Demirkaya ◽  
Saeb Besarati ◽  
Ricardo Vasquez Padilla ◽  
Antonio Ramos Archibold ◽  
D. Yogi Goswami ◽  
...  
Keyword(s):  
Thermodynamic Cycle ◽  
Solution Concentration ◽  
Working Fluid ◽  
Low Grade ◽  
Basic Solution ◽  
Heat Sources ◽  
Fluid Mixture ◽  
Cooling Cycle ◽  
Multi Objective ◽  
First Case

Optimization of thermodynamic cycles is important for the efficient utilization of energy sources; indeed, it is more crucial for the cycles utilizing low-grade heat sources where the cycle efficiencies are smaller compared to high temperature power cycles. This paper presents the optimization of a combined power/cooling cycle, also known as the Goswami cycle, which combines the Rankine and absorption refrigeration cycles. The cycle uses a special binary fluid mixture as the working fluid and produces a power and refrigeration. In this regard, multi-objective genetic algorithms (GAs) are used for Pareto approach optimization of the thermodynamic cycle. The optimization study includes two cases. In the first case, the performance of the cycle is evaluated as it is used as a bottoming cycle and in the second case, as it is used as a top cycle utilizing solar energy or geothermal sources. The important thermodynamic objectives that have been considered in this work are, namely, work output, cooling capacity, effective first law, and exergy efficiencies. Optimization is carried out by varying the selected design variables, such as boiler temperature and pressure, rectifier temperature, and basic solution concentration. The boiler temperature is varied between 70–150 °C and 150–250 °C for the first and the second cases, respectively.

Small Scale Supercritical CO2 Radial Inflow Turbine Meanline Design Considerations

2018 ◽  
Author(s):  
Tina Unglaube ◽  
Hsiao-Wei D. Chiang
Keyword(s):  
High Velocity ◽  
Gas Turbines ◽  
Velocity Ratio ◽  
Maximum Efficiency ◽  
Design Parameters ◽  
Working Fluid ◽  
Small Scale ◽  
Optimum Velocity ◽  
Set Up ◽  
Very High

In recent years closed loop supercritical carbon dioxide Brayton cycles have drawn the attention of many researchers as they are characterized by a higher theoretic efficiency and smaller turbomachinery size compared to the conventional steam Rankine cycle for power generation. Currently, first prototypes of this emerging technology are under development and thus small scale sCO2 turbomachinery needs to be developed. However, the design of sCO2 turbines faces several new challenges, such as the very high rotational speed and the high power density. Thus, the eligibility of well-established radial inflow gas turbine design principles has to be reviewed regarding their suitability for sCO2 turbines. Therefore, this work reviews different suggestion for optimum velocity ratios for gas turbines and aims to re-establish it for sCO2 turbines. A mean line design procedure is developed to obtain the geometric dimensions for small scale sCO2 radial inflow turbines. By varying the specific speed and the velocity ratio, different turbine configurations are set up. They are compared numerically by means of CFD analysis to conclude on optimum design parameters with regard to maximum total-to-static efficiency. Six sets of simulations with different specific speeds between 0.15 and 0.52 are set up. Higher specific speeds could not be analyzed, as they require very high rotational speeds (more than 140k RPM) for small scale sCO2 turbines (up to 150kWe). For each set of simulations, the velocity ratio that effectuates maximum efficiency is identified and compared to the optimum parameters recommended for radial inflow turbines using subcritical air as the working fluid. It is found that the values for optimum velocity ratios suggested by Rohlik (1968) are rather far away from the optimum values indicated by the conducted simulations. However, the optimum values suggested by Aungier (2005), although also established for subcritical gas turbines, show an approximate agreement with the simulation results for sCO2 turbines. Though, this agreement should be studied for a wider range of specific speeds and a finer resolution of velocity ratios. Furthermore, for high specific speeds in combination with high velocity ratios, the pressure drop of the designed turbines is too high, so that the outlet pressure is beyond the critical point. For low specific speeds in combination with low velocity ratios, the power output of the designed turbines becomes very small. Geometrically, turbines with low specific speeds and high velocity ratios are characterized by very small blade heights, turbines with high specific speeds and small velocity ratios by very small diameters.

Optimal sensor placement to detect ruptures in pipeline systems subject to uncertainty using an Adam-mutated genetic algorithm

2021 ◽  
pp. 147592172110565
Author(s):  
Chungeon Kim ◽  
Hyunseok Oh ◽  
Byung Chang Jung ◽  
Seok Jun Moon
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Sensor Network ◽  
Sensor Placement ◽  
Mixed Integer ◽  
Working Fluid ◽  
Small Scale ◽  
Pipeline System ◽  
Optimal Sensor Placement ◽  
Pipeline Network

Pipelines in critical engineered facilities, such as petrochemical and power plants, conduct important roles of fire extinguishing, cooling, and related essential tasks. Therefore, failure of a pipeline system can cause catastrophic disaster, which may include economic loss or even human casualty. Optimal sensor placement is required to detect and assess damage so that the optimal amount of resources is deployed and damage is minimized. This paper presents a novel methodology to determine the optimal location of sensors in a pipeline network for real-time monitoring. First, a lumped model of a small-scale pipeline network is built to simulate the behavior of working fluid. By propagating the inherent variability of hydraulic parameters in the simulation model, uncertainty in the behavior of the working fluid is evaluated. Sensor measurement error is also incorporated. Second, predefined damage scenarios are implemented in the simulation model and estimated through a damage classification algorithm using acquired data from the sensor network. Third, probabilistic detectability is measured as a performance metric of the sensor network. Finally, a detectability-based optimization problem is formulated as a mixed integer non-linear programming problem. An Adam-mutated genetic algorithm (AMGA) is proposed to solve the problem. The Adam-optimizer is incorporated as a mutation operator of the genetic algorithm to increase the capacity of the algorithm to escape from the local minimum. The performance of the AMGA is compared with that of the standard genetic algorithm. A case study using a pipeline system is presented to evaluate the performance of the proposed sensor network design methodology.

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