Organic Rankine Cycle Waste Heat Recovery System Research Articles

Data-driven identification and fast model predictive control of the ORC waste heat recovery system by using Koopman operator

Organic Rankine Cycle (ORC) has received its wide application in low-grade waste heat recovery (WHR) technology for its significant performance and easy access to its components. Given the highly fluctuating nature of the waste heat source, Model Predictive Control (MPC) is usually utilized to realize the reasonable adjustment of ORC based WHR systems and has performed satisfactorily. In order to apply MPC, a relatively precise model should be built up for the ORC system which ensures acceptable control performance. However, popular modeling methods based on the mechanism of the ORC establish the high-dimensional nonlinear model and suffer from computational costs when utilizing complicated nonlinear MPC. Even if linear MPC is employed for the purpose of reducing the calculation amount, the model obtained by linearization near the operating points usually makes it valid locally, thus bringing about suboptimal or unstable control performance. To address this problem, the Koopman operator is introduced for the data-driven identification and MPC of the ORC system. Koopman identification constructs a linear model in the lifted space in which the ORC system possesses nearly global linear evolution and enables the prediction of the nonlinear ORC dynamics from measurement data. In view of the possible online calculation burden increment caused by the rise of variable dimension through lifting action, the fast Koopman MPC (FKMPC) algorithm is thus proposed based on the invariance of the Hessian matrix of the optimization problem to shorten the computing time. Simulations on setpoint tracking and disturbance rejection are performed to verify the established model accuracy and the control effectiveness of the proposed strategy in comparison with other approaches.

Alleviating the thermal aging of three-way catalyst applied to natural gas engine based on organic Rankine cycle

Natural gas (NG) is a possible pathway for developing countries to reduce transportation carbon footprint. However, its high exhaust temperature decreases the thermal efficiency of NG engines and accelerates the thermal aging of three-way catalyst (TWC). This study proposes to place an organic Rankine cycle waste heat recovery (ORC-WHR) system between an NG engine and its TWC to recover exhaust energy and extend the useful life of TWC. The feasibility of this design concept is confirmed by the simulation results of an experimentally validated 1D NG engine model combined with an ORC-WHR model at three TWC working temperatures representing field-average, modern, and future TWC technologies. Results show that the decrease in the outlet temperature of the ORC-WHR system benefits the availability of exhaust energy, improving the overall efficiency of the engine plus ORC-WHR system and extending the useful life of the TWC. Hence, more advanced catalyst technologies, which can achieve high conversion efficiency at lower temperatures, are deemed more favorable for ORC-WHR coupling. The cost-effectiveness of such combinations is better due to more exhaust energy recovered and less noble metal catalyst needed to be added.

Effect of tooth head modification on the performance of a scroll expander for ORC waste heat recovery system

In order to cope with the energy crisis and improve energy efficiency, the use of organic Rankine cycle (ORC) to convert low-quality heat energy into electricity and use it is an effective method. Based on the ORC waste heat recovery system of vehicle engine, this paper explores the flow heat transfer and deformation law of the core component scroll expander under different tooth head corrections. Deformation has a significant impact on the performance of the expander. In this study, several flow-thermal-solid coupling models based on double circular arc correction and double circular arc plus straight-line correction are established. The effects of tooth head correction on the strength and stiffness of tooth head, flow field distribution of suction chamber and deformation characteristics of tooth head are studied. Finally, the deformation law of scroll tooth head with different correction angles was discussed. The results show that the EA-SAL correction makes the wall curvature of the tooth head change greatly, and the flow field in the center of the tooth head becomes more uneven and complicated. The tooth head area under EA-SAL modification is larger, and the tooth head strength and stiffness are improved by about 6%. Within a certain angle range, the tooth head deformation after EA-SAL correction is slightly larger than that after PMP correction, but the difference between them decreases and even reverses with the increase of angle. The maximum deformation of the EA-SAL modified tooth head under internal pressure is about 20% smaller than that of PMP. With a given initial correction angle ∅, the deformation of the corrected tooth head caused by a pressure or temperature load reduces when the correction angle γ is reduced, Therefore, reducing the correction angle properly is helpful to reduce the deformation of the tooth head.

Organic Rankine Cycle (ORC) as waste heat recovery system for micro-cogeneration: A preliminary study

Although the energy consumption pattern has been optimized, the main problem facing by energy revolution is the low conversion efficiency of renewable energy and waste heat. Among the utilization technologies of these waste heat, organic Rankine cycle (ORC), which has characteristics of simple structure and high efficiency is chosen as the potential candidate to overcome this situation. However, ORC is facing several limitations including having low turbine performance leading to low power production. Additionally, the design of ORC and the heat recovery system should be improved to reduce the investment cost. One of the ways to increase the performance of this ORC is to design ORC waste heat recovery system for cogeneration. Thus, this study will be focused on to identify the effect of different heat exchanger positions to the ORC thermal performance and to investigate the effect of integrating ORC for cogeneration. In order to achieve this, identification of the suitable heat exchanger for ORC will be performed by modelling and simulation to predict the effect of the new design to the ORC thermal performance. Then, the improved novel ORC design will be integrated to a cogeneration system to simulate the power produced by the combined system.

A Q-learning based transient power optimization method for organic Rankine cycle waste heat recovery system in heavy duty diesel engine applications

In recent years, the organic Rankine cycle waste heat recovery (ORC-WHR) technology gains popularity in heavy-duty diesel engine applications. Drastic fluctuations of the waste heat caused by variable daily operation of mobile heavy-duty trucks bring an extreme transient power optimization challenge to ORC-WHR systems. Existing power optimization methods either neglect transient behavior of the Rankine cycle system or compromise model accuracy for computation efficiency. Different from literature, this study first time proposes a model-free reinforcement learning method to achieve online transient power optimization for the ORC-WHR system and explains the benefits of learning method in this application. A tabular Q-learning is formulated to optimize the net power on an experimentally validated ORC-WHR system. Q-learning is explained in detail using states, action, and policy information. To quantify the power optimization of the proposed method, Proper-Integral-Derivative method, state-of-art offline and online Dynamic Programming methods are implemented. The results showed that Q-learning generated 22% more cumulative energy than the energy Proper-Integral-Derivative method generated. Furthermore, Q-learning produces 96.6% of cumulative energy that the offline Dynamic Programming generates over a transient engine condition, while it requires less computation cost and is executed online. Additionally, the Q-learning produces 0.5% more cumulative energy than the machine learning-based online Dynamic Programming results and exhibits better vapor temperature robustness than the online Dynamic Programming method (4 °C-28 °C superheat by Q-learning vs. 5 °C-94 °C superheat by online Dynamic Programming). Given the excellent power production performance, low computation cost requirement and high robustness, the proposed Q-learning method has the potential to improve the power production of the ORC-WHR system with different configurations.

Energy recovery efficiency analysis of organic Rankine cycle system in vehicle engine under different road conditions

The organic Rankine cycle (ORC) system can effectively recover the waste heat energy of the engine, but its performance is substantially affected by the operating conditions of the engine. The road conditions control the operating conditions of the engine, which determine the amount of waste heat energy of the engine and the performance of the ORC system. Therefore, the energy recovery efficiency of the ORC system in a vehicle engine under different road conditions must be studied. This study establishes a vehicle model including engine, ORC system, power transmission system, and control system, and verifies the accuracy of the engine and ORC system. The vehicle model is used to simulate and analyze the operating characteristics and energy recovery efficiency of the engine and ORC system under New York City Cycle (NYCC) and motorway of Common Artemis Driving Cycles (CADC) road conditions. Results show that the exhaust energy is low and fluctuates frequently under NYCC road condition, ranging from 5.45 kW to 24.28 kW, with an average exhaust energy of 10.4 kW and an average energy recovery efficiency of 1.43%. The exhaust energy is high and fluctuates slightly under motorway of CADC road condition, ranging from 5 kW to 44.5 kW, with an average exhaust energy of 26.9 kW and an average energy recovery efficiency of 5.50%. Therefore, the ORC waste heat recovery system is more suitable for motorway road conditions with high, stable vehicle velocity, while the urban road conditions with low or fluctuant vehicle velocity must be avoided as much as possible.

Optimization of an axial turbine for a small scale ORC waste heat recovery system

Low power Organic Rankine Cycle (ORC) turbines are typically characterised by flow efficiencies much smaller than those of large power steam or gas turbines. The paper concentrates on a possibility of improving the flow efficiency of an ORC axial turbine working on toluene using several optimization algorithms such as a simplex method of Nelder-Mead, a hybrid of genetic algorithm with the Nelder-Mead method, as well as implicit filtering. Values of the maximized objective function, which is the isentropic efficiency of the turbine stage, are found from 3D RANS computation of the flowpath geometry changing during the optimization process. Among the optimized geometric parameters are stator and rotor profile parametrization variables, rotor blade twist angle, circumferential lean and axial sweep angles, as well as parameters characterising the shape of endwall contours within the stator and rotor domain. The process of optimization leads to new 3D designs featuring increased efficiency compared to the original design, mainly due to a reduction in secondary and tip leakage flow losses as well as boundary layer, separation and leaving energy losses. The results especially highlight a large potential of the method of implicit filtering in optimizing multi-parameter objective functions. • A 45 kW turbine prepared for a small ORC CHP is shown. • Deterministic and hybrid methods of optimization are applied. • A wide range of variation of ORC turbine flowpath are investigated. • Performance maps for the best results are shown. • Turbine mechanical qualification is performed.

A comparative analysis of dynamic evaporator models for organic Rankine cycle waste heat recovery systems

As the Organic Rankine Cycle Waste Heat Recovery (ORC-WHR) gained research attention in recent years, the evaporator models are required in plant modeling and model-based controls. However, model comparison and selection works are lacking in ORC-WHR application. Different from the modeling work in literature, this paper aims to first time present a comparative study of three evaporator models for Organic Rankine Cycle Waste Heat Recovery (ORC-WHR) systems using the same set of identification parameters and experimental data. Finite volume model and moving boundary model are the most popular modeling methodologies in the field of ORC-WHR. Meanwhile, 0-D lumped models attract some research attention thanks to their low computational cost and least modeling effort. This paper first presents the three models, which are then validated with experiments data collected in a heavy-duty diesel engine ORC-WHR system. In the model comparison process, accuracy, computational cost and modeling effort are evaluated. All three models exhibit decent working fluid vapor temperature prediction accuracy with 6.6 K of mean error and 1.27% mean error percentage both in steady state and transient conditions. 0-D lumped model is found to be accurate enough for many application purposes, which is not found in literature. Based on the comparison results, model selection recommendation is given based on disparate application purposes and different phases of ORC-WHR system development.

Parametric optimization and performance analysis of a waste heat recovery system using Organic Rankine Cycle (ORC)

Organic Rankine Cycle (ORC) has been proven to be the most effective solution to utilize fully the waste heat energy produced from manufacturing and power plant. In this paper, thermodynamic analysis and performance optimization of an ORC waste heat recovery system is performed for an aircraft engine and R245-fa is chosen as the refrigerant. The main concern of this study is to maximize the total heat transfer rate through the evaporator, thus the optimization of the Thrust Specific Fuel Consumption (TSFC) and the Specific Thrust of the engine can be performed. The main parameter to conduct the optimization is Turbine Inlet Temperature (TIT) and preheating temperature of R245fa. From the analysis, by increasing the Turbine Inlet Temperature and the preheating temperature, the TSFC and Specific Thrust of the engine can be optimized.

Artificial neural network (ANN) based prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery

This paper presents performance prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery based on artificial neural network (ANN). An ANN based prediction model of the ORC system is established with consideration of mean squared error and correlation coefficient. A test bench of combined diesel engine and ORC waste heat recovery system is developed, and the experimental data used to train and test the proposed ANN model are collected. A genetic algorithm (GA) is also considered in this study to increase prediction accuracy, and the ANN model is evaluated with different learning rates, train functions and parameter settings. A prediction accuracy comparison of the ANN model with and without using GA is presented. The effects of seven key operating parameters on the power output of the ORC system are investigated. Finally, a performance prediction and parametric optimization for the ORC system are conducted based on the proposed ANN model. The results show that prediction error of the ANN model with using the GA is lower than that without using GA. Therefore, it is recommended to optimize the weights of the ANN model with GA for a high prediction accuracy. The proposed ANN model shows a strong learning ability and good generalization performance. Compared to the experimental data, the maximum relative error is less than 5%. The experimental results after optimizing the operating parameters are very close to ANN’s predictions, indicating one or more operating parameters can be adjusted to obtain a higher power output during the experiment process.

Modeling and optimal steady-state operating points of an ORC waste heat recovery system for diesel engines

Waste heat recovery (WHR) systems based on the Organic Rankine Cycle (ORC) are a promising method to reduce the fuel consumption of heavy-duty diesel engines. This article considers a setup with two parallel evaporators and a hydraulically closed low-pressure part. This gives additional degrees of freedom compared to a pressure balanced low-pressure part and thus allows to increase the recovering efficiency. However, these additional degrees of freedom lead to a higher system complexity, which complicates the calculation of power maximizing steady-state operating points. To determine these power maximizing steady-state operating points, this article develops a model based optimization strategy. For this task, models from the literature are extended and validated by test bench measurements. It is shown that the model has a high accuracy both in steady-state and dynamic operating situations. The optimal steady-state operating points of the considered WHR system are compared with other system topologies, utilizing, e.g., a pressure balanced low-pressure part or a single evaporator. The results of this paper can be utilized as the basis for designing optimal control strategies for the considered WHR system.

Iterative Approach for the Design of an Organic Rankine Cycle based on Thermodynamic Process Simulations and a Small-Scale Test Rig

Waste heat recovery from industrial processes may be a door opener for market penetration of Organic Rankine Cycle (ORC) systems. Within this study, an ORC for industrial waste heat recovery is designed by adopting an iterative approach. Therefore, experiments are performed in a thermal oil heated 1 kW test rig with internal recuperator and a maximum thermal efficiency of 10.6%. The results are iteratively implemented in thermodynamic process simulation. Thus, the simulation results of different stationary operating points can be compared to experimental measurements for different steps of the iterative design process. Results outline the importance of experimental results for the design of ORC systems. The simulation accuracy can be significantly improved with a single reimplementation of experimental data, which enables accurate sensitivity analysis on ORC waste heat recovery system performance. For two different representative operating points, the mean deviations between experiment and simulation decrease from 8.4% to 1.0% and 4.1% to 1.7% respectively, considering the enthalpy and pressure of all thermodynamic state points.

Radial Expander Design for an Engine Organic Rankine Cycle Waste Heat Recovery System

It is commonly accepted that waste heat recovery technologies are significant contenders in future powertrain thermal management to further minimize fuel consumption and CO2 emissions. Organic Rankine Cycle (ORC) systems are currently regarded as amongst the most potent candidates in recovering engine exhaust energy and converting it to electrical power. Crucial areas for the maximization of the efficiency of the ORC system are the appropriate selection of working fluid and the optimization of the expander design. In this study, a novel design methodology of a radial turbine expander for a heavy duty engine ORC waste heat recovery system is presented. The preliminary design of the radial turbine expander includes the development and utilization of an in-house 0/1D code that can be coupled with various organic fluids properties for the calculation of the basic expander geometry. The initial mean-line model for a 200kW-class Diesel engine application investigated produced a solution for a 20kW turbine with 73% isentropic efficiency. The preliminarily optimized expander geometry was used as an input in a detailed CFD code to further optimize rotor geometry. The rotor geometric optimization showed that by increasing exit tip radius by 10% and adopting a 54° back-swept blade design, the maximum isentropic efficiency achieved can exceed 83%.

Transient dynamic modeling and validation of an organic Rankine cycle waste heat recovery system for heavy duty diesel engine applications

This paper presents a dynamic organic Rankine cycle waste heat recovery (ORC-WHR) Simulink® model and an engine model for heavy-duty diesel applications. The dynamic, physics-based ORC-WHR system model includes parallel evaporators, flow control valves, a turbine expander, a reservoir, and pumps. The evaporator model contains an enhanced pressure drop model, which calculates pressure drop for each working fluid phase via a linear relation to the axial location inside each phase. The ORC-WHR component models parameters are identified over large range of steady state and transient experimental data, which are collected from an ORC-WHR system on a 13L heavy-duty diesel engine. The component models are integrated into an entire system model and the boundary conditions, inputs and outputs for the individual models are described. A GT-POWER® engine model and its transient validation is presented. The speed and torque profiles of a long-haul, constant speed variable-load heavy-duty cycle are processed through the engine model to produce the exhaust and recirculated exhaust gas transient conditions relevant for the ORC model. The ORC-WHR system then simulated over these highly transient engine conditions. Overall, this paper provides detailed guidelines for ORC-WHR system modeling, model calibration, and component models integration.

Investigation of waste heat recovery system at supercritical conditions with vehicle drive cycles

Waste heat recovery (WHR) for internal combustion engines in vehicles using Organic Rankine cycle (ORC) has been a promising technology. The operation of the ORC WHR system in supercritical conditions has a potential to generate more power output and thermal efficiency compared with the conventional subcritical conditions. However, in supercritical conditions, the heat transfer process in the evaporator, the key component of the ORC WHR system, becomes unpredictable as the thermo-physical properties of the working fluid change with the temperature. Furthermore, the transient heat source from the vehicle’s exhaust makes the operation of the WHR system difficult. We investigated the performance of the ORC WHR system at supercritical conditions with engine’s exhaust data from real city and highway drive cycles. The effects of operating variables, such as refrigerant flow rates, evaporator and condenser pressure, and evaporator outlet temperature, on the performance indicators of the WHR system in supercritical conditions were examined. Simulation of operating parameters and the boundary of the WHR system are also included in this paper.

Hybrid ORC Waste Heat Recovery System and Solar Thermal Plant in Ait Baha, Morocco

This paper presents the heat recovery system of a cement plant in Morocco. The particularity of the plant is that it utilizes a hybrid solution with an organic rankine cycle (ORC) turbogenerator. The heat used in the ORC unit to be transformed into electricity comes from both heat recovery from the cement production and from solar collectors through a thermal oil loop.

Effects of Degree of Superheat on the Running Performance of an Organic Rankine Cycle (ORC) Waste Heat Recovery System for Diesel Engines under Various Operating Conditions

This study analyzed the variation law of engine exhaust energy under various operating conditions to improve the thermal efficiency and fuel economy of diesel engines. An organic Rankine cycle (ORC) waste heat recovery system with internal heat exchanger (IHE) was designed to recover waste heat from the diesel engine exhaust. The zeotropic mixture R416A was used as the working fluid for the ORC. Three evaluation indexes were presented as follows: waste heat recovery efficiency (WHRE), engine thermal efficiency increasing ratio (ETEIR), and output energy density of working fluid (OEDWF). In terms of various operating conditions of the diesel engine, this study investigated the variation tendencies of the running performances of the ORC waste heat recovery system and the effects of the degree of superheat on the running performance of the ORC waste heat recovery system through theoretical calculations. The research findings showed that the net power output, WHRE, and ETEIR of the ORC waste heat recovery system reach their maxima when the degree of superheat is 40 K, engine speed is 2200 r/min, and engine torque is 1200 N·m. OEDWF gradually increases with the increase in the degree of superheat, which indicates that the required mass flow rate of R416A decreases for a certain net power output, thereby significantly decreasing the risk of environmental pollution.