Optimization Of Organic Rankine Cycle Research Articles

General integration method for system configuration of organic Rankine cycle based on stage-wise concept

Organic Rankine Cycle (ORC) integrated systems with heat sources consist of heat exchange processes and thermodynamic power conversion processes. Fully exploring feasible system configuration while considering fluid selection is crucial for enhancing ORC power generation and balancing economic costs. This study innovatively proposes a theoretical framework that decomposes the Rankine cycle into basic thermodynamic processes. The design of system configuration is regarded as the adjustment of the series-parallel relationships of these basic processes, aiming to achieve simultaneous optimization of the cycle structure and the HEN structure, thereby greatly expanded the search space for feasible ORC system configurations. The optimization problem is solved using a bi-level strategy, The outer layer determines the number of thermal power conversion components, operating parameters, and working fluid selection, then provides the associated stream information to the inner layer for optimizing the heat exchange scheme. Applying this method to two different case studies from the literature validated its effectiveness in optimizing scenarios with single and complex heat sources. The Pareto frontier obtained under the conditions of Case I indicates that the investment cost can be reduced by $33.04 k/yr while maintaining the same net power output. In exchange for an increase of $1.51 k/yr in investment cost, the maximum net power output can be improved by 124.74 kW. Under the conditions of Case II, the maximum net output power can increase by 9.71 %–52.5 %, and the Pareto frontier featuring outputs exceeding 50 kW is provided. By analyzing the relative positions of literature schemes and Pareto front within the solution space, the impact of system configuration improvements on the objective functions is explained. These results confirm the effectiveness of the proposed approach for designing optimal ORC energy recovery systems for heat sources. This contribution advances optimization methods for similar closed cycle configurations, which is significant for advancing the utilization of waste heat and addressing sustainability challenges.

Thermal-economic performance evaluation and bi-objective optimization of organic Rankine cycles using pure and mixed working fluids for waste heat recovery

To further enhance the recovery rate of low temperature waste heat, the low temperature flue gas in the sinter annular cooler is chosen as the heat source of organic Rankine cycle (ORC) system in the current study, and the system thermal-economic performance evaluation are conducted. The thermal-economic performance models of ORC system are established firstly, and the butane and isopentane are selected to constitute the mixed working fluid. Then the changes of system performance with the mass fraction of isopentane (MR601a) and ORC crucial parameters are evaluated comprehensively, and the bi-objective optimization is applied to ascertain the optimal ORC crucial parameters under various MR601a. The results indicate that the MR601a of 0.6 can obtain the maximum glide temperature. The higher the evaporating temperature is, and the lower the condensing temperature is, the larger the exergy efficiency is, while the smaller the levelized energy cost is. There is an optimal superheat degree to make the ORC system achieve the better overall performance under various MR601a. The exergy efficiency of butane is the maximum with a respectable waste heat recovery rate of 64.18 %, while the levelized energy cost of isopentane in the whole conditions is the minimum with the better economic performance.

Fast robust optimization of ORC based on an artificial neural network for waste heat recovery

Uncertainty in the organic Rankine cycle (ORC) system and the highly complex ORC models pose challenges to optimal operation. A data-driven robust parametric optimization for the ORC system is proposed to ensure high and stable performance under uncertainty. The uncertainty of the cyclic variables is estimated by their distribution parameters, and the average (expected) thermodynamic performance (the net output power of the ORC) is maximized as the optimization objective while minimizing its variance. An artificial neural network with the rectified linear unit is used as a surrogate model for optimization. Then the robust parametric optimization problem can be transformed into a mixed-integer linear optimization problem with a chance-constrained form, and the robust optimal solution can be solved quickly. Case studies show that the solution time of the robust optimization problem using the proposed method is about 1.4 s, which is much less than obtaining the optimal solution based on ORC mechanism models. Meanwhile, the optimal operating condition derived by the proposed robust optimization approach outperforms that obtained by the traditional deterministic strategy. The proposed approach not only improves the robustness of the system but also demonstrates the importance of considering uncertainty in parametric optimization.

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and eco-friendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWhth. The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R2) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kWe capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. This study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

A novel TLFD-GA algorithm for multi-objectives optimization of ORC power plants with the effect of pressure drop considered

This research introduces a novel TLFD-GA algorithm for the three-level criteria optimization of organic Rankine cycle (ORC) power plants. It replaces the non-dominated sorting of NSGA-II with three-level fuzzy decision to simultaneously optimize environmental, thermodynamic, and techno-economic criteria. The algorithm provides direct optimization results without needing additional decision-making methods. Furthermore, the impact of pressure drop in plate heat exchangers is investigated, revealing a proportional relationship between pressure drop and the increment of evaporation pressure. A parametric study on 24 basic and recuperative trans-critical geothermal ORC systems indicates that compensating for pressure drop leads to a 5% decrease in thermodynamic performance, a 20% decrease in techno-economic performance, and a 20–60% increase in heat transfer area per net output power. After TLFD-GA optimization, the saving to investment ratio improves by an average of 4.5% across scenarios. R1270 stands out with a remarkable ratio of 3.13 and 4.32 in medium and high-temperature geothermal reservoirs. Moreover, the proposed TLFD-GA optimization algorithm has demonstrated its superiority in terms of superb convergence and stability when compared to NSGA-II, which suggests its prospective application in the low-carbon and green energy fields.

Thermo-economic assessment and multi-objective optimization of organic Rankine cycle driven by solar energy and waste heat

An organic Rankine cycle (ORC) power generation system driven by integrated solar energy and waste heat is proposed based on the concept of multi-energy complementarity. Three types of solar collectors, two different heat source integration schemes and nine different candidate organic fluids are studied and compared. The effects of main operating parameters on thermo-economic performance are analyzed. A multi-objective optimization framework with a competitive mechanism based multi-objective particle swarm optimizer (CMOPSO) as the core is constructed and the system is optimized. The results of the multi-objective optimization guide the design of the multi-heat source ORC and the selection of the working fluid. When the temperature difference between two heat sources is greater than 50 °C, the heat exchangers are recommended to be connected in series for better overall performance. Besides, the series scheme favors the working fluid with a higher critical temperature, whereas the working fluid with a lower critical temperature is appropriate for the parallel scheme.

Performance analysis and multi-objective optimization of organic Rankine cycle for low-grade sinter waste heat recovery

In order to enhance the sinter waste heat recovery (WHR) rate efficiently, the organic Rankine cycle (ORC) for power production was applied to take the low-grade sinter cooling flue gas (SCFG) expelled from the waste heat boiler as the heat source. The system thermodynamic, thermo-economic and multi-objective optimization models were constructed firstly, and then R245fa was chosen as the ORC working fluid. Furthermore, the variations of system thermodynamic and thermo-economic performances with the ORC thermal parameters under different inlet temperatures of SCFG were analyzed in detail, and the ideal parameter combination was established through the multi-objective optimization approach. The results show that, the optimal inlet temperature of SCFG is determined to be 160 °C, and under the aforementioned condition of inlet temperature of SCFG, the optimal ORC thermal parameters are determined to be 95 °C for the working fluid evaporation temperature, 10 °C for the working fluid superheat degree, 28 °C for the working fluid condensation temperature and 9 °C for the pinch-point temperature difference in evaporator by considering the system thermodynamic and thermo-economic performances comprehensively. Meanwhile, the WHR rate of SCFG under the above ORC parameter combination could reach 64.86 %, showing remarkable energy-saving effect.

A study of the optimal conditions for organic Rankine cycles coupled with vapour compression refrigeration using a rigorous approach based on the Helmholtz energy function

VCR-ORC systems combine an organic Rankine cycle (ORC) to produce energy from low-moderate temperature sources and a standard refrigeration cycle (VCRC). Accurate objective functions for the optimal performance of the system are developed based on the Helmholtz energy function and its derivatives. Moreover, the utility of two objective functions is analysed in the search for the optimal conditions of a VCR-ORC system. Finally, it presents a comparative analysis of several working fluids to give the directives in selecting an optimal working fluid and its operation optimal conditions. The method described above uses a set of refrigerants and the PC-SAFT EOS as the prediction model. The results presented in this work show that variables such as the condenser temperature, T1, are fundamental for the optimisation of VCR-ORC systems. Pentane and R1233zd have the best performance for this system. However, the fourth-generation refrigerant shows the best operational condition in all the indicators among the studied fluids despite its wet expansion in optimal operation. In the idealised VCR-ORC cycle, the optimal ORC efficiency links with the optimal COP of the cycle while the extracted heat links with the optimal mechanical work produced by the ORC.

Optimization and exergy analysis of a cascade organic Rankine cycle integrated with liquefied natural gas regasification process

One of the most efficient methods of exergy recovery during the regasification process is integrating the LNG stream with an Organic Rankine Cycle (ORC) to generate electricity. This study employs a cascade structure of ORC consisting of two double-stage condensations operating at 6 bar regasification pressure. To obtain an optimal ORC system integrated with an LNG, three optimization levels for a specific heat source are addressed, including process variables, working fluids, and structure. Ten process variables and two working fluid variables for the top and bottom cycle among 13 candidates of refrigerants were optimized to provide the maximum power output. The results determined that refrigerants of R41 and R1150 have the best performance in the optimized process conditions for the top and bottom cycles, respectively. For the regasification of 36 tonnes per hour of an LNG stream, the produced net power and the exergy efficiency are achieved by 2116.76 kW and 0.29, respectively. The exergy analysis revealed that employing the double-stage condenser ORC is not a good choice. Accordingly, a cascade-parallel structure is proposed for further studies.

Ensemble learning-based nonlinear time series prediction and dynamic multi-objective optimization of organic rankine cycle (ORC) under actual driving cycle

Complicated road conditions make organic Rankine cycle (ORC) operation characteristics show hysteresis and uncertainty. Under the strong coupling correlation of many operating parameters, how to realize the dynamic optimization of ORC comprehensive performance is the key to obtain practical application potential. Based on ensemble learning mechanism, neural network modeling, ensemble system, unsupervised learning, partial mutual information and optimization algorithm are integrated. This paper presents a nonlinear time series prediction and dynamic multi-objective optimization scheme. The average accuracy increased by at least 59.6%. Taking the thermodynamic performance and environmental impact as optimization objectives, dynamic multi-objective optimization is carried out under road conditions. The optimization scheme can effectively trade off the nonlinear correlation between thermal efficiency and emissions of CO2 equivalent.

Information theory-based dynamic feature capture and global multi-objective optimization approach for organic Rankine cycle (ORC) considering road environment

Efficient capture and global optimization of organic Rankine cycle (ORC) operating features in road environment is the key to obtain actual waste heat recovery potential. The complexity of time-varying characteristics intensifies the nonlinear coupling relationship between ORC performance and parameters. This paper first designs and builds an ORC experimental system for recovering waste heat from internal combustion engine (ICE). The experimental system includes ICE and its measurement subsystem, ORC subsystem, expander lubrication subsystem, cooling subsystem, and ORC measurement subsystem. R245fa is used as working fluid; The expander adopts a specially designed single screw expander. The performance of ORC waste heat recovery is tested by adjusting the operating conditions of the ICE, expander, pump, and valve opening. The temperature range of waste heat is 627–686 K. Subsequently, a dynamic feature capture and global multi-objective optimization approach for ORC is proposed. The results show that the precision of dynamic feature capture can be improved at least 41.78% with the introduction of information theory in complex environment. Frequent fluctuation of vehicle speed is not conducive to the improvement of evaporator inlet temperature at working fluid side. As the speed of the vehicle is greatly reduced, the evaporator inlet temperature drops sharply. The frequent fluctuation of speed will intensify the nonlinear correlation between operating parameters and system performance and make the system performance more dependent on the coupling correlation between operating parameters. The approach proposed in this paper can provide a new idea for efficient capture of dynamic characteristics and global multi-objective optimization of ORC in road environment.

Analysis of the Maximum Efficiency and the Maximum Net Power as Objective Functions for Organic Rankine Cycles Optimization.

Maximum efficiency and maximum net power output are some of the most important goals to reach the optimal conditions of organic Rankine cycles. This work compares two objective functions, the maximum efficiency function, β, and the maximum net power output function, ω. The van der Waals and PC-SAFT equations of state are used to calculate the qualitative and quantitative behavior, respectively. The analysis is performed for a set of eight working fluids, considering hydrocarbons and fourth-generation refrigerants. The results show that the two objective functions and the maximum entropy point are excellent references for describing the optimal organic Rankine cycle conditions. These references enable attaining a zone where the optimal operating conditions of an organic Rankine cycle can be found for any working fluid. This zone corresponds to a temperature range determined by the boiler outlet temperature obtained by the maximum efficiency function, maximum net power output function, and maximum entropy point. This zone is named the optimal temperature range of the boiler in this work.

Off-design condition optimization of organic Rankine cycle based on genetic algorithm

Organic Rankine cycle (ORC) has been considered as one of the most promising technologies in industrial waste heat utilization and power generation. During the actual operation of ORC system, due to the fluctuation of cooling and heat sources, the system operates under off-design conditions in most cases. In this paper, thermodynamic model, heat transfer process description and power equipment model are established to evaluate the operating parameters of ORC for the off-design conditions. Evaporation temperature and condensation temperature are taken as independent parameters for the operation of ORC system. Genetic algorithm is adopted to optimize the independent parameters under the maximum net output power. The results show that the effect of optimizing independent parameters is to make the working fluid at the outlet of the preheater as close as possible to a saturated liquid state, and the working fluid at the inlet of the screw expander should be in a saturated gas state. With the optimal power output increasing by 19.1% for every 5 °C increase in hot water inlet temperature, 9.2% for every 20 kg/s increase in hot water mass flow rate, and 3.9% for every 1 °C decrease in cooling water temperature. The optimization method of off-design operating conditions has good system performance and good engineering application prospects.

Comparative Assessment of sCO2 Cycles, Optimal ORC, and Thermoelectric Generators for Exhaust Waste Heat Recovery Applications from Heavy-Duty Diesel Engines

This study aimed to investigate the potential of supercritical carbon dioxide (sCO2), organic Rankine cycle (ORC), and thermoelectric generator (TEG) systems for application in automotive exhaust waste heat recovery (WHR) applications. More specifically, this paper focuses on heavy-duty diesel engines applications such as marine, trucks, and locomotives. The results of the simulations show that sCO2 systems are capable of recovering the highest amount of power from exhaust gases, followed by ORC systems. The sCO2 system recovered 19.5 kW at the point of maximum brake power and 10.1 kW at the point of maximum torque. Similarly, the ORC system recovered 14.7 kW at the point of maximum brake power and 7.9 kW at the point of maximum torque. Furthermore, at a point of low power and torque, the sCO2 system recovered 4.2 kW of power and the ORC system recovered 3.3 kW. The TEG system produced significantly less power (533 W at maximum brake power, 126 W at maximum torque, and 7 W at low power and torque) at all three points of interest due to the low system efficiency in comparison to sCO2 and ORC systems. From the results, it can be concluded that sCO2 and ORC systems have the biggest potential impact in exhaust WHR applications provided the availability of heat and that their level of complexity does not become prohibitive.

Thermo-economic optimization of organic Rankine cycle with steam-water dual heat source

Dual-loop ORC (D-ORC) and single-loop ORC (S-ORC) systems can be employed to steam-water waste heat recovery. The maximum net output power and minimum electricity production cost (EPC) are considered as optimization objectives. To optimize the thermo-economic performance and obtain the Pareto front, non-dominated sorting genetic algorithm-II is employed, and the decision is made by TOPSIS and entropy weight method (EWM). The results show that the EPC of the S-ORC system is lower than that of the D-ORC system under any heat source condition. However, the net output power of the S-ORC system exceeds that of the D-ORC system when the steam mass flow rate and hot water inlet temperature are 10 kg/s and 110 °C, respectively. When the steam mass flow rate or the hot water inlet temperature is higher, the S-ORC system has more distinct advantages in terms of thermo-economic performance. When the working fluid at the outlet of hot water preheater of the S-ORC system is in a two-phase state, the optimal steam outlet pressure is invariably the lowest for operation, and cost can be reduced by removing the steam preheater. In the D-ORC system, the optimal steam outlet pressure is consistently the lowest allowable pressure.

Optimisation of organic Rankine cycle driven by waste heat recovery

The motivation for the present work is to design and develop an alternate power-producing cycle driven through a source of waste heat. In this research article, thermodynamic investigation has been done for waste heat-driven Organic Rankine cycle in MATLAB (2018a) software. Moreover, multi-objective optimisation and prediction analysis is done by Response Surface Methodology (RSM) and Artificial Intelligence (AI) respectively. The best performances of the organic Rankine cycle (ORC) system are achieved by 0.940 of the desirability function reflecting 38.2% of the exergetic efficiency, and 0.035 of the expander size parameter. The outcome of the present study is to set up such environment-friendly power generation techniques for the same capacity in the cement and steel industry.

Design and Optimization of Organic Rankine Cycle Based on Heat Transfer Enhancement and Novel Heat Exchanger: A Review

The effective exploitation of renewable energy and the recovery of waste heat are two crucial strategies in achieving carbon neutrality. As an efficient and reliable heat–to–power conversion technology, the organic Rankine cycle (ORC) has been recognized and accepted by academia and industry for use in solar energy, geothermal energy, biomass energy, and waste heat applications. However, there remain unsolved technical challenges related to the design and operation of the components and system. As the exergy destruction and investment cost of heat exchangers exert significant influence on the performance of ORC, investigations on the performance improvement of heat exchangers are of great significance. The aim of this paper was to provide a review on the performance improvement of ORC in relation to heat transfer enhancement, heat exchanger design optimization, and cycle construction based on a novel heat exchanger. The performance of ORC using different types of heat exchangers was discussed and the importance of revealing the influence of heat exchanger structural parameters on ORC performance was assessed. The heat transfer enhancement, novel heat exchanger investigation, and the ORC configuration development based on a novel heat exchanger were emphasized. Finally, developments and current challenges were summarized and future research trends were also identified.

Optimal coupling design for organic Rankine cycle and radial turbine rotor using CFD modeling, machine learning and genetic algorithm

The organic Rankine cycle (ORC) as a potential technology can be used to recover low-grade waste heat. This study provides a rapid and systematic methodology to design ORC system coupling with the radial turbine rotor. Firstly, the coupled model of ORC and the radial turbine is established, and the thermodynamic and economic performance is obtained to optimize the preliminary design parameters. Then, the CFD analysis for the turbine rotor is performed to generate the databases, and the machine learning algorithms (random forest, XGBoost, decision tree, and support vector machine) are used to train the surrogate models. And finally, the optimal shape of the meridional surface is obtained to improve ORC’ power output. The results indicated that the system net power output and the cost rate at the decision point achieved 393.06 kW and 13.59 $/h, respectively. The support vector machine exhibited the highest value of R2 (coefficient of determination) among the regression algorithms. The optimized results showed a more uniform pressure distribution is founding on the suction surface of the optimized structure compared with the basic structure’s, leading to the power output was increased by 7.5 %. The findings can provide references for the rapid coupling design and optimization of ORC and the turbine.

Effect of cooling water flow on heat transfer performance of horizontal tube spray falling film evaporator in ORC system

Organic Rankine cycle (ORC) uses low-temperature heat source to realize thermoelectric conversion, which is an important way to realize the effective recovery and utilization of waste heat. Based on the horizontal tube spray falling film evaporator, an orc power generation system with R245fa as the circulating working medium is built to study the influence of the change of cooling water flow on the heat transfer performance of the evaporator. The results show that under the condition of constant heat source temperature, the evaporation pressure and condensation pressure first decrease and then increase with the increase of cooling water flow, while the total heat transfer coefficient outside the evaporator tube first increases and then decreases. When the cooling water flow is greater than 3100 L/h, it has little effect on the heat exchange system of the evaporator, and it is more appropriate to keep the cooling water flow at about 3100 L/h. By studying the influence of cooling water flow on the heat transfer performance of evaporator, an important experimental basis is provided for the design and optimization of ORC cooling system.

Dynamic modeling and optimization of organic Rankine cycle in the waste heat recovery of the hydraulic system

The replacement of cooling system with the organic Rankine cycle could reduce cooling energy consumption and improve the overall energy efficiency in the hydraulic system. However, dynamic characteristics have a significant impact on stable operating and performance improvement of ORC systems in applications. Therefore, based on the physical prototype, the ORC dynamic model with whole process, including start-stop process, was established and calibration. Then the dynamic characteristics of the system were studied, and the response surface method was used to optimize the operating parameters with the dynamic model. The results show that the simulation model has sufficient accuracy under both steady and transient conditions. Compared with the oil flowrate, the connected-load affects the system performance more obvious. The evaporating pressure has increased by 3.4% as the connected-load increases from 60 W to 120 W. As to the response time of evaporating pressure and evaporator outlet temperature, they are 240 s and 290 s respectively in the starting stage, and are 210 s and 190 s respectively in the stopping stage. Through the optimization, the output power of the ORC system could reach the maximum value of 832 W, when the working medium pump and expander speed are 1500 rpm and 1400 rpm, respectively. The dynamic fluctuation of oil flowrate has relatively little influence on ORC system, it can work stably in the waste heat recovery of hydraulic system, and the operation and control should consider the long response time of ORC starting and stopping process.