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Organic Rankine cycle (ORC) is a promising thermal-to-power conversion technology utilizing low enthalpy renewable resources or waste heat energy. The coupling of environmental impact analysis and thermo-economic optimization is effective in evaluating and improving the comprehensive performance of the ORC. In the present study, a thermo-economic-environmental analysis and optimization methodology is proposed for the design of a waste heat driven ORC. A multi-objective mathematical programming model integrating the environmental impact and thermo-economic performance is formulated for the simultaneous optimization of the component configurations and operation parameters for a waste heat driven ORC. The objective functions include the minimization of the environmental impact and the maximization of the net power output. The specific investment cost is used to evaluate the economic performance of the ORC. A previous developed solution strategy is applied to solve the single objective optimization problem and the ε -constrained method is applied to solve the multi-objective optimization model. A case study is elaborated to test the proposed methodology and the formulated model. The single objective optimization results demonstrate the contradiction between the environmental objective and the thermo-economic objective. The trade-off solutions are achieved by multi-objective optimization. The Pareto-frontier is elaborated to show how the material allocation, component configuration, and operation parameters are influenced by the objective functions. Finally, a sensitivity analysis of the life cycle inventory of raw materials on the optimization results is conducted. [ABSTRACT FROM AUTHOR]

The organic Rankine cycle (ORC) has been regarded as one of the most potential technologies for converting low-grade heat into power. In the past decades, the design and operation optimization of ORC has undergone investigation, and most approaches use a sequential or step-by-step approach by separating the off-design operation from the system design and typically lose solution optimality. The current study proposes a simultaneous optimization of the design and off-design operation for a waste heat-driven ORC. The detailed component configuration models for the heat exchangers are developed. A multi-period optimization model is developed to synchronously obtain the configurations of components and scheme of off-design operation that minimizes the annual average electricity production cost. A case study validates the superiority of the proposed multi-period optimization method over a two-step optimization. The ORC obtained using multi-period simultaneous optimization method features 5.7%–16.6% lower average electricity production cost than those achieved with the conventional two-step method. • A simultaneous design and operation optimization method for ORC is proposed. • A multi-period optimization model is developed to minimize the AEPC of the ORC. • The influence of rated design condition on the ORC life-span performance is revealed. • The superiority of the proposed method over conventional two-step method is verified. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-objective optimization for balanced SCBC coal-fired power systems design. • Waste heat recovery enhances energetic, economic, and environmental performance. • SCBC-ARC design achieves highest efficiency and lowest environmental impact. • SCBC-ORC design achieves lowest levelized cost of electricity. • Turbomachinery improvement benefits efficiency and environmental performance. The efficiency of supercritical CO 2 (sCO 2) Brayton cycle (SCBC) based coal-fired power generation can be enhanced by harnessing the waste heat from sCO 2 cooling and flue gas, which currently remains largely untapped. In this paper, we propose two types of design roadmap for utilizing this waste heat. The first method involves using an organic Rankine cycle (ORC) to generate additional power, while the second method utilizes LiBr/H 2 O absorption refrigeration cycle (ARC) to further cool down compressor inlet sCO 2 , and thereby reduces its compression power consumption. An energy-economic-environmental multi-criteria models are formulated to access performance of the aforementioned designs and compare them with a standalone sCO 2 Brayton recompression cycle system (Standalone). The non-dominated sorting genetic algorithm II is applied to carry out the multi-objective optimization of the three systems. The results show that the SCBC-ARC system achieves the maximum thermal efficiency (η th) and minimum environmental impact load (EIL), while SCBC-ORC system achieves the minimum levelized cost of electricity (LCOE). We also find that minimizing LCOE conflicts with maximizing η th and minimizing EIL , respectively. The relationship between maximizing η th and minimizing EIL is consistent, suggesting that increasing efficiency will alleviate environmental impact of the systems. We also identify and discuss balanced designs for the systems, and our results show that the η th of SCBC-ORC and SCBC-ARC is 1.40% and 1.70% higher than the Standalone, respectively, the LCOE is 0.56% lower and 3.66% higher than Standalone, respectively, and EIL is 1.16% and 1.59% lower than the Standalone, respectively. [ABSTRACT FROM AUTHOR]

Membrane distillation (MD) is an emerging desalination technology powered by low-grade thermal energy. This paper presents the multi-objective optimal design of the membrane distillation desalination plant. The heat sources are supercritical CO 2 (sCO 2) Brayton cycle waste heat and geothermal energy. Multi-objective mixed-integer nonlinear programming models are developed to optimize the integrated systems' design and operating conditions based on economic and environmental metrics. The models consider the simultaneous optimization of water production costs (wpc) and environmental impacts (wpei). The environmental performance is quantified through a life cycle assessment using the widely used ReCiPe 2016 method, enabling the identification of the main environmental hotspots throughout the plant's life cycle. Our methodology demonstrates the sustainability of MD desalination plants through various case studies. The results indicate that an appropriate MD system design can significantly reduce the environmental burden with a slight increase in cost. For the sCO 2 -MD scenario, a cost-effective design can achieve a minimum wpc of 0.758 $/m3 and a minimum wpei of 0.172 Pt/m3 in an environmentally friendly design. A balanced design can reduce the environmental impact by 31.30% with a slight cost increase of 4.48% compared to a cost-effective design. The minimum wpc and minimum wpei for the geothermal MD (GTMD) scenario are 412.27% and 215.94% higher, respectively, compared to the sCO 2 -MD scenario. Moreover, reducing the wpei of the GTMD system is also more expensive, requiring a 10.67% increase in cost to reduce the environmental impact by 21.65%. [Display omitted] • A multi-objective optimization framework for membrane distillation system. • Economic and environmental impact are conflicting objectives. • Waste heat is a more economical and eco-friendly heat source than geothermal energy. • Maintaining moderate yield and recovery rate is beneficial for balanced design. [ABSTRACT FROM AUTHOR]

Superstructure-based mixed integer nonlinear programming framework for hybrid heat sources driven organic Rankine cycles optimization is addressed. [Display omitted] • Simultaneous optimization for hybrid heat sources-ORC integration. • Superstructure model to identify optimal match of working fluid and heat sources. • Tailored multi-step algorithm for global optimization of large size design problems. • Case studies show SWHORCs generally outperform SWPORCs in NPO and efficiency. • Toluene-SWHORC achieves the highest efficiency of 19.73% for waste heat at 473.15 K. Organic Rankine cycle (ORC) is a promising technology capable of harnessing low-grade energy, e.g. renewable energy and waste heat, and converting it into electricity. Conventional ORC often operates with single heat source, which can be unfavorable to its efficiency due to the poor matching between its working fluid and heat source. Implementing hybrid heat sources is generally more energy-efficient as multiple heat sources can effectively match with the working fluid, however, the design can be a challenging task. This study proposes a superstructure-based method for the ORC design that simultaneously synthesizes heat exchanger network for hybrid heat sources and working fluid, and optimizes the ORC and heat sources' parameters. A mixed-integer nonlinear programming model is formulated to achieve the simultaneous optimization. We also develop a tailored multi-step initialization algorithm to facilitate the optimization. The model is applied to the design and analysis of ORCs driven by solar energy and waste heat with four different working fluids. Results demonstrate that the hybrid heat source-driven ORC improves the system performance. Cyclohexane is found to be the optimal working fluid for the proposed ORC system with a 48.19% increase in net power output compared with the single heat source-driven ORCs running separately. [ABSTRACT FROM AUTHOR]

Membrane distillation is an emerging desalination technology using low-grade heat for sustainable water production. This paper proposes a novel integrated design of direct-contact membrane distillation process and a closed supercritical CO 2 Brayton cycle for water cogeneration. The membrane distillation uses the waste heat rejected by the Brayton cycle for seawater desalination without consuming high grade energy, as compared to the cogeneration with reverse osmosis. The design includes a "split flow" coupling of Brayton cycle's cooling water to fully utilize the temperature gradient of the waste heat for membrane distillation. A mathematical model is also developed to evaluate and optimize the thermo-economic performance of the systems. The proposed integrated design is applied to a 50 MWe supercritical CO 2 recompression Brayton cycle power plant combined with membrane distillation to demonstrate its efficacy. Results show that the proposed design can achieve a levelized water production cost of 1.39 $/m3 with a water production capacity of 2.06 × 105 m3/year, outperforming the design without the "split flow". [Display omitted] • A novel integrated design of MD-sCO 2 Brayton cycle system for water cogeneration. • Exploitation of waste heat temperature gradient without adding load on power cycle. • 1.39 $/m3 of water desalination cost is achieved for the optimal design. • Up to 2.40 × 105 m3/year of water can be produced for a 50 MWe sCO 2 Brayton cycle. [ABSTRACT FROM AUTHOR]

• Novel combined SCBC-ORC design for 50 MWe coal-fired power plant. • High level of detail design and optimization achieved by ANN-based grey-box model. • Tailored root-finding algorithm and GA for optimization. • Thermodynamic analysis shows 6.42% increase in system thermal efficiency. Supercritical CO 2 (sCO 2) Brayton cycle is a promising technology for coal-fired power generation with high efficiency and compact equipment size. However, its sophisticated construct and high-temperature waste heat rejection require a systematic design to maximize its performance. Herein, we develop a combined sCO 2 Brayton cycle-organic Rankine cycle (ORC) design for coal-fired power plant. A novel glass-box model that considers the specific designs of sCO 2 boiler, recuperators, coolers, and turbomachinery is formulated to optimize the power plant. A high-accuracy artificial neural network model is also developed to estimate the system's pressure drop to reduce model complexity. As a result, the glass-box model is reformulated into a grey-box model. The model is applied to three different combined cycles' design problem to evaluate their performance. Result shows that the grey-box model saves more than 50% of CPU time. With the turbine inlet at 620 °C/25 MPa and the main compressor inlet at 35 °C/7.38 MPa, the proposed combined cycle reaches a thermal efficiency of 45.73%, thereby achieving a 2.75 percentage point improvement compared with the standalone design. Sensitivity analysis is also carried out to evaluate the effects of ORC working fluid, flue gas temperature at the cooling wall outlet, main compressor inlet pressure, and evaporating temperature of ORC, on the system's performance. [ABSTRACT FROM AUTHOR]

Hydrogen fuel cell vehicles pave a promising technological pathway to achieve carbon neutrality. Conventional electric air-conditioning greatly increases hydrogen consumption and thus reduces the driving range. To recover waste heat for vehicle air-conditioning, this study proposes an integrated proton exchange membrane fuel cell (PEMFC) and microchannel membrane-based absorption cooling (MMAC) system. Using a validated model, the PEMFC-MMAC system is characterized under different vital parameters. The PEMFC parameters affect the performance of both PEMFC and MMAC. The coupled performance of the PEMFC-MMAC system increases under a higher operating temperature, a higher operating pressure, or a higher doping level. The MMAC parameters mainly affect the performance of MMAC. The coupled performance of the PEMFC-MMAC system increases under a lower microchannel width or a lower microchannel height. In the covered PEMFC and MMAC parameter ranges, the combined energy efficiencies are improved by 202–273% while the equivalent power efficiencies are improved by 11.4–14.8% with heat recovery. The cooling-to-electrical ratio is 2.02–2.73, the cooling capacity per volume is 129.4–345.9 kW/m3, while the cooling capacity per mass is 0.0439–0.1132 kW/kg. Compared to the existing falling-film absorption cooling technology, the MMAC improves the compactness by 165.1%, reduces the weight by 51.3%, and enhances the COP by 2.6%. This study can facilitate the development of highly-compact, light-weight, energy-efficient, and zero-GWP technology for waste-driven air-conditioning in hydrogen vehicles. • Novel microchannel membrane-based absorption cooling is proposed for PEMFC vehicles. • Performance is characterized under different fuel cell and microchannel parameters. • Equivalent power efficiency is improved by 11.4∼14.8% with waste airconditioning. • Cooling-to-electrical ratio of 2.73 and volumetric cooling capacity of 345.9 kW/m3. • Compactness increased by 165.1%, weight reduced by 51.3%, and COP increased by 2.6%. [ABSTRACT FROM AUTHOR]

This paper addresses the simultaneous optimization of a novel combined supercritical CO 2 Brayton cycle-organic Rankine cycle integrated with molten salt solar power tower plant. The supercritical CO 2 Brayton cycle adopts a two-stage compression intercooling design. The organic Rankine cycle is added as a bottoming cycle to recover the waste heat of the Brayton cycle to generate extra power. Due to its complexity, the integrated system involves many degrees of freedom, which make it challenging to optimize using metaheuristic methods. To tackle this issue, we develop an equation-based model that simultaneously optimizes stream thermodynamic properties and flowsheet mass/heat equilibrium of the integrated system. The problem is formulated as a nonlinear programming model, and a tailored two-step solution strategy is developed to improve its solution efficiency. Several numerical studies are carried out to demonstrate the effectiveness of the proposed optimization method, as well as the efficiency of the integrated system. Solution time of the model is less than 224 CPU seconds. Results show that the method obtains an increase up to 3.6% in thermal efficiency compared with literature results; the optimal intercooling design increases net power output by 2.7% comparing with recompression cycle; the recompression cycle-organic Rankine cycle design obtains a 3.5% increase; and the combined intercooling cycle-organic Rankine cycle design achieves a total 4.4% increase. • A novel concentrated solar power-sCO 2 Brayton cycle-ORC integrated system is proposed. • An NLP model is formulated for simultaneous optimization of the integrated system. • High accuracy thermodynamics module is embedded to estimate physical properties. • Four types of system design are optimized and compared for energy performance. [ABSTRACT FROM AUTHOR]

• A novel method is proposed for the PP locating and optimization of CO 2 cycle. • A multi-objective NLP model incorporating rigorous equation of state is developed. • Case study is elaborated to demonstrate the effectiveness of the proposed methodology. • Sensitivity analysis of key parameters on PP and optimization results is conducted. CO 2 power cycle is one of the promising sustainable technologies that generate power from fossil fuel, nuclear, solar, and various waste heat energy. The heat transfer process plays a key role in influencing the thermodynamic or thermo-economic performance of CO 2 power cycle. The drastic variation of CO 2 thermo-physical properties results in great difficulty in modeling and optimizing the heat exchangers and CO 2 cycle configurations. In the present study, a mathematical programming method is proposed for the simulation and optimization of simple, regenerative, and recompression super-critical CO 2 power systems. An accurate equation of state is applied to calculate CO 2 properties, thereby enabling the performance indicator a continuous function of system parameters. A multi-objective non-linear programming model is formulated in GAMS for the automatic heat exchange pinch locating and system optimization. The simulation and optimization models are validated by comparison with REFPROP-based method. The maximum and average simulation errors are 0.064% and 0.015%. The thermal efficiency values achieved using the developed optimization method are improved by 6.14–10.85% compared with previous solutions. Then, a case study of a 573.15 K waste heat driven super-critical CO 2 power system optimization is elaborated. Results show that pinch locating of all heat exchangers and system optimization can be simultaneously conducted within a short time. The solution optimality is validated by comparing the traditional pinch assignment concept and optimization method. Sensitivity analyses of heat source inlet temperature and heat sink temperature rise are also conducted. For both objectives of maximizing thermal efficiency and net power output, the recompression super-critical CO 2 cycle features highest in thermal efficiency and the regenerative super-critical CO 2 cycle features highest in net power output. Finally, a multi-objective optimization is conducted to achieve the Pareto Front for the studied three super-critical CO 2 power systems. [ABSTRACT FROM AUTHOR]