Maximum Net Output Research Articles

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.

Multi-criteria assessment of a new energy-saving and environmentally-friendly scheme for natural gas-fired power plants

Recently, natural gas-fired power plants have received wide attention for their environmental advantages. However, high-temperature waste gas causes a quantity of heat loss, and a large amount of carbon dioxide emissions exacerbate the greenhouse effect. In order to efficiently utilize the waste heat of flue gas and reduce the carbon dioxide emissions from power plants, a cascade system which combines waste heat recovery technologies, including the supercritical carbon dioxide (SCO2) cycle and trilateral organic cycle (TOC), with carbon dioxide capture device is proposed. After validating the accuracy of thermodynamic model, the optimum working fluid for the trilateral organic cycle is selected and some main factors affecting the thermodynamic performance are analyzed in detail. Finally, to test the feasibility of the design, this paper optimizes the economy performance of the cascade system and the amount of captured CO2. The results show that the maximum net output power, carbon dioxide capture and payback period of the system are 157.1 MW, 96.49 ton/h and 4.125 years. Moreover, compared with original power plant design, the net plant efficiency of the cascade system has a significantly increasing of 23.6%. Hence, the new scheme proposed in this paper is a feasible method to achieve the aim of energy conservation and emission reduction.

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.

Experimental investigation and machine learning optimization of a small-scale organic Rankine cycle

The system behaviors of a small-scale organic Rankine cycle (ORC) system using a scroll expander under various operating conditions, as well as the machine learning optimization based on back propagation artificial neural network (BPANN), are investigated in this study. The effects of pump outlet pressure, expander inlet temperature and mass flow rate on net power output and thermal efficiency are examined experimentally. A BP-ORC neural network model is constructed, and the prediction accuracy is analyzed by the errors between the experiment and predicted data. The effects of eight operating parameters on system performance are discussed. The bi-objective optimization for maximum net output power and maximum thermal efficiency is addressed. Results indicate that as the mass flow rate increases, the net power output presents an increase trend, whereas the thermal efficiency yields a smooth tendency. The absolute error in the net power output from the BP-ORC model is between −0.05 kW and 0.05 kW, while that in the thermal efficiency is between −8 × 10-5 and 8 × 10-5. The Pareto-optimal solution of thermal efficiency is 9.32 % and the net output power is 2.42 kW.

Optimization design and analysis of a novel total flow and Kalina cycle coupled system driven on low-medium temperature geothermal source with two-phase mixture

A novel total flow and Kalina cycle coupled system has been proposed to utilize the geothermal energy with a certain dryness. To confirm the feasibility and advantages of the proposed system, Particle Swarm Optimization is introduced to optimization design the operating conditions of the system. At design conditions, maximum net output power which is as the single-subjective optimized goal reaches 781.88 kW and the corresponding thermal efficiency and exergy efficiency achieves 12.96 % and 48.54 %, respectively. Meanwhile, thermodynamic properties in each state point of the system are calculated and compared with those of the basic Kalina cycle by selecting the evaporating pressure and the concentration of basic ammonia water as variables. The maximum net output power of the novel system is 111.92 kW more than that of the basic Kalina cycle, while the thermal and exergy efficiencies are also 1.07 % and 6.95 % higher at their respective design condition. In terms of exergy destruction, the evaporator and the condenser occupy the most parts of the system total exergy destruction. Comprehensively analyzing the system performance from the aspects of thermodynamic first and second laws, the proposed novel system has an excellent performance and a great potential to apply in the industrial field.

Operation characteristics and performance prediction of a 3 kW organic Rankine cycle (ORC) with automatic control system based on machine learning methodology

Automatic control system enables the laboratory organic Rankine cycle (ORC) to adapt to variable operating conditions of industrial application. In this study, the operation characteristics of a 3 kW ORC with automatic control system applied to a chemical plant, as well as the performance prediction and optimization using machine learning methodology, are addressed. The dynamic behaviors for startup, operating and stop stages are discussed. The BP-ORC neural network model is established based on 3400 sets of experimental data, while the prediction accuracy is analyzed based on the errors of the training and test samples. The effects of six operation parameters on system performance are examined, while the bi-objective optimization for maximum thermal efficiency and maximum net output work is investigated. Results indicate that the component response times for startup stage and stop stage are 90s and 300s, respectively. Increasing the mass flow rate, decreasing the expander outlet temperature and increasing the expander inlet temperature ensure a higher net output work, while increasing the expander inlet temperature, decreasing the expander outlet temperature and increasing pump outlet pressure enable a higher thermal efficiency. The optimum net output work and thermal efficiency from Pareto-optimal solution are 2.87 kW and 8.855%, respectively.

A multi-objective energy coordinative and management policy for solid oxide fuel cell using triune brain large-scale multi-agent deep deterministic policy gradient

In this paper, a data-driven multi-objective energy coordinative management policy is proposed in order to enhance the net output power and efficiency of a solid oxide fuel cell (SOFC) and prevent constraint violations. This study focuses on the optimization agent and controller design for a SOFC power system to maintain stable oxygen excess ratio (OER) and fuel utilization (FU) ratio as well as meet the load demand simultaneously. The optimization agent is responsible for output the reference OER and FU, aiming to achieve maximum net output power and operational efficiency as well as dynamic constraint satisfaction times in terms of OER and FU in real time. By applying reference OER and FU settings, the air and hydrogen flow within the SOFC can be effectively controlled by coordination of the air control agent and hydrogen control agent, respectively. In addition, a triune brain large-scale multi-agent deep deterministic policy gradient algorithm (TBL-MADDPG) is proposed. In order to improve the robustness of the proposed policy, the design of TBL-MADDPG entails curriculum learning, imitation learning and a large-scale multi-agent training framework. The performance of this proposed method is verified by the experiment.

Thermoeconomic Optimization Design of the ORC System Installed on a Light-Duty Vehicle for Waste Heat Recovery from Exhaust Heat

The organic Rankine cycle (ORC) has been widely studied to recover waste heat from internal combustion engines in commercial on-road vehicles. To achieve a cost-effective ORC, a trade-off between factors such as costs, power outputs, back pressure, and weight needs to be carefully worked out. However, the trade-off is still a huge challenge in engine waste heat recovery. In this study, a thermoeconomic optimization study of a vehicle-mounted ORC unit is proposed to recover waste heat from various exhaust gas conditions of a light-duty vehicle. The optimization is carried out for four organic working fluids with different critical temperatures, respectively. Under the investigated working fluids, the lower specific investment cost (SIC) and higher mean net output power (MEOP) of ORC can be achieved using the organic working fluid with higher critical temperature. The maximum mean net output power is obtained by taking RC490 as working fluid and the payback period (PB) is 3.01 years when the petrol is EUR 1.5 per liter. The proposed strategy is compared with a thermodynamic optimization method with MEOP as an optimized objective. It shows that the proposed strategy reached SIC results more economically. The importance of taking the ORC weight and the back pressure caused by ORC installation into consideration during the preliminary design phase is highlighted.

Study of the performance of thermoelectric generator for waste heat recovery from chimney: impact of nanofluid-microchannel cooling system.

A huge number of chimneys all over the world utilized in many industrial applications and applications like restaurants, homes, etc. contribute badly on the global warming and climate change due to their waste heat. So, in this paper, the performance of thermoelectric generator (TEG) cooled by microchannel heat spreader having nanofluid and used for waste heat recovery from vertical chimney is investigated. Using heat spreader with microchannel cooling system increases the output TEG power compared to natural convection cooling system. In this paper, the impact of microchannel sizes, using nanofluid and heat spreader with different sizes on the TEG performance and cooling, is considered. Three-dimensional mathematical models including TEG, microchannel, nanofluid, and heat spreader are presented and solved by Ansys Fluent software utilizing user-defined memory, user-defined function, and user-defined scalar. All TEG effects (Joule, Seebeck, and Thomson) are considered in TEG model. Results indicate that TEG power rises with increasing the heat spreader and microchannel sizes together. Increasing microchannel and heat spreader sizes four times of TEG size raises the TEG output power by 10%. This also achieves the maximum cooling system efficiency of 88.9% and the maximum net output power. Microchannel heat spreader cooling system raises the system (TEG power-pumping power) net power by 125.2% compared to the normal channel and decreases the required cooling fluid flow rate. Utilizing copper-water and Al2O3-water nanofluids rises maximally the TEG output power by 14% and 4%, respectively; however, it increases the pumping power. Moreover, using nanofluids increases the net output power at low Reynolds number and decreases it at higher Reynolds number.

Rankine cycle waste heat recovery for a heavy-duty natural gas engine meeting China VI emission standards

The China VI natural gas engine is based on the theory of the air–fuel ratio method, leading to a high exhaust temperature, large heat load and difficult cooling. The paper carried out a thermal balance experiment of the China VI natural gas engine under different working conditions. A dual-loop organic Rankine cycle system is designed to reduce the difficulty of cooling system and improve the thermal efficiency. The high-temperature loop uses water as working fluid to recover the heat of engine exhaust gas and recirculation exhaust gas. The low-temperature loop recovers the heat from cooling water and waste heat of the high-temperature loop. The high-temperature and low-temperature loops are coupled through a shared heat exchanger. The results show that the China VI natural gas engine has a higher and more stable waste heat temperature than traditional engines and is more adaptable to waste heat recovery under variable operating conditions. For fixed evaporation temperature, with the increase of inlet temperature of the expander, the net output power of high-temperature loop increases first and then decreases, reaching the maximum value at about 800 K. In the low-temperature loop working fluids R601a, R601b, R600, R600a and R12333zd, The maximum net output power of the waste heat recovery system based on the combination of water and R12333zd is approximately 75.4 kW under the rated condition, which is 22.24% of the rated power of the engine.

Experimental study on thermoelectric performance and power consumption characteristics of flat-plate thermoelectric generator

Thermoelectric generator can directly convert thermal energy into electrical energy, and applying it to recover waste heat from automobile exhaust is conducive to energy saving. In this paper, a thermoelectric generation experimental system is built, the power output performance and channel power consumption of the flat-plate thermoelectric power generation system under different exhaust gas flow rates are experimentally studied. The results show that when the exhaust flow rate is 40 Nm3/h and the exhaust inlet temperature is 400 °C, the maximum output power of the system is 26.8 W, and the maximum net output power is about 23.3 W. In addition, the exhaust flow rate is changed from 10 Nm3/h to 40 Nm3/h, and the proportion of power consumption in the hot air channel is changed from 1.91% to 12.85%, which has increased by more than six times.

A serial system of multi-stage reverse electrodialysis stacks for hydrogen production

Salinity gradient energy is converted to hydrogen energy by integrating reverse electrodialysis (RED) and electrolysis of water to produce hydrogen. In this work, a serial system of multi-stage RED sacks is proposed to improve the energy efficiency and working performance of direct hydrogen production. The experimental results show that, compared with a single-stage system, the multi-stage RED stack system showed significant improvements in both hydrogen production and power output. Appropriately reducing the working current while increasing the number of RED stacks was beneficial to net power output and energy conversion. Total hydrogen production was almost unaffected when the number of RED stacks was large. Maximum energy conversion efficiency occurred at an optimal feed solution velocity. Under these conditions, the maximum net output power, total hydrogen production, and total energy-conversion efficiency were 2.06 W, 881.88 mL h−1, and 7.74%, respectively. The results are of relevance to investigation of the thermal-energy-driven reverse-electrodialysis heat engine for hydrogen production.

Large-scale multi-agent deep reinforcement learning-based coordination strategy for energy optimization and control of proton exchange membrane fuel cell

To maximize the net output power and ensure the safe operation of proton exchange membrane fuel cells (PEMFCs), a coordination strategy is proposed in this paper to realize better optimization and control of a cell’s oxygen excess ratio (OER). There are two agents in this strategy. An optimization agent is employed to obtain an ideal OER in different states by considering both the maximum net output power and the power control performance and safety of the PEMFC. A control agent effectively controls the OER of the PEMFC by determining the ideal OER. In addition, an evolutionary curriculum imitation large-scale multiagent deep reinforcement learning algorithm (ECILS-MADDPG) is introduced for this framework, which draws from the pedagogical technique of curriculum learning and imitation learning to improve the robustness of the coordination strategy. Proven by experiments, the proposed coordination strategy can obtain the maximum net power while maintaining OER control performance and the safety constraints of the PEMFC. Moreover, the proposed method increases the net power by up to 0.70% compared with an equivalent net power minimization strategy, and the integrated absolute error (IAE) in the OER is reduced by up to 99%.

Energetic and Exergetic Investigation of Regenerative Gas Turbine Air-Bottoming/Steam -Bottoming Combined Cycle

The present study is a thermodynamic analysis of a Regenerative Air-Bottoming combined (RABC) cycle /Steam bottoming combined (RABC) cycle operated by the exhaust gases the topping gas turbine cycle. The fractional mass of exhaust gases passes through the first heat exchanger where it exchanges heat with the compressed air from the air compressor of topping cycle and remaining amount of exhaust gasses passes through a second heat exchanger where it uses to supply heat to RABC cycle or third heat exchanger where it uses to supply heat to RSBC cycle. The energetic and exergetic performance of RABC cycle and RSBC cycle is investigated using turbine inlet temperature (1000 K⩽ TIT⩽1500 K) and mass fraction of exhaust gas (0⩽x⩽1) of the topping cycle as the input variables. The work net output attained its peak value at x=0 which is 22.1 % to 27.3 % for RABC cycle and 22.7 % to 21.5 % for RSBC cycle whereas the maximum thermal efficiency and minimum specific fuel consumption is observed at x=1. Also exergy loss by exhaust gases is minimum at x=0 for both RABC cycle and RSBC cycle. Finally, it is concluded that for the maximum work net output and minimum exergy loss by exhaust gases, RABC cycle is the best option followed by RSBC cycle but for optimum thermal efficiency and minimum specific fuel consumption purely regenerative gas turbine cycle have no comparison with RABC cycle and RSBC cycle.

Low temperature performance evaluation of electrochemical energy storage technologies

• Low temperature performance of 9 commercial batteries and supercapacitors compared. • Performance loss mainly due to Ionic conductivity and interfacial charge transfer. • Reliable temperature estimation through single frequency phase angle demonstrated. • Optimal pre-heating temperature calculated to maximise cell net energy output. The performance of electrochemical energy storage technologies such as batteries and supercapacitors are strongly affected by operating temperature. At low temperatures (<0 °C), decrease in energy storage capacity and power can have a significant impact on applications such as electric vehicles, unmanned aircraft, spacecraft and stationary power storage. In this work, the discharge behaviour of nine different commercial electrochemical cells are evaluated, representing a variety of lithium-ion, nickel metal hydride, lead acid and supercapacitor technologies. Discharge capacity, energy, maximum power and impedance spectra with equivalent circuit analysis are compared at temperatures ranging from +20 °C to −70 °C. Results demonstrate that despite exhibiting the greatest loss in performance with temperature reduction, the lithium-ion batteries tested provide the highest energy and power densities down to −30 °C due to higher capacity and operating voltage. At lower temperatures, the lead-acid cell gives the highest energy density and supercapacitor the highest power density. A new simplified empirical method is introduced for lithium-ion cells to determine the optimum pre-heating temperature for maximum net energy output including heating efficiency. This new method can be used to assess the benefits of different cold-start thermal management strategies for electric vehicles. It is also demonstrated that the temperature of the lithium-ion cells tested can be accurately predicted from impedance phase change at low temperatures across a range of electrode materials.

Integration of biomass gasification with a supercritical CO2 and Kalina cycles in a combined heating and power system: A thermodynamic and exergoeconomic analysis

A novel cogeneration system based on a combination of a gas turbine cycle, a supercritical CO2 cycle, and a Kalina cycle is devised for heating and power generation. Energy, exergy, and exergoeconomic analysis are performed to assess the system’s performance and feasibility. According to the findings, the energy and exergy efficiencies of the system are obtained by 78.15% and 40.97%, respectively. In addition, heating capacity enhanced with the increment of air preheater’s terminal temperature difference (ΔTAP), air compressor’s pressure ratio (r1p), and pressure ratio of S–CO2 compressor (r2p). The system’s sum unit cost of the product (SUCP) decreased with the increment of ΔTAP and with the decrement of ammonia concentration. Besides, the minimum value of SUCP is obtained at the air compressor pressure ratio of r1p=13.24 and r2p=2.63. The maximum value of exergy efficiency is evaluated at ΔTAP=262K, r1p=14.5, and r2p=4.21. Moreover, the maximum net output power is obtained where the design parameters are set as ΔTAP=262K, r1p=14.5, and r2p=3.5. Furthermore, the economic analysis revealed that the payback period and net present value are evaluated to be 6.9 years and 5.374×10+6 $, respectively, for the electricity price of 0.07 $/kWh and fuel cost of 2 $/GJ.

Performance prediction and optimization of an organic Rankine cycle (ORC) for waste heat recovery using back propagation neural network

Performance prediction and multi-objective optimization for an organic Rankine cycle (ORC) using back propagation (BP) neural network are investigated in this study. A 3 kW ORC experiment platform is used to obtain 950 sets of basic experimental data, and a BP-ORC model using back propagation neural network is established by training the experimental data. The prediction accuracy of the BP-ORC model is analyzed according to the errors of the training samples and test samples. The effects of six operation parameters on thermal efficiency and net output work are addressed. The Pareto optimal frontier for maximum net output work and maximum thermal efficiency is examined. The results demonstrate that the prediction error of BP-ORC model is very low, and the system performance can be improved by adjusting several operating parameters experimentally according to the model prediction. A tradeoff relation is appeared between net output work and thermal efficiency. The optimal thermal efficiency and net output work for Pareto-optimal solution are obtained.

Simulation and optimization of liquefied natural gas cold energy power generation system on floating storage and regasification unit

In this paper, based on the idea of reducing heat exchanger exergy destruction and increasing turbine work, a new three-stage cascade Rankine system and a new four-stage cascade Rankine system is proposed to improve the cold energy utilization rate during liquefied natural gas gasification on liquefied natural gas-floating storage and regasification unit. Then compare them with the original cascade Rankine cycle established under the same conditions. The results show that under the condition of 175 tonne per hour liquefied natural gas flow, the maximum net output power of the new three-stage cascade Rankine cycle system is 4593.31 kW, the exergy efficiency is 20.644%. The maximum net output power of the new four-stage cascade Rankine cycle system is 5013.93 kW, and the exergy efficiency is 22.509%. Compared with the original cascade Rankine cycle system, the maximum net output power of the new three-stage cascade Rankine cycle system and the new four-stage cascade Rankine cycle system is increased by 9.41% and 11.45%, respectively, and the system exergy efficiency is increased by 9.29% and 11.28%, respectively.

A Hot Water Split-Flow Dual-Pressure Strategy to Improve System Performance for Organic Rankine Cycle

The organic Rankine cycle (ORC) is widely used to recover industrial waste heat. For an ORC system using industrial waste hot water as a heat source, a novel hot water split-flow dual-pressure organic Rankine cycle (SFD-ORC) system is developed to improve the performance of the ORC. The maximum net power output was selected to compare three ORC systems, including basic ORC (B-ORC), conventional dual-pressure ORC (CD-ORC) and SFD-ORC. A genetic algorithm (GA) was used to optimize the parameters to search the maximum net power output of ORCs. The maximum net output power was taken as the standard of performance evaluation. The results show that, under the same hot water inlet temperature condition, the optimal hot water outlet temperature of B-ORC is much higher than that of CD-ORC and SFD-ORC, which indicates that less thermal energy could be utilized to convert to power in B-ORC. The optimal hot water temperature at the outlet of evaporator 1 in SFD-ORC is higher than that in CD-ORC, which means SFD-ORC could make more efficient use of the high-grade thermal energy of hot water. The SFD-ORC could obtain the highest net output power under the optimal parameter conditions, followed by the CD-ORC system, while the B-ORC has the lowest net output power. Moreover, with the increase in the hot water inlet temperature, the advantage of SFD-ORC becomes increasingly obvious. When the hot water inlet temperature is 90 °C, the net output power of SFD-ORC at is 6.22% higher than that of CD-ORC. The net output power of SFD-ORC at 130 °C increases to 9.7% higher than that of CD-ORC. The SFD-ORC presents better system performance and has great engineering application potential.

Conversion of Low-Grade Heat from Multiple Streams in Methanol to Olefin (MTO) Process Based on Organic Rankine Cycle (ORC)

The organic rankine cycle (ORC) has been widely used to convert low-grade thermal energy to electricity. The selection of the cycle configuration, working fluid, and operating parameters is crucial for the economic profitability of the ORC system. In the methanol to olefin (MTO) process, multi-stream low-temperature waste heat has not been effectively utilized. The previous study mostly focused on the optimization of a single stream system and rarely considered the comprehensive optimization of multi-stream ORC systems which have multi-temperature heat sources. This paper proposes five kinds of system design schemes, and determines the optimal output work and the highest exergy efficiency through the selection of working fluid and optimization of system parameters. In addition, the influence of mixed working fluid on the thermodynamic performance of the system was also investigated. It is found that there is an optimal evaporation temperature due to the restriction of pinch temperature. At the optimal temperature the ORC system obtains the maximum net output power of 4.95 MW. The optimization results show that the working fluid R227EA selected from seven candidate working fluids shows the optimal thermodynamic performance in all the five design schemes, and obtains the maximum output work and exergy efficiency.