Net Power Gain Research Articles

Innovative design for thermoelectric power generation: Two-stage thermoelectric generator with variable twist ratio twisted tapes optimizing maximum output

In recent years, considerable effort has been dedicated to the development of highly efficient thermoelectric generators for waste heat recovery and thermoelectric power generation. In this study, we present employing twisted tapes with variable twist ratio to enhance thermal energy extraction efficiency, coupled with two-stage thermoelectric modules for heat-to-electricity conversion, resulting in a substantial increase in the power output of the thermoelectric generator. We established an experimental system that validated the superior power generation and heat recovery characteristics of the two-stage thermoelectric generator. Building upon these findings, we propose further optimizing the variable twist ratio twisted tapes to enhance the power output. We investigated the impact of tape pitch ratio, twist ratio, and twist ratio variation range on thermoelectric performance. Experimental results indicate that the influence of flow instability is more pronounced than that of swirl intensity, and twist tapes with the maximum twist ratio variation rate yield the highest net output power. Compared to an unmodified thermoelectric generator, the two-stage thermoelectric generator employing twist tapes with a twist ratio increase from π to 3π achieves a maximum net output power gain of up to 100%. These findings provide a practical framework for integrating innovative power generation modules and optimized heat exchanger designs into the application of waste heat recovery thermoelectric generators, marking a significant advancement in the field of thermoelectric generators.

Solar PV tracking system using arithmetic optimization with dual axis and sensor

Presently, PV system is considered the best renewable energy source for electricity production. In order to maximize energy output in photovoltaic systems, a system for tracking the sun's position and adjusting panel positions was created. Despite the fact that several models for tracking solar radiation have been suggested to improve energy production, it faces challenges in continuous tracking and power consumption. This paper proposes a novel sensor-based solar tracking system with numerical optimization to increase photovoltaic systems' energy output. The initial model was for a two-axis tracking system based on sensors. Solar panel and sun positions are detected by this system using ultraviolet and microelectromechanical sun sensors. To improve tracking movements and photovoltaic energy production, we recommend using solar sensors to construct a novel two-axis solar tracking device. This technology benefits from increased solar radiation and solar energy harvesting capabilities. The main disadvantage of dual-axis active solar tracking systems is that the drive mechanism frequently uses up the output power of the solar panels. As a result, the net power gain of the solar panel is less than its maximum. Further, a control system was developed with proportional integral derivative (PID) controller and arithmetic optimization (AO) to adjust the panel position relative to suns movement. The AO technique tunes the PID controller gains until it reaches its desired level to enhance the production of power. With the use of sensors, the tracking system can use mathematical optimization algorithms and the sun's position to minimize power consumption while still maintaining optimal solar panel positioning. The developed model was designed in the MATLAB software and the outcomes are analyzed. The paper also presents an energy analysis of the system, which evaluates the energy input, output and overall system efficiency. We recommend using solar sensors to create a unique dual-axis solar tracking system. This technology benefits from increased solar radiation and solar energy harvesting capabilities.

A Reinforcement Learning framework for Wake Steering of Wind Turbines

Ideally, optimum power for a single turbine is obtained when the wind-turbine is aligned with the wind direction. However in multi-turbine wind-farm set-up, wake effects lead to decreased power production from downstream turbine [1, 2, 3, 4, 5]. Hence, a control strategy based on wake steering involves misalignment of upstream turbines with the wind direction causing their wakes to deflect away from downstream wind turbines needs to be investigated. A great deal of work has been put into dynamically controlling the orientation of the individual wind turbines to maximize the power output of the farm [6, 7, 8, 9]. In the wake-steering based control, the misaligned wind turbines produce less power, while the performance of downstream turbines gets enhanced which increases overall net power gain for the wind power plant. Traditionally, the benefits of wake steering have been demonstrated assuming fixed wind directions (e.g., using high-fidelity modeling). Amongst the most recent techniques, particularly promising is the use of Reinforcement learning (RL), which is a branch of machine learning where models are trained to make decisions based on observations of their environment. It is a flexible framework for devising strategies for solving optimal control problems in a broad range of applications across the sciences. Early attempts at using Reinforcement learning for wake steering have been carried out [7, 8, 9], and show promising results. In practice, however, wake-steering controllers must operate in dynamic wind environments in which the wind conditions are estimated from imperfect measurements. Hence, a reinforcement learning framework is developed in this work for dynamic wind conditions. The results show that the framework is promising, and we compare the deep reinforcement learning approach against a considerably more expensive traditional optimization approach which serves as a good baseline. Future work could include looking at more realistic wake models, steering in the presence of noisy observations, and incorporating weather predictions.

Large-Eddy Simulation of swirled flame stabilisation using NRP discharges at atmospheric pressure

In this work, the use of Nanosecond Repetitively Pulsed (NRP) discharges is investigated numerically to improve the stabilisation of the flame in a swirl burner. The studied configuration is the PACCI burner test rig set up at KAUST, in which it was experimentally demonstrated that NRP discharges can effectively enhance flame stability. Simulations are performed with the reactive compressible Navier–Stokes solver AVBP, using a recently developed phenomenological model for plasma-assisted combustion of methane-air premixed flame. The ability of the numerical model to reproduce the main flow behaviours is first assessed by comparison with PIV measurements in cold flow conditions. Then, a lean atmospheric pressure case (ϕ=0.67) without plasma actuation is simulated and compared with OH* chemiluminescence image from experiment. Both numerical and experimental results reveal an unstable turbulent flame, with intermittent attachment to the burner exit. Finally, two operating conditions with NRP discharges are simulated. The NRP discharges correspond to 10 kV pulses applied at a frequency of 20 and 30 kHz, respectively corresponding to a discharge power 0.72 and 1.17% of the thermal flame power. First, a significant stabilisation effect is observed when applying the discharges, which efficiently mitigate the flame lifting. This effect is quantitatively demonstrated by tracking the flame centre of gravity, which shows that the flame moves upstream under the influence of the plasma, in good agreement with experimental observations. Results also show that a net power gain is obtained by applying NRP discharges to combustion by comparing the thermal flame power to the plasma power. In particular, an increase of plasma actuation efficiency from 4 to 6 as been observed in the cases studied by increasing the plasma power.

Thermoacoustic cascade engine free from resonance length

The high reliability and long lifespan of thermoacoustic generators (TAG) make them ideal for waste heat recovery applications. However, the size and weight of these generators is still a challenge. This paper introduces a traveling-wave thermoacoustic generator that is free from a wavelength long loop. The new generator consists of an acoustic driver (linear motor), thermoacoustic engine and a linear alternator. The linear motor introduces the initial acoustic power into the thermoacoustic engine which amplifies it, then the amplified acoustic power is converted into electricity through the linear alternator. The electric power obtained from the alternator exceeds the initial input (“seed”) power consumed by the motor to kick-start the thermoacoustic amplification, thus providing the net power gain. The advantage lies in decoupling the operation from the reliance on the acoustic resonance. A two-stage engine can be built with half a meter length, while a three-stage engine can be less than a meter long including a coiled inertance pipe. The three-stage TAG can generate 120.5 W of electricity, at a thermal to acoustic efficiency of 34.2% and a total efficiency of 20.5%.

Experimental characterization of a geothermal cooling system for enhancement of the efficiency of solar photovoltaic panels

The efficiency of solar photovoltaic panels reduces when their temperature increases during normal operation conditions, resulting in a very significant power output reduction. This phenomenon is especially relevant in regions with high photovoltaic potential where irradiance and ambient temperature are particularly high as well. To overcome this issue, a compact cooling system for commercial photovoltaic panels based on low-enthalpy geothermal cooling is proposed. Overheating is evacuated from the solar panel by a single-phase close-loop cooling system that gets benefit of a natural underground heat sink, which is at a constant and low temperature. A prototype, integrating a single axis sun tracking mechanism, has been assembled and tested in outdoor conditions in June 2022 in Alcalá de Henares, Madrid, Spain. As it has been experimentally demonstrated, with a coolant flowrate of 1.8 l/min per square meter of panel surface, the cooling system reduces the temperature of the cooled panel up to 20 °C, which resulted in a real improvement of the panel’s efficiency up to 13.8%. Finally, a sensitivity analysis of the net power gain and the net extra energy produced by the cooled panel is presented.

Optimal design of annular thermoelectric generator with twisted tape for performance enhancement

The adaptation of annular thermoelectric generator (ATEG) to cylindrical heat sources exhibits a better performance compared to widely studied flat plate type thermoelectric generator (FTEG). To enhance heat transfer and improve the overall performance, a novel structure of the heat exchanger of the twisted-tape annular thermoelectric generator (TT-ATEG) is proposed in this paper. A three-dimensional finite element model of TT-ATEG is established for the first time. The net power gain coefficient and the efficiency gain coefficient are defined to quantify the performance of TT-ATEG, and the gain effects of the length, twist ratio and radius of the twisted tape are analyzed respectively. To maximize the comprehensive performance of TT-ATEG, the optimal weighting factor of net power and efficiency are determined, and the full-parameter optimization of the twisted tape is completed. The results reveal that the optimal performance of TT-ATEG is obtained if the weight ratio of net power and conversion efficiency is 1:4. In our case study, dimensionless factors radius ratio Rr, length ratio Lr and twist ratio of the twisted tape are 0.714, 0.479 and 136.84 respectively. Compared with the ATEG without twisted tape, the net power and efficiency are improved by 10.41% and 22.51%, respectively. The results demonstrate that the novel design of TT-ATEG could accelerate the heat transfer effectively and enhance the overall performance.

Study of three wake control strategies for power maximization of offshore wind farms with different layouts

The wake regulation by cooperative yaw control, axis induction control, or their combination can significantly improve the total power output of wind farms. However, a comprehensive study of the three control strategies is still lacking, which hinders their engineering applications. To this end, the optimized yaw angles, induction factors, and total power promotion are systematically compared for the three control strategies on both a regularly arranged wind farm and an irregularly arranged realistic offshore wind farm. The results indicate that all the three strategies work similarly to achieve a net power gain by enhancing the power output of the downstream turbines while slightly downgrading the upstream turbines. For the regularly arranged wind farm, very notable power promotions are obtained in the aligned direction, and all the three control strategies show similar performance, but the promotions almost disappear with a small misalignment. In contrast, power promotion is less sensitive to the wind direction for the irregularly arranged wind farm. The promotion of the yaw control is much more predominate than that of the induction control, and the combined control only slightly outperforms the single yaw control in the realistic wind farm. In the prevailing wind direction, the total power of the realistic wind farm can be increased by 2.1% by the combined control strategy under the wind speed of 6 m/s.

Blockchain-Based Gas Auctioning Coupled with a Novel Economic Dispatch Formulation for Gas-Deficient Thermal Plants

Inadequate gas supply is partly responsible for the energy shortfall experienced in some energy-poor nations. Favorable market conditions would boost investment in the gas supply sector; hence, we propose a blockchain-based fair, transparent, and secure gas trading scheme that facilitates peer-to-peer trading of gas. The scheme is developed using an Ethereum-based smart contract that receives offers from gas suppliers and bid(s) from the thermal plant operator. Giving priority to the cheapest offers, the smart contract determines the winning suppliers. This paper also proposes an economic dispatch model for gas-deficient plants. Conventional economic dispatch seeks to satisfy electric load demand whilst minimizing the total gas cost of generating units. Implicit in its formulation is the assumption that gas supply to generating units is sufficient to satisfy available demand. In energy poor nations, this is hardly the case as there is often inadequate gas supply and conventional economic dispatch is of little practical value. The proposed economic dispatch model’s objective function maximizes the quantity of available gas and determines the optimal power output of each generating unit. The mathematical formulation is verified using data from the Egbin thermal station which is the largest thermal station in Nigeria and is solved using the General Algebraic Modeling System (GAMS). Obtained results indicate the viability of the novel approach as it results in a net power gain of 35 MW. On the other hand, the smart contract proved effective in accurately selecting winning suppliers and making payment.

Prediction of System-Level Energy Harvesting Characteristics of a Thermoelectric Generator Operating in a Diesel Engine Using Artificial Neural Networks

This study evaluated the potential of artificial neural networks (ANNs) to predict the system-level performance of a thermoelectric generator (TEG), whose performance depends on various variables including engine load, engine rotation speed, and external load resistance. Therefore, a Python code was developed to determine an optimal ANN structure by tracking the training/prediction errors of the ANN as a function of the number of hidden layers and nodes of hidden layers. The optimal ANN was trained using 484 output current (I)–load resistance (R) datasets obtained under three different engine rotation speeds and five different engine loads. The prediction accuracy of the ANN was validated by comparing 88 I–R datasets reproduced by the ANN using experimental data that were not used for training. In the validation procedure, differences of only 3.49% and 2.59% were observed in the experimental and ANN-predicted output power obtained for the 1000 rpm–0.8 MPa brake mean effective pressure (BMEP) and 1500 rpm–0.4 MPa BMEP scenarios, respectively. The exhaust gas flow characteristics were used for training and validation to predict the pumping loss caused by the installation of the TEG in the middle of the exhaust tailpipe with high accuracy. The results demonstrated that the ANN effectively reproduced datasets to fill the gaps between the discretized experimental results for all the experimental scenarios without any noticeable overfitting and underfitting. The net power gain obtained by the ANN exhibited a clear peak point for the engine rotation speed of 2000 rpm, which is difficult to obtain using experimental data.

CFD Investigation of Separation Control on a Vertical Axis Wind Turbine: Steady and Unsteady Suction

High-fidelity two-dimensional unsteady Reynolds-averaged Navier-Stokes (URANS) simulations are employed to investigate the influence of boundary layer suction through a slot located near the leading edge of a vertical axis wind turbine operating in dynamic stall. The analysis includes both steady and unsteady suction with different frequencies. The results shows that: (i) when the suction slot is located within the chordwise extent of the laminar separation bubble, dynamic stall can be avoided with minimal suction amplitude; (ii) the most promising suction location is the most upstream suction location studied, at 8.5%c where c is the blade chord length; (iii) the suction only needs to be applied during the azimuthal angles when dynamic stall occurs; (iv) the oscillation frequency of the suction velocity has insignificant influence on the obtained turbine power gain; (v) applying unsteady suction is interesting as it reduces the energy consumption of the suction system, thus the net power gain.

Theoretical and Numerical Study of a Photovoltaic System with Active Fluid Cooling by a Fully-Coupled 3D Thermal and Electric Model

The paper deals with the three-dimensional theoretical and numerical investigation of the electrical performance of a Photovoltaic System (PV) with active fluid cooling (PVFC) in order to increase its efficiency in converting solar radiation into electricity. The paper represents a refinement of a previous study by the authors in which a one-dimensional theoretical model was presented to evaluate the best compromise, in terms of fluid flow rate, of net power gain in a cooled PV system. The PV system includes 20 modules cooled by a fluid circulating on the bottom, the piping network, and the circulating pump. The fully coupled thermal and electrical model was developed in a three-dimensional geometry and the results were discussed with respect to the one-dimensional approximation and to experimental tests. Numerical simulations show that a competitive mechanism between the power gain due to the cell temperature reduction and the power consumption of the pump exists, and that a best compromise, in terms of fluid flow rate, can be found. The optimum flow rate can be automatically calculated by using a semi-analytical approach in which irradiance and ambient temperature of the site are known and the piping network losses are fully characterized.

Identification of optimal operating strategy of direct air-cooling condenser for Rankine cycle based power plants

Direct air-cooling condenser has attracted significant attention in the last decade due to the employment of Rankine-cycle based power plants from renewable (e.g., concentrated solar) or traditional (e.g., coal) heat sources in water-scarce areas. The optimal operating strategy of direct air-cooling condenser to maximize net power gain under given plant status and boundary conditions is rather complicated due to strong impacts from the steam turbine subsystem and varying ambient conditions. This paper aims at determining, for various boundary conditions, the optimal operating fan frequency and the corresponding back pressure of a typical large-scale air-cooled coal-fired power plant via accurate off-design models of both the turbine subsystem and air-cooling condenser, which are derived by combining aggregated physical equations and real operating data. Several data pre-processing techniques, e.g., quasi steady-state selection, are employed first to improve the data quality. Then, the processed data are divided into two parts for the performance characterization of involved equipment and the accuracy testing of the derived models, respectively. The results show that good agreement has been achieved between the prediction of the established models and the real operating data within a wide range of load factor (50–100%), and ambient temperature (10–30 °C). To maximize the plant profit, practical and quantitative operating guidelines of the air fans have been derived, which are further employed to examine current operating strategy of the air-cooling condenser of the considered power plant. It is found that with a load factor over 85%, even the full-load operation of all equipped air fans cannot deliver the theoretical optimal back pressure for the steam turbine subsystem, indicating potential benefits of enlarging the condenser for high operating loads. The proposed identification procedure can be easily implemented as an online monitoring and supervision system to practically assist the optimal plant operation.

Pyrolysis of waste tires: A modeling and parameter estimation study using Aspen Plus®

This paper presents a simulation flowsheet model of a waste tire pyrolysis process with feed capacity of 150kg/h. A kinetic rate-based reaction model is formulated in a form implementable in the simulation package Aspen Plus, giving the flowsheet model the capability to predict more than 110 tire pyrolysis products as reported in experiments by Laresgoiti et al. (2004) and Williams (2013) for the oil and gas products respectively. The simulation model is successfully validated in two stages: firstly against experimental data from Olazar et al. (2008) by comparing the mass fractions for the oil products (gas, liquids (non-aromatics), aromatics, and tar) at temperatures of 425, 500, 550 and 610°C, and secondly against experimental results of main hydrocarbon products (C7 to C15) obtained by Laresgoiti et al. (2004) at temperatures of 400, 500, 600, and 700°C. The model was then used to analyze the effect of pyrolysis process temperature and showed that increased temperatures led to chain fractions from C10 and higher to decrease while smaller chains increased; this is attributed to the extensive cracking of the larger hydrocarbon chains at higher temperatures. The utility of the flowsheet model was highlighted through an energy analysis that targeted power efficiency of the process determined through production profiles of gasoline and diesel at various temperatures. This shows, through the summation of the net power gain from the plant for gasoline plus diesel that the maximum net power lies at the lower temperatures corresponding to minimum production of gasoline and maximum production of diesel. This simulation model can thus serve as a robust tool to respond to market conditions that dictate fuel demand and prices while at the same time identifying optimum process conditions (e.g. temperature) driven by process economics.

Maximizing Net Power in Circular Turns for Solar and Autonomous Soaring Aircraft

This study investigates maximizing net power input from a solar-photovoltaic array and/or a thermal updraft while performing constant bank angle, circular flight-path turns (that is, an orbit). The process inputs are the aircraft sink polar (or, equivalently, the power required curve), the date, the time, the location, and the flight altitude. A solar insolation model is combined with a best-turn performance calculation to determine the bank angle that maximizes power input from a solar-photovoltaic array at varying sun elevation angles. In general, for low sun elevation angles, the maximum net power gain from solar input and drag output is found at higher bank angles and shows 15% (absolute) gain over the limiting case of wings-level orbits in the same conditions. For high sun elevation angles, the maximum net power is found at low bank angles. The break point between high and low sun elevation angles varies with aircraft parameters and is approximately 25 deg for the example aircraft in this paper. The relative power losses of off-optimum orbits at a given bank angle are quantified. Finally, a thermal-updraft model is included in the net power calculations to determine an optimal bank angle that maximizes the average power input from a combination of solar photovoltaics and thermal updrafts. This paper shows that soaring and solar photovoltaics can be mutually beneficial, and it provides a method to calculate losses at off-optimum conditions.

Energy Flux in the Cochlea: Evidence Against Power Amplification of the Traveling Wave.

Traveling waves in the inner ear exhibit an amplitude peak that shifts with frequency. The peaking is commonly believed to rely on motile processes that amplify the wave by inserting energy. We recorded the vibrations at adjacent positions on the basilar membrane in sensitive gerbil cochleae and tested the putative power amplification in two ways. First, we determined the energy flux of the traveling wave at its peak and compared it to the acoustic power entering the ear, thereby obtaining the net cochlear power gain. For soft sounds, the energy flux at the peak was 1 ± 0.6 dB less than the middle ear input power. For more intense sounds, increasingly smaller fractions of the acoustic power actually reached the peak region. Thus, we found no net power amplification of soft sounds and a strong net attenuation of intense sounds. Second, we analyzed local wave propagation on the basilar membrane. We found that the waves slowed down abruptly when approaching their peak, causing an energy densification that quantitatively matched the amplitude peaking, similar to the growth of sea waves approaching the beach. Thus, we found no local power amplification of soft sounds and strong local attenuation of intense sounds. The most parsimonious interpretation of these findings is that cochlear sensitivity is not realized by amplifying acoustic energy, but by spatially focusing it, and that dynamic compression is realized by adjusting the amount of dissipation to sound intensity.

Solar thermal energy conversion to electrical power

The conversion of solar energy to electricity currently relies primarily on the photovoltaic effect in which photon bombardment of photovoltaic cells drives an electromotive force within the material. Alternatively, recent studies have investigated the potential of converting solar radiation to electricity by way of the Seebeck effect in which charge carrier mobility is generated by an asymmetric thermal differential. The present study builds upon these latest advancements in the state-of-the-art of thermoelectric system management by combining solar evacuated tube technology with commercially available Bismuth Telluride semiconductor modules. The target heat source is solar radiation and the target heat sink is thermal convection into the ambient air relying on wind aided forced convection. These sources of energy are reproduced in a laboratory controlled environment in order to maintain a thermal dipole across a thermoelectric module. The apparatus is then tested in a natural environment. The novelty of the present work lies in a net thermoelectric power gain for ambient environment applications and an experimental validation of theoretical electrical characteristics relative to a varying electrical load.

Spherical plasma oscillations in a reversed-polarity inertial-electrostatic confinement device

A pulsed reversed-polarity inertial-electrostatic confinement device has been investigated experimentally using voltage and spectroscopic diagnostics. Large-amplitude oscillations were observed in the floating potential of the plasma immediately following the initiation of the discharge. It is postulated that the observations were the result of coherent ion oscillations within a harmonic potential well formed by a uniform electron density in the center of the device. A simple model of the system predicts the depth of this transient potential well to be approximately 100 V. Observations of the relative occupation of the third and fourth energy levels of hydrogen in the plasma indicated the formation of a Maxwellian electron energy distribution after 20 μs. The results suggest a promising avenue toward a net fusion power gain by utilizing these oscillations to periodically compress and heat the plasma to thermonuclear densities and energies.

Saturated small-signal gain of Si quantum dots embedded in SiO2/SiOx/SiO2 strip-loaded waveguide amplifier made on quartz

A SiO2/SiOx/SiO2 strip-loaded waveguide with buried Si quantum dots is optically pumped to provide amplified spontaneous emission centered at 805 nm with spectral linewidth of 140 nm. By top-pumping the 350-nm-thick SiOx with He–Cd laser of 40 mW at 325 nm, the optical gain of 65 cm−1 and loss coefficient of 5 cm−1 are determined. Under a 785 nm small-signal injection diagnosis, the power-dependent gain curve fitting with gain-saturated amplifier model reveals a peak gain of 27 dB (not including waveguide loss) and a net power gain of 9.5 dB for the Si-rich SiOx waveguide amplifier with a length of 5 mm.

Channel and rib geometric scale effects of flowfield plates on the performance and transient thermal behavior of a micro-PEM fuel cell

Effects of channel and rib widths with an aspect ratio ( H/ W) of 0.67 of rectangular cross-sections flowfield plates on cell performance in terms of VI/ PI curves versus flowfield pressure drop of a micro-proton exchange membrane (PEM) fuel cell were extensively examined. The channel-to-rib width ratios of flowfield plates were varied from 0.5 to 2. It was found that a channel-to-rib width ratio of unity was secured as far as the best performance of the VI/ PI curves are concerned. Moreover, the pressure drop in flowfield on both anode and cathode was also measured. With the aid of pressure drop obtained for H 2/air delivery, an optimal channel-to-rib width ratio in terms of the net power gain factor (=power gain/power consumption) of 0.67 can be obtained for the cases under study. Furthermore, a simple lumped capacitance model was used to predict the temperature evolution of the fuel cell system, and results show that this model performs quite well, and the channel-to-rib width ratio seems no significant influence on the fuel cell temperature evolution of the flowfield plates.