Power Output In Terms Research Articles

Techno-economic optimization of ORC system structure, size and working fluid within biomass-fired municipal cogeneration plant retrofitting project

This paper continues discussion on financial viability and design optimisation of biomass-fired Organic Rankine Cycle (ORC) Combined Heat and Power (CHP) systems. It examines influence of such decision variables as ORC system rated electric power output, architecture and working fluid. The considered ORC system structures are simple, regenerative and regenerative cycle with split heat exchanger. Eight working fluids are considered, namely: MM, MDM, MD2M, D4, D5, toluene, ethylbenzene, and cyclohexane. The system was modelled and simulated using Ebsilon® Professional software. Sample project is assessed in terms of power generation efficiency, Primary Energy Savings (PES), and financial indicators, such as Net Present Value (NPV) and Internal Rate of Return (IRR). Results revealed considerable differences in optimal power output. The optimal value of the ORC generator power output in terms of NPV is within the range from 1000 to 2600 kW depending on the system configuration and the working fluid. In terms of IRR the optimal rated power is between 750 and 1400 kW. The highest values of nominal rated power output have been obtained for ethylbenzene. What is more, the economic indicators get higher values for hydrocarbons than for silicone oils, which are nowadays widely used in biomass fired ORC systems.

Development of Wind Power Prediction Models for Pawan Danavi Wind Farm in Sri Lanka

This paper presents the development of wind power prediction models for a wind farm in Sri Lanka using an artificial neural network (ANN), multiple linear regression (MLR), and power regression (PR) techniques. Power generation data over five years since 2015 were used as the dependent variable in modeling, while the corresponding wind speed and ambient temperature values were used as independent variables. Variation of these three variables over time was analyzed to identify monthly, seasonal, and annual patterns. The monthly patterns are coherent with the seasonal monsoon winds exhibiting little annual variation, in the absence of extreme meteorological changes during the period of 2015–2020. The correlation within each pair of variables was also examined by applying statistical techniques, which are presented in terms of Pearson’s and Spearman’s correlation coefficients. The impact of unit increase (or decrease) in the wind speed and ambient temperature around their mean values on the output power was also quantified. Finally, the accuracy of each model was evaluated by means of the correlation coefficient, root mean squared error (RMSE), bias, and the Nash number. All the models demonstrated acceptable accuracy with correlation coefficient and Nash number closer to 1, very low RMSE, and bias closer to 0. Although the ANN-based model is the most accurate due to advanced features in machine learning, it does not express the generated power output in terms of the independent variables. In contrast, the regression-based statistical models of MLR and PR are advantageous, providing an insight into modeling the power generated by the other wind farms in the same region, which are influenced by similar climate conditions.

Stochastic analysis of a galloping-random wind energy harvesting performance on a buoy platform

A new concept of a galloping-random wind energy harvester, which is a galloping-based piezoelectric harvester mounted on a buoy platform is proposed. The galloping-random wind energy harvester can concurrently harvest galloping energy due to the aero-instability and stochastic vibration energy due to the ocean wave. The harvester performance is comprehensively investigated through wind tunnel experiments and theoretical investigation. The mathematical model of the system is formulated, and its aerodynamic galloping is then validated with wind tunnel experimental measurements. Based on the verified mathematical model of the galloping-random wind energy harvester, the stochastic average method is applied to analytically obtain the probability density functions of the system’s stochastic responses and the average harvested power. The fidelity of the analytical solution is also verified by the numerical integration using the Euler-Maruyama algorithm. The results show that a unique crater phenomenon is discovered in the joint PDF of the responses, owing to the concurrent galloping and stochastic vibrations. In this case, the energy harvester exhibits a periodic galloping response with a fluctuating amplitude. The annulus range is wider when the galloping response is dominant and becomes stronger. In addition, this study investigates the average power output in terms of the stochastic excitation intensity, structural natural frequency, aerodynamic mass ratio, and normalized electrical term, to provide the useful design guidelines. The results show that the strong stochastic excitation intensity is beneficial to broadband energy harvesting and especially provides a high advantage for the low wind speed. The low structural natural frequency and large aerodynamic mass ratio can improve the performance. The parametric study also uncovers the optimal electrical term that can significantly improve the broadband average power output.

Utilization of Nanomaterials as Anode Modifiers for Improving Microbial Fuel Cells Performance

Microbial fuel cells (MFCs) are an attractive innovation at the nexus of energy and water security for the future. MFC utilizes electrochemically active microorganisms to oxidize biodegradable substrates and generate bioelectricity in a single step. The material of the anode plays a vital role in increasing the MFC’s power output. The anode in MFC can be upgraded using nanomaterials providing benefits of exceptional physicochemical properties. The nanomaterials in anode gives a high surface area, improved electron transfer promotes electroactive biofilm. Enhanced power output in terms of Direct current (DC) can be obtained as the consequence of improved microbe-electrode interaction. However, several limitations like complex synthesis and degeneration of property do exist in the development of nanomaterial-based anode. The present review discusses different renewable nanomaterial applied in the anode to recover bioelectricity in MFC. Carbon nanomaterials have emerged in the past decade as promising materials for anode construction. Composite materials have also demonstrated the capacity to become potential anode materials of choice. Application of a few transition metal oxides have been explored for efficient extracellular electron transport (EET) from microbes to the anode.

Optimization of wave-guided luminescence for higher efficiency of bifacial thin-film microscale GaAs solar cells

In pursuit of capturing more wave-guided luminescence for surface-printed bifacial GaAs μ-cells, the pyramid structure has been incorporated with specular back side reflector (BSR) to change the direction of photon propagation. Based on ray tracing model, the calculated photon capturing efficiency of GaAs μ-cells from back side via pyramid, dependent on the parameters of pyramid structure, achieve the largest 1.7× increase for dye absorption peak of 480 nm compared to the case without pyramid. More significantly, the short circuit current in experiment has been improved from original 16.5 mA/cm2 to 23.75 mA/cm2 for the AM 1.5G solar spectrum. Further experiment demonstrates that the optimized pyramid structure enables the integrated luminescent intensity to reach ∼3× increase in a smaller distance of optical transport, which means the advantages in photon capturing efficiency for cells with higher aspect ratio. The calculation further confirms that the cells with higher aspect ratio, among all cells with the same area, realize the higher concentration ratio for the same geometric gain. This provides a guideline for design of cell geometries to guarantee a higher power output in terms of cell modules.

Power fluctuation and power loss of wind turbines due to wind shear and tower shadow

The magnitude and stability of power output are two key indices of wind turbines. This study investigates the effects of wind shear and tower shadow on power output in terms of power fluctuation and power loss to estimate the capacity and quality of the power generated by a wind turbine. First, wind speed models, particularly the wind shear model and the tower shadow model, are described in detail. The widely accepted tower shadow model is modified in view of the cone-shaped towers of modern large-scale wind turbines. Power fluctuation and power loss due to wind shear and tower shadow are analyzed by performing theoretical calculations and case analysis within the framework of a modified version of blade element momentum theory. Results indicate that power fluctuation is mainly caused by tower shadow, whereas power loss is primarily induced by wind shear. Under steady wind conditions, power loss can be divided into wind farm loss and rotor loss. Wind farm loss is constant at 3α(3α–1)R2/(8H2). By contrast, rotor loss is strongly influenced by the wind turbine control strategies and wind speed. That is, when the wind speed is measured in a region where a variable-speed controller works, the rotor loss stabilizes around zero, but when the wind speed is measured in a region where the blade pitch controller works, the rotor loss increases as the wind speed intensifies. The results of this study can serve as a reference for accurate power estimation and strategy development to mitigate the fluctuations in aerodynamic loads and power output due to wind shear and tower shadow.

Uncertainty quantification of infinite aligned wind farm performance using non‐intrusive polynomial chaos and a distributed roughness model

AbstractUncertainty of wind farm parameters can have a significant effect on wind farm power output. Knowledge of the uncertainty‐produced stochastic distribution of the entire wind farm power output and the corresponding uncertainty propagation mechanisms is very important for evaluating the uncertainty effects on the wind farm performance during wind farm planning stage and providing insights on improving the performance of the existing wind farms. In this work, the propagation of uncertainties from surface roughness and induction factor in infinite aligned wind farms modeled by a modified distributed roughness model is investigated using non‐intrusive polynomial chaos. Stochastic analysis of surface roughness indicates that 30% uncertainty can propagate such that there is up a 8% uncertainty in the power output of the wind farm by affecting the uncertainty in the position of the individual wind turbines in the vertical boundary layer profile and uncertainty in vertical momentum fluxes which replenish energy in the wake in large wind farms. Induction factor uncertainty of the wind turbines can also have a significant effect on power output. Not only does its uncertainty substantially affect the vertical boundary layer profile, but the uncertainty in turbine wake growth which affects how neighboring turbine wakes interact. We found that optimal power output in terms of reduction of uncertainty closely correlates with the Betz limit and is dependent on the mean induction factor. Copyright © 2016 John Wiley & Sons, Ltd.

Performance analysis of energy conversion via caloric effects in first-order ferroic phase transformations.

A finite-time thermodynamic model of ferroic refrigerators and generators, based on first order phase transformation, is given. We use this model to evaluate a novel method of converting heat directly into electricity based on the martensitic phase transformation accompanied by an abrupt change in magnetic ordering recently discovered [Srivastava et al., Adv. Energy Mater., 2011, 1, 97]. In this paper, we study the efficiency and power output of this method. The formulas of efficiency and power output in terms of material constants, design parameters, and working conditions are derived. The Clausius-Clapeyron coefficient is shown to be important to the efficiency. The figure of merit, as a dimensionless parameter, of energy conversion using the new method is introduced. It is shown that, as the figure of merit goes to infinity, the efficiency approaches the Carnot efficiency. Thermodynamic cycles of the new energy conversion method are optimized for a maximum power output. The matching criteria between materials and working temperatures of such optimized cycles are derived. Using these criteria, one can choose the most suitable materials under given working conditions, or decide the best working conditions for available materials.

Dynamic Simulations of Semiconductor Optical Amplifier by Analytical Solution of Traveling-Wave Equation

Traveling-wave equation of the semiconductor optical amplifier is solved analytically in order to study the dynamical properties of the power output in terms of the input parameters that can influence its operation of semiconductor optical amplifier. Power output (number of photons) was calculated as a function of carrier density, input signal, and bias current. Material gain is found for the amplifier at different wavelengths of the input signal. The model investigated the population inversion along the waveguide of the amplifier. The model, which is used in this article, is one of many mathematical models that can be found in literature . The design of semiconductor amplifier in order to predict the operational characteristics can be obtained from its model. The simplicity of our model is in its ability to incorporate with any external stimulus on the amplifier directly in the wave equation. Keywords: SOA, Traveling-wave equation , Numerical simulations.

The influence of cadence and power output on force application and in-shoe pressure distribution during cycling by competitive and recreational cyclists

The aim of this study was to determine the response of cyclists to manipulations of cadence and power output in terms of force application and plantar pressure distribution. Two groups of cyclists, 17 recreational and 12 competitive, rode at three nominal cadences (60, 80, 100 rev min -1 ) and four power outputs (100, 200, 300, 400 W) while simultaneous force and in-shoe pressure data were collected. Two piezoelectric triaxial force transducers mounted in the right pedal measured components of the pedal force and orientation, and a discrete transducer system with 12 transducers recorded the in-shoe pressures. Force application was characterized by calculating peak resultant and peak effective pedal forces and positive and negative impulses. In-shoe pressures were analysed as peak pressures and as the percent relative load. The force data showed no significant group effect but there was a cadence and power main effect. The impulse data showed a significant three-way interaction. Increased cadence resulted in a decreased positive impulse, while increased power output resulted in an increased impulse. The competitive group produced less positive impulse but the difference became less at higher cadences. Few between-group differences were found in pressure, notable only in the pressure under the first metatarsal region. This showed a consistent pattern of in-shoe pressure distribution, where the primary loading structures were the first metatarsal and hallux. There was no indication that pressure at specific sites influenced the pedal force application. The absence of group differences indicated that pressure distribution was not the result of training, but reflected the intrinsic relationship between the foot, the shoe and the pedal.

Maximal physical work performance with European standard based fire-protective clothing system and equipment in relation to individual characteristics.

Every fire fighter needs to wear fire-protective clothing and a self-contained breathing apparatus (SCBA) several times a year while carrying out various fire-fighting and rescue operations in hazardous work environments. The aim of the present study was to quantify the effects of a multilayer turnout suit designed to fulfil European standard EN 469 used over standardized (Nordic) clothing and with SCBA (total mass 25.9 kg) on maximal physical work performance, and to evaluate the relationship between individual characteristics and power output with the fire-protective clothing system and SCBA. The subjects were 12 healthy firemen aged 26-46 years. The range of their body mass, body fat and maximal oxygen consumption was 69-101 kg, 10-20% and 2.70-5.86 l.min-1, respectively. The maximal tests without (control) and with the fire-protective clothing system and SCBA were carried out on a treadmill in a thermoneutral environment. When compared to the control test, the decrease in the maximal power output in terms of maximal working time and walking speed averaged 25% (P < 0.001) varying from 18% to 34% with the fire-protective clothing system and SCBA. At maximum, no significant differences were found in pulmonary ventilation, absolute oxygen consumption, the respiratory exchange ratio, heart rate, systolic blood pressure, the rate-pressure product, mechanical efficiency, and the rating of perceived exertion between the tests with and without the fire-protective clothing system and SCBA. The reduction of the power output was related to the extra mass of the fire protective clothing and SCBA.(ABSTRACT TRUNCATED AT 250 WORDS)

Optimum source amplitude for reduction of sound radiation by several point sources

A computer simulation of an array of point sources will be the focus of the noise reduction study. The amplitude of a select few of the point sources will be varied with the goal to reduce total sound output. The computer model will accept an array of up to ten points in any two-dimensional geometry. The phase and amplitude of the point sources can all be set independently. The chosen point sources will then have their amplitude varied over a specified range. The resulting total sound power output in terms of the amplitudes of the two varied sources can then be studied. There will be similarities in the behavior of a simple array of point sources and more complex vibrating structures such as a box. Understanding the behavior of the point source model will help lead to a method of optimization for more complex objects. [Work supported by NSF MSS-9103377.]