Index of content:
Volume 8, Issue 1, January 2016
- Bioenergy and Biofuels
Layer characterization and photovoltaic properties of CdS/multi-wall carbon nanotube/n-Si device with an n-p-n transistor structure8(2016); http://dx.doi.org/10.1063/1.4939506View Description Hide Description
A new type of n-p-n transistorphotovoltaic device based on CdS/multi-wall carbon nanotube (MWNT)/n-Si configuration was fabricated in a facile process. CdS quantum dots were deposited on fluorine-doped tin-oxide glass using a chemical bath deposition method, and MWNTfilm was coated on n-type Si substrate by airbrushing. The materials used for the n-p-n transistorsolar cells were characterized by multiple techniques including X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, Raman, Ultraviolet visible (UV-vis) spectrophotometer, and I-V characteristic measurements. The CdS layer acts as a good n-type material for the transistorsolar cells. The thickness of the CdS layer can be controlled by the chemical bath deposition time to achieve different photovoltaic responses. I-V characteristic measurements show that the efficiency increases with increasing the thickness of the CdS thin layer. Compared with the tandem solar cells based on (p/n)–(p/n) semiconductor junctions, our n-p-n transistorsolar cell has a simple structure without using tunnel junctions or wafer bonding schemes for interconnecting the cells.
8(2016); http://dx.doi.org/10.1063/1.4939561View Description Hide Description
This work evaluates the influence of temperature and irradiation on the behavior of mono-crystalline silicon, poly-crystalline silicon, and Copper Indium diselenide (CIS), modules which have been exposed to real conditions. An outdoor experimental setup has been installed, at a Mediterranean site in north latitude 38 °, in order to collect results from current-voltage measurements that corresponded at constant radiation level in order to evaluate the effect of temperature and results from measurements realized at about the same temperature in order to study the effect of irradiation. The results present that the daily generated power normalized to the manufacturer's value is positively influenced by the irradiation and not by the negative effect of temperature. The performance of mono and poly Si appears superior to that of CIS early in the morning, while this advantage is diminished during midday, when the temperature and irradiance are highest, as CIS performance becomes comparable to the other two. However, the temperature affects the efficiency and fill factor for the mono and poly-Si modules recording the lower values on higher temperatures, while it does not the same for the CIS modules. This experimental study can provide information for locations with similar climatic conditions because it helps to take into account variation in temperatures together with variation in radiation and to avoid under-designing of photovoltaic systems and system malfunction.
Comparative performance analysis of jatropha, karanja, mahua, and polanga based biodiesel engine using hybrid genetic algorithm8(2016); http://dx.doi.org/10.1063/1.4939513View Description Hide Description
The nonedible based biodiesels (jatropha, karanja, mahua, and polanga) have been evaluated in a single cylinder, direct injection diesel engine for their performance, combustion, and emission parameters using hybrid response surface methodology-non-dominated sorting genetic algorithm-II technique. The sets of pareto optimum solutions for each biodiesel produced have also been presented in the form. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results. None of the solutions is better than the other, and each solution has its own importance. The summary of desired performance, combustion, and emission parameters of produced biodiesels is presented for further use in the diesel engine. The results obtained are far reaching and they can be directly referred to for similar types of diesel engines.
A novel combined forecasting model for short-term wind power based on ensemble empirical mode decomposition and optimal virtual prediction8(2016); http://dx.doi.org/10.1063/1.4939543View Description Hide Description
As one of the most promising renewable energy, wind energy plays a vital role in optimizing the configuration of energy resources in power system nowadays. However, wind generation with the intermittent and uncertain characteristics has brought new challenges for the integration of large-scale wind power into power system. Consequently, the accurate forecasting of wind power is the most effective and applicable solution to meet the challenges. A novel combined forecasting approach is proposed by integrating the ensemble empirical mode decomposition (EEMD) technique and the combination of individual forecasting methods based on optimal virtual prediction for the purpose of improving the short-term wind power prediction performance. There are three steps in this presented approach. First, EEMD is adopted to decompose the original wind power series into a number of intrinsic mode functions (IMFs) and a residue. Second, the prediction of each IMF is achieved by using four individual methods, and the prediction of the residue is obtained from the nonlinear grey Bernoulli model based on particle swarm optimization. Finally, the combined forecasting model based on optimal virtual prediction is developed, and the weight matrix in this model is optimized by a self-adaptive differential evolution algorithm, which aims to minimize the forecasting errors at the virtual prediction points. The real wind power data from a wind farm in China are used to verify the performance of the proposed model, and the simulation results show that this model has demonstrated the optimal forecasting accuracy and robustness compared with other forecasting models, which is a promising alternative for short-term wind power forecasting.
8(2016); http://dx.doi.org/10.1063/1.4939554View Description Hide Description
This study proposes a new method for direct generation of synthetic wind power time series for a wind farm. The method combines the random nature of wind with the operational information of the wind turbines (i.e., failure and repair rates). It uses chronological or sequential Monte Carlo Simulation instead of non-sequential one due to its usefulness and flexibility in preserving statistical characteristics of the chronological processes. The validity of the synthetic values generated by the proposed method and the conventional Markov Chain Monte Carlo methods is compared with the measured data in terms of average and variance values, Probability Distribution Function, and Auto-Correlation Function. Due to increasing interest in the use of the storage system in paralleling with wind power generation, a practical application of the proposed method is also included. Optimal sizing of various energy storage technologies is obtained through a cost-benefit analysis in a typical Micro-Grid.
Voltage band based improved particle swarm optimization technique for maximum power point tracking in solar photovoltaic system8(2016); http://dx.doi.org/10.1063/1.4939531View Description Hide Description
The extraction of maximum power from solar photovoltaic (PV) using Maximum Power Point Tracking (MPPT) methods is a promising research area in the recent past. Many methods including conventional methods, such as Hill Climbing and Incremental Conductance, and methods based on neural network, Fuzzy logic and bio-inspired algorithms, were proposed for MPPT application. However, all these methods suffer from drawbacks such as slower convergence, reduced power output, predominant steady state oscillations, larger memory requirement, and complex structure. Hence, in this paper an attempt is made to enhance existing Particle Swarm Optimization technique by emphasizing proper initial value selection. The key features of this method include the ability to track the global peak power accurately under partial shading conditions with almost zero steady state oscillations, faster dynamic response, and easy implementation. Simulations are carried out for different shading patterns and the results obtained are compared with existing methods. Further, simulation results are validated via experimental values.
Optimizing the physical parameters for bio-hydrogen production from food waste co-digested with mixed consortia of clostridium8(2016); http://dx.doi.org/10.1063/1.4939767View Description Hide Description
Food waste along with its two individual components, noodle waste and rice waste, were tested for bio-hydrogen production by using sludge as a source of mix consortia of Clostridium under different physical conditions (pH 5, 6, and 7; temperature 37 °C and 55 °C). The increase in pH increased the bio-hydrogen yield for all tested wastes, whereas an increase in temperature increased the bio-hydrogen yield just for food waste. The highest experimental yield of 115.76 ml/VSremoved was produced in the mesophilic noodle waste reactor at pH 7. The drop in pH from 7 to 4.8 ± 0.2 was found optimum for bio-hydrogen production for all tested wastes under mesophilic as well as thermophilic conditions. Most of the hydrogen production was observed within 72 h of incubation, which can be used as the optimum bio-hydrogen production period for food waste. The bio-hydrogen yield, final volatile fatty acids (VFA), and glucose consumption at 72 h were analyzed with the help of the response surface methodology. The resultant plots represented an increase in glucose consumption with the increase in pH from 5 till pH 6 ± 0.5, after which glucose consumption started to decrease up to pH 7. The final VFA represented a similar trend as that observed for glucose except that the change in VFA production was observed due to the temperature and transition was observed at 47.5 ± 1.5 °C for food waste as well as for noodle waste.
8(2016); http://dx.doi.org/10.1063/1.4940660View Description Hide Description
To enhance the value of corn stalk and promote the utilization of corn stalk in pellet fuel, the pelletizing process of corn stalk rind using a flat die pelletizer was studied. A central composite design (CCD) methodology of four factors and five levels was applied to determine the effects of four process variables, i.e., material temperature, moisture content, die hole length-diameter ratio, and spindle speed, on responses such as pellet density and power consumption per ton. The statistical analysis of data was performed using Design-expert software and second-order polynomial models generated after analysis of variance applied for the responses. Using response surface methodology, the optimal range of process variable was obtained as follows: material temperature of 78.7 to 91.1 °C moisture content of 17.6% to 26.9%, die hole length-diameter ratio of 2.62–3.04, and spindle speed of 168.2–210.5 rpm. Under these conditions, the pellet density is over 1.0 g/cm3 and power consumption per ton is below 90 kW · h/t.
- Wind Energy
Characterization of wind velocities in the upstream induction zone of a wind turbine using scanning continuous-wave lidars8(2016); http://dx.doi.org/10.1063/1.4940025View Description Hide Description
As a wind turbine generates power, induced velocities, lower than the freestream velocity, will be present upstream of the turbine due to perturbation of the flow by the rotor. In this study, the upstream induction zone of a 225 kW horizontal axis Vestas V27 wind turbine located at the Danish Technical University's Risø campus is investigated using a scanning Light Detection and Ranging(lidar) system. Three short-range continuous-wave “WindScanner” lidars are positioned in the field around the V27 turbine allowing detection of all three components of the wind velocity vectors within the induction zone. The time-averaged mean wind speeds at different locations in the upstream induction zone are measured by scanning a horizontal plane at hub height and a vertical plane centered at the middle of the rotor extending roughly 1.5 rotor diameters (D) upstream of the rotor. Turbulence statistics in the induction zone are studied by more rapidly scanning along individual lines perpendicular to the rotor at different radial distances from the hub. The mean velocity measurements reveal that the longitudinal velocity reductions become greater closer to the rotor plane and closer to the center of the rotor. Velocity deficits of 1%–3% of the freestream value were observed 1 D upstream of the rotor, increasing at the rotor plane to 7.4% near the edge of the rotor and 18% near the center of the rotor while the turbine was operating with a high estimated mechanical coefficient of power (CP) of 0.56 yielding an estimated axial induction factor of 0.25. The velocity reductions relative to the freestream velocity become smaller when the turbine's coefficient of power decreases; for a low CP of 0.16 resulting in an estimated induction factor of 0.04, the velocity deficits are ∼1% of the freestream value 1 D upstream of the rotor and only 6% at the rotor plane near the center of the rotor. Additionally, the mean radial wind speeds were found to increase close to the edge of the rotor disk indicating an expansion of the incoming flow around the rotor. Radial velocity magnitudes at the edge of the rotor disk of approximately 9% and 3% of the freestream longitudinal wind speed were measured for the abovementioned high and low CP values, respectively. Turbulence statistics, calculated using 2.5-min time series, suggest that the standard deviation of the longitudinal wind component decreases close to the rotor, while the standard deviation of the radial wind component appears to increase. When the turbine was operating with a high CP of 0.54 resulting in an estimated induction factor of 0.22, standard deviation decreases of up to 22% of the estimated freestream value and increases of up to 46% were observed for the longitudinal and radial components, respectively, near the center of the rotor.
A wind power forecasting system based on the weather research and forecasting model and Kalman filtering over a wind-farm in Japan8(2016); http://dx.doi.org/10.1063/1.4940208View Description Hide Description
The rapid development of wind energy in Japan and the associated high uncertainties and fluctuations in power generation present a big challenge for both wind power generators and electric grids. Accurate and reliable wind power predictions are necessary to optimize the integration of wind power into existing electrical systems. In this study, a hybrid forecasting system of wind power generation was developed by integrating the Kalman filter (KF) with the high resolution Weather Research and Forecasting (WRF) model as well as an empirical formula of wind power output (power curve). The system has been validated with observations including wind speed and power output over a six-month period for 15 turbine sites at a wind farm in Awaji-island, Japan. The results show that the tuned WRF model is able to provide hub-height wind speed prediction for the target area with reliability to some extent. The predicted wind field can be substantially improved by the Kalman filter as a post-processing procedure. The 15-turbine averaged improvements of mean error, root mean square error, and correlation coefficient are 97%, 22%, and 10%, respectively. Meanwhile, the Kalman filter also demonstrates a promising capability of reducing the uncertainties in the power curve model. Systematic validations regarding both wind speed and power output were carried out against the observations for the target wind farm, which show that the hybrid power forecasting system presented in this paper can be an effective and practical tool for short-term predictions of wind speed and power output in Japan area.
Wind tunnel investigation on the two- and three-blade Savonius rotor with central shaft at different gap ratio8(2016); http://dx.doi.org/10.1063/1.4940434View Description Hide Description
The Savonius rotor seems to be a promising wind turbine as it not only has the simplest and cheapest design but also is capable of yielding a higher annual energy output at low wind speed than the Darrieus rotor. Moreover, the Savonius rotor can also be used in ventilation systems, for local electricity production, as the start-up device for the Darrieus rotor, and small hydrokinetic turbines operating at low velocity. As a two-blade Savonius rotor suffers from negative average static torque coefficient (ACTS) at some azimuth angles and large-amplitude variation of ACTS, several studies have been conducted in recent years to improve ACTS. The three-blade rotor seems to be a potential candidate for ACTS improvement. However, less research has been done on three-blade rotors with a 180° arc and central shaft at different gap ratios (GRs) for different wind speeds. Therefore, the focus of the present work is to compare the two- and three-blade rotor in terms of ACTS and power coefficient (CP) through a wind tunnel experiment. Results show that the wind speed had a small effect on ACTS. However, negative azimuth angle range is narrowed and the negative azimuth angle range is moved upward as GR increased. Hence, the Savonius rotor with three blades could not only eliminate the negative range of ACTS but also smooth ACTS curves. In terms of the CP, the maximum power coefficient of the two-blade configuration was approximately 1.5 times that of the three-blade configuration. The 1/6 GR test data exhibited the attainment of super performance for all wind speed and blade number.
- Marine and Hydroelectric Energy
8(2016); http://dx.doi.org/10.1063/1.4940023View Description Hide Description
This study presents full transient numerical simulations of a cross-flow vertical-axis marine current turbine (straight-bladed Darrieus type) with particular emphasis on the analysis of hydrodynamic characteristics. Turbine design and performance are studied using a time-accurate Reynolds-averaged Navier–Stokes commercial solver. A physical transient rotor-stator model with a sliding mesh technique is used to capture changes in flow field at a particular time step. A shear stress transport k-ω turbulencemodel was initially employed to modelturbulent features of the flow. Two dimensional simulations are used to parametrically study the influence of selected geometrical parameters of the airfoil (camber, thickness, and symmetry-asymmetry) on the performance prediction (torque and force coefficients) of the turbine. As a result, torque increases with blade thickness-to-chord ratio up to 15% and camber reduces the average load in the turbine shaft. Additionally, the influence of blockage ratio, profile trailing edge geometry, and selected turbulencemodels on the turbine performance prediction is investigated.
- Energy Efficient Buildings
8(2016); http://dx.doi.org/10.1063/1.4940433View Description Hide Description
In this paper, a double-glazed solar air heater (SAH) using paraffin wax as phase changematerial (PCM) was designed, fabricated, and tested under the climatic condition of Mashhad, Iran (latitude, 37° 28′ N and longitude, 57° 20′ E) during three typical days in the summer. The PCM stores solar radiation of the sun as latent and sensible heat during daytime and then restores such stored energy during the night. Exploitation of both first and second laws of Thermodynamics, the energy and exergy efficiencies of this system are assessed. According to the experiments undertaken, it is found that the daily energy efficiency of the system varies between 58.33% and 68.77%, whereas the daily exergy efficiency varies from 14.45% to 26.34%. Eventually, the economic analysis shows that the cost of 1 kg of heated air utilizing double-glazed SAH would be 0.0036$.
- Power Distribution and Systems Modeling
Research and application of a hybrid forecasting model based on simulated annealing algorithm: A case study of wind speed forecasting8(2016); http://dx.doi.org/10.1063/1.4940408View Description Hide Description
As a promising renewable energy source, wind energy has increasingly gained worldwide attention. Providing high accuracy wind energy forecasting allows us to improve the economic and social benefits of wind power management, which reduces the generation costs and improves the security of the wind power system. In this paper, a novel hybrid forecasting model called E-SA-BP, which combines ensemble empirical mode decomposition, a simulated annealing (SA) algorithm, and a back-propagation neural network (BPNN), is developed to perform wind speed forecasting. First, ensemble empirical mode decomposition is used to decompose the original wind speed data series aiming to de-noise and then reconstruct the data series. Next, BPNN is applied to perform short-term wind speed forecasting, because BPNN can implement any complex nonlinear mapping function (as proven by mathematical theory) and approximate an arbitrary nonlinear function with satisfactory accuracy. However, due to the instability of the structure of the BPNN, SA is utilized to optimize the weight and threshold values of the BPNN through simulating the annealing process of metal objects after heating. Last, the data of six wind speed observation sites in Jiaodong Peninsula of China are chosen to test the performance of the forecasting models. The results show an effective decrease in the forecasting errors of E-SA-BP when it is compared with the Moving Average(1), Exponential Smoothing (ES)(1), ES(2), Autoregressive Moving Average Model, Autoregressive Integrated Moving Average, BP, SA-BP, and E-BP models.
- Sustainable Transportation
8(2016); http://dx.doi.org/10.1063/1.4938552View Description Hide Description
Energy management strategies significantly influence the fuel efficiency of hybrid electric vehicles. They play a crucial role in splitting the power between two sources, namely, engine and the battery. Power split between these two intelligently will enhance the fuel economy and regulates the power flow. Power split between engine and motor depends on state of charge (SOC) of battery, power required at the wheels, and engine's operating range. Various parameters of power train are considered to control the toggling between engine and battery. To achieve parameter optimization, genetic algorithm is practised to realize the optimal performance. A modified SOC estimation algorithm is employed with different battery models to analyze the vehicle performance. The battery models with internal resistance only and combinations of 1RC and 2RC are used. Parameter optimization over different battery models with modified SOC estimation algorithm is performed in different situations and a comparative study is elaborated.
Modeling operation of electric vehicles aggregator with energy storage system in reserve services market8(2016); http://dx.doi.org/10.1063/1.4940406View Description Hide Description
An electric vehicles aggregator is in fact an intermediate between electric vehicles and the operator of the power grid. The Electric Vehicles (EVs) aggregator is responsible for the management of EVs in order to supply the owners with their orders and also for maximizing the profit of the power grid in the electricity market. In this study, an optimization model was developed for the operation of the EVs aggregator with an energy storage system in the reserve services market of the distribution network. In the proposed model, the reserve services market was formed after termination of the energy market. In this paper, the markets were created 24 h earlier.
- Renewable Energy Economics and Policy
Energy efficiency measures for airlines: An application of virtual frontier dynamic range adjusted measure8(2016); http://dx.doi.org/10.1063/1.4938221View Description Hide Description
In this paper, the energy efficiency of airlines is measured. Number of employees and tons of aviation kerosene are chosen as the inputs. Revenue tonne kilometers, revenue passenger kilometers, and total business income are the outputs. Capital stock is selected as the dynamic factor. A new model, Virtual Frontier Dynamic range adjusted measure (RAM), is proposed to calculate the energy efficiencies of 22 airlines from 2008 to 2012. In Virtual Frontier Dynamic RAM, the reference DMU (decision-making unit) set and the evaluated DMU set are two different sets to distinguish between efficient DMUs. The results demonstrate the following: (1) Air Greenland exhibits the highest energy efficiency, while the efficiency score of Air France-KLM is at the bottom of the 22 airlines. (2) Aggregate airline energy efficiency consistently increased from 2008 to 2012.
A new approach in solar-to-laser power conversion based on the use of external solar spectrum frequency converters8(2016); http://dx.doi.org/10.1063/1.4939505View Description Hide Description
A new approach based on the use of external frequency converters for Nd:YAG solar pumped lasers providing effective conversion of solar-to-laser power is proposed. The possibility of a more than four-fold increase in Nd:YAG solar pumped laser efficiency is shown by the simulation calculation method.
A conceptual model to select project contractors for environmental management system in photovoltaic energy companies8(2016); http://dx.doi.org/10.1063/1.4939058View Description Hide Description
Firms in the power industry are currently facing challenges to maintain competitiveness while maintaining minimal environmental impacts. Responding to the above challenges, environmental management systems (EMSs) are becoming more popular within organizational policies, programs, and operating agendas. Especially in the knowledge-based photovoltaic energy industry, the learning efforts of EMSs can effectively improve technological development, managing efficiency, and firm performance at the same time. However, with rapidly changing technologies along with increasingly complicated environments, how to select a suitable project contractor for EMS has become an important issue that has never been discussed comprehensively. Through the proposed methodology, practitioners can fully understand the expected performance of each EMS contractor under various aspects, and the most appropriate EMS contractor with the best synthesized performance can be selected under the complex and dynamic environment. The methodology shall enable firms to select the most suitable EMS project contractors.