Modeling and simulation of photovoltaic (PV) system during partial shading based on a two-diode model

This paper proposes accurate partial shading modeling of photovoltaic (PV) system. The main contribution of this work is the utilization of the two-diode model to represent the PV cell. This model requires only four parameters and known to have better accuracy at low irradiance level, allowing for more accurate prediction of PV system performance during partial shading condition. The proposed model supports a large array simulation that can be interfaced with MPPT algorithms and power electronic converters. The accurateness of the modeling technique is validated by real time simulator data and compared with the three other types of modeling, namely Neural Network, P&O and single-diode model. It is envisaged that the proposed work is very useful for PV professionals who require simple, fast and accurate PV model to design their systems.     

The performance analysis of photovoltaic generation using the improved incremental conductance method under varying solar irradiance

Microsystem Technologies - Photovoltaic (PV) is an important clean and free-pollution renewable energy. The performance of a photovoltaic module is mostly affected by array configuration and solar...     

太阳能光伏电池测试系统硬件电路设计

设计了一种低成本、高可靠性和高灵活性的光伏电池测试系统的硬件测试电路,论述了硬件电路的设计方案、模块划分和相应电路的具体实现,为今后开发出能满足实际需要的光伏电池测试系统搭建了一个框架和系统平台。     

Optimisation of SU-8 processing parameters for deep X-ray lithography

The negative photoresist SU-8 has been recognised as an unique resist, equally useful for conventional UV lithography as well as deep X-ray lithography (DXRL) applications [2, 7, 12, 17, 18]. One of the major limitations in the use of SU-8 in lithographic processes is the occurrence of internal stress [15]. The processing parameters investigated for DXRL of SU-8 included resist thickness (450–850 m), soft bake time (7–11 h), exposure dose (30–70 J/cm³), post exposure bake time (20, 40, 60 min) and development time. The effect of these parameters on stress was evaluated using wafer curvature measurements. Taguchi optimisation techniques have been used to asses the contribution of these parameters on the stress of the developed structures. This study shows that softbake time contributes the most to stress in the SU-8 film at 50%, followed by the exposure dose and post exposure bake with 30% and 15% respectively. Stress varied somewhat linearly with thickness. At higher thickness, the deposition process needs to be changed for very high aspect ratio structures. The main objective of this work has been to optimise the processing conditions of thick SU-8 films for DXRL.This paper was first presented at the High Aspect Ratio Microstructurres (HARMST) conference in Montery California, June 2003.This work was supported by the Australian Synchrotron Research Program, which is funded by the Commonwealth of Australia under the Major National Research Facilities Program. Use of the Advanced Photon Source was supported by the U.S. Department of Energy, under Contract No. W-31-109-Eng-38. Support received from CRC for microTechnology (Australia) is also gratefully acknowledged. We also thank Dr. Brett Sexton and Fiona Smith from CSIRO (Australia), Dr. Francesco DeCarlo , Dr. Chian Liu, and Judy Yaeger from APS, and Dr. Jason Hayes and Dr. Matthew Solomon from Swinburne University for useful discussions and their help during some experimental work.     

An efficient concentrative photovoltaic solar system with Bayesian selection of optimal solar tracking algorithms

As the importance of sustainable energy has been rapidly growing, a concentrative photovoltaic (CPV) solar system is drawing much attention. In order for a system to operate efficiently, a deliberate solar tracking system must be equipped because an optimal tilt of solar panel is changed as the Sun orbits its trajectory. However, many existing tracking methods did not clearly consider the effect of various weather conditions, even though the performance of tracking method is subject to them. In this paper, we propose a CPV solar system that chooses the most proper solar tracking method among the group of heterogeneous tracking algorithms, based on an inference on the current weather conditions with Bayesian network (BN). We use 13 features derived from image processing and implement four tracking algorithms which have relative performance depending on nine different weather conditions. We constructed the working CPV system and collected the 1630 image data every three minutes for five hours over a period of 16 days. The proposed BN shows 93.9% accuracy for inferencing weather conditions, and the proposed system shows 16.58% higher power productivity, compared to a pinhole system and other existing methods.     

Prediction of ground motion parameters using randomized ANFIS (RANFIS)

In this paper, a novel neuro-fuzzy learning machine called randomized adaptive neuro-fuzzy inference system (RANFIS) is proposed for predicting the parameters of ground motion associated with seismic signals. This advanced learning machine integrates the explicit knowledge of the fuzzy systems with the learning capabilities of neural networks, as in the case of conventional adaptive neuro-fuzzy inference system (ANFIS). In RANFIS, to accelerate the learning speed without compromising the generalization capability, the fuzzy layer parameters are not tuned. The three time domain ground motion parameters which are predicted by the model are peak ground acceleration (PGA), peak ground velocity (PGV) and peak ground displacement (PGD). The model is developed using the database released by PEER (Pacific Earthquake Engineering Research Center). Each ground motion parameter is related to mainly to four seismic parameters, namely earthquake magnitude, faulting mechanism, source to site distance and average soil shear wave velocity. The experimental results validate the improved performance of the machine, with lesser computation time compared to prior studies.     

一种基于云台的智能太阳能光伏系统的设计

为了提高太阳能光伏系统的发电效率,设计了一种以单片机与光信号采集模块相结合控制步进电机转动的智能太阳能光伏系统。该系统以MSP-EXP430G2单片机为控制核心,以光敏阵列为信号采集模块,云台为动力模块。利用单片机对采集模块获得的光信号进行处理,通过ULN2003芯片组成的驱动电路驱动电机旋转,从而达到驱动云台上的光伏面板朝向光侧旋转一定角度的目的,最终实现太阳光的自动跟踪。结果表明,该系统运行稳定,可广泛应用于道路两侧、景区、公园等场所。     

Reconfiguration analysis of photovoltaic arrays based on parameters estimation

A method to determine the photovoltaic (PV) series–parallel array configuration that provides the highest Global Maximum Power Point (GMPP) is proposed in this paper. Such a procedure was designed to only require measurements of voltage and current of each string, which avoids to perform experiments in each module. The ideal single-diode model parameters of each module in the string are obtained from the analysis of the voltage vs. current characteristics of the string. Using the estimated parameters, all feasible PV array configurations are evaluated to determine the array configuration that provides the highest GMPP. Finally, the proposed solution is validated using simulations and experimental data.     

Modeling and simulation of a grid connected PV system based on the evaluation of main PV module parameters

In this work we present a new method for the modeling and simulation study of a photovoltaic grid connected system and its experimental validation. This method has been applied in the simulation of a grid connected PV system with a rated power of 3.2 Kw_p, composed by a photovoltaic generator and a single phase grid connected inverter. First, a PV module, forming part of the whole PV array is modeled by a single diode lumped circuit and main parameters of the PV module are evaluated. Results obtained for the PV module characteristics have been validated experimentally by carrying out outdoor I-V characteristic measurements. To take into account the power conversion efficiency, the measured AC output power against DC input power is fitted to a second order efficiency model to derive its specific parameters.The simulation results have been performed through Matlab/Simulink environment. Results has shown good agreement with experimental data, whether for the I-V characteristics or for the whole operating system. The significant error indicators are reported in order to show the effectiveness of the simulation model to predict energy generation for such PV system.     

Fabrication and photovoltaic effect of ZnO/silicon nanopillars heterojunction solar cell

Microsystem Technologies - A 300 nm thickness layer of zinc oxide (ZnO) film covers on the p-type silicon nanopillars surface to heterojunction solar cell. The original nanopillars are...     

Optimisation of algorithm control parameters in cultural differential evolution applied to molecular crystallography

Evolutionary search and optimisation algorithms have been used successfully in many areas of materials science and chemistry. In recent years, these techniques have been applied to, and revolutionised the study of crystal structures from powder diffraction data. In this paper we present the application of a hybrid global optimisation technique, cultural differential evolution (CDE), to crystal structure determination from powder diffraction data. The combination of the principles of social evolution and biological evolution, through the pruning of the parameter search space shows significant improvement in the efficiency of the calculations over traditional dictates of biological evolution alone. Results are presented in which a range of algorithm control parameters, i.e., population size, mutation and recombination rates, extent of culture-based pruning are used to assess the performance of this hybrid technique. The effects of these control parameters on the speed and efficiency of the optimisation calculations are discussed, and the potential advantages of the CDE approach demonstrated through an average 40% improvement in terms of speed of convergence of the calculations presented, and a maximum gain of 68% with larger population size.     

Long term (1983-1994) calibration of the Meteosat solar (VIS) channel using desert and ocean targets

The successive operational Meteosat solar (VIS) sensors have shown significant variations of their spectral band which affected their relative sensitivities to the light scattering by aerosols, molecules and Earth surface. This paper provides a calibration of the various Meteosat VIS sensors used between June 1983, the beginning of data archiving for the International Satellite Cloud Climatology Project (ISCCP), and December 1994, taking into account the characteristics of their individual spectral band thanks to an atmospheric radiative transfer model. The method is based on a monitoring of the reflectance of desert and ocean targets free of clouds and aerosols, and relies on the absolute vicarious calibration of Meteosat-2 performed in late 1981. We find different sensitivities and temporal evolutions for Meteosat-2, -3, -4, and -5, and our results compare well with other more limited calibration studies     

Optimisation of construction site layout using a hybrid simulation-based system

The layout of temporary facilities for a construction project greatly impacts project performance as demonstrated in many prior studies. This paper demonstrates how the site layout process can be automated for specific types of construction. Utility tunnel construction was selected as the specialty area, for which a partially automated site layout application was built. This approach integrates general purpose simulation for modelling space, logistics and resource dynamics with genetic algorithms for optimizing the layout based on various constraints and rules. We achieve this by implementing a site layout optimisation system within a simulation environment which already models tunnel construction processes. The new modelling strategy provides a medium for seamless integration between the resulting site layout and the discrete event production simulation models. The paper describes the approach taken and the system developed, presenting a practical case study from a tunnelling project in Edmonton, Canada to illustrate the system’s performance and its validation.     

Optimisation of garment design using fuzzy logic and sensory evaluation techniques

The ease allowance is an important criterion in garment design. It is often taken into account in the process of construction of garment patterns. However, the existing pattern generation methods cannot provide a suitable estimation of ease allowance, which is strongly related to wearer's body shapes and movements and used fabrics. They can only produce 2D patterns for fixed standard values of ease allowance. In this paper, we present a new method for optimizing the estimation of ease allowance of a garment using fuzzy logic and sensory evaluation. Based on the optimized values of ease allowance generated from fuzzy models related to different key body positions and different wearer's movements, we obtain an aggregated ease allowance using the OWA operator. This aggregated result can further improve the wearer's fitting perception of a garment and adjust the compromise between the style of garments and the fitting comfort sensation of wearers. The related weights of the OWA operator are determined according to designer's linguistic criteria on comfort and garment style. The effectiveness of our method has been validated in the design of trousers of jean type. It can be also applied for designing other types of garment.     

Optimisation of control parameters for genetic algorithms to test computer networks under realistic traffic loads

Although many studies have focused on testing computer networks under realistic traffic loads by means of genetic algorithms (GAs), little attention has been paid to optimising the parameters of the GAs in this problem. The objective of this work is to design and validate a system that, given some constraints on traffic bandwidth, generates the worst-case traffic for a given computer network and finds the traffic configuration (critical background traffic) that minimises throughput in that computer network. The proposed system is based on a meta-GA, which is combined with an adaptation strategy that finds the optimum values for the GA control parameters and adjusts them to improve the GA's performance. To validate the approach, different comparisons are performed with the goal of assessing the acceptable optimisation power of the proposed system. Moreover, a statistical analysis was conducted to ascertain whether differences between the proposed system and other algorithms are significant. The results demonstrate the effectiveness of the system and prove that, when the background traffic is driven by a GA that uses the parameters obtained from the system, the computer network's performance is much lower than when the traffic is generated by Poisson statistical processes or by other algorithms. This system has identified the worst traffic pattern for the protocol under analysis.     

Estimation of solar radiation using artificial neural networks with different input parameters for Mediterranean region of Anatolia in Turkey

An artificial neural network (ANN) model was used to estimate the solar radiation parameters for seven cities from Mediterranean region of Anatolia in Turkey. As well known that Turkey is a bridge between Asia and Europe and it lies in a sunny belt, between 36° and 42°N latitudes. Indeed, the country has sufficient solar radiation intensities for solar applications. In order to make estimation of solar radiation, the data from the Turkish State and Meteorological Service were used. Data of 2006 were used for testing and data of 2005, 2007, and 2008 were estimated. Effects of number of input parameters were tested on solar radiation that was output layer. With this aim, number of input layer parameters changed from 2 to 6. The obtained results indicated that the method could be used by researchers or scientists to design high efficiency solar devices. It was also found that number of input parameters was the most effective parameter on estimation of future data on solar radiation.