A note on design of linear dielectric compound parabolic concentrators
Abstracts:In this communication, three-dimensional radiation transfer within linear dielectric compound parabolic concentrators (DCPC) is investigated based on vector algebra and solar geometry, and the design of DCPC oriented in east-west direction is addressed. The analysis shows that, the projected incident and refractive angles of solar rays on the cross-section of DCPC are not subjected to the correlation as Snell law except for incident rays on the cross-section, hence, the acceptance half-angle (θa ) of DCPC should be determined based on time variations of projected refractive angle and minimum time (2t c) required to concentrate direct sunlight in all days of a year. It is also found that, to make all refractive radiation within θa are totally internally reflected onto the absorber, DCPC with a restricted exit angle (DCPC-θa /θe should be employed, and solar leakage from walls of DCPC-/90 can be avoided or reduced by increasing θa and number of periodical tilt-angle adjustment in a year. Calculations show that, the minimum θa of DCPC depends on tc and strategy of tilt-angle adjustment; and for a given tc , the ratio (Rc ) of maximum geometric concentration of DCPC to that of reflective CPC (n = 1) is dependent on number of periodical tilt-angle adjustment in a year, but always larger than refractive index (n) of dielectric. Calculations also indicate that, for DCPCs with n > 1.4, when solar rays incident towards onto right/left wall, the radiation incident on its opposite wall (left/right) will be totally internally reflected, and multiple reflections of solar rays on way to the absorber will also be total internal reflection for radiation within its acceptance angle.
Five-year performance and reliability analysis of monocrystalline photovoltaic modules with different backsheet materials
Abstracts:Elevated operating temperatures decrease the energy yield and reliability of photovoltaic (PV) systems. In order to minimize these thermal losses and stresses, different types of packaging materials for PV modules need to be examined with respect to their electrical and thermal performance but also their reliability and durability. This study analyses the performance and reliability of identical monocrystalline Silicon PV modules with different backsheet materials including aesthetically enhanced all-black PV modules employing black backsheets. The modules were installed to form grid-connected systems with an approximate nominal capacity of 1.2 kWp, and were exposed under the warm climatic conditions of Cyprus. The results of the five-year evaluation period showed that despite the use of black backsheets, temperature improvements were achieved verifying that backsheets influence the cell temperature and enhance performance by operating at lower temperatures. More specifically, the comparative analysis of the thermal behavior, based on acquired cell temperature measurements, verified that backsheets can be designed to influence the cell temperature and enhance performance by operating at lower temperatures in some cases up to 10 °C. The systems with the backsheets that retained lower operating temperatures produced higher annual energy yield, under the warm conditions exposed due to reduced thermal losses. In particular, the annual energy yield results showed that the systems equipped with the white control and black color thermal management backsheet produced consistently the highest annual energy yield over the evaluation period. Finally, the results of the indoor and outdoor degradation rate analysis showed that, over the five-year period, there was no significant difference in the estimated degradation rate amongst the installed systems, since the results are within the uncertainty range.
Day-ahead probabilistic PV generation forecast for buildings energy management systems
Abstracts:The photovoltaic (PV) generation forecast is a key element to an efficient building energy management system (EMS) operation. The forecast’s uncertainties and generation variabilities expose the loads to misplanning, and hence decrease building autonomy, self-sufficiency, and potential costs savings. In this paper, a novel approach for a day-ahead PV power generation probabilistic forecast is proposed that is especially optimized for building EMS applications. The model consists of several modules to develop the probabilistic forecast. Initially, a clear sky model is tuned to incorporate the system and temperature losses and partial shading. The deviation of the PV power from the clear sky power is used to train a bagging regression tree, which produces a deterministic point forecast. The probabilistic forecast is developed based on the probabilistic analysis of the point forecast and regenerating it based on the given weather conditions. The model is developed based on the available data in buildings such as the historic PV measurements acquired from the inverter and the weather forecasts. The probabilistic forecast was validated over a complete-year data set of a rooftop PV system in Munich, Germany, where the results showed its capability to provide an accurate and reliable forecast for EMS applications.
A novel single switch dc-dc converter with high voltage gain capability for solar PV based power generation systems
Abstracts:This paper presents a single switch non-isolated DC-DC converter with high voltage gain capability for solar photovoltaic (PV) applications. The proposed converter is synthesized from passive switched inductor (SI) and switched capacitor (SC) topologies and integrated with an additional voltage boost capacitor to enhance the voltage gain. Due to the converter structure and adopted gain extension technique, the voltage stress on the switch and three diodes is 50% of the output voltage, while the remaining diodes experience a voltage stress of only 25% of the output voltage. Experimental results obtained from a 34 V/380 V, 200 W prototype converter validate the proposed concept, adopted design procedure and illustrates the fact that the proposed converter operates at a full load efficiency of 93%. Further, the proposed converter provides better component utilization compared to some existing converters.
A multi-model benchmarking of direct and global clear-sky solar irradiance predictions at arid sites using a reference physical radiative transfer model
Abstracts:This study provides a comparison of the predictions of fifteen clear-sky irradiance models against those from the RRTMG radiative transfer. RRTMG is selected as the benchmarking reference here because its code is open source and features a good compromise between accuracy, ease of use, and speed of execution, which should guarantee reproducible results by a majority of solar analysts. The model comparisons are undertaken at ten worldwide sites of importance for concentrating solar power (CSP) projects, and at a highly turbid desert site. The models’ inputs are directly or indirectly obtained from worldwide reanalyses having a spatial resolution of 1.125° × 1.125°. The simulations of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are done hourly over a whole year (2012).
Parameter identification for solar cells and module using a Hybrid Firefly and Pattern Search Algorithms
Abstracts:Accurate estimation the electrical equivalent circuit parameters of photovoltaic arrays of solar cells is needed to enhance the performance of solar energy systems. Thus this field has attracted the attention of various researchers. Since the current versus voltage I-V characteristics of photovoltaic is nonlinear, thus an optimization technique is necessary to adjust experimental data to the solar cell model. Some optimization algorithms have been used to estimate the electrical parameters of the model. However, more investigation is needed to improve estimation of the model. The Firefly algorithm is one of the recently proposed swarm intelligence based optimization algorithm that showed impressive performance in solving optimization problems. This algorithm is good for exploring solution if applied alone but need a local optimization method to improve exploitation. In this study, we combine pattern search as a local optimization method with firefly algorithm to improve this algorithm. The proposed algorithm is applied for parameter estimation of single and double diode solar cell models. To show the performance of this algorithm the results are compared, with the other optimization algorithms for parameters of photovoltaic. The results show that the proposed algorithm is a competitive algorithm to be considered in the modeling of solar cell systems.
Synthesis of MoS2/YVO4 composite and its high photocatalytic performance in methyl orange degradation and H2 evolution
Abstracts:This work was designed to ameliorate the photocatalytic performance of YVO4 by using MoS2 as a co-catalyst. MoS2 was in-situ decorated on the surface of YVO4 nanoparticles through a simple hydrothermal process. The synthesized MoS2/YVO4 composite was characterized by various techniques, including XRD, Raman, XPS, SEM, TEM, DRS, PL, EIS and PC. Results indicate that MoS2 acts as an electron trapper in the binary system, which hinders the recombination of charge carriers and enhances the utilization of the photogenerated charge carriers in the photocatalytic reaction. Therefore, MoS2/YVO4 composite presents high activity in the photocatalytic degradation of methyl orange (MO) and the generation of H2 under simulated sunlight irradiation. 2.5% MoS2/YVO4 sample has the best performance in H2 generation with a H2-evolution rate of 134 μmol g−1 h−1, which is 11.2 times higher than that of pure YVO4. For photocatalytic degradation of MO, 10%MoS2/YVO4 shows the best efficiency. The degradation rate constant is 4.4 times larger than that of pure YVO4. The different optimal content of MoS2 can be ascribed to that the two reactions are performed in different ways. This work may provide some valuable information for the future design of high efficient photocatalysts by using MoS2 as a co-catalyst.
Design and verification of photovoltaic MPPT algorithm as an automotive-based embedded software
Abstracts:This paper presents the design and verification process of the Maximum Power Point Tracking Controller in accordance with the automotive development process standards, which could be used in Photovoltaic charging stations or in on-board chargers of electric vehicles. Considered as an automotive embedded software, the designed MPPT controller follows a sequence of three tests of the Model-based design MBD Approach to be verified and validated. The ultimate aim is to present a road map to design, test and validate an embedded software of the MPPT algorithm in vehicle based software. We design a modified Perturb and Observe P&O algorithm, then we generate optimized C code for a 32 bit ARM cortex microcontroller. Next, the algorithm is simulated through Model-in-the loop MIL, Software-in-the loop SIL, and finally co-simulated through Processor-in-the-loop PIL technique in the low cost STM32F429 discovery development board. During all the different tests, the designed embedded software shows a high accordance with MPPT requirement and high performances.
Probabilistic forecasting of solar power, electricity consumption and net load: Investigating the effect of seasons, aggregation and penetration on prediction intervals
Abstracts:This paper presents a study into the effect of aggregation of customers and an increasing share of photovoltaic (PV) power in the net load on prediction intervals (PIs) of probabilistic forecasting methods applied to distribution grid customers during winter and spring. These seasons are shown to represent challenging cases due to the increased variability of electricity consumption during winter and the increased variability in PV power production during spring. We employ a dynamic Gaussian process (GP) and quantile regression (QR) to produce probabilistic forecasts on data from 300 de-identified customers in the metropolitan area of Sydney, Australia. In case of the dynamic GP, we also optimize the training window width and show that it produces sharp and reliable PIs with a training set of up to 3 weeks. In case of aggregation, the results indicate that the aggregation of a modest number of PV systems improves both the sharpness and the reliability of PIs due to the smoothing effect, and that this positive effect propagates into the net load forecasts, especially for low levels of aggregation. Finally, we show that increasing the share of PV power in the net load actually increases the sharpness and reliability of PIs for aggregations of 30 and 210 customers, most likely due to the added benefit of the smoothing effect.
In situ growth of ultrathin Co-MOF nanosheets on α-Fe2O3 hematite nanorods for efficient photoelectrochemical water oxidation
Abstracts:Efficient charge transport is an important factor in photoelectrochemical (PEC) water splitting. The charge transfer at the semiconductor/electrolyte interface is of great importance, especially for the complex water oxidation reaction. In this study, we explored the feasibility of improving charge transfer efficiency at the interface of semiconductor/electrolyte by in situ growth of Co based Metal-Organic Frame work (Co-MOF) through a facile ion-exchanging method. Under optimized conditions, the Co-MOF nanosheet-modified hematite gave a photocurrent density of 2.0 mA cm−2 (200% improvement) at 1.23 VRHE with a cathodic shift of 180 mV in the photocurrent onset potential, in comparison to bare α-Fe2O3 (0.71 mA cm−email@example.com VRHE). To elucidate the role of Co-MOF, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy and Mott-Schottky measurements were carried out. It was found that the atomically distributed Co2+ in Co-MOF possessed excellent hole storage capability and charge transfer efficiency, as evidenced by the high surface capacitance and extremely low surface charge transfer resistance.