PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.

Equações de Painlevé mistas e modelo PIII-PV simétrico

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelling real solar cell using PSCAD/MATLAB

This paper presents the development of a solar photovoltaic (PV) model based on PSCAD/EMTDC - Power System Computer Aided Design – including a mathematical model study. An additional algorithm has been implemented in MATLAB software in order to calculate several parameters required by the PSCAD developed model. All the simulation study has been performed in PSCAD/MATLAB software simulation tool. A real data base concerning irradiance, cell temperature and PV power generation was used in order to support the evaluation of the implemented PV model.

Modeling of Distributed Generation under Next Generation Interconnection Requirements

Thesis (Master's)--University of Washington, 2016-06

Experimental Model to estimate shading losses on PV arrays

This paper presents a simple mathematical model to estimateshadinglosses on PVarrays. The model is applied directly to power calculations, without the need to consider the whole current–voltage curve. This allows the model to be used with common yield estimation software. The model takes into account both the shaded fraction of the array area and the number of blocks (a group of solar cells protected by a bypass diode) affected by shade. The results of an experimental testing campaign on several shaded PVarrays to check the validity of model are also reported.

Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model

The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

Experimental model to estimate shading losses on PV arrays

This paper presents a simple mathematical model to estimate shading losses on PV arrays. The model is applied directly to power calculations, without the need to consider the whole current–voltage curve. This allows the model to be used with common yield estimation software. The model takes into account both the shaded fraction of the array area and the number of blocks (a group of solar cells protected by a bypass diode) affected by shade. The results of an experimental testing campaign on several shaded PV arrays to check the validity of model are also reported.

An accurate model for simulating energetic behavior of PV grid connected inverters

This paper proposes a new model for characterizing the energetic behavior of grid connected PV inverters. The model has been obtained from a detailed study of main loss processes in small size PV inverters in the market. The main advantage of the used method is to obtain a model that comprises two antagonistic features, since both are simple, easy to compute and apply, and accurate. One of the main features of this model is how it handles the maximum power point tracking (MPPT) and the efficiency: in both parts the model uses the same approach and it is achieved by two resistive elements which simulate the losses inherent to each parameter. This makes this model easy to implement, compact and refined. The model presented here also includes other parameters, such as start threshold, standby consumption and islanding behavior. In order to validate the model, the values of all the parameters listed above have been obtained and adjusted using field measurements for several commercial inverters, and the behavior of the model applied to a particular inverter has been compared with real data under different working conditions, taken from a facility located in Madrid. The results show a good fit between the model values and the real data. As an example, the model has been implemented in PSPICE electronic simulator, and this approach has been used to teach grid-connected PV systems. The use of this model for the maintenance of working PV facilities is also shown.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Genetic redox dysregulation induces behavioural deficits in the adult mouse: an animal model for schizophrenia

Background: Glutathione (GSH), a major cellular redox regulator and antioxidant, is decreased in cerebrospinal fluid and prefrontal cortex of schizophrenia patients. The gene of the key GSH-synthesizing enzyme, glutamate-cysteine ligase, modifier (GCLM) subunit, is associated with schizophrenia, suggesting that the deficit in the GSH system is of genetic origin. Using the GCLM knock-out (KO) mouse as model system with 60% decreased brain GSH levels and, thus, strong vulnerability to oxidative stress, we have shown that GSH dysregulation results in abnormal mouse brain morphology (e.g., reduced parvalbumin, PV, immuno-reactivity in frontal areas) and function. Additional oxidative stress, induced by GBR12909 (a dopamine re-uptake inhibitor), enhances morphological changes even further. Aim: In the present study we use the GCLM KO mouse model system, asking now, whether GSH dysregulation also compromises mouse behaviour and cognition. Methods: Male and female wildtype (WT) and GCLM-KO mice are treated with GBR12909 or phosphate buffered saline (PBS) from postnatal day (P) 5 to 10, and are behaviourally tested at P 60 and older. Results: In comparison to WT, KO animals of both sexes are hyperactive in the open field, display more frequent open arm entries on the elevated plus maze, longer float latencies in the Porsolt swim test, and more frequent contacts of novel and familiar objects. Contrary to other reports of animal models with reduced PV immuno-reactivity, GCLM-KO mice display normal rule learning capacity and perform normally on a spatial recognition task. GCLM-KO mice do, however, show a strong deficit in object-recognition after a 15 minutes retention delay. GBR12909 treatment exerts no additional effect. Conclusions: The results suggest that animals with impaired regulation of brain oxidative stress are impulsive and have reduced behavioural control in novel, unpredictable contexts. Moreover, GSH dysregulation seems to induce a selective attentional or stimulus-encoding deficit: despite intensive object exploration, GCLM-KO mice cannot discriminate between novel and familiar objects. In conclusion, the present data indicate that GSH dysregulation may contribute to the manifestation of behavioural and cognitive anomalies that are associated with schizophrenia.

A validated assay for measuring doxorubicin in biological fluids and tissues in an isolated lung perfusion model: matrix effect and heparin interference strongly influence doxorubicin measurements.

Doxorubicin is an antineoplasic agent active against sarcoma pulmonary metastasis, but its clinical use is hampered by its myelotoxicity and its cumulative cardiotoxicity, when administered systemically. This limitation may be circumvented using the isolated lung perfusion (ILP) approach, wherein a therapeutic agent is infused locoregionally after vascular isolation of the lung. The influence of the mode of infusion (anterograde (AG): through the pulmonary artery (PA); retrograde (RG): through the pulmonary vein (PV)) on doxorubicin pharmacokinetics and lung distribution was unknown. Therefore, a simple, rapid and sensitive high-performance liquid chromatography method has been developed to quantify doxorubicin in four different biological matrices (infusion effluent, serum, tissues with low or high levels of doxorubicin). The related compound daunorubicin was used as internal standard (I.S.). Following a single-step protein precipitation of 500 microl samples with 250 microl acetone and 50 microl zinc sulfate 70% aqueous solution, the obtained supernatant was evaporated to dryness at 60 degrees C for exactly 45 min under a stream of nitrogen and the solid residue was solubilized in 200 microl of purified water. A 100 microl-volume was subjected to HPLC analysis onto a Nucleosil 100-5 microm C18 AB column equipped with a guard column (Nucleosil 100-5 microm C(6)H(5) (phenyl) end-capped) using a gradient elution of acetonitrile and 1-heptanesulfonic acid 0.2% pH 4: 15/85 at 0 min-->50/50 at 20 min-->100/0 at 22 min-->15/85 at 24 min-->15/85 at 26 min, delivered at 1 ml/min. The analytes were detected by fluorescence detection with excitation and emission wavelength set at 480 and 550 nm, respectively. The calibration curves were linear over the range of 2-1000 ng/ml for effluent and plasma matrices, and 0.1 microg/g-750 microg/g for tissues matrices. The method is precise with inter-day and intra-day relative standard deviation within 0.5 and 6.7% and accurate with inter-day and intra-day deviations between -5.4 and +7.7%. The in vitro stability in all matrices and in processed samples has been studied at -80 degrees C for 1 month, and at 4 degrees C for 48 h, respectively. During initial studies, heparin used as anticoagulant was found to profoundly influence the measurements of doxorubicin in effluents collected from animals under ILP. Moreover, the strong matrix effect observed with tissues samples indicate that it is mandatory to prepare doxorubicin calibration standard samples in biological matrices which would reflect at best the composition of samples to be analyzed. This method was successfully applied in animal studies for the analysis of effluent, serum and tissue samples collected from pigs and rats undergoing ILP.

Natural variability in Arabidopsis thaliana germplasm response to Xanthomonas campestris pv. campestris

This work aimed to study the interaction between the model plant Arabidopsis thaliana and Xanthomonas campestris pv. campestris (Xcc), the pathogen responsible for black rot of crucifers. The response of 32 accessions of A. thaliana to the Brazilian isolate of Xcc CNPH 17 was evaluated. No immunity-like response was observed. "CS1308", "CS1566" and "CS1643" grown in continuous light were among the accessions that showed strongest resistance when inoculated with 5 x 10(6) CFU/mL. In contrast, "CS1194" and "CS1492" were among the most susceptible accessions. Similar results were obtained when plants were grown under short-day conditions. To quantify the differences in disease symptoms, total chlorophyll was extracted from contrasting accessions at different time points after inoculation. Chlorophyll levels from controls and Xcc inoculated plants showed a similar reduction in resistant accessions, whereas Xcc-inoculated susceptible accessions showed a greater reduction compared to controls. To test the specificity of resistance, accessions CS1308, CS1566, CS1643 and CS1438 (which showed partial resistance to CNPH 17), were inoculated with a more aggressive isolate of Xcc (CNPH 77) and Ralstonia solanacearum. Among the accessions tested, "CS1566" was the most resistant to Xcc CNPH 77 and also displayed resistance to R. solanacearum. Accessions CS1308, CS1566 and CS1643 were also inoculated with a high titer of Xcc CNPH 17 (5 x 10(8) CFU/mL). No collapse of tissue was observed up to 48 h after inoculation, indicating that a hypersensitive response is not involved in the resistance displayed by these accessions.

Comparative Analysis of Solar PV Business Models

The goal of the thesis is to analyze the strengths and weaknesses of solar PV business model and point out key factors that affect the efficiency of business model, the results are expected to help in creating new business strategy. The methodology of case study research is chosen as theoretical background to structure the design of the thesis indicating how to choose the right research method and conduction of a case study research. Business model canvas is adopted as the tool for analyzing the case studies of SolarCity and Sungevity. The results are presented through the comparison between the cases studies. Solar services and products, cost in customer acquisition, intellectual resource and powerful sales channels are identified as the major factors for TPO model.