Assessment of PV Systems Performance in the Madeira Island Using Typical Meteorological Year Data

This paper focus on the development of an algorithm using Matlab to generate Typical Meteorological Years from weather data of eight locations in the Madeira Island and to predict the energy generation of photovoltaic systems based on solar cells modelling. Solar cells model includes the effect of ambient temperature and wind speed. The analysis of the PV system performance is carried out through the Weather Corrected Performance Ratio and the PV system yield for the entire island is estimated using spatial interpolation tools.

Spatial and temporal downscaling of solar global radiation and mean air temperature from weather forecast data - an introductory numerical study and validation

This short paper presents a numerical method for spatial and temporal downscaling of solar global radiation and mean air temperature data from global weather forecast models and its validation. The final objective is to develop a prediction algorithm to be integrated in energy management models and forecast of energy harvesting in solar thermal systems of medium/low temperature. Initially, hourly prediction and measurement data of solar global radiation and mean air temperature were obtained, being then numerically downscaled to half-hourly prediction values for the location where measurements were taken. The differences between predictions and measurements were analyzed for more than one year of data of mean air temperature and solar global radiation on clear sky days, resulting in relative daily deviations of around -0.9±3.8% and 0.02±3.92%, respectively.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

On the zeros of the Abelian integrals for a class of Liénard systems

A planar polynomial differential system has a finite number of limit cycles. However, finding the upper bound of the number of limit cycles is an open problem for the general nonlinear dynamical systems. In this paper, we investigated a class of Liénard systems of the form x'=y, y'=f(x)+y g(x) with deg f=5 and deg g=4. We proved that the related elliptic integrals of the Liénard systems have at most three zeros including multiple zeros, which implies that the number of limit cycles bifurcated from the periodic orbits of the unperturbed system is less than or equal to 3.