Solar energy is a safe, clean, environmentally-friendly and renewable energy source without any carbon emissions to the atmosphere. Therefore, there are many studies in the field of solar energy in order to obtain the maximum solar radiation during the day time, to estimate the amount of solar energy to be produced, and to increase the efficiency of solar energy systems. In this study, it was aimed to predict the daily photovoltaic power production using air temperature, relative humidity, total horizontal solar radiation and diffuse horizontal solar radiation parameters as multi-tupled inputs. For this purpose, grey wolf, ant lion and whale optimization algorithms were integrated to the multilayer perceptron. In addition, the effects of sigmoid, sinus and hyperbolic tangent activation functions on the prediction performance were analyzed in detail. As a result of overall accuracy indictors achieved, the grey wolf optimization algorithm-based multilayer perceptron model was found to be more successful and competitive for the daily photovoltaic power prediction. Furthermore, many meaningful patterns were revealed about the constructed models, input tuples and activation functions.

Solar and wind based renewable energy sources are highly variable according to unstable energy sources due to variable meteorological conditions. Providing a stable DC bus voltage to the inverter’s input by eliminating voltage fluctuations in the generated electrical energy is the main concern of researchers and is highly sensitive in the integration of distributed energy sources. In this study, in order to provide stable and sustainable output voltage at the output of a DC/DC converter, parametric simulation studies are carried out according to different input voltage, duty ratio, and switching frequency values of a DC/DC power converter circuit in a system fed with a solar energy source. Using this dataset obtained from a solar energy source, a parameter estimation in the smart grid structure is studied using artificial hybrid prediction intelligence techniques. Grey wolf and marine predators optimization algorithms are integrated to the multilayer perceptron in the stage of developing the hybrid prediction models. Then, the accuracy of the prediction processes is tested and verified with the power electronics circuit software. Thus, a data analysis approach based on parametric simulation studies in smart grid structures is reported in order to give clear ideas to researchers before designing a prototype.

In the title compound, C₁₅H₁₅ClN₂O₅S, the tetrahydrofuran ring adopts an envelope conformation with the O atom as the flap. The pyrrolidine ring adopts an envelope conformation with the chlorine-substituted C atom as the flap. In the crystal, two types of C—H...O hydrogen bonds generateR²₂(20) andR⁴₄(26) rings, with adjacent rings running parallel toacplane. Further C—H...O hydrogen bonds form aC(6) chain, linking the molecules in theb-axis direction.

The development of renewable energy technologies is an inevitable requirement to cope with environmental, economic and political challenges. Solar energy is regarded as one of the most promising types among renewable energy sources. So, the characterization of solar parameters is a significant process in solar energy installations. In this paper, we use three different curve fitting methods called Fourier, sum of sines and smoothing spline in order to model global solar radiation and air temperature parameters at 10-min intervals over a month. In the stage of accuracy comparison, we computed the coefficient of determination (R²) and the root mean squared error (RMSE) for the mentioned methods. In consequence, the smoothing spline model leads to the best modeling results.

Güvenli, çevre dostu ve sürdürülebilir olan fotovoltaik enerji sistemlerinin kurulumlarında solar parametreler hakkındaki bilgiler önemlidir. Bu çalışmada, öncelikle, Ankara ilinin uzun dönem global güneş ışınım şiddeti, güneşlenme süresi ve hava sıcaklığı verileri yıllık, aylık ve günlük bazda detaylı olarak analiz edilmiştir. Sonrasında, uzun dönem aylık toplam global güneş ışınım şiddeti, aylık toplam güneşlenme süresi ve aylık ortalama hava sıcaklığı verilerinin modellenmesi amacıyla polinom, Gauss ve Fourier olmak üzere üç farklı ampirik metot kullanılmıştır. Söz konusu ampirik metotların veri modelleme performanslarını kıyaslamak için belirlilik katsayısı ve karekök ortalama hata istatistiksel test ölçekleri olarak hesaplanmıştır. En iyi sonuçları sağlayan ampirik metotlar Ankara iline ait solar karakteristiklerin yüksek kararlılıkta modellenmesine imkan vermiş ve elde edilen çıktılar benzer iklim koşullarına sahip diğer yerler için önemli bir kaynak teşkil etmektedir.

1. The worldwide energy scene is in the midst of a profound evolution, primarily driven by the escalating prominence of renewable energy systems [1]. Various factors such as climate change, the dep...