The building integrated semitransparent photovoltaic (BISTPV) system is an emerging technology which replaces the conventional building material envelopes and roof. The performance prediction of the BISTPV system places a vital role in the reduction of the energy consumption in the building. In this work, the artificial neural network (ANN) is used to predict the performance of this system by optimizing the important parameter of the feature selection. The Elman neural network (EN) algorithm, feed forward neural network (FN), and generalized regression neural network model (GRN) are investigated in this study. The performance metrics of the errors are analysed such as the root mean square error (RMSE), mean absolute percentage error (MAPE), and mean square root (MSE). According to the findings, the model behaves consistently at the specified time and place in the experiment. Forecasters utilizing neural network models will have better accuracy if they use techniques like EN, FFN, and GRN having the RMSE of 0.25, 0.37, and 0.45, respectively.
High power applications such as motor drive control requires a higher voltage level of the DC-DC power converter fed from low-level DC input sources. For increasing the output voltage, a gain of the converter is increased using the pump circuit consisting of inductors and capacitors connected in different forms. The effect of adding the energy storage elements includes the parasitic resistances in the converter and affects the performance. This research paper is intended to model and investigate the effects of non-idealities in two stages cascaded lift circuit type Luo converter with positive output voltage. To analyze the non-ideal effects, state-space averaging (SSA) technique is used to model the converter. The converter is modeled in the presence of equivalent series resistance (ESR) of inductances and capacitances to study the effect of parasitic resistances on the converter performances. The transient and frequency response of the converter is plotted using the MATLAB simulation and observed that the ringing in the transient response is damped and oscillation at corner frequency is mitigated. The effect of ESR reduces the voltage gain and improves the stability of the system by increasing the gain and phase margin. Step response and bode plot of the converter is plotted at ideal and non- ideal condition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.