Accurately predicting the power produced during solar power generation can greatly reduce
the impact of the randomness and volatility of power generation on the stability of the power …

Bearing in mind European Green Deal assumptions regarding a significant reduction of
green house emissions, electricity generation from Renewable Energy Sources (RES) is …

The optimization of solar energy integration into the power grid relies heavily on accurate
forecasting of solar irradiance. In this study, a new approach for short-term solar irradiance …

Problems with erroneous forecasts of electricity production from solar farms create serious
operational, technological, and financial challenges to both Solar farm owners and electricity …

In cases where a dye-sensitized solar cell (DSSC) is exposed to light, thermal energy
accumulates inside the device, reducing the maximum power output. Utilizing this energy via …

Introduction Therapeutic advances in drug therapy of chronic obstructive pulmonary disease
(COPD) really effective in suppressing the pathological processes underlying the disease …

We present SolarFlux Predictor, a novel deep-learning model designed to revolutionize
photovoltaic (PV) power forecasting in South Korea. This model uses a self-attention-based …

Renewable energy sources (RES) are continuously gaining in importance, especially
because diversification of energy supply through RES ensures sustainability. However, the …

The primary objective of this study is to develop a strategy to maximize the potential of
Building Applied Photovoltaics (BAPV) by providing researchers and experts in the field with …

This paper presents a photovoltaic (PV) system designed to reduce the DC-link capacitance
present in double-stage PV microinverters without increasing the capacitor interfacing the …