Recent advances toward sustainable cities have promoted the concept of near-zero energy
consumption. A Positive Energy Building (PEB) model has been developed by the European …

Forecasting for wind and solar renewable energy is becoming more important as the amount
of energy generated from these sources increases. Forecast skill is improving, but so too is …

Accurate photovoltaic power forecasting is of great help to the operation of photovoltaic
power generation system. However, due to the instability, intermittence, and randomness of …

The outputs of photovoltaic (PV) power are random and uncertain due to the variations of
meteorological elements, which may disturb the safety and stability of power system …

Recently, many machine learning techniques have been successfully employed in
photovoltaic (PV) power output prediction because of their strong non-linear regression …

PV power forecasting models are predominantly based on machine learning algorithms
which do not provide any insight into or explanation about their predictions (black boxes) …

Conventional models and artificial intelligence (AI)-based models have been widely applied
for energy consumption forecasting over the past decades. This paper reviews conventional …

Due to the intermittency and uncertainty in photovoltaic (PV) power outputs, not only
deterministic point predictions (DPPs), but also associated prediction Intervals (PIs) are …

Quantifying uncertainties in the prediction of building energy consumption is critical to
building energy management systems. In this study, a deep-learning-based interval …

Solar energy has received increasing attention as renewable clean energy in recent years.
Power grid operators and researchers widely value probabilistic solar irradiance forecasting …