Abstract
The renewable energy use in power systems is growing during recent years. While renewable energy resources provide cheap energy and much lower levels of pollution, their addition introduces new problems to the power system. One of the important issues is their unreliability. There are many studies aimed at resolving this issue specifically by generating accurate forecasts to predict the power output in the future. Photo Voltaic (PV) units are one of the most common renewable energy resources in power systems. Many studies have explored solar power forecasting in recent decades. Recently, instead of point forecasts, the focus is shifted towards probabilistic forecasts which provide more information to the power system operators and equip them with more tools to manage the power system. This study explores different methods applied to probabilistic forecasting in solar power area. We also implement the forecasting methods for solar power prediction and compare the results using different metrics to find the most effective method for probabilistic forecasting.
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