The electricity produced by renewable energy sources (RES) is constantly increasing worldwide thanks to government policies and technological advancements. Photo voltaic cells are
actually a fast rising technology as the source of its power is a commodity that is abundant in
this part of the hemisphere. Uncertainty also dominates in the area of the conditions at which
the photovoltaic cells are operating, their optimal weather conditions and the effect of the
conditions on their output. In this project the existing forecasting techniques for generation
and consumption were studied so that they can be used in the multi-agent power grid control
strategy, which will be developed in the upcoming tasks. The type of Forecasting method
used in the project was the Numerical Weather Predictions model which uses meteorological
data such as Irradiance, Ambient Temperature and with the aid of Computer models such as
Artificial Neural Networks to model the power outputs of PV systems. These forecasts can be
used to enhance knowledge in the area of power allocation in PV systems as a form of
Renewable Power sources. The power outputs used in the project i.e Measured Power output
and the Predicted Power Outputs were quite similar which means this model can be safely
used as a mode of determining the amount of PV power required for a location and the power
it is likely to produce at different times. The project concluded that this form of forecast
actually produced values with high correlation values which means it can be used practically
as a form of power sharing when PV systems are used as grided form of electricity
