  Estimation of the generated power of renewable energy resources is in general
important for planning operations as well as demand balance and power quality.
This paper addresses the problem of the estimation of the short-term (3-hour
ahead) and medium-term (1-day ahead) generated power of a photovoltaic plant.
Firstly, the design of day-ahead solar radiation predictors is investigated
with different setups of time series models, and with their combinations with
the weather forecast services using ensemble methods. Support Vector Machine
methods are also adopted in this stage, to cluster data. Secondly, under a
similar ensemble framework, the generated power prediction is investigated. The
whole generated power and solar radiation prediction tasks are then implemented
on a low-cost, embedded mini PC module Raspberry Pi 3. As an application, the
prediction is employed in the control system of a typical microgrid settings
focusing on energy management problem. The impact of the quality of generated
power prediction on the performance of the controller is also evaluated in this
paper.
