Resource-efficient Model-Predictive PV control data communication

For the control of decentralized energy resources (DERs), Virtual Power Plants (VPPs) have been introduced to match the volatile production with the demand of energy consumers. However, due to their fluctuating feed-in, renewable energy sources such as photovoltaic (PV) systems need to be closely monitored and controlled, which in turn results in considerable communication effort. Aiming at reducing the periodic, costly wide-area communication of monitoring data between the PVs and the VPP, we introduce and validate in this paper our approach of Model Predictive PV Control Communication (MPCC). Leveraging a dedicated Efficient PV Production (EPVP) model which synchronously estimates the PV production on both ends of the wide-area communication path, i.e. the DERs and the VPP, the amount of transmitted monitoring data can be reduced considerably (up to 100% depending on weather conditions and acceptable prediction error). The introduced EPVP model is validated with real-life data of various PV systems. Finally, the proper parametrization and efficiency of the proposed MPCC has been analysed for various weather conditions.