Small grid-connected photovoltaic systems up to 5 kW p are often not monitored because advanced surveillance systems are not economical. Hence, some system failures which lead to partial energy losses stay unnoticed for a long time. Even a failure that results in a larger energy deficit can be difficult to detect by PV laymen due to the fluctuating energy yields.Within the EU project PVSAT-2, a fully automated performance check has been developed to assure maximum energy yields and to optimize system maintenance for small grid-connected PV systems. The aim is the early detection of system malfunctions and changing operating conditions to prevent energy and subsequent financial losses for the operator. The developed procedure is based on satellitederived solar irradiance information that replaces on-site measurements. In conjunction with a simulation model the expected energy yield of a PV system is calculated. In case of the occurrence of a defined difference between the simulated and actual energy yield, an automated failure detection routine searches for the most probable failure sources and notifies the operator.This paper describes the individual components of the developed procedure-the satellite-derived irradiance, the used PV simulation model, and the principles of the automated failure detection routine. Moreover, it presents results of an 8-months test phase with 100 PV systems in three European countries.

The fundamental changes in the energy sector, due to the rise of renewable energy resources and the possibilities of the digitalisation process, result in the demand for new methodologies for testing Smart Grid concepts and control strategies. Using the Power Hardware-in-the-Loop (PHIL) methodology is one of the key elements for such evaluations. PHIL and other in-the-loop concepts cannot be considered as plug’n’play and, for a wider adoption, the obstacles have to be reduced. This paper presents the comparison of two different setups for the evaluation of components and systems focused on undisturbed operational conditions. The first setup is a conventional PHIL setup and the second is a simplified setup based on a quasi-dynamic PHIL (QDPHIL) approach which involves fast and continuously steady state load flow calculations. A case study which analyses a simple superimposed voltage control algorithm gives an example for the actual usage of the quasi-dynamic setup. Furthermore, this article also provides a comparison and discussion of the achieved results with the two setups and it concludes with an outlook about further research.

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The scientific output expressed is based on the current information available to the author, and does not imply a policy position of the European Commission.

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