The renewable power generation aggregated across Europe exhibits strong seasonal behaviors. Wind power generation is much stronger in winter than in summer. The opposite is true for solar power generation. In a future Europe with a very high share of renewable power generation those two opposite behaviors are able to counterbalance each other to a certain extent to follow the seasonal load curve. The best point of counterbalancing represents the seasonal optimal mix between wind and solar power generation. It leads to a pronounced minimum in required stored energy. For a 100% renewable Europe the seasonal optimal mix becomes 55% wind and 45% solar power generation. For less than 100% renewable scenarios the fraction of wind power generation increases and that of solar power generation decreases

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 aim of this work is to develop an algorithm that can utilize historical PV power measurements to establish the parameters of a physical model for power production. The chosen approach consists in evaluating the parameters of a PV model that maximize the likelihood that simulations match with power measurements. The proposed method offers advantages beyond the standard approaches used for the simulation or prediction of PV power production, as it makes maxinnun use of the information typically available on a PV plant (plant description and measurement history). Furthermore, an interpretation and control of the algorithm output is made possible. The performance of the proposed approach has been evaluated and analyzed using measurements from two PV plants, It is shown that the proposed approach may identify the orientation angles of a PV module to within an accuracy of less than 2 degrees in optimal cases, Situations were also found with a difference between the estimated and actual angles of 5 degrees, for which the estimated parameters lead to better simulation/forecast accuracy than the actual ones as they balance the systematic error of the chosen PV-model

EC Directives (EC in SEC 85/3, 2008; EP, EC in COM 19, 2008) give individual targets in emission reduction and renewable energy share to the member states of the European Union. Germany is obligated to reduce its green house gas emissions by 14 % until the year 2020 related to the year 2005 and to increase its share of renewable energy in the final energy consumption to 18 %. For electrical energywhich is the main topic of this paperthe portion of electricity based on renewable energy sources (RES) is projected to increased from 15 % in 2008 to 40 % until 2020 (Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit, 2012). Because of the short period of time, this ambiguous target represents a big challenge in development of adequate renewable generation. The high shares of wind or PV in the supply system necessitates to expand the storage capacities, extend the transmission and distribution grids and improve flexible operation of the entire energy system, star ting with generation and ending with demand side. Long term scenarios of electricity generation and demand in Europe until 2040 can be found in Eurel (2012). To maintain the high standard of security of supply in the German grid, a Task Force of VDE has investigated the needs to balance the German energy system under the aspect of high penetration of RES. For the analysis of the consequences for the non-renewable power generation, a simulation model of the German energy system had been elaborated, which considers the development of RES shown in the reference scenario (VDE AT40, 2012), for the following development of RES until the year 2020: wind 60 GW, PV 60 GW, run-of-river hydro 5 GW (constant) and biomass 7 GW. In total the installed power of RES might achieve 130 GW. Considering the coincidence of RES generation, it will touch the grid load many times over the year and to a small extend overshoot the existing demand. The system simulations show, that the thermal fleet will be facing load gradients of up to 15 GW/h over 1 h in the year 2020. These high gradients will need flexible thermal power plants, which will be able to respond to fast changing

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