Experience shows that most solar PV power plants do not operate at their optimum. In particular, in locations with good solar irradiation and/or high feed-in-tariffs this can lead to significant losses in power and revenues for plant owners and investors, and thus implies an operational risk for lenders and operators. From another perspective harvesting maximum energy yields from solar PV power plants provides a tremendous upside potential. PV|Harvester is a software tool developed by the University of Applied Sciences Upper Austria together with deea Solutions GmbH, Germany with the aim to quickly assess the operational performance of solar PV systems. The tool, developed in Python, is a result of many years of experience in planning, designing, and data analysis of solar PV power plants. PV|Harvester delivers detailed and fast performance analysis on string level, a clear view on improvement potentials, and a thorough health check of the asset. It can also be applied to a due diligence analysis as part of an asset transfer, for calculation of liquidated damages, and a general failure analysis and localization.
|Title of host publication||EU PVSEC 2019|
|Publication status||Published - 2019|
|Event||EU PVSEC - Marseille, France|
Duration: 9 Sep 2019 → 13 Sep 2019
|Period||09.09.2019 → 13.09.2019|