IHAPS
Intelligent Health Assessment of PV Systems
Publieke samenvatting / Public summary
Aanleiding
The increase of the amount of residential PV systems and the lack of awareness of system owners easily may lead to undetected underperformance of these systems. While monitoring visualisation exists (web-based, apps), system owners cannot judge if energy yield is as expected and if their system is functioning well or not.
Doelstelling
This project aims to set-up an automatic health check for residential PV systems. A database of thousands of PV systems will be created and automated performance assessment of these systems will be performed in order to inform system owners on the functioning of their system. Collection of data can be done via APIs (application programming interfaces) of inverters nowadays as these are connected to the Internet. Algorithms will run on the server that hosts the database of systems and will detect malfunctions related to shade or other causes, and will automatic inform the PV system owner. With early detection the energy yield of systems will increase, as well as operational safety, which is perfectly in line with the aims of the programme line of TKI Urban Energy. Our method will thus increase reliability of PV systems, which will allow faster large-scale deployment of PV systems as a worry-free local renewable energy source.
Korte omschrijving
UU and SunData will closely collaborate on setting up this health check application. To that end, SunData will set up a server with a database of thousands of PV systems by means of collecting performance data from inverters using their APIs. UU will select a sample of the database with a limited number of systems to test malfunctioning algorithms that have been developed in the TKI project AMDIS, but tested only on a small testing facility. The limited number of actual systems will be used as training dataset for testing the algorithms and based on the results we expect that these will need to be modified by UU. Subsequently, they will be run on the server of SunData on the full database of PV systems and their feasibility will be assessed.
Resultaat
The project will yield an automatic health check of PV systems in the residential sector. System owners can rely on this check such that optimum annual performance is warranted. A user-friendly web-interface will attract many PV system owners to share their data and they will be informed on the functioning of their system. With expected national coverage, the database will show what the actual PV system performance is in the Netherlands.
The increase of the amount of residential PV systems and the lack of awareness of system owners easily may lead to undetected underperformance of these systems. While monitoring visualisation exists (web-based, apps), system owners cannot judge if energy yield is as expected and if their system is functioning well or not.
Doelstelling
This project aims to set-up an automatic health check for residential PV systems. A database of thousands of PV systems will be created and automated performance assessment of these systems will be performed in order to inform system owners on the functioning of their system. Collection of data can be done via APIs (application programming interfaces) of inverters nowadays as these are connected to the Internet. Algorithms will run on the server that hosts the database of systems and will detect malfunctions related to shade or other causes, and will automatic inform the PV system owner. With early detection the energy yield of systems will increase, as well as operational safety, which is perfectly in line with the aims of the programme line of TKI Urban Energy. Our method will thus increase reliability of PV systems, which will allow faster large-scale deployment of PV systems as a worry-free local renewable energy source.
Korte omschrijving
UU and SunData will closely collaborate on setting up this health check application. To that end, SunData will set up a server with a database of thousands of PV systems by means of collecting performance data from inverters using their APIs. UU will select a sample of the database with a limited number of systems to test malfunctioning algorithms that have been developed in the TKI project AMDIS, but tested only on a small testing facility. The limited number of actual systems will be used as training dataset for testing the algorithms and based on the results we expect that these will need to be modified by UU. Subsequently, they will be run on the server of SunData on the full database of PV systems and their feasibility will be assessed.
Resultaat
The project will yield an automatic health check of PV systems in the residential sector. System owners can rely on this check such that optimum annual performance is warranted. A user-friendly web-interface will attract many PV system owners to share their data and they will be informed on the functioning of their system. With expected national coverage, the database will show what the actual PV system performance is in the Netherlands.