This would benefit different investors like municipalities, building companies, housing associations and private persons. To have access to accurate data for validation of PV software, an operative PV system network is created at three SMHI weather stations with complete irradiance measurements. To cope with the lack of complete data at other stations, this project aims to utilize the most cutting-edge machine learning techniques to generate missing data fundamental for the uses of several software tools. The best PV simulation tool will be recommended. Future foreseen solar radiation for Sweden will be performed to quantitatively analyze the effects of likely climate changes on PV systems yield.
The specific goals of the projects are:
- Five different software tools (three commercial and two free) will be validated with weather data and PV power generation data measured at the same sites.
- Based on the results recommendations will be given on what software to use in Sweden for simulation of PV power generation.
- Review and comparison of machine learning techniques, to generate missing radiation data from SMHI weather stations and to explore opportunities to make short term forecasts, will be conducted.
- Analyze the effects of climate change on the solar radiation and temperature patterns that can significantly affect the future PV energy production.
- Construct a map of predicted PV system yield for Sweden.
Funding, partners and project period
The project is lead by Mälardalens högskola and is carried out in collaboration with SMHI and Solkompaniet Konsult Sverige AB. The project duration is 2017-2019 and is funded by the Swedish Energy Agency.
Contact person at SMHI is Tomas Landelius.