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Energy efficiency and reduction of emissions

Renewable Energy

SnowSat-an AI approach towards efficient hydropower production

This project will lead to improved management of the hydropower sector, increased hydropower production, and enhanced preparedness to extreme weather events. This will further contribute to Sweden’s zero net-emission goal and help the society develop better climate mitigation and adaptation strategies.

Start

2020-11-20

Planned completion

2023-11-19

Main financing

Vinnova

Collaboration partners

Umeälvens Vattenregleringsföretag

Research area

Project manager at MDH

Associate Senior Lecturer

Pietro Campana

+4621101469

pietro.campana@mdh.se

Snowmelt is an important source for hydropower production, which accounts for about 40% of the total electricity production in Sweden and will play an even more important role in the future Swedish energy system. Spatially distributed and temporally dynamic information on snow amount are highly valuable for the planning of hydropower sector and flood risk
assessments. However, accurate depiction of total snow amount remains one of the biggest challenges. Inaccurate quantification of the snow storage upstream of hydropower dams leads to water spills during the snow melting periods and thus significant losses of potential hydraulic energy. Remote sensing provides a great tool for large-scale and dynamic snow
monitoring.

The big data generated by satellite observations combined with the development of artificial intelligence (AI) and Internet-of-Things (IoT) technologies offers great opportunities for a better understanding of snow conditions. In this project, the overall goal is to use AI and IoT technologies for improving the estimation of snow water storage in Sweden from satellite observations. The proposed solution will lead to improved management of the hydropower sector, increased hydropower production up to 10% and enhanced societal preparedness to extreme weather events, which will contribute to Sweden’s zero net-emission goal and help the society develop better mitigation and adaptation strategies to climate change.


Purpose

Climate change is rapidly altering the snow conditions all over the world, especially in high latitudes. Accurate depiction of snow distribution and amount is highly valuable for water management and climate studies, but still remains a big challenge. In this project, we aim to use Artificial Intelligence (AI) and Internet-of-Things (IoT) for improving the estimation of snow water storage in Sweden from satellite observations.

Project objectives

This project will lead to improved management of the hydropower sector, increased hydropower production, and enhanced preparedness to extreme weather events. This will further contribute to Sweden’s zero net-emission goal and help the society develop better climate mitigation and adaptation strategies.

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