IntHydro (2020-2023)

Reducing carbon emissions

Project partners:

  1. Norges Teknisk-Naturvitenskapelige Universitet including Hydro Center at NTNU (Norway, project coordinator)
  2. Smart Innovation Norway (Norway)
  3. Lyse Produksjon AS (Norway)
  4. Østfold Energi AS (Norway)
  5. Hohai University (China)
  6. NanJing Nari Water Resources and Hydropower Technology Company, Ltd (China)
  7. Yalong River Hydropower Development Company, Ltd (China)
With the requirement of reducing carbon emissions and mitigating the climate change, the renewable energy as the green energy will play an important role in the future energy sectors. 

Hydropower as one of the main renewable energy sources will substantially have a great contribution to release the climate impact. Norway and China, as two of the main hydropower production countries in the world, surely have the requirement of developing the hydropower technology to increase the hydropower penetration in the energy market, as well as contributing to reduce the carbon emission amount.

Therefore, the research cooperation about hydropower technoloy between China and Norway will make bilateral benefits to the hydropower scheduling technology development.

Project goals

The main objective of IntHydro is to explore and define intelligent hydropower scheduling using machine learning techniques. The scheduling methodology will address shortcomings in existing hydropower scheduling models to deal with uncertainties brought by the high share of variable renewable energy resources in both the Norwegian and Chinese power system.

There are three main objectives that IntHydro will achieve:

  1. What is the benefit of the digitalization of hydropower scheduling?
  2. Elaborate on the digital platform for the integration of artficial intelligence (AI) in different stages of hydropower scheduling models and define comprehensive coupling principles between the strategic and operational modelling.
  3. Develop a prototype for fundamental hydropower modelling that allows modelling of renewable energy sources on a detailed time scale.

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