Intelligent dispatching and optimal operation of cascade hydropower plants based on spatiotemporal big data

In Norway, hydropower is the primary source of electricity, and it accounts for 96% of electricity generation. Moreover, China's hydropower sector has grown twenty-fold to a total capacity of 352 GW for the past 40 years. This represents over a quarter of the world's hydropower installed capacity. The players in today's power market have a long tradition of using fundamental stochastic market models. These models assume that all uncertainty is revealed in weekly steps and that all functional relationships are linear. However, in a power market with increasing shares of variable renewable energy and time resolutions going down to 15 minutes, decision support tools that can swiftly adapt to changes in the power system is essential. IntHydro's primary objective is to develop and demonstrate a new hydropower scheduling tool based on machine learning techniques, which manages the hydropower plants more efficiently and effectively through optimising water resource management and multi-dispatch between hydropower and variable renewable energy sources. IntHydro's goal will be attained by achieving the following objectives: -What is the benefit of the digitalisation of hydropower scheduling? -Elaborate on the digital platform for the integration of artificial intelligence in different stages of hydropower scheduling models and define comprehensive coupling principles between the strategic and operational modelling -Develop a prototype for fundamental hydropower modelling that allows modelling of RES on a detailed time scale The complete innovation chain in IntHydro consists of sub-innovations that can be assigned to intelligent monitoring systems, decision support for optimal operation and handle the real-time challenges. By implementing a practical demonstration tool, the research carried out within IntHydro will allow to accurately quantify the potential value of the scheduling strategies regarding real cases in terms of technical and economic issues.

The scope of the IntHydro project is at the centre of the thematic area ‘Digitalisation of traditional industries’ in the RCN Chinese-Norwegian Collaborative Projects on Digitalisation call. The aim of the IntHydro project is to explore and define intelligent hydropower scheduling using ML 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 Norwegian and Chinese power system. To this end, the primary objective of IntHydro can be summarised as: “Develop and demonstrate a new hydropower scheduling tool based on machine learning techniques, which manages the hydropower plants more efficiently and effectively through optimizing water resource management and multi-dispatch between hydropower and variable renewable energy sources.” In “IntHydro”, NTNU is the grant applicant and will be the project leader. The Norwegian research partners are Smart Innovation Norway (SIN) and HydroCen. The Norwegian industry partners are Østfold Energi and Lyse. Chinese partners are Houhai University, NanJing NARI Water Resources and Hydropower Technology Company, Ltd, and Yalong River Hydropower Development Company, Ltd. The Norwegian partners will be involved in the daily operation of the project and will also be invited into a steering board is the governing body of the project. In addition to being active in the research, the Chinese partner will be advisors to the management group on scientific matters. There will be one PhD student, and the candidate will play a central role in developing methodologies and participate in the other issues.