Optimal hydro design in the future power system
The objective is to develop methods and models for calculation of future revenues for hydropower and to support decisions regarding optimal investments in upgrading and expansion projects.
The basic idea of the project is to build on existing models and knowledge and to use a modular approach that allows individual model development which is flexible with regard to changes of concepts or individual models.
We propose to use API interfaces and to program as much as possible in a high level programming language like Python. The project involves all relevant aspects of the three dimensional investment problem, type, size and timing. To begin with we propose that the PhD student focuses on the three dimensional investment problem and that SINTEF start to further develop the whole concept and focuses on calculation of operational revenues for given system.
Specifically, for 2017 we propose to implement and make a model that uses the standard SHOP model to solve the weekly scheduling problem in a serial simulation. Water values are given for each week by cuts from the ProdRisk model. In other words a ProdRisk type model with SHOP providing the final simulation results. The new model will most likely be implemented in Python and use existing SHOP and ProdRisk models with newly developed API interface. This new model is only the first small step to fulfil the ultimate goal of the project but still it will give useful results:
- It will show the concept, test and build competence on the building blocks
- It will give more realistic operation and simulated profit for some systems, i.e. an improvement to current methods
- Provide information about concept challenges, .e.g. computation time possible need for feedback to strategic level (ProdRisk).
Further development in this project will include development of existing standard models, further development of the Python simulator or development of new models. The concept will benefit from possible development in other research projects like the MultiSharm project and the IBM project, both focusing on balancing markets and possible consequences for short and long-term operation.
We plan to start the project with a concept specification activity. Fagutvalget will be in important part if this activity.
Conference Proceedings 2019
Mo, Birger; Martino, Sara; Naversen, Christian Øyn; Aronsen, Gunnar; Rismark, Ole.
Benchmarking Hydro Operation by Use of a Simulator. I: Proceedings of the 6th International Workshop on Hydro Scheduling in Competitive Electricity Markets. Springer Nature 2019 ISBN 978-3-030-03311-8. s. 41-51
Schäffer, Linn Emelie; Haugen, Mari.
Analysis from HydroCen. User Meeting Hydro Scheduling; 2019-03-13 - 2019-03-14
Schäffer, Linn Emelie.
Hydropower flexibility - enabler for intermitted technology storage. Hydropower Norway Conference 2019; 2019-05-28 - 2019-05-28
Kleiven, Andreas; Steinsland, Ingelin.
Inflow Forecasting for Hydropower Operations: Bayesian Model Averaging for Postprocessing Hydrological Ensembles. I: Proceedings of the 6th International Workshop on Hydro Scheduling in Competitive Electricity Markets. Springer Nature 2019 ISBN 978-3-030-03311-8. s. 33-40
Fleten, Stein-Erik; Löhndorf, Nils; Dimoski, Joakim; Nersten, Sveinung.
Dynamic hedging for the real option management of electricity storage. Workshop Nord U Bodø; 2019-05-08 - 2019-05-09
Optimization-based offering of storage-backed power into short-term electricity markets. The xv international conference on stochastic programming; 2019-07-29 - 2019-08-02
Fleten, Stein-Erik; Mauritzen, Johannes; Ullrich, Carl J..
The other renewable: Hydropower upgrades and renewable portfolio standards. Energy Journal 2018 ;Volum 39.(2) s. 197-217. BI NTNU
Conference Proceedings 2018
Fleten, Stein-Erik; Klæboe, Gro.
Coordinated vs sequential bidding into short-term electricity markets. 7th International Ruhr Energy Conference; 2018-09-24 - 2018-09-25. NTNU
Fleten, Stein-Erik; Klæboe, Gro.
Optimization-based offering of hydropower into short-term electricity markets. Optimization course; 2018-10-24 - 2018-10-24. NTNU
Kleiven, Andreas; Fleten, Stein-Erik; Fram, Benjamin P.; Ullrich, Carl J..
Optimal Inspection Strategies for Turbine Runners in Hydropower Plants. INFORMS Annual Meeting 2018; 2018-11-04 - 2018-11-07. NTNU NHH
Ødegård, Heidi Liljeblad; Eidsvik, Jo; Fleten, Stein-Erik.
Value of information analysis of snow measurements for the scheduling of hydropower production. Energy Systems, Springer Verlag 2017 s. -
About the project
Full project title: Optimal hydro design in future power systems
Objective: To develop methods and models for calculation of future revenues for hydropower to support decisions for optimal investments in upgrading and expansion projects.
Researchers working on the project: Birger Mo, Arnt Ove Eggen, Eivind Solvang, Magnus Korpås, Stein-Erik Fleten, Christan Øyn Naversen, Per Eilif Wahl, Hans Olav Hågenvik.
R&D Partners: NTNU, SINTEF, NINA
Associated projects: IBM - Integrated Balancing Markets in Hydropower Scheduling Methods (KPN project, 2014-2018)
PhD working on the project: Andreas Kleiven