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Ellen Krohn Aasgård

Sivilingeniør

Ellen Krohn Aasgård

Sivilingeniør

Ellen Krohn Aasgård
Telefon: 934 06 340
Mobil: 934 06 340
Avdeling: Energisystemer
Kontorsted: Trondheim

Publikasjoner og ansvarsområder

Publikasjoner

Publikasjon

Optimizing day-ahead bid curves in hydropower production

http://www.sintef.no/publikasjoner/publikasjon/?pubid=CRIStin+1454798

In deregulated electricity markets, hydropower producers must bid their production into the day-ahead market. For price-taking producers, it is optimal to offer energy according to marginal costs, which for hydropower are determined by the opportunity cost of using water that could have been stored ...

Forfattere Aasgård Ellen Krohn Naversen Christian Øyn Fodstad Marte Skjelbred Hans Ivar
År 2017
Type Tidsskriftsartikkel
Publikasjon

Applying successive linear programming for stochastic short-term hydropower optimization

http://www.sintef.no/publikasjoner/publikasjon/?pubid=CRIStin+1278556

We present a model for operational stochastic short-term hydropower scheduling, taking into account the uncertainty in future prices and inflow, and illustrate how the benefits of using a stochastic rather than a deterministic model can be quantified. The solution method is based on stochastic succe...

År 2016
Type Tidsskriftsartikkel
Publikasjon

Comparing Bidding Methods for Hydropower

http://www.sintef.no/publikasjoner/publikasjon/?pubid=CRIStin+1331907

In this paper we compare several methods used by hydropower producers for the determination of bids to the day-ahead market. The methods currently used by the hydropower industry are based on heuristics and expert assessments, but we also include a new method for formal optimization of the bid decis...

År 2016
Type Tidsskriftsartikkel
Publikasjon

Evaluating a stochastic-programming-based bidding model for a multireservoir system

http://www.sintef.no/publikasjoner/publikasjon/?pubid=CRIStin+1141432

Hydropower producers need to schedule when to release water from reservoirs and participate in wholesale electricity markets where the day-ahead production is physically traded. A mixed-integer linear stochastic model for bid optimization and short-term production allocation is developed and tested ...

Forfattere Aasgård Ellen Krohn Andersen Gørild Fleten Stein-Erik Haugstvedt Daniel
År 2014
Type Tidsskriftsartikkel