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dc.contributor.advisorDoorman, Gerard
dc.contributor.advisorHystad, Jan
dc.contributor.advisorSetréus, Johan
dc.contributor.advisorElkington, Katherine
dc.contributor.authorSvarstad, Vegard Bremerthun
dc.date.accessioned2016-10-06T14:00:38Z
dc.date.available2016-10-06T14:00:38Z
dc.date.created2016-06-21
dc.date.issued2016
dc.identifierntnudaim:15822
dc.identifier.urihttp://hdl.handle.net/11250/2413290
dc.description.abstractIn these days, the Nordic TSOs examines the possibility to introduce Flow-Based(FB) market clearing in the Nordic power market. The FB market clearing will theoretically give a better market solution than the current Net Transfer Capacity (NTC) method, because a simplified grid model included in the market optimization gives the market the ability to prioritize flows that are the most economically efficient in managing congestion. The simplified grid model contains Power Transfer Distribution Factors (PTDFs), which describe the connection between a change in net position and change in injection. Because the Nordic area is divided into bidding areas, the node-to-line PTDFs have to be aggregated to area-to-CNE PTDFs to reflect how an injection in an area influences the lines in the grid. In this aggregation, a Generation Shift Key (GSK) is used, and describe how a change in net position of an area is divided on the nodes in that specific area. A GSK strategy is rules or linearization methods for generating the GSK to find the most accurate estimated power flow, compared to the real physical flow. There are no theoretical right or wrong methodology when determining the GSK strategy, and there is not necessarily only one general optimal strategy. Therefore, several GSK strategies are developed in the Nordic countries. The task in this thesis is to compare these strategies, and find the optimal GSK in each Nordic bidding area contributing to a most accurate estimated power flow. The TSOs cannot precisely estimate the power flow in the grid due to uncertainty. To handle the uncertainty, the FB method use the Flow Reliability Margin (FRM). To compare the different GSK strategies and find which one suited in each Nordic bidding area, a Python code is written in this thesis using the FRM parameter. To find the combination of optimal GSKs in each area to minimize the error in estimated flow, the code have the objective to minimize a weighted FRM norm. The results of the studied period 01.02.2016-17.04.2016 show that it is beneficial to have the optimal GSK in each bidding area instead of one global strategy in the entire system. The areas with the largest benefit of having optimal GSK in the area was NO2 and SE3. The best strategies in these areas are GSK3 and GSK7, respectively. However, in some areas like NO1 and NO3 all GSK strategies performed similar regarding a calculated delta value. This implies that the areas with similar results for all GSKs are strong and non-sensitive areas. Results show that the characteristics of each area affect which GSK optimal. In general, GSK3 and GSK5 are good strategies in areas with export and mainly hydropower generation from reservoirs, while GSK7 and GSK2 are good strategies when the area has an import of power or mainly nuclear or the generation in the area is mainly from nuclear power plants.
dc.languageeng
dc.publisherNTNU
dc.subjectEnergi og miljø, Energianalyse og planlegging
dc.titleFlow based market clearing - GSK strategies
dc.typeMaster thesis
dc.source.pagenumber100


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