Optimizing Pricing Strategies to Maximize Profits for Balancing Service Providers in FCR-N and FCR-D Reserve Markets

annif.suggestionsprices|pricing|marketing|simulation|markets (systems)|optimisation|electricity market|profitability|batteries|modelling (representation)|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p750|http://www.yso.fi/onto/yso/p10773|http://www.yso.fi/onto/yso/p5878|http://www.yso.fi/onto/yso/p4787|http://www.yso.fi/onto/yso/p1865|http://www.yso.fi/onto/yso/p13477|http://www.yso.fi/onto/yso/p16837|http://www.yso.fi/onto/yso/p4257|http://www.yso.fi/onto/yso/p2307|http://www.yso.fi/onto/yso/p3533en
dc.contributor.authorHossain, Amjad
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2025-06-19T10:18:05Z
dc.date.accessioned2025-06-25T17:54:12Z
dc.date.available2025-06-19T10:18:05Z
dc.date.issued2025-06-07
dc.description.abstractThe goal of this thesis is to determine how a 1 MW battery can profit in Finland’s frequency reserve markets with smart pricing strategies. It consists of two markets: FCR-N, run continuously and FCR-D which is brought in when there are unusual fluctuations in frequency. This work looks at how different pricing methods can change the profit a battery system earns. Using real data from Fingrid's 2024 frequency reserve markets, a battery operating model was run to provide the findings reported in this master's thesis. For FCR-N, two control methods were examined: a straightforward rule based one and an advanced approach using practical logic that responds to changes in prices and frequency. The easy-to-use model earned more profit, yet the market rules were better followed with the improved logic. A review of FCR-D was included, though a lack of activation data results in imprecise and less trustworthy findings. This study demonstrates that using a good strategy and precise information, battery systems may do well in FCR-N. Future work on the model could add battery aging as a factor, make the controlling system more complex and include the complete set of FCR-D activation data.-
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent56-
dc.identifier.olddbid24012
dc.identifier.oldhandle10024/19871
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/12220
dc.identifier.urnURN:NBN:fi-fe2025060762730-
dc.language.isoeng-
dc.rightsCC BY-NC 4.0-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/19871
dc.subject.degreeprogrammeMaster´s Programme in Smart Energy-
dc.subject.disciplinefi=Sähkö- ja energiatekniikka|en=Electrical Engineering and Energy Technology|-
dc.subject.ysopricing-
dc.subject.ysosimulation-
dc.subject.ysooptimisation-
dc.subject.ysoelectricity market-
dc.subject.ysoprofitability-
dc.subject.ysobatteries-
dc.titleOptimizing Pricing Strategies to Maximize Profits for Balancing Service Providers in FCR-N and FCR-D Reserve Markets-
dc.type.ontasotfi=Pro gradu -tutkielma|en=Master's thesis|sv=Pro gradu -avhandling|-

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