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Optimizing Demand Response of Aggregated Residential Energy Storages

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Seilonen, Ilkka, Dr., Aalto University, Department of Electrical Engineering and Automation, Finland
dc.contributor.author Kilkki, Olli
dc.date.accessioned 2018-09-22T09:02:58Z
dc.date.available 2018-09-22T09:02:58Z
dc.date.issued 2018
dc.identifier.isbn 978-952-60-8181-6 (electronic)
dc.identifier.isbn 978-952-60-8180-9 (printed)
dc.identifier.issn 1799-4942 (electronic)
dc.identifier.issn 1799-4934 (printed)
dc.identifier.issn 1799-4934 (ISSN-L)
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/34068
dc.description.abstract The increase in uncontrollable volatile renewable generation leads to a growing need for flexibility also on the consumption side of electricity. Residential consumers, especially with energy storages such as water heaters and batteries, could shift and curtail their energy consumption. However, in order to provide suitable changes to the consumption profiles of the consumers, appropriate methods for control and incentives have to be developed. This thesis presents several developed optimization methods for an aggregating retailer to aggregate multiple mostly independently acting consumers for diverse market participation. The first set of contributions included methods for planning aggregate consumptions schedules for the day-aheadmarket, as well as for taking into account the potential intra-day flexibility of the optimized schedules. In addition, analysis were made on how much the aggregator can shift the consumption of its consumers depending on whether the consumption is responsive to changes in prices or if the aggregator can directly alter the consumption. Secondly, the participation of residential consumption in frequency control was considered. Centralized control was simulated utilizing a proposed agent-basedmodel, under uncertain communication latencies. Furthermore, methods were proposed for optimizing day-ahead schedules for participation in the frequency reserve market. The optimization frameworks were extended to include various uncertainties in the resulting electricity demand and market prices, as well as coordination of charging and reserve participation plans between the consumers under the different conditions. In order to test the various developed methods, multiple stochastic programming models are devised and simulated for large populations of residential consumers. The results indicate that flexibility of residential consumption could potentially be utilized for participation in the wholesale market, intra-day trading and frequency reserves. Furthermore, the performed simulations illustrate the benefit of considering flexibility during the day-ahead planning of electricity consumption. en
dc.format.extent 103 + app. 73
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Aalto University en
dc.publisher Aalto-yliopisto fi
dc.relation.ispartofseries Aalto University publication series DOCTORAL DISSERTATIONS en
dc.relation.ispartofseries 176/2018
dc.relation.haspart [Publication 1]: Olli Kilkki, Antti Alahäivälä, Ilkka Seilonen. Optimized Control of Price-based Demand Response with Electric Storage Space Heating. IEEE Transactions of Industrial Informatics, Volume 11, Pages 281–288, Feb 2015. DOI: 10.1109/TII.2014.2342032
dc.relation.haspart [Publication 2]: Olli Kilkki, Ilkka Seilonen, Kai Zenger, Valeriy Vyatkin. Incentives for Shaping the Consumption Profile of an Energy Storage Population. IEEE PES ISGT Europe 2016, Ljubljana, October 2016. DOI: 10.1109/ISGTEurope.2016.7856253
dc.relation.haspart [Publication 3]: Olli Kilkki, Antti Kangasrääsiö, Raimo Nikkilä, Antti Alahäivälä, Ilkka Seilonen. Agent-based modeling and simulation of a smart grid: A case study of communication effects on frequency control.Engineering Applications of Artificial Intelligence, Volume 33, Pages 91–98, August 2014. DOI: 10.1016/j.engappai.2014.04.007
dc.relation.haspart [Publication 4]: Antti Alahäivälä, Olli Kilkki, Merkebu Z. Degefa, Ilkka Seilonen, Matti Lehtonen. A Virtual Power Plant for the Aggregation of Domestic Heating Load Flexibility. In IEEE PES ISGT Europe 2014, Istanbul, October 2014. DOI: 10.1109/ISGTEurope.2014.7028861
dc.relation.haspart [Publication 5]: Olli Kilkki, Ilkka Seilonen, Valeriy Vyatkin. Optimization of Decentralized Energy Storage Flexibility for Frequency Reserves. IECON 2015, Yokohama, November 2015. DOI: 10.1109/IECON.2015.7392431
dc.relation.haspart [Publication 6]: Olli Kilkki, Kai Zenger, Ilkka Seilonen, Valeriy Vyatkin. Optimizing Residential Heating and Energy Storage Flexibility for Frequency Reserves. International Journal of Electrical Power & Energy Systems, Accepted – pre-review version, Final version at DOI: 10.1016/j.ijepes.2018.02.047
dc.relation.haspart [Errata file]: Errata of publication 2 and 5
dc.subject.other Electrical engineering en
dc.subject.other Computer science en
dc.subject.other Energy en
dc.title Optimizing Demand Response of Aggregated Residential Energy Storages en
dc.title Kysyntäjouston optimointi käyttäen aggregoituja energiavarastoja fi
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.contributor.school School of Electrical Engineering en
dc.contributor.department Sähkötekniikan ja automaation laitos fi
dc.contributor.department Department of Electrical Engineering and Automation en
dc.subject.keyword demand response en
dc.subject.keyword smart grid en
dc.subject.keyword optimization en
dc.subject.keyword energy storage en
dc.subject.keyword kysyntäjousto fi
dc.subject.keyword älykkäät sähköverkot fi
dc.subject.keyword optimointi fi
dc.subject.keyword energiavarasto fi
dc.identifier.urn URN:ISBN:978-952-60-8181-6
dc.type.dcmitype text en
dc.type.ontasot Doctoral dissertation (article-based) en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.contributor.supervisor Vyatkin, Valeriy, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
dc.opn Huang, Alex, Prof., University of Texas, USA
dc.contributor.lab Information Technologies in Industrial Automation en
dc.rev Järventausta, Pertti, Prof., Tampere University of Technology, Finland
dc.rev Sindhya, Karthik, Dr., University of Jyväskylä, Finland
dc.date.defence 2018-10-12
local.aalto.acrisexportstatus checked
local.aalto.formfolder 2018_09_21_klo_13_26
local.aalto.archive yes

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