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Peak-shaving and profit-sharing model by Aggregators in residential buildings with PV- a case study in Eskilstuna, Sweden
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
KTH Royal Institute of Technology, Stockholm, Sweden.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-1351-9245
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH Royal Institute of Technology, Stockholm, Sweden.ORCID iD: 0000-0003-0300-0762
2017 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 142, p. 3182-3193Article in journal (Refereed) Published
Abstract [en]

Nowadays, photovoltaic (PV) system combined with energy storage systems is playing increasing significant role in residential buildings in Sweden. At the same time it brings reliability problems because of the intermittency of electricity production and exceptionally distributed reservoir which is followed by the peak-valley electricity prices and power grid fluctuations. There is an increasing need for new business model and economic paradigm for a third party aggregator to bridge the gap between Power Grid and end-users. Providing the valuable electricity services at scale and breaking regulatory arbitrage, aggregators help to deliver desired levels of residents’ engagements, value-added services and feasible level of unbundling of electricity market. This paper analyzes how the aggregators grab the indisputable business opportunity to interact between residents and Power Grid from the perspective of physical electricity flows and benefits share of peak-shaving. We employ a real case in Eskilstuna in Sweden to design new business model and validate using data. And the result indicates the compatibility of the aggregator service and its business model. It further sheds light on the pricing model of generated electricity by PV system, and benefits share ratio design.

Place, publisher, year, edition, pages
Elsevier Ltd , 2017. Vol. 142, p. 3182-3193
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-38719DOI: 10.1016/j.egypro.2017.12.488Scopus ID: 2-s2.0-85041532112OAI: oai:DiVA.org:mdh-38719DiVA, id: diva2:1186779
Available from: 2018-03-01 Created: 2018-03-01 Last updated: 2018-03-01Bibliographically approved

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Yang, YingCampana, Pietro EliaYan, Jinyue

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