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Pv-load matching based on combination of different consumers: A case study in Swedish contexts
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Heat and Power Technology.ORCID iD: 0000-0001-6866-3036
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Heat and Power Technology.ORCID iD: 0000-0002-8888-4474
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Heat and Power Technology.ORCID iD: 0000-0003-0504-6158
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Heat and Power Technology.ORCID iD: 0000-0003-4134-3520
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2024 (English)In: Solar Energy, ISSN 0038-092X, E-ISSN 1471-1257, Vol. 281, article id 112885Article in journal (Refereed) Published
Abstract [en]

The transition towards sustainability necessitates robust growth of renewable energy, especially solar power. However, increasing the shares of solar power may lead to mismatch of electricity supply and demand, thus worse solar power performance could be received due to lower self-consumption and self-sufficiency. This issue has attracted more attention recently as it also requires additional costs for controlling and battery integration. This study combines several load profiles from consumers having different behaviors with different proportions to find out the optimal shares with higher level of PV penetration and self-sufficiency. A visualizing matching layout is proposed to present the PV-load matching level of all the possibilities at different seasons based on a Swedish context. It is found an 8% improvement of self-sufficiency reaching 70% in summer without additional equipment and scarification of self-consumption. The results could assist in the design and planning of the future power sector. Regarding specific targets, various optimal solutions could be found based on the layout.

Place, publisher, year, edition, pages
Elsevier BV , 2024. Vol. 281, article id 112885
Keywords [en]
Load profile combination, Matching heatmap, Performance improvement, PV loading matching, Urban areas
National Category
Energy Engineering Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-353483DOI: 10.1016/j.solener.2024.112885ISI: 001310501900001Scopus ID: 2-s2.0-85202337103OAI: oai:DiVA.org:kth-353483DiVA, id: diva2:1899158
Note

QC 20240919

Available from: 2024-09-19 Created: 2024-09-19 Last updated: 2024-09-27Bibliographically approved

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Ruan, TianqiTopel, MonikaPadovani, FilippoWang, WujunLaumert, Björn

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