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Multi objective particle swarm optimization of hybrid micro-grid system: A case study in Sweden
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-4589-7045
2017 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 123, 108-118 p.Article in journal (Refereed) Published
Abstract [en]

Distributed energy resources DERs are small scale energy system which could provide local supply when placed at customers' premises. They aggregate multiple local and diffuse production installations, consumer facilities, storage facilities and monitoring tools and demand management. The main challenges when assessing the performance of an off-grid hybrid micro-grid system HMGS are the reliability of the system, the cost of electricity production and the operation environmental impact. Hence the tradeoff between three conflicting objectives makes the design of an optimal HMGS seen as a multi-objective optimization task. In this paper, we consider the optimization and the assessment of a HMGS in different Swedish cities to point out the potential of each location for HMGS investment. The HMGS consists of photovoltaic panels, wind turbines, diesel generator and battery storage. The HMGS model was simulated under one-year weather conditions data. A multi objective particle swarm optimization is used to find the optimal system configuration and the optimal component size for each location. An energy management system is applied to manage the operation of the different component of the system when feeding the load. The techno economics analysis shows the potential of HMGS in the Swedish rural development. (C) 2017 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD , 2017. Vol. 123, 108-118 p.
Keyword [en]
Hybrid micro-grid, DERs, Renewable energy, Multi-objective optimization, Particle swarm optimization, Sensitivity analysis
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-35309DOI: 10.1016/j.energy.2017.01.149ISI: 000399510900009OAI: oai:DiVA.org:mdh-35309DiVA: diva2:1095225
Available from: 2017-05-12 Created: 2017-05-12 Last updated: 2017-05-12Bibliographically approved

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Maher, AzazaWallin, Fredrik
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf