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Multi objective particle swarm optimization of hybrid micro-grid system: A case study in Sweden
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.ORCID-id: 0000-0003-4589-7045
2017 (engelsk)Inngår i: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 123, s. 108-118Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
PERGAMON-ELSEVIER SCIENCE LTD , 2017. Vol. 123, s. 108-118
Emneord [en]
Hybrid micro-grid, DERs, Renewable energy, Multi-objective optimization, Particle swarm optimization, Sensitivity analysis
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-35309DOI: 10.1016/j.energy.2017.01.149ISI: 000399510900009Scopus ID: 2-s2.0-85011948998OAI: oai:DiVA.org:mdh-35309DiVA, id: diva2:1095225
Tilgjengelig fra: 2017-05-12 Laget: 2017-05-12 Sist oppdatert: 2017-05-12bibliografisk kontrollert

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