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Optimal location and capacity planning for distributed generation with independent power production and self-generation
University of Strathclyde, United Kingdom.
University of Technology Sydney, Australia.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-6279-4446
University of Liverpool, United Kingdom.
2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 188, 140-150 p.Article in journal (Refereed) Published
Abstract [en]

This paper proposes a planning model for power distribution companies (DISCOs) to maximize profit. The model determines optimal network location and capacity for renewable energy source, which are categorized as independent power production (IPP) and self-generation (SG). IPP refers to generators owned by third-party investors and linked to a quota obligation mechanism. SG encompasses smaller generators, supported by feed-in tariffs, that produce energy for local consumption, exporting any surplus generation to the distribution network. The obtained optimal planning model is able to evaluate network capacity to maximize profit when the DISCO is obliged to provide network access to SG and IPP. Distinct parts of the objective function, owing to the definition of SG, are revenue erosion, recovery as well as the cost of excess energy. Together with the quota mechanism for IPP, the combination of all profit components creates a connection trade-off between IPP and SG for networks with limited capacity. The effectiveness of the model is tested on 33- and 69-bus test distribution systems and compared to standard models that maximize generation capacity with predefined capacity diffusion. Simulation results demonstrate the model outperforms the standard models in satisfying the following binding constraints: minimum IPP capacity and SG net energy. It is further revealed that integrating SG and IPP with the proposed model increases profit by up to 23.7%, adding an improvement of 8% over a feasible standard model.

Place, publisher, year, edition, pages
2017. Vol. 188, 140-150 p.
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-34610DOI: 10.1016/j.apenergy.2016.11.125ScopusID: 2-s2.0-85007314346OAI: oai:DiVA.org:mdh-34610DiVA: diva2:1065138
Available from: 2017-01-13 Created: 2017-01-13 Last updated: 2017-01-25Bibliographically approved

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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