Advertisement

A Generic Framework for DGS Nanogrids

  • Kaveh Rajab Khalilpour
  • Anthony Vassallo
Chapter
  • 639 Downloads
Part of the Green Energy and Technology book series (GREEN)

Abstract

The goal of the research reported here was to develop a generic integrated decision support tool for concurrent optimal selection, sizing, and operation scheduling of grid-connected or off-grid multi-generation/multi-storage distributed generation and storage (DGS) systems with respect to the dynamics of historical/projected periodical weather data, electricity price, DGS system cost, DGS aging, and the major critical design and operational parameters.

Keywords

Wind Turbine Storage System Planning Horizon Electricity Price Shopping Center 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Dierauf T et al (2013) Weather-corrected performance ratio. NRELGoogle Scholar
  2. 2.
    Velasco G et al (2010) Power sizing factor design of central inverter PV grid-connected systems: a simulation approach. Int Power Elect MotGoogle Scholar
  3. 3.
    Griva I, Nash SG, Sofer A (2009) Linear and nonliner optimization, 2nd Edn. Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)Google Scholar
  4. 4.
    Fesharaki et al (2011) The effect of temperature on photovoltaic cell efficiency. In: Proceedings of the 1st international conference on emerging trends in energy conservation, Tehran, 20–21 Nov 2011Google Scholar
  5. 5.
    KEMA-Sandia (2012) ES-Select™ documentation and user’s manual-version 2.0. Sandia National LaboratoriesGoogle Scholar
  6. 6.
    IPART (2013) Solar feed-in tariffs-the subsidy-free value of electricity from small-scale solar PV units from 1 July 2013. Independent Pricing and Regulatory Tribunal of New South Wales, SydneyGoogle Scholar
  7. 7.
    Summers VM, Wimer JG (2011) QGESS: cost estimation methodology for NETL assessments of power plant performance. National Energy Technology Laboratory, USDOEGoogle Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Kaveh Rajab Khalilpour
    • 1
  • Anthony Vassallo
    • 1
  1. 1.School of Chemical and Biomolecular EngineeringUniversity of SydneySydneyAustralia

Personalised recommendations