Optimal Sizing of Energy Storage with Embedded Wind Power Generation

Nicholas Roche, Jane Courtney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Energy storage technologies are key to increased penetration of renewable energies on the distribution system. Not only do they increase availability of energy, but they contribute to the overall reliability of the system. However, the cost of large-scale storage systems can often be prohibitive, and storage needs to be sized appropriately, both to fill the energy gaps inevitable in renewable energies such as wind and to minimize costs. In this work, a Monte Carlo Simulation is performed to optimally size an energy storage system while minimizing overall system cost. 30 years of historical wind speed data are used to model the probabilistic behaviour of the wind and the seasonal variation of the wind is captured in the model. A generation adequacy assessment shows the system reliability increasing with energy storage. The energy storage is sized for reliable operation of the case study system with 60% wind penetration. The levelized cost of storage is calculated for the optimally sized level of storage and for the level of storage required to make wind power generation reliable.

Original languageEnglish
Title of host publicationUPEC 2020 - 2020 55th International Universities Power Engineering Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728110783
DOIs
Publication statusPublished - Sep 2020
Event55th International Universities Power Engineering Conference, UPEC 2020 - Virtual, Torino, Italy
Duration: 1 Sep 20204 Sep 2020

Publication series

NameUPEC 2020 - 2020 55th International Universities Power Engineering Conference, Proceedings

Conference

Conference55th International Universities Power Engineering Conference, UPEC 2020
Country/TerritoryItaly
CityVirtual, Torino
Period1/09/204/09/20

Keywords

  • Embedded Generation
  • energy storage
  • reliability
  • wind power

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