A Probabilistic Method Combining Electrical Energy Storage and Real-Time Thermal Ratings to Defer Network Reinforcement

David M. Greenwood*, Neal S. Wade, Philip C. Taylor, Panagiotis Papadopoulos, Nick Heyward

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

21 Citations (Scopus)

Abstract

When a primary substation reaches its capacity limit, the standard solution is to reinforce the network with additional circuits. Under the right conditions, the required additional peak capacity can be provided by energy storage systems (ESS), real-time thermal ratings (RTTR) or a combination of the two. We present a probabilistic method for calculating the size of an electrical energy storage system for a demand peak shaving application. The impact of both power and energy capacity are considered, along with the reliability of the energy storage and the existing overhead lines. We also consider the combination of energy storage and RTTR - taking advantage of the inherent variability in power line rating as a result of changing weather conditions - for enhancing reliability, deferring conventional reinforcement, and increasing the availability of energy storage to participate in commercial service markets. The method is demonstrated in a case study on a network with an ongoing 6-MW/10-MWh ESS innovation project.

Original languageEnglish
Article number7543510
Pages (from-to)374-384
Number of pages11
JournalIEEE Transactions on Sustainable Energy
Volume8
Issue number1
DOIs
Publication statusPublished - Jan 2017

Keywords

  • Energy storage
  • power distribution
  • power system planning
  • smart grids

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