A Case for Using Distributed Energy Storage for Load Balancing and Power Loss Minimization in Distribution Networks

Shaun Duerr, Cristinel Ababei, Dan M. Ionel

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Abstract—We introduce an algorithm to solve the problem of load balancing and loss minimization in distribution networks impacted by temporary service restoration activities. The novelty of the proposed algorithm lies in employing utility directed usage of customer distributed battery energy storage systems, which are assumed to be present and available in the network. With increasing penetration of distributed renewable energy sources, such as photovoltaics and wind turbines, it is projected that batteries will also increasingly be adopted to address some of the new challenges with renewables, such as the so-called duck curve challenge. The deployment of the proposed solution is achieved through demand response signals. To verify its benefits, we develop a co-simulation framework which can be used to develop and study distribution level optimization techniques that exploit the interaction between a smart electric grid, smart buildings and distributed energy storage to achieve energy and cost savings and better energy management practices beyond what one can achieve through techniques applied at the building or network levels only. The proposed algorithm is implemented and verified within the co-simulation framework tool, SmartBuilds. Simulations show that energy storage systems can be used for temporary relief of distribution networks impacted by line failures.

Original languageEnglish
Pages (from-to)1063-1076
Number of pages14
JournalElectric Power Components and Systems
Issue number9-10
StatePublished - Oct 19 2020

Bibliographical note

Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.


  • SmartBuilds
  • battery energy storage system
  • controllable load
  • demand side management
  • distributed generation
  • distribution system analysis and control
  • fault modeling
  • integration of renewable energy sources to grid systems
  • parallel building co-simulation
  • power system optimization

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Mechanical Engineering
  • Electrical and Electronic Engineering


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