Phase balancing using energy storage in power grids under uncertainty

Sun Sun, Ben Liang, Min Dong, Joshua A. Taylor

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Phase balancing is essential to safe power system operation. We consider a substation connected to multiple phases, each with single-phase loads, generation, and energy storage. A representative of the substation operates the system and aims to minimize the cost of all phases and to balance loads among phases. We first consider ideal energy storage with lossless charging and discharging, and propose both centralized and distributed real-time algorithms taking into account system uncertainty. The proposed algorithm does not require any system statistics and asymptotically achieves the minimum system cost with large energy storage. We then extend the algorithm to accommodate more realistic non-ideal energy storage that has imperfect charging and discharging. The performance of the proposed algorithm is evaluated through extensive simulation and compared with that of a benchmark greedy algorithm. Simulation shows that our algorithm leads to strong performance over a wide range of storage characteristics.

Original languageEnglish (US)
Article number7331335
Pages (from-to)3891-3903
Number of pages13
JournalIEEE Transactions on Power Systems
Volume31
Issue number5
DOIs
StatePublished - Sep 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Keywords

  • Distributed algorithm
  • energy storage
  • phase balancing
  • stochastic optimization

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