Multiagent-Based Energy Trading Platform for Energy Storage Systems in Distribution Systems with Interconnected Microgrids

H. S.V.S.Kumar Nunna, Anudeep Sesetti, Akshay Kumar Rathore, Suryanarayana Doolla

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In this article, an agent-based transactive energy (TE) trading platform to integrate energy storage systems (ESSs) into the microgrids' energy management system is proposed. Using this platform, two different types of energy storage market models are proposed to promote local-level (within the microgrid) and communal- or global-level ESSs' participation in the intra- and intermicrogrid TE markets. Also, a reinforcement learning algorithm known as simulated-annealing-based Q-learning is used to develop bidding strategies for ESSs to participate in the TE markets. Besides energy trading, the proposed system also accounts for the losses caused by energy transactions between ESSs and microgrids using a complex current-tracing-based loss allocation method. The overall efficacy of the proposed energy market management system is demonstrated using a modified IEEE 123-bus distribution system with multiple microgrids and ESSs. Based on simulation results, it is observed that the proposed model can effectively reinforce the balance between the supply and the demand in the microgrids using the mix of local and global ESSs.

Original languageEnglish
Article number9031382
Pages (from-to)3207-3217
Number of pages11
JournalIEEE Transactions on Industry Applications
Volume56
Issue number3
DOIs
Publication statusPublished - May 1 2020

Keywords

  • Electricity markets
  • energy storage systems (ESSs)
  • microgrids
  • multiagent systems
  • transactive energy (TE)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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