Distributed Transactive Framework for Congestion Management of Multiple-Microgrid Distribution Systems

Journal article (2022)

Authors

Sajjad Fattaheian-Dehkordi Aalto University, Sharif University of Technology
A. Rajaei Intelligent Electrical Power Grids - EEMCS , Sharif University of Technology
Ali Abbaspour Sharif University of Technology
Mahmud Fotuhi-Firuzabad Aalto University, Sharif University of Technology
Matti Lehtonen Aalto University
Research Group
Intelligent Electrical Power Grids (EEMCS) (TU Delft)
Copyright: © 2022 Sajjad Fattaheian-Dehkordi, A. Rajaei, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Matti Lehtonen
DOI: https://doi.org/10.1109/TSG.2021.3135139
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Published Date

2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

Intelligent Electrical Power Grids

Abstract

The privatization of distribution systems has resulted in the development of multiple-microgrid (multiple-MG) systems where each microgrid independently operates its local resources. Moreover, the high integration of independent distributed energy sources could lead to operational issues such as grid congestion in future distribution systems. Therefore, this paper provides a transactive-based energy management framework to operate multiple-MG distribution systems; while, alleviating grid congestion in a decentralized manner. In this respect, alternating direction method of multipliers (ADMM) is considered to develop an operational framework that copes with distributed nature of multiple-MG systems. In this context, a novel procedure in the context of ADMM is proposed to distributedly determine transactive coordinator signals which address energy prices as well as power losses and grid congestions. Furthermore, each MG takes into account stochastic programming and the conditional value-at-risk index to handle the uncertainty of its operational scheduling. At last, the proposed framework is applied on IEEE 37-bus and 123-bus test grids to investigate its efficacy in distributed energy management of multiple-MG systems.

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