A new two-layer model for energy management in the smart distribution network containing flexi-renewable virtual power plant

Saeed Abrisham Foroushan Asl, Leila Bagherzadeh, Sasan Pirouzi, Mohammadali Norouzi, Matti Lehtonen*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

This paper presents a two-layer energy management model (EMM) in the smart distribution network (SDN) considering flexi-renewable virtual power plants (FRVPPs) that participate in the day-ahead energy and reserve markets. The first layer of EMM is applied to the FRVPPs to maximize their profit in the proposed markets subjected to the constraints of renewable and flexible sources with considering coordination between these sources and VPP operator (VPPO). Also, the second layer of EMM creates coordination between VPPOs and the distribution system operator to manage the SDN based on minimizing the summation of network energy loss and voltage deviation function as a linear normalized objective function while it subjects to the linear format of AC optimal power flow equations. This model contains uncertainties of load, market price, maximum power of renewable energy sources and demand of flexible sources, where stochastic programming is used to model these uncertain parameters. The proposed model includes bi-level optimization model that is solved by the Benders decomposition approach to achieve an optimal solution at low calculation time. Finally, the capabilities of the proposed model have been investigated by implementing on the IEEE 69-bus distribution network.

Original languageEnglish
Article number107085
Number of pages10
JournalElectric Power Systems Research
Volume194
DOIs
Publication statusPublished - May 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • Benders decomposition method
  • Bi-level optimization model
  • Day-ahead energy and reserve market
  • Flexi-renewable virtual power plant
  • Smart distribution network
  • Two-layer energy management model

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