Transactive Energy Management of V2G-Capable Electric Vehicles in Residential Buildings: An MILP Approach

Hossein Saber, Hossein Ranjbar, Sajjad Fattaheian-Dehkordi, Moein Moeini-Aghtaie, Mehdi Ehsan, Mohammad Shahidehpour

Research output: Contribution to journalArticleScientificpeer-review

26 Citations (Scopus)

Abstract

This paper proposes a new energy management model for residential buildings to handle the uncertainties of demand and on-site PV generation. For this purpose, the building energy management system (BEMS) organizes a transactive energy (TE) market among plug-in electric vehicles (PEVs) to determine their charge/discharge scheduling. According to the proposed TE framework, the PEV owners get reimbursed by the BEMS for the flexibility they offer. In this regard, the PEV owners submit their response curves for reimbursement upon arrival. Then, the BEMS solves an optimization problem to maximize its own profit and determine the real-time TE market-clearing price. Afterward, based on the clearing price, the real-time scheduling of PEV batteries and the reimbursements to the PEV owners for their responses are determined. Additionally, the original mixed-integer non-linear optimization problem is reformulated as a mixed-integer linear programming one using a set of linearization techniques. Finally, the proposed model is applied to a residential building with 50 PEV charging piles, and the simulation results show that the proposed model decreases the actual charging payment of PEV owners by 17.6% and 52.3%, and the total cost of BEMS by 5.1% and 10.8% compared to demand response concept-based and uncontrolled charging models, respectively.

Original languageEnglish
Pages (from-to)1734-1743
Number of pages10
JournalIEEE Transactions on Sustainable Energy
Volume13
Issue number3
Early online date2022
DOIs
Publication statusPublished - Jul 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Batteries
  • Buildings
  • Costs
  • Optimal scheduling
  • Real-time systems
  • State of charge
  • Uncertainty

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