Optimal Planning of Distribution Systems and Charging Stations Considering PV-Grid-EV Transactions

Haotian Yao, Yue Xiang, Chenghong Gu, Junyong Liu

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Abstract

Uncertainties associated with large-scale deployment of electric vehicles (EVs) and photovoltaic (PV) pose challenges to distribution network expansion planning (DNEP). This paper proposes an optimal planning method for EV charging stations (EVCS) and distribution systems to accommodate the ever-increasing uncertainties. It is achieved by entailing PV-grid-EV transactions, which enables EVCS and PV prosumers to trade energy to make profits while complying with grid securities. It offers a cost-effective operational alternative to long-term planning, which would otherwise result in PV curtailment or unnecessary DNEP. The transactive market operates on a peer-to-peer (P2P) basis and is cleared via a decentralized algorithm to protect privacy and enable autonomous decision-making. EVCS is incentivized by a designed network charge, quantifying its impact on adhering to security constraints from both long-term and short-term perspectives. Considering EV users’ charging decisions, we derive optimal EV charging prices to regulate EV charging flow. We employ multiple linearization techniques to ensure the convergence of the non-convex model. Results demonstrate that the proposed method enables the distribution networks to accommodate the large-scale integration of EV and PV more effectively.

Original languageEnglish
Number of pages13
JournalIEEE Transactions on Smart Grid
Early online date16 Jul 2024
DOIs
Publication statusPublished - 16 Jul 2024

Keywords

  • Costs
  • Distribution network expansion planning
  • Distribution networks
  • Electric vehicle charging
  • EV charging station
  • Indexes
  • network charges
  • Peer-to-peer computing
  • Planning
  • PV prosumer
  • PV-grid-EV transactions
  • Substations

ASJC Scopus subject areas

  • General Computer Science

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