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Optimal centralized scheduling strategy for bidirectional charging of PEV fleets in low-voltage microgrids

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10259310" target="_blank" >RIV/61989100:27240/25:10259310 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/61989100:27730/25:10259310

  • Výsledek na webu

    <a href="https://www.sciencedirect.com/science/article/pii/S2772671125002426" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2772671125002426</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.prime.2025.101136" target="_blank" >10.1016/j.prime.2025.101136</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Optimal centralized scheduling strategy for bidirectional charging of PEV fleets in low-voltage microgrids

  • Popis výsledku v původním jazyce

    Rapid growth of plug-in electric vehicles (PEVs) is reshaping demand in low-voltage microgrids where voltage stability and power-quality margins are tight. Uncoordinated charging deepens evening peaks, stresses feeder limits, and constrains renewable hosting. This paper proposes a centralized, optimization-based scheduling strategy for bidirectional charging coordinating grid-to-vehicle (G2V) and vehicle-to-grid (V2G) dispatch to jointly minimize energy cost and enhance voltage stability. A linear programming (LP) model optimizes charging/discharging over discrete intervals subject to realistic constraints: charger power limits, state-of-charge (SoC) bounds, nodal-voltage regulation, and line-flow limits. The optimization is embedded in a forward-backward sweep load-flow loop to respect feeder physics. Using the IEEE European LV 8-bus system, we evaluate five scenarios single tariff, time-of-use (ToU) tariff, holiday load growth, ToU under holiday load, and photovoltaic (PV) integration. Relative to an uncontrolled baseline, the centralized strategy shifts demand off-peak, reduces peaks by up to 40% (12.0 to 7.2 kW), lowers energy cost by up to 25% (₹192.0 to ₹144.0), and improves minimum node voltages to 400–407 V; with PV, energy cost reaches ₹96.0 and minimum voltage rises to 412 V, all within EN 50,160 (±10%) bounds. These results validate a practical, scalable demand-side management (DSM) approach that improves reliability, reduces operating cost, and facilitates renewable integration; extensions to real-time, data-driven, or decentralized variants for larger fleets are outlined. © 2025 The Author(s)

  • Název v anglickém jazyce

    Optimal centralized scheduling strategy for bidirectional charging of PEV fleets in low-voltage microgrids

  • Popis výsledku anglicky

    Rapid growth of plug-in electric vehicles (PEVs) is reshaping demand in low-voltage microgrids where voltage stability and power-quality margins are tight. Uncoordinated charging deepens evening peaks, stresses feeder limits, and constrains renewable hosting. This paper proposes a centralized, optimization-based scheduling strategy for bidirectional charging coordinating grid-to-vehicle (G2V) and vehicle-to-grid (V2G) dispatch to jointly minimize energy cost and enhance voltage stability. A linear programming (LP) model optimizes charging/discharging over discrete intervals subject to realistic constraints: charger power limits, state-of-charge (SoC) bounds, nodal-voltage regulation, and line-flow limits. The optimization is embedded in a forward-backward sweep load-flow loop to respect feeder physics. Using the IEEE European LV 8-bus system, we evaluate five scenarios single tariff, time-of-use (ToU) tariff, holiday load growth, ToU under holiday load, and photovoltaic (PV) integration. Relative to an uncontrolled baseline, the centralized strategy shifts demand off-peak, reduces peaks by up to 40% (12.0 to 7.2 kW), lowers energy cost by up to 25% (₹192.0 to ₹144.0), and improves minimum node voltages to 400–407 V; with PV, energy cost reaches ₹96.0 and minimum voltage rises to 412 V, all within EN 50,160 (±10%) bounds. These results validate a practical, scalable demand-side management (DSM) approach that improves reliability, reduces operating cost, and facilitates renewable integration; extensions to real-time, data-driven, or decentralized variants for larger fleets are outlined. © 2025 The Author(s)

Klasifikace

  • Druh

    J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS

  • CEP obor

  • OECD FORD obor

    20200 - Electrical engineering, Electronic engineering, Information engineering

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2025

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    e-Prime - Advances in Electrical Engineering, Electronics and Energy

  • ISSN

    2772-6711

  • e-ISSN

    2772-6711

  • Svazek periodika

    14

  • Číslo periodika v rámci svazku

    101136

  • Stát vydavatele periodika

    GB - Spojené království Velké Británie a Severního Irska

  • Počet stran výsledku

    22

  • Strana od-do

    1-22

  • Kód UT WoS článku

  • EID výsledku v databázi Scopus

    2-s2.0-105023317390