Optimal centralized scheduling strategy for bidirectional charging of PEV fleets in low-voltage microgrids
• Proposes a centralized, linear programming-based strategy for optimal bidirectional scheduling of PEV fleets in low-voltage microgrids. • Integrates forward-backward sweep load flow analysis to ensure real-time voltage stability during G2V and V2G operations. • Demonstrates significant energy cost reduction (up to 50 %) and voltage improvement through Time-of-Use tariffs and PV integration. • Considers realistic operational constraints including SoC limits, charger ratings, voltage bounds, and feeder power capacities. • Provides a scalable and adaptable framework for demand-side management applicable to future smart grids and real-time control systems. 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.
Authors
- Binod Kumar Sahu (ORCID: https://orcid.org/0000-0001-5639-9928)
- Indu Sekhar Samanta (ORCID: https://orcid.org/0000-0003-1149-5603)
- Mohit Bajaj (ORCID: https://orcid.org/0000-0002-1086-457X)
- Vojtěch Blažek (ORCID: https://orcid.org/0000-0003-0508-8518)
- Subhasis Panda (ORCID: https://orcid.org/0000-0002-9753-7255)
- Cansu Ayvaz Güven (ORCID: https://orcid.org/0000-0001-8907-1718)
- Lukáš Prokop (ORCID: https://orcid.org/0000-0003-0495-5499)
- Buddhadeva Sahoo (ORCID: https://orcid.org/0000-0002-5601-1513)
- Pravat Kumar Rout (ORCID: https://orcid.org/0000-0003-0462-9781)
Institutions
- Al-Ahliyya Amman University (JO)
- National Institute of Technology Warangal (IN)
- VSB - Technical University of Ostrava (CZ)
- Siksha O Anusandhan University (IN)
- Sri Sri University (IN)
- Yalova University (TR)
- Graphic Era University (IN)
Publication Details
- Journal
- e-Prime - Advances in Electrical Engineering Electronics and Energy
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1016/j.prime.2025.101136
- Citations
- 1
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 0.73