Local and Central Supervision of Optimal Plug-In Electric Vehicles Energy Dispatching for Load Smoothing within the Innovative Smart Grid
This paper deals with optimal Plug-in electric vehicles (PEVs) energy dispatching with electrical grid incorporating cooperative central and local supervision. The Central Supervision Center (CSC) aims to achieve the collaborative power scheduling for numerous Charging Stations (CSs) equipped with PEVs. In the Local Supervision Center (LSC), the PEVs power management has been established to flatten the conventional load for each Charging Station (CS). Consequently, the CSC gathers information taking into account various constraints, including the load of the respective CS and neighboring CSs, the availability of PEVs at the considered CS and among PEVs' neighbors, the initial State Of Charge (SOC) of the PEVs connected to the respective CS and that of PEVs' neighbors, as well as the allowable lower and upper limits for PEVs battery SOC as inputs data. We considered a simulation of the conventional power for three studied CSs in which the supervision strategy appropriately collaborates among them to guarantee their power smoothness thanks to the bi-directional PEVs energy management. The results highlight the load power improvement achieved by valleys filling and peaks shaving in each CS power profile through four distinctive operating modes. Compared to existing methods in the field, these outcomes reveal the effectiveness of this approach in reducing power fluctuations, achieved through both LSC and CSC, with the goal of alleviating stress on the smart grid. While incentivizing the PEVs integration and Vehicle-to-Grid (V2G) profits, dynamics, lifetime, and cost modelling of PEVs batteries might be included into future studies to enhance their charging process.
Publication Details
- Journal
- International Journal of Renewable Energy Research
- Published
- 2025-01-01
- DOI
- https://doi.org/10.20508/ijrer.v15i1.14710.g9015
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 0.00