Skip to content
Open access

Look-Ahead Vehicle-to-Grid-Aware Distribution Optimal Power Flow Approach Considering Enhanced C-ADMM-Based Electric Vehicle Aggregation Scheduling

2026 · Energy Engineering · Vol 123, pp. 1-10 · 0 citations · 27 references

Abstract

: To address the impact of electric vehicle (EV) aggregation services on distribution network operation, this paper proposes a look-ahead vehicle-to-grid (V2G)-aware distribution optimal power flow (DOPF) approach that explicitly incorporates the time-varying V2G control errors arising from EV battery dispatch into real-time DOPF decisions. The V2G dispatch model is reformulated into a decomposable structure comprising one master problem and multiple subproblems, where the master problem updates the Lagrange multipliers and each subproblem optimizes the charging and discharging schedule of an individual EV. An enhanced consensus alternating direction method of multipliers algorithm is further developed by incorporating a tailored warm-start strategy to improve computational efficiency. Numerical simulations are performed on distribution networks with a fleet of EVs managed by a real-world EV aggregator. The results demonstrate that the proposed method can effectively account for time-varying V2G control errors and improve the performance of real-time DOPF operation.

Read PDF

Similar papers

Open access Sep 2026

Model Predictive Control for Multi-Objective Vehicle-to-Grid Dispatch: Jointly Optimizing Peak Shaving, Renewable Utilization, Battery Degradation, and Economic Revenue in Smart EV Infrastructures

Vehicle-to-grid (V2G) technology lets a parked electric vehicle push power back to the network, so a fleet of cars can act as distributed storage. Many studies report large benefits from this, such as peak shaving and better use of renewable energy, but most describe their simulation only in words, name no test network...

Muhammad Abdullah Bin Arif, S. Iqbal, Sanchari Deb · 0 citations
Open access Sep 2026

Topology Aware Mixed Discrete Optimization for Optimal Siting and Sizing of Distribution-Static Synchronous Compensators in Electric Vehicle Charging Stations Connected Microgrid Considering Reactive Power Tariffs

Optimal allocation of Distribution Static Synchronous Compensators (D-STATCOMs) is critical for enhancing modern distribution grid performance. However, integrating load and generation volatility alongside technoeconomic objectives yields a highly complex, non-linear, mixed-integer optimization problem. Existing method...

S. Dash · 0 citations
Open access Sep 2026

Multi Scenario Hosting Capacity Optimization of Electric Vehicle Charging Stations in Distribution Networks Considering Managed Charging and Charger Power Factor

The accelerated deployment of electric vehicles requires planning tools able to quantify how much charging infrastructure can be integrated into distribution systems without violating operational constraints. This paper proposes a multi-scenario optimization framework for the siting and sizing of electric vehicle charg...

D. Sanín-Villa, Vanessa Botero-Gómez, Daniel Hincapié-Baena · 0 citations
Aug 2026

Graph-Aware Multi-Agent Power Dispatch in V2G-Enabled Distribution Networks

Large-scale integration of renewable energy and electric vehicles (EVs) increases voltage regulation and coordination challenges in active distribution networks (ADNs). This paper proposes a graph-aware multi-agent coordinated active and reactive power dispatch method for vehicle-to-grid (V2G) enabled ADNs. The propose...

Chao He, Xiao-Yan Liu · 0 citations
Open access Aug 2026

Optimal integration of electric vehicle charging stations and distributed generator in microgrids using bio-inspired optimization techniques

The prompt adoption of Electric Vehicles (EVs) offers substantial challenges to modern power distribution systems, incorporating enlarged power demand, voltage variability, and elevated energy losses. To solve such problems, this paper proposes an integrated optimization scheme for the simultaneous allocation of EV Cha...

A. I. Omar, Mahmoud M. Elbaz, Mahmoud N. Ali et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.