Researchers have proposed a planning framework for integrating bidirectional electric vehicle battery networks into sustainable communities, offering a way to evaluate how EVs could support local energy systems before neighborhoods are built or upgraded. The framework is designed for neighborhood-level planning and focuses on how EV batteries can both draw power from the grid and supply power back during periods of high demand.
As cities and communities pursue net-zero energy goals, electric vehicles are increasingly being viewed not only as transportation assets, but also as flexible energy resources. When connected through bidirectional charging infrastructure, EV batteries may help store excess renewable energy during off-peak periods and discharge electricity when neighborhood demand rises. That possibility is promising, but it also creates a planning challenge: energy and urban planners need tools that can test how different EV use patterns, charging behaviors, and seasonal building loads interact at the community scale.
The new study addresses this challenge by developing an integrated bidirectional EV battery storage network for net-zero communities. Rather than treating vehicle charging as a simple added electricity load, the framework models EVs as active participants in the neighborhood energy system. According to the article, the approach is intended to help planners examine grid interaction, state of charge, and energy exchange characteristics under specific user behaviors and charging scenarios.
A key feature of the work is the combined use of MATLAB-Simulink and EnergyPlus to simulate EV battery networks in neighborhood settings. This allows the framework to connect electrical-system behavior with building energy demand, which is important because neighborhood energy performance depends on both the mobility patterns of EV users and the heating, cooling, and household loads of buildings. By linking these simulation environments, the study creates a way to test multiple EV microgrid integration scenarios during the early planning stage.
For demonstration, the authors considered a neighborhood archetype made up of 48 single-family detached houses and five electric vehicle use profiles, or EVPs. The analysis examined how the EV battery network could respond across seasons. In the winter scenario, EVPs eliminated peak loads during the early morning hours from 1 am to 6 am by discharging stored energy. In spring, loads exceeded the base load from 1 am to 10 am, with all EVPs discharging energy until 9 am before recharging during off-peak hours.
The seasonal results also showed why charging management cannot rely on one fixed schedule. In summer, the study found that strategic charging management was needed, with EVPs supporting peak loads from 7 am to 6 pm. In fall, EVPs discharged from 12:01 am to 6 am and recharged from 10 am to 6 pm. These patterns suggest that the value of bidirectional EV batteries depends strongly on local demand timing, seasonal building energy needs, and the way drivers use their vehicles.
To support real-time decision-making, the study introduces an EVP peak support index. According to the paper, this index is intended to facilitate real-time charging adjustments and encourage greater participation. Smart charging systems could use such an index to control charging times based on grid needs, helping improve energy distribution and grid stability while still accounting for user behavior.
For sustainable community planning, the framework may be useful because it brings EV charging, distributed storage, and neighborhood energy modeling into a single scenario-generation process. Instead of waiting until infrastructure is deployed to discover whether charging patterns stress or support the grid, planners could use the framework to compare scenarios earlier, evaluate seasonal behavior, and design more coordinated charging strategies for future net-zero neighborhoods.
Further work will still be needed to validate the framework across a wider range of community types, electricity tariffs, renewable generation profiles, charging infrastructure designs, and real-world driver behavior. Even so, the study offers a strong indication that bidirectional EV battery networks can be planned as part of a broader community energy system, not merely as an afterthought to transportation electrification. As EV adoption grows, tools that help neighborhoods coordinate mobility and energy use may become increasingly important for resilient, low-carbon urban development.
Reference
Author:
Srisanthosh Sekar a b , Alampratap Singh Tiwana a c , Kuljeet Singh Grewal a
Title of original paper:
Integrated bidirectional electric vehicle battery network for sustainable communities: A planning framework
Article link:
https://www.sciencedirect.com/science/article/pii/S2773153725000830
Journal:
Green Energy and Intelligent Transportation
DOI:
10.1016/j.geits.2025.100333
Affiliations:
a Future Urban and Energy Lab for Sustainability (FUEL-S), Faculty of Sustainable Design Engineering (FSDE), University of Prince Edward Island, 550 University Ave, Charlottetown, PE, C1A 4P3, Canada
b Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, Tamilnadu, India
c Department of Electrical Engineering, Indian Institute of Technology (IIT) Ropar, Rupnagar, Punjab, 140001, India
Green Energy and Intelligent Transportation
Experimental study
Not applicable
Integrated bidirectional electric vehicle battery network for sustainable communities: A planning framework
30-Jan-2026