Collaboration creates important new grid simulation tool



Quick Take: Utilities around the world are finding that new distribution technologies bring new benefits... but also new challenges. What's the best way to understand and prepare for those challenges? Well you COULD install everything, flip the switch and pray for the best. But a better method is to simulate things in the computer first. And that's just what AEP Ohio did with the help of Battelle.


The result is something that looks to be one of the most powerful simulation tools yet. I thought you'd want to hear about it. -- Jesse Berst


As part of its Department of Energy-funded gridSMART program,
AEP Ohio, a unit of American Electric Power (
AEP), is investigating the impacts of several new distribution technologies. They include Volt/
VAR optimization, energy storage, demand response (DR), electric vehicles (EV), and distributed solar PV.


AEP Ohio worked with Battelle to develop a methodology to accurately model the interactions of these technologies on its diverse set of feeders. The eventual result was a new offering from Battelle called Grid Commandâ„¢ Distribution (GCD). GCD was designed to allow utilities to formulate a roadmap for efficient integration and operation.

GCD's automated visualization of GIS layout supports model validation, modification and analysis.


Real-world applications and benefits

The resulting analysis has enabled
AEP to better determine the benefits of deploying energy storage,  Volt-VAR optimization, and DR across its Ohio service territory, as well a clear vision of the investments needed to manage customer deployments of EV and PV.


 "GCD allowed us to create and modify feeder models containing hundreds of thousands of line of code,” said Karen Sloneker, director - Customer Services and Marketing for
AEP Ohio and project director for
AEP Ohio’s gridSMART Demonstration Project. "A large-scale simulation project would not have been feasible without this resource.”


The benefits of using GCD with GridLab-D included:

1.     Understanding the optimal locations and levels of technology deployment.

2.     Identifying future investment requirements for integrating PV and EV seamlessly.

3.     Providing additional support for rate case development.

4.     Providing a platform for future assessments of vendor offerings in Distribution Automation (DA) and Distributed Energy Resources (

5.     Reducing time to develop a feeder model by 500 times.

6.     Identifying the optimal mix of tariffs for a variety of technology deployment scenarios.

7.     Understanding the interaction effects of PV, EV, DR, Volt-VAR optimization, and energy storage.


Lessons learned

What would Battelle and AEP Ohio do differently or better the next time around? For one thing, they'd increase the upfront scenario planning to ensure that all important potential future states are included. They also discovered that choosing the appropriate time scale, weather scenarios, and time horizon are critical to maximizing insights while minimizing effort. Finally, they found that it was important to have an integrated team with members from both organizations to focus development on features that would be most valuable to
AEP Ohio.