Installing 500,000 electric vehicle charging stations in the next eight years will require cloud-based deployment management tools to coordinate work, manage budgets, facilitate real-time tracking and reporting and create a single source of truth for field staff and local leaders.
President Joe Biden announced on Sept. 14 the release of $900 million to start the mass rollout of electric vehicle charging stations across 35 states. That’s the first tranche of the $7.5 billion the Inflation Reduction Act will ultimately deliver to build out 500,000 EV charging stations nationwide by 2030.
“The great American road trip is going to be fully electrified, whether you’re driving coast to coast along I-10 or on I-75 here in Michigan,” Biden told reporters at the Detroit Auto Show. “Charging stations will be up and as easy to find as gas stations are now.”
Finding them may be easy at some point soon. But building out a nationwide EV charging network? Not so much.
While $7.5 billion is a nice chunk of change, the enormous challenges associated with siting, sourcing and managing thousands of EV charging-station installations at once will take more than throwing money at the problem. Getting to 500,000 charging stations in the next eight years means adding more than 3,000 public charging stations each month. That’s more than double the current pace of public EV-charger deployment. Don’t forget, either, that this mass deployment will happen atop an aging electrical grid, amid a tight labor market for highly skilled technicians and constrained by very real supply chain problems. Governments from town halls to the National Mall will be heavily invested in the process. But how to proceed?
Fortunately, those managing this immense rollout have the examples of the mass deployments of telecommunications towers and base stations (most recently 5G) as well as of commercial and residential solar panels to learn from. What lessons might the experience of those mass deployments have to offer?
Let’s start with challenges specific to EV charging station deployments:
- Public EV charging stations involve real estate, and they’re not making more of it. Companies are racing to identify and secure the best spots and build out quickly in what amounts to a land grab for public-charging locations.
- Installation activities among customers, contractors, utilities and government are diverse, and they’re difficult to coordinate and quality-assure.
- Permitting and easement processes add uncertainty to deployments.
- Financing comes from many sources, often including federal and state grants, with differing requirements around reporting.
- Qualified staff and contractors are hard to find and retain; supply chain issues can put schedules at risk.
Remember, these hurdles are on top of the challenges presented by the sheer volume of EV charging station deployments ahead.
Experience with mass solar and telecom deployments has shown that legacy deployment software – construction management tools, spreadsheets and disparate systems for project management, financial management, asset management and field-crew management – aren’t up to the task of tracking and managing thousands of simultaneous technology installations. Many solar and telecom companies have turned to a new type of software: deployment operations management solutions. (Full disclosure: Mine is among the companies that develop such software). A few of the key features help explain why:
- Templates enable standardization based on industrywide and organization-specific best practices. This cuts redundancy, avoids mistakes and speeds up work to shorten project timelines. At the same time, deployment operations management solutions enable site-by-site variation based on equipment, accessibility, priority, staffing, material availability and other factors.
- Cloud-based architectures provide a centralized data pool that provides a single source of truth for everyone from field techs to top management.
- Centralized data models offer real-time tracking and reporting across the parties and activities involved, including outside contractors. That tracking extends to maintenance, helping shorten response times.
- Sophisticated budgeting and finance functionality smooths the project-finance process and makes it easier to manage the different requirements of various funding sources.
- Machine-learning algorithms harness the data amassed from past and current deployments to improve forecasting and scheduling across a portfolio of EV charging station installations.
Currently, the machine-learning capabilities of these systems are still nascent. But with rising cloud-based data volumes and the continued development of artificial intelligence algorithms feeding on that data, deployment operations management solutions enable machine learning and advanced analytics in ways legacy systems cannot match. Already, they can help forecast project milestones and overall completion times based on the analyses of inputs from project managers, contractors, jurisdictions and market conditions.
Another example already in practice is applying AI to the historical permitting-time duration of various municipalities, counties or other jurisdictions and automatically adjusting project timelines based on that. AI can also help managers prioritize overall project sequences (that is, which EV charging station to deploy when) based on projected completion times.
The mass rollout of EV charging stations involves many hurdles, and state-of-the-art software alone won’t clear them all. But experience has shown that challenges of the sort seen with mass deployments of solar, telecom and EV charging stations are far easier to tackle with the right cloud tools.
Giuseppe Incitti is CEO of Sitetracker.