May 08, 2026
Feasibility study for co-located energy storage at EV charging hubs
Operators expanding EV charging networks faced rising grid connection costs and capacity charges — and needed a defensible business case for co-locating Battery Energy Storage Systems (BESS) with charging infrastructure.
Grid connection cost
↓
Duration
10 weeks
Team
3 people
Challenge
The rapid expansion of EV charging networks introduces significant grid constraints and high capacity costs for operators. To mitigate these issues and create new revenue streams, stakeholders must evaluate the complex business case for co-locating BESS directly with charging infrastructure.
Solution
We conducted a comprehensive investment feasibility study focused on integrating energy storage at EV charging hubs. The team modeled dynamic operational scenarios, analyzing the financial impact of peak shaving, load shifting and energy arbitrage to determine optimal sizing and operational strategy for the storage units under varying demand conditions.
Outcome
The analysis delivered a clear assessment of investment profitability, detailing significant reductions in grid connection costs and capacity fees. We then developed a strategic roadmap for the hybrid assets to actively participate in balancing services — transforming the EV charging infrastructure from a pure cost center into a flexible, revenue-generating component of the power system.
What was happening
Charging-network expansion was throwing two cost lines into the operator's P&L faster than the revenue model could absorb: grid connection upgrades and capacity charges scaled with peak demand at each hub.
Co-located BESS was an obvious mitigation in principle — but sizing, cycling strategy and the commercial case across peak shaving, load shifting and arbitrage had not been modelled against the operator's actual load curves.
What changed
We built a dynamic operational model: BESS sizing varied with demand profile, charging mix and grid tariff structure. Peak shaving, load shifting and energy arbitrage were modelled as separate revenue lines, not lumped together.
The output was a defensible investment case and a deployment roadmap — including how the hybrid asset would later participate in balancing services to push it past break-even and into active revenue contribution.
- Dynamic operational modeling per charging hub profile
- Separate financial modeling: peak shaving, load shifting, arbitrage
- Optimal BESS sizing under varying demand conditions
- Roadmap for balancing-services participation post-deployment
AI Transformation, Process Optimization & Cost Efficiency