European Smart Grid Software Firm Adds AI-Powered Tool for Long-Term Distribution Planning

envelio, a Cologne-based smart grid software provider, has introduced a new digital planning tool designed to help distribution utilities navigate the rapidly changing conditions of the energy transition. The application, called the Strategic Grid Planner, extends the company’s Intelligent Grid Platform (IGP) and focuses on enabling loadflow-based, multi-year system planning for distribution networks.

The launch comes as distribution operators across the U.S. and Europe confront unprecedented complexity from distributed generation, electric vehicles, battery storage, and volatile load profiles. Many utilities are simultaneously facing interconnection backlogs, rising capital requirements, and pressure to improve scenario-based planning for future system states.

AI-Driven Analysis Across Multiple Time Horizons

According to envelio, the Strategic Grid Planner evaluates thousands of technically feasible and economically optimized planning alternatives for future target years such as 2030, 2035 and 2045. The system uses high-performance simulation, network modeling, and algorithmic optimization to coordinate planning decisions across scenarios and time horizons.

The goal is to support planners who must make multi-billion-dollar investment decisions without modern digital tools that can fully assess the range of viable network upgrades and non-wires alternatives.

“The current pace of change in the distribution grid is unprecedented,” said Luigi Montana, CEO of envelio Inc. “The decisions made today will affect the next 5-20 years and beyond. But today’s approach to system planning was not designed for the current complexity and volatility.”

Evaluating Optimization, Flexibility, Reinforcement and Expansion

The new application incorporates several planning steps that utilities increasingly consider as DER penetrations rise. The software evaluates grid optimization and flexibility options before moving to reinforcement and expansion measures.

For example, the platform can analyze switch state optimization across an entire primary network to maximize load balancing before recommending infrastructure upgrades. The company says the tool can also support cluster-study analyses by evaluating multiple interconnection requests under shared system constraints—an area of growing focus for U.S. utilities trying to manage clean energy queues.

Self-Learning Algorithm for Continuous Improvement

At the core of the Strategic Grid Planner is a self-learning algorithm that adapts over time as it runs additional scenarios. The model identifies patterns from successful expansion strategies and uses those insights to refine its recommendations and reduce planning cycle time. Planners can review and amend machine-generated proposals if needed.

Toward Automated and Defensible Planning

Utilities globally have been exploring how AI-driven analytics could supplement traditional planning methods and provide more defensible reasoning for capital allocation under evolving regulatory scrutiny. Tools that automate scenario evaluation and cost comparison are viewed as one pathway to faster interconnection studies, improved visibility of constraints, and better prioritization of grid investments.

The Strategic Grid Planner sits within envelio’s broader Intelligent Grid Platform, which includes applications for grid operations, control, and planning.