Press Conference: Integrating Load Forecasting with Distribution System Planning
At DTECH 2026, during a press conference at the envelio booth, Luigi Montana, CEO of envelio, and Scott Smith, President of Integral Analytics, addressed a challenge reshaping utility planning: load forecasting is becoming more complex, and planning workflows must evolve to keep pace.
The two companies have partnered to integrate Integral Analytics’ LoadSEER® forecasting application with envelio’s Intelligent Grid Platform (IGP). The integration enables utilities to carry long-term load assumptions directly into a grid-aware distribution system model, allowing forecast outputs to be evaluated within the same analytical environment used for engineering-grade studies.
Forecasting future demand is growing more difficult as load growth, distributed energy resources (DERs), storage adoption, and electrification introduce greater variability into long-term assumptions.
As Luigi explained:
“On the one hand, forecasting, looking into the future, gets more complex with load growth. We have DERs going onto the grid, storage, more complexity overall – you have more volatility, more uncertainty.”
At the same time, operational constraints are intensifying:
“On the other side, also solving the grid constraints is getting more complex. We're looking at flexibilities. How can we make the grid expansion with less is more affordable in the future.”
Together, these dynamics are increasing both the volume of planning scenarios utilities must evaluate and the analytical effort required to understand their impact on the distribution system.
From Scenario Development to Feeder-Level Insight
As forecasting becomes more scenario-driven, utilities must move from high-level demand assumptions to feeder-level system analysis.
Utilities are planning for electrification, distributed energy resource growth, evolving customer demand, and increasingly concentrated loads such as data centers. LoadSEER supports long-term scenario modeling across these trajectories, generating granular hourly load shapes over multi-decade planning horizons.
“LoadSEER is designed to create 30 years’ worth of hourly load shapes and many ‘what if’ scenarios,” Scott explained.
However, generating scenarios is only the first step. As Scott added:
“Our utilities are challenged with building multiple scenarios and just getting through one scenario or getting through a base case requires hours and hours of labor.”
Once those scenarios are defined, each one must be translated into feeder-level simulations to understand its operational impact.
Luigi underscored the scale of that responsibility:
“When you're dealing with thousands of scenarios, thousands of different versions of the future, this means you have to also assess what is the impact on the grid — and this typically means you have to run millions and millions of load flows to see ‘how do my feeders behave? What is the impact on my linear assets and my other assets? How can I solve these constraints?’”
This is where the integration between LoadSEER and the Intelligent Grid Platform becomes operationally significant. Rather than exporting forecast results and rebuilding study cases across separate tools, utilities can apply forecast assumptions directly within a maintained, computable model of the distribution network. That enables consistent scenario evaluation across planning studies, hosting capacity assessments, interconnection analyses, and reinforcement planning workflows.
Evaluating those impacts consistently requires a model capable of supporting large volumes of scenario-based load flow analysis while maintaining data quality and network integrity.
Luigi explained how the IGP provides that foundation:
“With the IGP, we gave our customers the ability to do exactly that by [...] giving them a network model orchestration, so the data quality and the right data to do this analysis, by giving them a powerful simulation engine that is able to run millions of load flows in a short amount of time and produce results that they can take, they can trust and they feel they can put in front of their stakeholders to find an affordable way to invest into the system going forward.”
By keeping forecast assumptions aligned with grid modeling workflows, utilities can reduce manual case-building effort and increase confidence that long-term planning inputs are consistently reflected in engineering simulations.
Planning in a Time of Uncertainty
Utilities are no longer evaluating a single demand trajectory. Electrification trends, DER adoption, evolving customer behavior, and policy-driven shifts require planners to consider multiple possible futures — and understand their operational consequences across the distribution system.
Luigi summarized the objective during the press conference:
“By bringing these two products together, we're giving utilities and engineers the tool to do planning to deal with uncertainty and to make sure that they make the right decisions in this time of [volatility] and make the right investment decisions.”
The discussion at DTECH reflected a broader shift across the industry: effective distribution system planning increasingly depends on integrating long-term forecasting with grid-aware modeling in a single, scalable analytical workflow.
For a formal overview of the collaboration between envelio and Integral Analytics, see the official partnership press release.