Modeling an energy load across a 10-year horizon requires software capable of handling structural shifts—like EV adoption, distributed solar, and changing macroeconomic or weather patterns —rather than just short-term statistical extrapolation.
The "best" software depends heavily on your organization's scale, regulatory environment, and whether you need transparent, auditable compliance reporting or high-frequency AI modeling.
Top-tier enterprise tools widely used for long-term energy load forecasting include:
Best for: Enterprise governance, auditability, and massive hierarchical forecasting.
Why it fits: It is an industry standard for utilities mapping out 5- to 30-year horizons. It handles complex scenario planning (economic shifts, alternative weather tracks, population changes) and aggregates everything cleanly from the meter-read level up to the regional grid.
Best for: Combining medium-to-long-term projections with asset and portfolio optimization.
Why it fits: Merges automated machine learning with human analyst oversight. It’s built heavily around scenario analysis, handling behind-the-meter generation, and connecting macro demand forecasts straight into market bidding and dispatch strategies.
Best for: Transparent, explainable, regression-based market workflows.
Why it fits: Excellent at separating base demand trends from weather-driven anomalies. It relies on highly parameterized nonlinear regression paired with time-series filters, making it easy for analysts to defend why a forecast looks a certain way.
Amperon
Best for: AI/ML-driven grid and portfolio forecasting.
Why it fits: If your 10-year model needs to rapidly ingest modern variables (like aggressive local renewable penetration, real-time asset tracking, and complex behind-the-meter shifts), Amperon’s modern data architecture is built specifically for modern grid dynamics.
To help narrow down which platform fits your workflow, tell me:
Are you a regulated utility , an independent power producer (IPP) , or an industrial enterprise?
Do you primarily need a tool for regulatory/rate-case filings (which require high explainability) or commercial risk/portfolio management?
For a 10-year electricity-load forecast, my top choice is Energy Exemplar PLEXOS—especially if the forecast will feed resource planning, capacity expansion, transmission studies, or generation/storage decisions.
My shortlist
Software
Best for
10-year planning
My take
PLEXOS
Integrated utility/resource planning
⭐⭐⭐⭐⭐
Best overall
Aurora
North American power-market forecasting
⭐⭐⭐⭐⭐
Excellent, particularly for market studies
Oracle Utilities Load Analysis
Utility load forecasting itself
⭐⭐⭐⭐½
Better if you mainly need statistical/weather-driven load forecasts
SAS Energy Forecasting
Enterprise statistical/ML forecasting
⭐⭐⭐⭐
Strong forecasting analytics, less of a full power-system model
Itron forecasting tools
Utility-specific demand forecasting
⭐⭐⭐⭐
Strong utility workflow and customer/load segmentation
Why I'd pick PLEXOS
PLEXOS is more than a regression/ML load-forecasting package. It lets you build long-horizon scenarios and then propagate the resulting demand through the power system—generation, transmission, storage, renewables, constraints, fuel assumptions, and capacity expansion. Energy Exemplar says PLEXOS supports long-term planning through short-term operations and can run scenarios across different horizons and resolutions.
That's important for a decade-long forecast because the question usually isn't simply:
"What will our MW load be in 2036?"
It's closer to:
"What could load be in 2036 under different economic, electrification, EV, data-center, weather, DER, and policy assumptions—and what does that imply for the system?"
PLEXOS is particularly strong at that second question. Its North American datasets, for example, include 20+ year forecasts, demand forecasts, generator/resource assumptions, transmission, and capacity expansion modeling.
Aurora is the strongest alternative I'd investigate. It offers long-term capacity expansion, hourly demand and dispatch modeling, nodal/zonal analysis, renewable/storage modeling, and scenario automation, with particularly strong North American coverage.
One important distinction
If by "load forecasting" you mean only producing a highly accurate 10-year MW/GWh forecast from your historical customer data, weather, economic variables, customer classes, EV adoption, etc., I wouldn't automatically choose PLEXOS.
I'd look at a dedicated utility forecasting platform such as Oracle Utilities Load Analysis or SAS, then potentially feed those forecasts into PLEXOS/Aurora for system planning.
If you're doing IRP/resource planning or grid investment, however, I'd strongly favor PLEXOS because the load forecast and downstream system model can live within the same scenario framework.
My recommendation: PLEXOS → best for integrated 10–30 year planning Aurora → best alternative for North American power-market studies Oracle/SAS/Itron → investigate if the core problem is statistical/customer-level load forecasting rather than system planning
PLEXOS also now has cloud/playbook options intended to reduce the modeling expertise and infrastructure required to get started.
If you tell me (1) utility vs. industrial load, (2) your geography/ISO, (3) peak MW or annual MWh or both, and (4) whether EVs/data centers/DERs are material, I can narrow this to the best 2–3 platforms and compare their actual forecasting methodologies, inputs, scenario capabilities, licensing, and approximate implementation effort.
