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Utility Planner

Conducting transmission and distribution system studies

Enhances✓ Available Now

What You Do Today

Run power flow, contingency, short circuit, and stability studies to identify system limitations and determine where investment is needed.

AI That Applies

AI automates routine study cases, identifies critical contingencies more efficiently, and screens thousands of scenarios to find the ones that matter.

Technologies

How It Works

For conducting transmission and distribution system studies, the system identifies critical contingencies more efficiently. The simulation engine runs thousands of scenarios by varying each uncertain input across its probability range, building a distribution of outcomes that quantifies the risk. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

Scenario screening is orders of magnitude faster. AI identifies the critical cases from thousands of combinations rather than you manually setting up each study.

What Stays

Engineering interpretation of results and solution development. Knowing that a line is overloaded is data — designing the right fix is engineering.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for conducting transmission and distribution system studies, understand your current state.

Map your current process: Document how conducting transmission and distribution system studies works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Engineering interpretation of results and solution development. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support PSS/E tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long conducting transmission and distribution system studies takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your VP Operations or COO

What data do we already have that could improve how we handle conducting transmission and distribution system studies?

They're prioritizing which operational processes to automate

your process improvement or lean lead

Who on our team has the deepest experience with conducting transmission and distribution system studies, and what tools are they already using?

They understand the workflow dependencies that AI tools need to respect

a frontline supervisor

If we brought in AI tools for conducting transmission and distribution system studies, what would we measure before and after to know it actually helped?

They see the daily reality that AI tools need to fit into

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.