Energy & Utilities

Measure interventions that improve output, uptime, and efficiency.

Energy and utilities teams operate complex systems where small optimizations compound at scale. Decision Process helps you run controlled experiments on maintenance schedules, demand response programs, and equipment configurations — and quantify the effect before you commit.

Experiment Templates

Ready-to-run experiments

Demand Response Incentive Test

Time-of-use pricing incentives reduce peak demand more than flat rate plans.

Conditions

  • Flat rate plan (control)
  • Time-of-use pricing

Metrics

  • Energy Output (MWh)
  • Efficiency Rate (%)
  • Cost per kWh (USD)
Site−18% peak demand

Turbine Maintenance Interval Optimization

90-day preventive maintenance intervals outperform 60-day for output and uptime.

Conditions

  • 60-day PM (control)
  • 90-day PM
  • Condition-based

Metrics

  • Downtime Hours (hrs/month)
  • Energy Output (MWh)
  • Maintenance Cost (USD/yr)
Turbine−36% downtime hrs

Solar Panel Orientation A/B

East-west bifacial panel orientation produces higher daily yield vs. south-facing.

Conditions

  • South-facing (control)
  • East-west bifacial

Metrics

  • Energy Output (MWh)
  • Capacity Factor (%)
  • Cost per kWh (USD)
Panel array+9% annual yield

Worked Example

Preventive maintenance intervals across 18 wind turbines

A wind farm operator randomly assigns turbines to one of three PM schedules: 60-day (current standard), 90-day extended, or condition-based triggered by sensor thresholds. 6 turbines per arm, measured over 9 months.

Results: downtime_hours / month

60-day PM (control)

mean: 14.2 hrs/mo

95% CI: 11.4–17.0

90-day PM

mean: 13.8 hrs/mo

95% CI: 11.0–16.6

P(better) = 61%

Condition-based PM

mean: 9.1 hrs/mo

95% CI: 7.0–11.2

P(better) = 97%

Condition-based maintenance reduces downtime by −5.1 hrs/month (d = −0.79, large effect) at 97% posterior probability vs. the 60-day schedule. The 90-day schedule shows no meaningful improvement — interval extension alone doesn't drive the gain. Recommendation: pilot condition-based PM across the full fleet.

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