Peak Demand Management + Load Shifting Playbook

Reduce demand charges by controlling peaks, smoothing loads, and shifting flexible usage (beginner-friendly, not engineering advice)

Run the OperationPlaybook60 min

Important: This is operational guidance, not engineering advice. Work with qualified professionals for controls changes and safety-critical systems.

What you'll accomplish

  • Understand what "peak demand" means and why it drives costs
  • Identify the specific equipment and behaviors causing peaks
  • Implement low-cost peak reduction tactics first (controls and operations)
  • Decide when to consider automation, storage, or demand response programs
  • Measure results using a simple pre/post approach

Who this is for

  • Facilities/ops teams responsible for building performance
  • Finance teams seeing rising demand charges
  • Sustainability teams wanting measurable efficiency improvements
  • Anyone adding new electric loads (EV charging, electrified heating)

When to use this

Use this when:

  • Demand charges are a meaningful portion of electricity cost
  • Monthly bills show high peak kW spikes
  • You see "one bad hour" driving the month
  • New loads are coming online (EVs, electrification)

Prerequisites (minimum viable)

  • 12 months of electricity bills (to see demand charges)
  • If possible: interval data (15-min or hourly) for at least 1–3 months

Quick start (60 minutes)

For one site:

  • Estimate demand charge share from bills (Template 1)
  • Request interval data (Template 2)
  • Identify top 3 peak days/hours (Template 3)
  • Pick two no/low-cost tactics to test (Template 4)
  • Set a peak target (Template 5)

Peak demand in plain English

  • kWh = how much electricity you used over time

  • kW = how fast you used it at a moment (power draw)

Demand charges often bill you based on your highest measured kW during a window.

Beginner rule: You can lower demand charges without lowering total kWh by reducing peak spikes.

Step-by-step

Step 1 — Confirm demand is worth targeting

If demand charges are small, focus elsewhere. If demand charges are large or rising, proceed.

Step 2 — Get interval data (even a little is useful)

You don't need years of data. A few months is enough to find peak patterns.

Step 3 — Identify what causes peaks

Common peak drivers:

  • HVAC start-up (morning warm-up/cool-down)
  • simultaneous equipment start (fans, pumps, compressors)
  • EV charging clusters
  • electric reheating
  • kitchen loads (where applicable)
  • large motors without staggered starts

Step 4 — Apply "no/low-cost" strategies first

Examples:

  • stagger equipment start times (5–15 minute offsets)
  • adjust morning warm-up preheat/pre-cool strategy
  • cap EV charging power during peak windows
  • shift cleaning/laundry/process loads off-peak (if flexible)
  • enforce schedules (turn off what shouldn't run)

Step 5 — Consider "medium-cost" controls improvements

Examples:

  • demand limiting controls
  • smarter setpoint and schedule optimization
  • building automation sequence updates

Step 6 — Evaluate "hardware" options only when needed

Examples:

  • battery storage for peak shaving
  • thermal storage (site dependent)
  • equipment upgrades
  • onsite generation (solar) helps some peaks (site dependent)

Step 7 — Measure results and lock the playbook

You need:

  • implementation date
  • baseline demand
  • post-change demand
  • notes on what changed

Templates

Template 1 — Demand Charge Snapshot (from bills)

Demand Charge Snapshot

| Site | Month | Total $ | Demand charges $ | Demand share % | Peak kW (if shown) | Notes |
|---|---|---:|---:|---:|---:|---|

Template 2 — Interval Data Request Email

Interval Data Request Email

Subject: Request: interval electricity usage data — Account [#]

Hello,
Please provide interval electricity data for account [#] for the period [start–end], including:
- interval length (15-min/hourly)
- timestamps
- kW or kWh per interval
CSV export preferred.

Thanks,
[Name]

Template 3 — Peak Event Log

Peak Event Log

| Site | Peak date | Peak time window | Peak kW | Suspected driver | Evidence link | Notes |
|---|---|---|---:|---|---|---|

Template 4 — Peak Reduction Tactics Menu (starter)

Peak Reduction Tactics Menu

Low/no-cost tactics:
- Stagger equipment start times
- Adjust warm-up/cool-down sequences
- Schedule enforcement (turn off unused loads)
- Shift flexible loads off-peak
- EV charging caps in peak windows

Medium-cost:
- Demand limiting controls
- BAS sequence updates
- Setpoint optimization with constraints

Hardware:
- Battery storage (peak shaving)
- Equipment upgrades (motors, VFDs)
- Onsite generation (site dependent)

Template 5 — Peak Target Plan

Peak Target Plan

Peak Target Plan

Site:
Current observed peak (kW):
Target peak (kW):
Why this target is feasible:
Tactics to implement:
Implementation date:
Owner:
Measurement method:

Template 6 — M and V Summary

M&V Summary

Peak Demand M&V Summary

Site:
Baseline period:
Post period:
Changes made:
Result:
- peak kW change:
- demand charges change:
Confidence (High/Med/Low) and why:

Common pitfalls

  • Trying to solve peak demand without interval data
  • Changing controls without documenting what changed (no proof)
  • Over-optimizing comfort out of the building (creates backlash)
  • Installing batteries without first fixing scheduling and controls
  • Ignoring EV charging as a new peak driver

KPIs

  • Monthly peak kW
  • Demand charge share of total bill
  • Peak events per month above target threshold
  • Comfort complaint count (to ensure you didn't break experience)

Change log

v1.0 (2026-01): Latest release