The single most important distinction in electric utility ratemaking — and the foundation of fair, defensible cost allocation.
Every electric bill, every rate study, and every cost-of-service analysis rests on understanding two things: demand and energy. They are related but fundamentally different — and confusing them leads to rates that over- or under-charge entire customer classes.
The maximum rate at which electricity is used
Think of it like the size of the pipe. How much water can flow at once? A bigger pipe costs more to build, even if you don’t always use full flow.
The average rate at which electricity is used over time
Think of it like the total water consumed. How many gallons did you actually use this month? More usage means more fuel burned.
Imagine two customers who each use 1,000 kWh per month. Customer A runs equipment steadily all day. Customer B runs everything at once for a few peak hours. They use the same energy, but Customer B requires far more demand — meaning the utility must build and maintain much more capacity. This is why demand and energy must be measured and charged separately to achieve fair rates.
Two customers each using 720 kWh/month — but with very different demand profiles.
Next: Why does this distinction matter so much? Because it determines who pays what — and whether rates send the right signals.
The way costs are split between demand and energy determines who pays what — and whether rates send the right price signals to customers.
Fixed costs don’t change with how much electricity is produced. They represent the capacity that must be in place to serve peak demand, regardless of whether it’s used every hour.
Variable costs change directly with the amount of electricity generated and delivered. The more kWh produced, the higher these costs.
For most utilities, the majority of costs are fixed (demand-related), yet many rate structures recover them through variable (energy) charges.
When fixed costs are recovered through energy charges, customers who use less energy avoid paying their fair share of the infrastructure that still serves them. This creates cross-subsidies between customer classes and undermines cost causation — the bedrock principle of equitable ratemaking.
Next: How do utilities actually classify their costs into demand, energy, and customer categories?
Once a utility establishes its total revenue requirement, costs must be functionalized (assigned to production, transmission, distribution, or customer service) and then classified as demand-related, energy-related, or customer-related.
For a typical vertically integrated electric utility, 65–75% of the total revenue requirement consists of fixed, demand-related costs. Only 25–35% varies with the amount of energy produced. Yet in many retail rate structures, the majority of revenue is collected through energy charges — creating a fundamental mismatch between cost causation and cost recovery.
Next: The load duration curve is the analytical tool that makes demand/energy classification possible.
A load duration curve is one of the most powerful tools in ratemaking. It sorts every hour of the year from highest demand to lowest, revealing how a system’s capacity is actually used — and how costs should be classified.
8,760 hours sorted by demand (MW). The gap between peak and average demand defines the system’s load factor.
Load factor is the ratio of average demand to peak demand. It measures how efficiently a customer (or system) uses its available capacity.
LOAD FACTOR =
Average Demand ÷ Peak Demand
or equivalently: Total kWh ÷ (Peak kW × Hours)
A higher load factor means the customer uses capacity more evenly, spreading fixed costs over more kWh — resulting in a lower average rate.
Industrial plants, hospitals, data centers. Steady usage, lower average cost per kWh.
Residential, small commercial. Peaky usage patterns mean fixed costs are spread over fewer kWh.
Higher load factor customers use the system more efficiently. Interactive — hover for details.
Next: Different classification methods use load data differently — and the choice significantly affects cost allocation results.
There is no single “correct” way to classify production costs between demand and energy. The choice of method significantly affects which customer classes bear more of the fixed cost burden. Three families of methods are commonly used.
All fixed production costs are classified as demand and allocated based on each class’s contribution to the system peak. This is the strictest cost-causation approach: the infrastructure exists because of peak demand.
Methods: 1-CP, 4-CP, 12-CP
Uses the system load factor to split fixed costs: the load factor percentage goes to energy, the remainder to demand. This “Average & Excess Demand” method recognizes that some capacity serves base load.
Example: 55% LF → 55% energy, 45% demand
Assigns costs based on when generation assets are dispatched. Baseload plants (always on) are classified as energy. Intermediate and peaking plants (on for peaks) are classified as demand.
Base / Intermediate / Peaking split
See how the same $100M in production costs gets classified differently depending on the method chosen. Click a method to compare.
Next: How do these wholesale-level classification decisions cascade into retail rate design?
The classification and allocation decisions made at the wholesale level cascade directly into retail rate design. Understanding this chain is critical for distribution utilities that purchase power from wholesale providers.
Total costs to be recovered
Production, Trans., Dist., Customer
Demand, Energy, or Customer
Assign to customer classes
Set charges per class
For distribution utilities that purchase power from a wholesale provider (like a joint action agency or power pool), the wholesale rate structure determines how production costs are classified.
If the wholesale provider classifies costs strictly (all fixed → demand), the distribution utility’s wholesale demand charges will be higher and energy charges lower. This pricing signal should ideally be passed through to retail customers.
However, many retail utilities historically embed wholesale demand charges into flat energy rates, obscuring the cost-causation signal and shifting costs between customer classes.
Fixed costs → Demand charge ($/kW)
Variable costs → Energy charge ($/kWh)
Result: Strong price signal for peak reduction
Some fixed costs → Energy charge
Result: Low load factor customers under-pay for their share of system capacity costs
Next: Demand charges are the rate design tool that directly addresses the demand/energy mismatch.
Demand charges are the rate design mechanism that directly recovers fixed, capacity-related costs based on a customer’s peak usage. The decision of which customers receive demand charges — and how they’re structured — is one of the most consequential in retail rate design.
Two concepts determine how much a customer class contributes to system costs:
The ratio of a class’s demand at the time of the system peak to the sum of the individual customer peaks within that class (ranges from 0 to 1). A high coincidence factor (common for commercial/industrial classes) means the class tends to peak when the system peaks — imposing proportionally more system cost. Diversity factor is its reciprocal (always ≥ 1).
The inverse of coincidence. Residential customers have high diversity — their individual peaks happen at different times. The sum of individual peaks far exceeds their contribution to the system peak.
Small customers with highly diverse loads traditionally have no explicit demand charge — their demand costs are embedded in energy charges. As customer size grows, demand charges become essential:
For a 50 kW commercial customer at different load factors. Demand-based rates better reflect cost causation.
Next: Distributed energy resources are changing everything — making the demand/energy distinction more critical than ever.
The distinction between demand and energy has never been more important than it is today. Distributed energy resources, battery storage, and electrification are fundamentally changing how customers interact with the grid — and exposing the weaknesses of traditional rate structures.
Solar customers can reduce their energy charges to near zero, yet they still rely on the grid for capacity at all hours. Under energy-only rates, they avoid paying for the fixed infrastructure they still use — shifting costs to non-solar customers.
Behind-the-meter batteries can shave a customer’s peak demand, reducing their demand charge. While this benefits the individual customer, if it doesn’t reduce system peak, the utility’s fixed costs remain — and must be recovered elsewhere.
As transportation and heating electrify, utilities face new load shapes and higher peaks. Demand-based rates send proper signals about the true cost of adding capacity to serve fast-charging stations and heat pumps.
A typical residential solar customer’s daily profile. They still rely on the grid during morning and evening hours, but under energy-only rates, they avoid fixed cost recovery.
Proper demand-energy classification isn’t just an academic exercise. It’s the foundation for rates that remain fair as the grid evolves. Utilities that correctly classify and recover fixed costs through demand-based mechanisms are better positioned to integrate DER, support electrification, and maintain equity across all customer classes.
Battery Storage Blurs the Line: Battery energy storage fundamentally complicates the demand vs. energy distinction. A battery consumes energy when charging (increasing energy consumption) but reduces demand when discharging during peaks (decreasing demand charges). It can arbitrage between on-peak and off-peak prices, provide capacity without consuming net energy, and reshape a customer’s load profile entirely. For rate designers, this means traditional demand charges based on monthly peak may no longer send accurate price signals — customers with storage can “game” demand charges by discharging during peak windows, potentially shifting costs to customers without storage.
From Demand Charges to Demand Flexibility: Traditional demand charges penalize customers for high peak usage. An emerging alternative is demand flexibility — programs that reward customers for shifting load rather than just penalizing peaks. Managed EV charging programs offer credits for allowing the utility to control charging timing. Smart thermostat programs pre-cool or pre-heat homes before peak hours. Time-of-use rates incentivize voluntary load shifting. These approaches achieve the same goal as demand charges (reducing system peak) but through positive incentives rather than punitive pricing, often with higher customer acceptance.
Dedicated EV tariffs typically offer lower off-peak energy rates (sometimes via a separate meter or sub-meter) to incentivize overnight charging. Some utilities offer managed charging programs with bill credits in exchange for allowing the utility to curtail charging during system peaks. The demand vs. energy distinction is central: EV charging is highly flexible in when energy is consumed but adds significant demand if unmanaged.
As building electrification accelerates, utilities are designing rates that encourage fuel switching from gas to electric. Whole-home time-of-use rates, winter off-peak discounts, and heat pump-specific tariffs address the concern that electrification could increase winter peaks. The rate design challenge: encouraging beneficial electrification while managing the demand impact on a system historically sized for summer peaks.
The Evening Peak Shift: Rooftop solar reduces a customer’s energy consumption and non-coincident peak during daytime hours. But it does nothing to reduce — and may worsen — the customer’s contribution to the system coincident peak, which in solar-heavy regions has shifted from afternoon to evening (the “duck curve” neck). A customer with solar may have a low NCP but a high CP contribution. This disconnect means traditional NCP-based demand charges may undercharge solar customers for their actual contribution to the peak that sizes the system — a direct application of the demand vs. energy framework to modern DER policy.
Should your utility use a strict cost accounting approach or an energy-weighted method like AED? The answer depends on your generation mix, regulatory environment, and policy objectives.
At what customer size should demand charges apply? Industry practice ranges from 10 kW to 50 kW. Lower thresholds improve cost causation but add billing complexity.
How should the utility balance fixed-cost recovery between customer charges, demand charges, and energy charges? The answer affects equity, revenue stability, and conservation signals.
As more customers adopt solar, storage, and EVs, does your rate structure send accurate price signals? Or does it create cross-subsidies that undermine long-term fairness?
Getting demand and energy classification right is the foundation of every defensible rate study. We’ve spent decades helping utilities navigate this critical decision.
We’ve guided utilities of every size and structure through cost-of-service and rate design — from small municipals to large investor-owned systems.
Our recommendations are built on rigorous methodology that holds up under scrutiny — whether before city councils, public utility commissions, or cooperative boards.
We help utilities unlock insights from billing, financial, and load data to build smarter classification methods and more accurate cost allocations.
Every state and commission has its own regulatory landscape. We understand the precedents, expectations, and tailor our approach to fit your jurisdiction.
Distributed energy, electrification, shifting demographics — we help you build rate frameworks that are ready for the challenges ahead.
We translate complex demand-energy analysis into clear narratives for staff, elected officials, regulators, and customers.
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