Time-of-Use Rate (TOU)

Unlike dynamic pricing, TOU rates rely on fixed time blocks established months or years in advance. The utility divides the calendar into distinct periods—typically on-peak, mid-peak, and off-peak—with each block assigned a static $/kWh rate. This structure provides price certainty for consumers but lacks the granularity to reflect real-time grid stress. The schedule is deterministic, allowing building management systems to program automated load shifts without receiving a live signal.

The primary engineering goal of a TOU rate is to reduce peak coincidence factor—the ratio of a customer's demand during the system peak to their maximum demand. By imposing a steep differential (often 3:1 or 5:1) between on-peak and off-peak energy charges, the tariff creates a financial incentive to shift deferrable loads like electric vehicle charging or HVAC precooling to overnight hours. This flattens the aggregate system load curve without requiring direct utility control.

TOU structures often incorporate a seasonal component to address weather-driven load variability. A summer schedule (June–September) may define a broad 4–9 PM peak window to capture air conditioning load, while a winter schedule shifts the peak to early morning hours for electric heating. This temporal segmentation ensures the rate design aligns with the net load profile of the specific service territory, preventing cost misallocation between seasons.

A critical technical distinction: TOU is a passive rate structure, not a dispatchable resource. The utility cannot toggle the price to address an unexpected contingency. If a generator trips offline during an off-peak period, the TOU rate remains low, providing no incentive for load reduction. This limitation is why TOU is often layered with Critical Peak Pricing (CPP) overlays or Automated Demand Response (ADR) programs to handle low-probability, high-impact grid events.

Unlike incentive-based demand response programs that require a Customer Baseline Load (CBL) calculation to measure performance, TOU rates settle purely on metered consumption. The financial incentive is embedded directly in the volumetric charge. This eliminates the complex Measurement and Verification (M&V) disputes common in pay-for-performance contracts. The trade-off is that the utility pays for load reduction regardless of whether the grid actually needed it at that specific moment.

Regulatory design significantly impacts TOU adoption elasticity. In an opt-out model, customers are defaulted onto the time-varying rate and must actively choose to return to a flat tariff. This exploits status quo bias and typically achieves >80% enrollment. In an opt-in model, flat rates remain the default, requiring proactive customer selection. The opt-out approach is critical for achieving the portfolio scale necessary to measurably shift the system load duration curve.

An electricity rate structure where the price per kilowatt-hour fluctuates at hourly or sub-hourly intervals to reflect actual wholesale market conditions. Unlike TOU's fixed schedule, RTP exposes consumers to the true locational marginal price (LMP) of generation.

• Granularity: Typically 60-minute intervals
• Risk Profile: Higher volatility than TOU
• Enabling Technology: Requires smart meter infrastructure and automated price-responsive controls

A real-time or time-varying electricity rate transmitted to consumers to incentivize load reduction when generation costs or grid stress are high. TOU is the simplest form of dynamic pricing, while RTP and CPP represent more advanced variants.

• Purpose: Align retail consumption with wholesale cost
• Communication Path: Utility server → smart meter → home energy management system
• Standard Protocols: OpenADR 2.0b, IEEE 2030.5

A statistical calculation of what a customer's energy consumption would have been in the absence of a TOU rate or demand response event. CBL is the reference point against which load shifting or reduction is measured.

• Common Methods: 10-day average, regression models, matched-day control groups
• Critical Function: Determines financial settlement for demand response performance
• TOU Interaction: CBL analysis validates whether TOU pricing actually modifies behavior

The process of rescheduling energy consumption from peak demand periods to off-peak periods without necessarily reducing total energy usage. TOU rates are the primary economic mechanism designed to incentivize this behavior.

• Example: Running a dishwasher at 2:00 AM instead of 6:00 PM
• Industrial Application: Pre-cooling thermal storage during low-rate hours
• Measurement: Evaluated against CBL to confirm temporal redistribution

A metric quantifying the degree to which consumer electricity consumption changes in response to a fluctuation in the retail price of power. This is the fundamental behavioral assumption underlying TOU rate design.

• Typical Residential Range: -0.1 to -0.3 (inelastic)
• TOU Impact: Even low elasticity can shift 3-7% of peak load
• Enabling Factors: Automation increases effective elasticity by removing manual decision-making