What Is Load Analysis? Definition & Guide

Key Takeaways

Load analysis determines how much electricity a building uses and when it uses it
Accurate load data prevents oversizing (wasted investment) and undersizing (unmet expectations)
Monthly utility bills provide annual totals; interval data reveals hourly consumption patterns
Seasonal variation in consumption directly affects optimal system size and payback calculations
Load growth projections (EV charging, heat pumps) should factor into system sizing decisions
Self-consumption ratio depends on how well solar production aligns with the building’s load profile

What Is Load Analysis?

Load analysis is the process of evaluating a building’s electricity consumption to determine the appropriate size for a solar PV system. It answers two fundamental questions: how much energy does this building use, and when does it use it?

At its simplest, load analysis involves reviewing 12 months of utility bills to calculate annual consumption in kWh. At its most detailed, it uses 15-minute interval meter data to map exactly how consumption varies by hour, day, season, and weather condition. The depth of analysis directly affects the accuracy of system sizing, financial projections, and customer satisfaction.

For solar professionals using solar design software, load analysis is the starting point for every project. Without it, you’re guessing at system size — and guessing leads to either oversized systems (lower ROI for the customer) or undersized systems (unmet savings expectations).

A 10% error in load analysis can shift the payback period by 1-2 years. Getting consumption data right is as important as getting the roof model right.

How Load Analysis Works

The load analysis process follows a logical progression from data collection to system sizing recommendation:

Collect Utility Data

Gather 12 months of electricity bills showing monthly kWh consumption. Request interval data (15-min or hourly) from the utility if available for more precise analysis.

Identify Consumption Patterns

Analyze when peak usage occurs — morning, midday, evening. Determine if consumption is driven by HVAC (seasonal), lighting (daily), or industrial processes (consistent baseload).

Calculate Annual Baseline

Sum all monthly consumption to establish the annual kWh baseline. Normalize for any unusual months (extended vacations, construction activity, extreme weather events).

Project Future Load Changes

Account for planned additions: EV chargers (3,000-5,000 kWh/year), heat pumps (4,000-8,000 kWh/year), pool heaters, or home office equipment that will increase consumption.

Determine Target Offset

Decide what percentage of consumption the solar system should offset — 80%, 100%, or 120% — based on net metering policy, rate structure, and customer budget.

Size the System

Calculate the required system capacity (kW) by dividing target annual production by the site’s specific yield (kWh/kW), accounting for all system losses.

Basic System Sizing Formula

System Size (kW) = (Annual Consumption × Target Offset %) / (Specific Yield × (1 − System Losses))

Types of Load Data

Different data sources provide different levels of insight for load analysis.

Minimum Required

Monthly Utility Bills

12 months of billed kWh consumption. Provides annual total and seasonal variation. Sufficient for basic residential system sizing but lacks hourly detail needed for TOU or self-consumption optimization.

Recommended

Green Button / Interval Data

15-minute or hourly kWh readings from the smart meter. Reveals daily consumption shape, peak demand times, and baseload levels. Available from most utilities via online portals or data request.

Commercial

Demand (kW) Data

Peak power demand in kW alongside energy consumption in kWh. Required for commercial accounts with demand charges. Affects system sizing strategy and battery storage evaluation.

Advanced

Sub-Metered Circuit Data

Individual circuit monitoring showing consumption by appliance or system (HVAC, lighting, plug loads). Enables load-shifting recommendations and precise self-consumption modeling.

Designer’s Note

When interval data is unavailable, financial modeling tools can generate synthetic load profiles based on building type, square footage, climate zone, and occupancy patterns. These estimates are better than using flat monthly averages but are less accurate than actual meter data.

Key Metrics & Calculations

Load analysis produces several metrics that feed directly into system design and financial modeling:

Metric	Unit	What It Tells You
Annual Consumption	kWh/year	Total energy the building uses in a year — the baseline for system sizing
Peak Demand	kW	Maximum instantaneous power draw — affects interconnection and demand charge analysis
Baseload	kW	Minimum continuous power draw (nighttime/weekend minimum) — sets floor for self-consumption
Load Factor	%	Average demand ÷ peak demand — higher = more consistent consumption pattern
Seasonal Ratio	ratio	Summer vs. winter consumption — indicates HVAC-driven loads
Daytime Consumption Share	%	Percentage of total load occurring during solar production hours (9am-5pm)

Self-Consumption Estimate

Self-Consumption Ratio ≈ Daytime Load / Total Solar Production (simplified, without storage)

Practical Guidance

Load analysis affects every team member’s work, from initial qualification to system commissioning:

Always request 12 full months of data. Partial-year data leads to seasonal bias. A customer who signs up in July may show high summer consumption that doesn’t represent their annual average.
Ask about planned load additions. An EV purchase planned for next year adds 3,000-5,000 kWh/year. A system sized to today’s load will fall short within months of installation.
Match system size to net metering policy. In markets with full retail-rate net metering, oversizing slightly (110-120%) is safe. In net billing markets, size to consumption to maximize self-consumption value.
Use interval data when available. Hourly data enables accurate self-consumption modeling and identifies whether battery storage adds meaningful financial value for this specific customer.

Verify main panel capacity. Load analysis should include confirming the electrical panel has sufficient bus rating and available breaker space for the solar interconnection.
Check for 120% bus bar rule compliance. NEC 705.12 limits solar backfeed based on the panel bus rating. The load analysis determines existing load that factors into this calculation.
Note any non-obvious large loads. Well pumps, electric water heaters, shop equipment, and server rooms may not appear on standard utility bills but affect panel sizing and interconnection.
Document meter configuration. Multiple meters, sub-panels, or generator interlocks affect how the load analysis translates to system design and interconnection requirements.

Collect utility bills at first contact. Requesting bills early in the sales process accelerates proposal generation and demonstrates professionalism.
Explain the sizing rationale. Walk the customer through how their consumption data drove the system size recommendation. This transparency builds trust and reduces objections.
Present multiple offset scenarios. Show 80%, 100%, and 120% offset options with corresponding costs and savings. Let the customer choose based on their budget and goals.
Use rate escalation in projections. Historical utility rate increases of 2-4% per year compound significantly over 25 years. A load analysis combined with rate escalation shows the growing value of solar over time.

Import Load Data for Accurate Sizing

SurgePV’s generation and financial tool imports utility bills and interval data to size systems precisely — matching solar production to actual consumption patterns.

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Real-World Examples

Residential: Family of Four with EV

A family in Colorado consumes 10,800 kWh/year based on utility bills. They plan to purchase an EV within 6 months, adding an estimated 4,200 kWh/year of charging load. The designer uses solar software to model total projected consumption of 15,000 kWh/year and recommends a 10.2 kW system instead of the 7.3 kW system that would only cover current usage. The larger system achieves a 6.1-year payback including the EV load.

Commercial: Retail Store with TOU Rate

A retail store in California consumes 185,000 kWh/year on a TOU rate. Interval data reveals 62% of consumption occurs during on-peak hours (4pm-9pm) when the store is busiest — but solar production peaks at midday. The load analysis shows that without battery storage, only 38% of solar production would be self-consumed during peak rates. Adding a 100 kWh battery shifts the self-consumption peak-hour match to 71%, improving the financial return by 24%.

Industrial: Manufacturing Facility

A manufacturing plant in Ohio operates two shifts (6am-10pm weekdays) consuming 1.2 GWh/year with a consistent 140 kW baseload. The load analysis reveals weekend baseload drops to 35 kW. The designer sizes a 280 kW system to match weekday production with daytime consumption, achieving an 82% self-consumption ratio. Weekend overproduction is exported under the facility’s net billing agreement at the wholesale rate.

Impact on System Design

Load analysis data drives multiple design decisions:

Design Decision	With Load Analysis	Without Load Analysis
System Size	Matched to actual consumption ± planned additions	Estimated from roof area or customer request
Offset Percentage	Optimized for net metering policy and rate structure	Defaulted to 100% without financial justification
Battery Recommendation	Based on load-production mismatch analysis	Generic recommendation without financial basis
Array Orientation	Can optimize for self-consumption timing	Defaults to maximum annual production
Financial Accuracy	ROI based on actual rate schedule and usage	ROI based on average rates and estimated usage

Pro Tip

When utility bills show a dramatic spike in one or two months (typically summer or winter), ask the customer about the cause. If it’s an aging HVAC system, they may be planning a heat pump upgrade — which changes the load profile and should be modeled separately in your analysis.

Frequently Asked Questions

What data do I need for a solar load analysis?

At minimum, you need 12 months of electricity bills showing monthly kWh consumption. For more accurate analysis, request interval data (15-minute or hourly readings) from the utility’s online portal or Green Button data export. Commercial projects should also include demand (kW) data if the account has demand charges.

How does load analysis affect solar system sizing?

Load analysis provides the consumption baseline that determines how large a solar system should be. Without accurate load data, systems are sized based on assumptions that may over- or underestimate actual consumption by 15-30%. The analysis also reveals whether the consumption pattern favors a standard grid-tied system or whether battery storage would significantly improve self-consumption and savings.

Should I account for future electricity usage when sizing a solar system?

Yes. If the customer plans to add an electric vehicle (3,000-5,000 kWh/year), heat pump (4,000-8,000 kWh/year), or other significant electrical loads, these should be factored into the system sizing. It’s more cost-effective to install the right-sized system initially than to expand later, due to permitting, engineering, and mobilization costs for a system addition.

What is the difference between load analysis and load profile analysis?

Load analysis broadly assesses total consumption to determine system size. Load profile analysis is a more detailed examination that maps time-varying consumption patterns — typically using 15-minute or hourly interval data — to optimize the match between solar production and demand curves. Load profile analysis is especially important for TOU rate optimization, battery sizing, and self-consumption maximization.