When evaluating an energy project for an industrial facility, businesses often begin with questions such as: How much Solar PV capacity do we need? What BESS configuration might be required? Which systems should be improved to optimize electricity costs?
Before deciding on capacity or technology, however, a more fundamental question needs to be answered:
How does the facility actually use electricity?
Monthly electricity consumption shows how many kWh the facility uses, but it does not reveal when that electricity is consumed, when peak demand occurs, the level of the base load, or which operating activities drive those changes.
This is why industrial load profile analysis should precede many energy investment decisions. Load data helps businesses understand how electricity is being used and provides a stronger basis for evaluating Solar PV, BESS, EMS, or energy efficiency measures under actual operating conditions.
Why Is Total Energy Consumption Alone Not Enough to Understand the Load Profile?
Two industrial facilities can consume approximately the same amount of electricity over a given period while having very different load profiles.
Two industrial facilities can have approximately the same total energy consumption while exhibiting very different load profiles over time. Qualitative illustration only; not project data.
One facility may operate at a relatively stable power level throughout most of its production hours. Another may remain at a lower load for extended periods but experience significant demand peaks when several production lines or major systems operate simultaneously.
If the assessment relies only on the total kWh shown on the electricity bill, this difference may not be visible. For an energy project, however, when electricity is used, the level of power demand, and how the load varies over time can directly influence how a solution should be evaluated and configured.
Interval load data helps reveal when demand increases, how long demand peaks last, the level of the base load, and how electricity use changes across shifts or operating days.
An industrial facility should therefore not be assessed only by asking, “How much electricity does it consume?” It is equally important to understand when electricity is used and what causes the load to change.
The objective is not to collect as much data as possible. It is to obtain the right data for the decision that needs to be made.
What Data Should Be Reviewed When Analyzing an Industrial Load Profile?
A useful data set should help the business understand four areas: how much electricity is used, when it is used, what drives the load, and how that load may change in the future.
1. Electricity Bills and Historical Consumption
Electricity bills are a logical starting point for understanding consumption levels and cost structure, but one month of data is rarely enough to represent the full operating pattern of an industrial facility.
For an initial assessment, around 12 months of billing data is often a useful starting point for observing a full operating cycle, seasonal effects, and differences between production periods.
If the facility has recently expanded capacity, significantly changed its production schedule, or experienced unusual operating periods, a longer data history may be needed to avoid establishing a baseline from an unrepresentative period.
Beyond total kWh, businesses should also review other factors that may affect electricity costs, such as demand-related charges, power factor, and applicable tariff conditions.
Where the objective is energy cost optimization, the assessment should use the current tariff structure, time-of-use periods, and applicable conditions for the specific metering point or customer category being assessed, rather than relying on a generic average electricity price.
2. Interval Load Data and Load Profile
If the electricity bill answers “how much,” the load profile helps answer “when.”
Interval data allows the technical team to observe how power demand changes throughout the day: at shift start-up, when multiple production lines operate simultaneously, during breaks, on weekends, or during periods of reduced production.
This can help identify the base load, periods of high demand, the duration and frequency of demand peaks, and differences between shifts or operating days.
Not every project requires the same data resolution.
Data at 15-minute, 30-minute, hourly, or other intervals should be selected according to the phenomenon being investigated. If the objective involves short demand peaks, monthly or even daily aggregate data may not provide enough detail for an informed conclusion.
In practical terms, the resolution of the data should be appropriate to the decision being made.
3. Production Schedules and Output
A load curve shows when power demand rises or falls, but it does not explain the cause on its own.
To turn electricity data into useful information for investment decisions, the facility’s load profile should be assessed alongside shift schedules, production schedules, production output, shutdowns, maintenance periods, and the operating hours of major systems.
A demand peak may occur because several motors start at the same time, a cooling system increases its load, compressed-air demand rises, or multiple production lines are scheduled to operate simultaneously.
Without this operating context, a business may be able to identify a peak but still be unable to determine its cause or whether there is a practical opportunity to intervene.
This context is also important when comparing performance across different periods. Higher electricity consumption does not necessarily mean lower efficiency if production output has increased accordingly. Conversely, unchanged electricity consumption does not automatically indicate stable efficiency if production output has declined.
4. Major Energy-Consuming Loads and Systems
A facility-level meter shows how the site as a whole is using electricity. When deeper analysis is required, the next question becomes:
Which systems are driving that load?
Depending on the facility, these may include chillers, compressed-air systems, HVAC, pumps, fans, large motors, or major production equipment.
This does not mean every piece of equipment needs to be separately metered.
Measurement points should be selected according to the value of the information they can provide for the decision being made. If a system represents a significant share of demand or has an operating pattern that needs to be understood more clearly, submetering that area may provide more useful information than expanding metering across the entire facility.
A practical principle is:
Measure what is necessary to answer the question that needs to be resolved.
This approach is also consistent with the energy management principles of ISO 50001: energy data and measurement points should be defined according to the organization’s energy management needs, facility scale, complexity, resources, and existing metering infrastructure rather than collected without a clear purpose.
5. Expected Future Changes in Load
Historical data shows how the facility has operated in the past, but energy projects are typically designed to operate for many years.
Businesses should therefore include planned changes that are reasonably expected, such as adding production lines, increasing the number of shifts, expanding the facility, replacing major equipment, or significantly changing the production schedule.
There is no need to predict every possible future development.
However, changes that are reasonably expected and could materially affect the load profile should be included in scenario analysis before the solution configuration is finalized.
Otherwise, a solution that fits the facility’s current load may become less appropriate after operating conditions change.
How Does Load Data Affect Solar PV, BESS, and EMS Decisions?
The value of industrial load profile analysis is that the same foundation of operating data can support several different energy decisions.
For Solar PV, businesses need to understand not only total electricity demand but also how closely the timing of that demand aligns with periods of onsite solar generation. Two facilities with similar overall electricity consumption but different load profiles may have very different opportunities to utilize onsite solar generation.
For BESS, load data is one of the key inputs for defining the application before evaluating power requirements, energy capacity, and control strategy. It also provides the foundation for integrating Solar PV and BESS for industrial facilities in line with the facility’s actual load profile and operating objectives, rather than deriving the BESS configuration solely from installed Solar PV capacity or total electricity consumption.
For energy efficiency measures, facility-level data can help identify areas that require investigation, while system- or equipment-level data can help determine which loads require deeper analysis. A large electrical load does not automatically represent a large savings opportunity; process requirements, operating conditions, and current system efficiency must also be considered.
For EMS, the initial analysis helps determine which data points genuinely need to be monitored. The value of an energy management system does not lie in displaying more charts on a dashboard, but in turning relevant data into information that supports operations and decision-making.
From an investment perspective, the principle is straightforward:
Technology should be configured around the facility’s load characteristics and operating objectives, rather than selecting technology first and then adapting the facility to a predetermined configuration.
What Initial Data Should Be Prepared Before an Assessment?
A business does not need a complete energy data infrastructure before an initial screening can begin.
A useful starting package can include electricity bills and the applicable tariff structure; interval load data where available; shift schedules, production schedules, and output data; information on major energy-consuming systems and their operating hours; planned changes in production or capacity; and details of any existing Solar PV or other onsite energy sources.
If some of this information is unavailable, that does not necessarily prevent the assessment from starting.
A data gap is itself a useful output of the screening process. It helps determine what should be measured next, where additional measurement is required, how long data should be collected, and what level of detail is necessary before a material investment decision is made.
Energy Investment Decisions Should Start With How the Facility Actually Operates
Load profile analysis is not simply a procedural step before selecting technology. It provides the foundation for defining which energy problem actually needs to be solved.
An industrial facility may ultimately require Solar PV, BESS, EMS, energy efficiency measures, or a combination of several solutions. But configuration decisions are better grounded when the business understands how electricity is used, when demand occurs, what drives changes in the load, and which operating conditions must be maintained.
At 365Energy, technology is not the starting point. The first step is to clarify the industrial facility’s energy challenge, then determine what additional data is required, what should be assessed, and which solution approach is appropriate.
Start With Your Facility’s Load Data
If your business is evaluating Solar PV, BESS, EMS, or other energy optimization opportunities, a practical next step is to review the data already available and identify the gaps that need to be addressed.
Talk to 365Energy to define the required input data and assessment scope before determining the solution configuration.