Analysis & Practice

The load profile
in manufacturing.

Shift start times, machine start-ups, and delivery deadlines determine your day. Your load profile shows how these factors generate energy demand. We use this data to align your procurement with actual operations.

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OPTUM / KNOWLEDGEAnalysis & Practice AI Visualization

The load profile in manufacturing

The annual statement shows how much electricity your business has consumed. The load profile adds information about when this demand arose. This makes shift starts, production peaks, breaks, and the base load after business hours visible.

A load profile analysis combines measurement data with your processes. It helps to specifically examine anomalies and better describe procurement needs. You can try it out yourself using the interactive daily example on this page: Move the slider from the start of production until the end of the workday. The values are an explanatory model and not customer data.

INTERACTIVELY EXPLAINED / 01

One day. 96 measurement intervals.

Discover what lies behind a load curve.

MODEL EXAMPLE
06012018024000:0006:0012:0018:0024:00Average Power · kW
Time08:00–08:15
Average power210 kW
Energy in 15 minutes52.5 kWh

The peak load indicates the highest power demand of the day. Duration and frequency are also taken into account for assessment.

The relationship210 kW × 0.25 h = 52.5 kWh

This is a freely chosen example; no customer data is used. All 96 values are quarter-hourly averages. Daily energy consumption in the model is 1,856.2 kWh. Electricity costs cannot be derived from the curve alone.

What exactly is a load profile?

Power is height. Energy is area.
A load profile shows power over time: baseload and peaks become visible.A high individual reading can affect grid charges. The area under the curve represents energy consumed over time.A fictional model day. The interactive example remains separately usable.Schematic illustration · Example values

A load profile describes the time course of power consumption. For electricity, quarter-hourly averages are often displayed in kilowatts. Some data exports, however, contain energy quantities per interval in kilowatt-hours. Therefore, first check the unit, interval length, and timestamp.

Power × Time = Energy. An average power demand of 210 kW over 15 minutes corresponds to 210 × 0.25 = 52.5 kWh. A peak value of 210 kW should not be interpreted as an energy consumption of 210 kWh.

A typical 24-hour day has 96 quarter hours. When the clocks change, there can be 92 or 100 quarter hours in local time. Missing readings should not be interpreted as zero consumption. The example on this page explicitly uses a standard 24-hour model day.

Standard load profile and measured load curve

A standard load profile depicts a typical time course for a group of consumers. It supports forecasting and balancing, but is not an individual measurement curve for your business. You cannot reliably tell from this profile when a specific machine was switched on.

In contrast, a measured load profile contains time-based measurement data from the delivery point. Whether such data is available and at what resolution it is provided depends on the metering concept and access conditions. A digital meter alone does not guarantee that live analysis is available at all times.

What a load profile analysis can help with in your business

Operating hours and base load

Compare operating hours with the consumption patterns. If power demand remains unexpectedly high at night or on weekends, cooling, compressed air, ventilation, or other systems could be responsible. Which components are actually responsible must be determined based on the operating conditions or additional measurements.

Power peaks

Simultaneous start-ups or processes can generate high quarter-hour averages. Reducing these peaks is particularly relevant when billed demand is part of the pricing model. A brief electrical start-up pulse is not automatically the same as a billable quarter-hour peak.

Maintenance and efficiency

Changes in patterns can indicate altered capacity utilization or a need for technical inspection. However, a curve alone does not diagnose a defect. Relate any anomalies to production volumes, weather, downtime, and maintenance.

Data quality

Check completeness, time zone, and the labeling of estimated values. Compare at least one typical production day with a day off work and then observe several weeks. This will help you identify whether a pattern is typical for the operation or an exception. Seasonal processes require correspondingly longer comparison periods.

Read a production example

In the model, the load increases at the start of production. At 8:00 a.m., the peak 15-minute load is 210 kW. Later, the load decreases with changing utilization and returns to the base load at the end of operations. You can use the slider to view the intervals and their energy consumption individually.

An operational analysis would then ask: Which processes were running simultaneously? Was the high power demand necessary for production? Can starts be staggered without compromising safety, quality, or deadlines? Only this assessment transforms a measurement into a potential starting point.

High power demand and high exchange prices are two different things. A shift in energy consumption only affects costs according to the actual tariff. With a constant energy price, simply using a different time of day does not make the same amount of energy cheaper.

Two experts observe machines starting simultaneously and a symbolic load curve.
OPTUM / ILLUSTRATEDA look at the processes behind the curve: Which systems start together, which have to run simultaneously?

Distinguish between multiple facilities and locations

The total load profile of a delivery point includes all consumers measured there together. Submeters or coordinated measurements may be necessary to assign these to a single installation. Do not use a blanket allocation if significant consumers operate differently.

For multiple sites, use consistent periods and the same data structure. Seasonal businesses and continuous production should not be assessed alike just because annual consumption is equal. Also examine individual installations in the electricity cost calculator using average power and operating time.

Load profile data, market prices and the energy transition

A high proportion of weather-dependent generation can influence the price structure over time. Flexible consumption can be attractive for a business if the technical possibilities and contract model are a good match. This requires suitable data and clearly defined limits.

If photovoltaics or storage are being considered, the load profile initially shows when the business needs electricity from the grid. Generation times, storage operation, and residual electricity demand can then be analyzed together. Separate technical and contractual requirements apply to feed-in or other market offerings.

The collaboration in the evaluation

For initial assessment, at least the relevant invoices, existing load profile files, a shift schedule, and information on key equipment will be helpful. Known production changes and shutdowns should be noted.

Analysis and operational experience complement each other: A noticeable curve can be caused by a planned order, while a consistently high base load can indicate continuously running auxiliary systems. Therefore, results should be discussed with those responsible on site.

Consider load profile and procurement together

Compare your load profile with your supply contract: Does a large portion of your consumption fall within expensive time windows? Are the quantities for the next delivery year still plausible? Using your data, we'll discuss the resulting requirements for your offer. We'll agree on the scope of any further analysis with you.

The article Strategies for electricity procurement explains fixed price, tranches, spot market and hybrid models. A suitable model takes into account not only the volume requirement but also planning certainty and risk budget.

What your load profile can tell you

Start with three questions: What is the base load? When do the highest quarter-hourly averages occur? What are the differences between production and downtime days? Note any data gaps and known special events.

For the initial exchange, highlight three anomalies in the load profile and add details of what happened during those times. This will make the discussion more concrete: Which cause can be explained, where are measurements missing, and which factor could influence procurement? Prepare the discussion with your consumption data →

SUITABLE FOR YOUR QUESTION

Delve deeper into what will move you forward.

Check load profile data: Identify CSV, units, and data gapsA load profile file can appear complete and still be incorrectly evaluated. These checks help before comparing offers and analyzing consumption.
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Check peak loads and network charges for RLM customersDistinguish between peak loads, kilowatts, and kilowatt-hours: Verify measurement data, network price list, and operational measures.
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