# Table of Contents

• The meaning of looking at the self-consumption rate in solar power generation simulations

• Don’t confuse self-consumption rate with self-sufficiency rate

• Actual electricity usage to organize before simulation

• Judging by generation alone can mislead the self-consumption rate

• Consider generation and usage by time of day together

• Approaches to increase self-consumption rate in residences

• Perspectives for corporations and facilities on self-consumption rate

• What to check before installing battery storage

• Checkpoints to avoid overestimation

• Translating simulation results into design decisions

• Summary

# The meaning of looking at the self-consumption rate in solar power generation simulations

When performing a solar power generation simulation, many responsible parties first focus on annual generation. How much will be generated annually, how much can be expected month by month, and how much capacity can be placed on the roof or site are basic considerations for installation review. However, what becomes truly important in practice is the perspective of how much of the generated electricity can be used on site. That ratio is the self-consumption rate.

The self-consumption rate refers to the proportion of the electricity generated by solar power that is used directly within the building or facility. For example, electricity generated during the daytime used for lighting, air conditioning, machinery, water heating, charging, or office equipment counts as self-consumption. Conversely, electricity that is generated but not fully consumed during that time and flows externally is not included in self-consumption.

Solar power is most effective when the times of generation and electricity use coincide. No matter how much is generated, if it does not match the desired usage times, the self-consumption rate will not increase. Conversely, even if the generated amount is not extremely large, if the daytime electricity usage and the generation peak overlap well, the expected benefits of installation can be forecast more stably.

Therefore, in solar power generation simulations, it is necessary not only to present large generation figures but to check how much of the generated electricity is used in which time periods. Especially when the goals are reducing electricity bills, emergency preparedness, reducing environmental impact, or stabilizing facility operations, how you read the self-consumption rate directly impacts design decisions.

For practitioners, the important thing is not to make the self-consumption rate look high but to read it realistically in a way that is close to actual operation. There are many factors that affect generation and usage, such as roof orientation, installed capacity, insolation conditions, holiday operation, seasonal air-conditioning loads, and the presence or absence of lunch breaks or nighttime operations. Judging solely by annual generation without organizing these factors tends to create discrepancies where the actual effect after installation is less than expected.

# Don’t confuse self-consumption rate with self-sufficiency rate

One common misunderstanding in solar power generation simulations is confusing self-consumption rate with self-sufficiency rate. Although the terms sound similar, they look in different directions. The self-consumption rate is an indicator of how much of the generated electricity was used by the generator’s side. The self-sufficiency rate is an indicator of how much of the electricity used was covered by solar power.

The self-consumption rate is a generation-side ratio. It is used to check whether the generated electricity is being used without waste. If the amount self-consumed relative to the generated amount is large, the self-consumption rate is high. If the installed capacity is too large and daytime surplus increases, the self-consumption rate tends to decrease.

On the other hand, the self-sufficiency rate is a demand-side ratio. It shows how much of the building or facility’s electricity use is covered by solar power. In facilities with large electricity consumption, even if most of the generated electricity is self-consumed, the proportion relative to total usage may not be very high. Conversely, in residences with low usage, a certain amount of generation may make the self-sufficiency rate appear high.

If you view simulation results without understanding this difference, you may make incorrect judgments. For example, a high self-consumption rate does not necessarily mean that most of the electricity is covered by solar power. Although the generated amount is being well-used, if the facility’s overall usage is large, purchased electricity from outside may still be significant.

Conversely, if you increase installed capacity to raise self-sufficiency, the daytime generation peak may exceed usage and the self-consumption rate can drop. In other words, you cannot look at only one of self-consumption rate or self-sufficiency rate; you need to balance them according to your objectives.

In practice, it is important to first clarify the installation purpose. Whether you want to reduce purchased electricity, use generated electricity as efficiently as possible, secure a power source during emergencies, or emphasize environmental value will change which indicators to prioritize. Among these, the self-consumption rate is a central indicator for confirming how well the generated electricity aligns with building operations.

# Actual electricity usage to organize before simulation

When considering the self-consumption rate, the first thing to organize is not the generation conditions but the actual electricity usage. In solar power generation simulations, attention tends to focus on roof area, orientation, tilt, insolation, and panel capacity, but to read the self-consumption rate you need to grasp when, where, and for what the electricity is used.

For residences, whether people are at home during the day is a major factor. Households where both partners work and daytime usage is low are likely to see a mismatch between generation peaks and usage peaks. Households with daytime telework or those that use air conditioning, water heating, cooking, or washer-dryer during the day tend to self-consume more. If electricity use is concentrated at night, it is difficult to use generated electricity directly, and you need to consider storage batteries or operational changes.

For corporations and facilities, usage varies greatly depending on industry and operating patterns. Offices tend to center electricity use in weekday daytime and often match well with solar generation. Factories, warehouses, stores, schools, welfare facilities, and agricultural facilities are influenced by operating days, business hours, air-conditioning load, refrigeration equipment, motor-driven equipment, and holiday usage. Facilities with significant nighttime operation face the challenge of how to use daytime generation.

Monthly usage alone is not sufficient. Monthly energy totals are useful for overall understanding, but the self-consumption rate is determined by time-of-day coincidence. Even with the same monthly usage, facilities that use electricity daytime and those that use it at night have entirely different compatibility with solar generation. Therefore, if possible, check usage patterns by time of day, or at least separate weekdays and holidays, daytime and nighttime.

You also need to consider future changes in usage. If there are plans for equipment additions, air-conditioning updates, introduction of electric equipment, changes in operating hours, increases or decreases in telework, or installation of charging equipment, basing simulation on current usage alone may diverge from future reality. Since solar power is a long-term asset, it is important to look not only at the present but also at the direction of electricity usage several years ahead.

# Judging by generation alone can mislead the self-consumption rate

Increasing generation in a solar power generation simulation does not necessarily lead to a higher self-consumption rate. Increasing installed capacity raises annual generation, but if the number of time periods when generation exceeds usage increases, surplus electricity also increases. In that case, even with large generation, the self-consumption rate may fall.

Special attention should be paid to daytime generation peaks. Solar power tends to generate most around late morning to early afternoon on sunny days. If the building’s usage during that time is sufficiently large, self-consumption is easier. However, in buildings with low daytime usage, generation peaks are likely to exceed demand. A generation graph alone may look like an excellent simulation, but when overlaid with a demand graph, it may show a large surplus.

When considering self-consumption rate, optimizing for demand rather than maximizing generation is important. Loading as much as possible onto the roof may be appropriate in some cases, but it is not the correct approach for every project. If you prioritize self-consumption, you should consider a capacity that is unlikely to produce excessive generation by looking at daytime minimum demand, average demand, holiday usage, and seasonal variations.

Also, even if annual generation numbers are the same, self-consumption rate varies depending on monthly and time-of-day breakdowns. Facilities with large air-conditioning loads in summer may find that high summer generation overlaps with demand. Conversely, facilities with large heating or water heating loads in winter may see increased demand when insolation is low, making it difficult to cover with solar alone. Judging by annual values without considering these seasonal differences can cause the simulated self-consumption rate to diverge from the actual feeling.

Generation is a basic indicator of solar power, but when considering self-consumption rate, do not evaluate generation in isolation. By separating times when generated electricity is used, not used, or in surplus, you can see the appropriateness of equipment capacity and operational methods.

# Consider generation and usage by time of day together

To read the self-consumption rate in practice, it is essential to overlay generation and usage by time of day. By overlaying the generation curve obtained from the simulation with the building’s electricity usage curve, you can specifically identify which time periods enable self-consumption and which produce surplus.

Mornings are a time when generation gradually ramps up. In residences, usage may increase due to breakfast, air conditioning, laundry, and personal preparation, but generation may still be small. In offices and factories, equipment may start running around the start of business, increasing usage. This time is a point to check whether generation can catch up with demand.

Late morning to early afternoon tends to be the peak generation period. If usage is low here, surplus easily occurs. Residences often overlap with absence during the day, and corporations may see reduced equipment load during lunch breaks. If the generation peak coincides with a usage valley, the self-consumption rate tends to fall.

In the evening, generation decreases while residences see increased usage after returning home, and facilities may have remaining operation before closing. During this time, generation alone is less likely to cover demand. If evening and nighttime usage is large, consider storing daytime surplus or shifting usage to daytime where possible.

Handling of holidays and non-business days is also important. A facility that expects high self-consumption on weekdays may see its annual self-consumption rate depressed if generation is high and usage low on holidays. In corporate projects, reflecting holidays, long closures, and seasonal breaks—not just weekdays—yields results closer to reality.

Viewing by time of day makes measures to increase self-consumption concrete. It becomes clear whether there are devices whose operating times can be shifted to daytime, whether air-conditioning start times can be adjusted, whether charging or water heating can be aligned with generation times, or whether operational peaks can be slightly shifted. Self-consumption rate is an indicator affected not only by equipment design but also by usage patterns.

# Approaches to increase self-consumption rate in residences

When simulating solar generation for residences, the self-consumption rate is greatly influenced by lifestyle patterns. Whether people are at home during the day, when they operate electrical equipment, and how they use water heating and air conditioning all affect the proportion of self-consumption for the same generation.

In residences, be aware that usage tends to be low during the hours when generation is high. Households absent during the day may not be able to use all the generated electricity on site. In such cases, moving easy-to-time-shift electricity uses—laundry drying, dishwashing, water heating, pre-cooling or pre-heating of air conditioning, charging—into daytime can potentially increase the self-consumption rate.

However, it is unrealistic to change operations to the point that daily life becomes inconvenient just to raise the self-consumption rate. In simulations, it is important to assume not only ideal usage but also usage that can be continued without undue burden. Conditions that require daily fine operations are likely to result in actual performance worse than the simulation.

Seasonal variation is also large in residences. Usage changes with cooling in summer and heating or water heating in winter. Spring and autumn may have low air-conditioning loads and relatively little usage compared to generation. While annual averages may appear balanced, monthly breakdowns can show periods of large surplus and periods of high purchased electricity.

Also consider future lifestyle changes. Family composition, home presence, increases in electric devices, updates to water heating, and vehicle charging can change daytime usage. If daytime demand is expected to increase in the future, you may not want to base capacity solely on the current self-consumption rate.

In residential simulations, it is important to read the relationship among generation, usage, surplus, and purchased electricity in line with daily living patterns. Looking at how much electricity is naturally usable in daily life, not just the amount generated, increases satisfaction after installation.

# Perspectives for corporations and facilities on self-consumption rate

In corporate and facility solar generation simulations, the approach to self-consumption rate is more complex than for residences. Because electricity consumption is large and equipment types are diverse, high self-consumption can be expected if daytime demand matches generation, but inputting incorrect operating patterns can cause large deviations in results.

First check the difference between weekdays and holidays. On weekdays, offices, factories, stores, and warehouses may have high electricity use and be conducive to self-consumption. However, on holidays or closures, usage may drop significantly and generation may be in surplus. To consider the annual self-consumption rate, always confirm how business days and non-business days are handled.

Next, look at the stability of daytime load. Facilities with continuously operating air conditioning, ventilation, refrigeration, pumps, manufacturing equipment, and information systems can absorb generation variability more easily. Conversely, facilities with many short-duration high-power devices may have large instantaneous demand but, if not coincident with generation times, this does not lead to self-consumption.

In corporate projects, not only peak demand but minimum demand is important. When generation increases on sunny daytime, how much constant demand the building has affects the self-consumption rate. Installing capacity that greatly exceeds minimum demand tends to produce surplus. Especially if you overlook weekend or long-closure minimum demand, the simulated self-consumption rate may look higher than reality.

Operational changes to equipment can increase self-consumption. If there are loads whose timing can be adjusted—charging, water heating, startup of heating/cooling, thermal storage, wastewater treatment, partial operation of conveying equipment—bringing them closer to generation hours can increase self-consumed electricity. However, avoid operational changes that impact productivity, service quality, or safety. Simulations should assume only operations that the site can actually maintain.

Because many stakeholders are involved in corporate or facility projects, sharing how to read simulations is important. Facilities managers, executives, site supervisors, maintenance personnel, and designers may emphasize different points even when looking at the same numbers. Explaining self-consumption rate as an indicator of alignment between generation facilities and the building’s operations helps decision-making proceed.

# What to check before installing battery storage

Considering battery storage is a common way to try to increase self-consumption. Storing surplus electricity during the day and using it in the evening or night can increase self-consumed electricity. However, battery storage does not always yield large benefits simply by being installed. First, you need to confirm how much surplus occurs without batteries.

In generation simulations, check how much daytime surplus energy exists, in which months and time periods surplus occurs, and whether there is a stable surplus that can be stored continuously. If surplus is small, installing a battery will leave little electricity available for charging. Conversely, if surplus is large but nighttime usage is small, stored electricity may not be fully used.

When considering batteries, charging and discharging timing is as important as capacity. Consider what time periods to charge and discharge in relation to building usage patterns. In residences, evening-to-night usage is a key point; in corporations, after-hours load and the presence of nighttime equipment matter. If you emphasize emergency use, consider not only normal self-consumption rate but also which loads you want to maintain during outages.

Also note that assuming battery storage can make simulations optimistic. Charging/discharging incur losses and do not always operate ideally. Consecutive poor weather days reduce charging, and if usage increases more than expected, discharge can deplete quickly. Simulations with batteries should realistically include cloudy and rainy days and seasonal variability, not just sunny days.

Batteries are a powerful means to increase self-consumption, but instead of assuming them from the outset, first identify the mismatch between generation and usage and see how much of that mismatch can be reduced by operational changes. Then judge how much a battery would help with remaining surplus and nighttime demand to avoid over-designing the system.

# Checkpoints to avoid overestimation

When considering the self-consumption rate in solar generation simulations, the biggest thing to avoid is overestimation. If you calculate under conditions that make the self-consumption rate look high, the expected benefits will also look large. But if actual operations do not match those conditions, expectations will not be met.

First, confirm the granularity of usage data. Calculating self-consumption from monthly usage alone hides time-of-day mismatches. Reflect time-of-day usage tendencies as much as possible, and at minimum separate daytime and nighttime and weekdays and holidays. If detailed data is lacking, set reasonable assumptions from business hours or lifestyle patterns and avoid excessive optimism.

Next, confirm the treatment of holidays and long closures. In corporate projects, basing calculations only on high weekday usage can make self-consumption look higher than it is. On holidays when generation is high and usage low, annual surplus increases. In residences, consider travel or prolonged absence periods and seasonal differences in time spent at home; daily patterns alone may miss important factors.

Projected insolation conditions are also important. Simulations should consider regional insolation, orientation, tilt, shading impacts, soiling, degradation, and equipment losses. If generation is overestimated, self-consumed electricity may also be overestimated. Conversely, larger generation can increase surplus and thus lower the self-consumption rate. Separate confirmation of generation and self-consumption relationships is necessary.

Be cautious about assumptions regarding installed capacity. Just because you can install a lot on the roof or site does not mean it is appropriate relative to demand. If you prioritize self-consumption, check how much the generation peak will exceed demand and compare self-consumption rate changes when capacity is increased. Slightly reducing capacity can sometimes improve self-consumption rate and operational stability.

Also avoid overly expecting future increases in usage. Even if demand is expected to rise, if the plan is not finalized, view baseline and future scenarios separately. Designing a large capacity based on uncertain demand increases may lower the short-term self-consumption rate. Separating certain present conditions, plausible futures, and optimistic futures makes decisions easier.

# Translating simulation results into design decisions

The purpose of considering the self-consumption rate is not just to check numbers. The real goal is to use simulation results to decide installed capacity, equipment composition, operational methods, and room for future expansion. To do that, read the results not as a simple list but in a way that leads to decision-making.

First look at how self-consumption rate changes when you vary installed capacity. Increasing capacity raises generation but can lower the self-consumption rate. Decreasing capacity reduces generation but may make it easier to consume the generated electricity. Which is preferable depends on the installation purpose. Decide whether you prioritize reducing purchased electricity, minimizing surplus, or preparing for future demand increases.

Next, check monthly biases. Even if the annual self-consumption rate looks high, certain months may have large surplus. It is common for facilities with heavy cooling or heating loads to self-consume more in summer or winter and have more surplus in spring and autumn. Understanding these biases helps guide operational improvements, battery considerations, and capacity adjustments.

Time-of-day results also help design decisions. If surplus is concentrated around midday, look for loads that can be moved to daytime. If evening purchased electricity is large, consider battery storage or operational changes. For facilities with large morning ramp-up demand, consider how to handle power use before generation ramps up sufficiently.

Also, do not view simulation results for just one condition. Compare multiple cases—standard conditions, somewhat lower generation, changed usage patterns, smaller holiday demand—so you can see the range of results. In practice, choose a design that remains viable even if conditions change slightly, rather than the most favorable single-case number.

Finally, confirm consistency with on-site conditions. Even if installation seems possible on paper, actual constraints such as shading, obstacles, roof usage, inspection routes, equipment space, safety, and future construction can limit feasibility. Conducting generation simulation and self-consumption analysis together with on-site verification reduces post-installation discrepancies.

# Summary

When considering the self-consumption rate in a solar power generation simulation, it is important not to judge solely by the magnitude of annual generation. The self-consumption rate indicates how much of the generated electricity was used on site. If generation is large but does not match usage times, surplus increases. Conversely, even if generation is not extremely large, if it overlaps with daytime demand, practical effects are easier to obtain.

To read the self-consumption rate correctly, understand the difference from self-sufficiency rate and organize actual electricity usage. In residences, living hours, presence at home, and usage of water heating, air conditioning, and charging affect outcomes. In corporations and facilities, weekdays versus holidays, operating hours, minimum demand, equipment loads, and handling of long closures are key. Overlaying time-of-day generation and usage rather than relying on monthly totals yields results closer to reality.

Methods to increase self-consumption are not limited to adding equipment. Options include shifting usage to generation hours, revising operations, sizing capacity to demand, and considering battery storage as needed. However, unrealistic operational changes or optimistic assumptions can lead to large gaps between expected and actual performance. Simulations should reflect sustainable operations, realistic demand, seasonal variation, and holiday conditions.

For solar power planning, accurate on-site verification is as indispensable as desk simulations. The more precisely you confirm roof and site shapes, candidate installation areas, obstacles, shading sources, equipment layout, and inspection routes, the better the accuracy of generation and self-consumption assessments. Particularly for existing facilities or wide sites, accurately acquiring position information and reflecting on-site conditions in design information is important.

As a way to streamline such on-site verification, LRTK—a GNSS positioning device that attaches to an iPhone and acquires high-precision location information—is an easily applicable option for solar power planning. By confirming installation candidate locations, linking site photos with position information, recording obstacles and areas around equipment, and smoothing later drawing checks, it helps organize the assumptions for generation simulations. To consider self-consumption in a manner close to reality, accurately understanding the site is as important as analyzing electricity data. To translate simulation numbers into actual design decisions, it is necessary to confirm generation conditions, usage conditions, and site conditions together.