When looking at solar PV generation simulations, many practitioners focus on annual generation, monthly generation, system capacity, roof orientation, tilt angle, and the presence or absence of shading. However, a commonly overlooked aspect in actual deployment decisions and proposal materials is the interpretation of cloudy-day risk. If you look only at maximum generation under clear skies, a plan may appear promising, but actual generation can underperform expectations due to regional characteristics, seasonal variation, and irradiance variability.

Cloudy-day risk is not judged simply by whether there are many cloudy days. You need to check annual irradiance, monthly generation imbalances, consecutive low-irradiance periods, morning/evening generation drops, short-term fluctuations caused by clouds, compatibility with installation angles, and effects on storage and self-consumption. This article organizes and explains seven items for assessing cloudy-day risk in a way that is practical for practitioners searching for information on "solar PV generation simulation."

# Table of Contents

• Cloudy-day risk cannot be judged by annual generation alone

• Item 1: Check annual irradiance and regional differences

• Item 2: Check monthly generation drops

• Item 3: Check the impact of consecutive cloudy periods

• Item 4: Check generation tendencies at dawn/dusk and under low irradiance

• Item 5: Check short-term fluctuations caused by clouds

• Item 6: Check how orientation and tilt affect generation under cloudy conditions

• Item 7: Check effects on self-consumption and battery operation

• How to proceed with simulation checks considering cloudy-day risk

• Summary

# Cloudy-day risk cannot be judged by annual generation alone

In solar PV generation simulations, people often first look at annual generation. If you can tell how many kWh can be generated annually, you can roughly judge the appropriateness of system size, the relationship with electricity usage, and prospects for selling or self-consuming power. Therefore, annual generation is a very important indicator.

However, when evaluating cloudy-day risk, annual generation alone is insufficient. Annual figures are the result of smoothing clear, cloudy, and rainy days, seasonal irradiance conditions, and efficiency changes due to temperature. A large drop in one month can be masked by favorable conditions in another month in the annual total. For both residential and commercial facilities, what really matters is when generation occurs, how much is generated during required time periods, and whether prolonged low irradiance creates operational problems.

Especially for self-consumption type PV systems, even if annual generation is high, if generation falls short during peak demand times or seasons, expected power savings may not be achieved. Conversely, even if clear-sky generation is ample, prolonged cloudy periods can increase purchased power and make it difficult to level power costs. Therefore, when assessing cloudy-day risk you should use annual generation as an entry point and then decompose and check monthly, daily, hourly, and low-irradiance behavior.

Cloudy-day risk has different characteristics depending on the region. Some areas are prone to cloudy skies and snowfall in winter, while others see irradiance reductions during the rainy season or typhoon season. Cloud formation, humidity, fog, and localized weather differences vary in coastal areas, mountainous regions, basins, and urban areas. In other words, solar PV generation simulations should not be judged by nationwide averages but should reflect the meteorological characteristics of the installation site.

The purpose of properly assessing cloudy-day risk is not to reject solar PV. Rather, it is to make post-installation expectations realistic and to solidify decisions about system capacity, panel layout, battery thinking, power contracts, and operational policies. If you identify conditions prone to downside generation beforehand, you can avoid excessive expectations and imprudent investment decisions and create an installation plan that fulfills accountability.

# Item 1: Check annual irradiance and regional differences

The first item for assessing cloudy-day risk is annual irradiance and regional differences. Solar generation is strongly influenced by the irradiance energy reaching the PV cells. Even with the same equipment performance, annual generation differs between regions with high and low irradiance. Therefore, when reviewing simulation results, you need to confirm to what extent the region’s irradiance conditions are reflected, rather than estimating generation solely from system capacity.

When checking annual irradiance, do not judge by regional averages alone. Even within the same prefecture, conditions vary between coastal, inland, mountain, snow-prone, and urban areas. For example, areas near mountains may have afternoon cloud formation, basins may experience fog or haze, and coastal areas may see different cloud behavior due to sea breezes and humidity. Looking beyond the address or broad region name to the surroundings of the installation point reduces misreading of cloudy-day risk.

When confirming annual irradiance in a simulation, check whether average irradiance based on past weather data, representative-year data, or long-term averages are used. Relying on short-term data can be influenced by a year that happens to be unusually sunny or cloudy. For installation decisions, thinking based on multi-year trends smoothed over several years is more realistic than assuming a single year’s favorable conditions.

Reading annual irradiance is easier if you look at annual generation per 1 kW of system capacity. Even if system sizes differ, looking at generation per unit capacity helps you grasp how favorable the region and installation conditions are for generation. For example, two 10 kW systems can have different annual generation depending on irradiance conditions; organizing this per unit capacity makes over- or underestimation easier to spot.

Also, even if annual irradiance looks sufficient, that does not necessarily mean cloudy-day risk is low. A region may have a steady annual total while suffering significant drops in specific seasons. Annual irradiance is merely a total and does not directly indicate generation stability. Therefore, after checking annual irradiance you should always proceed to monthly and seasonal distributions.

In practice, proposal or internal review materials sometimes prominently display only the annual generation. Even in such cases, it is important to confirm that the underlying irradiance, regional characteristics, and installation surface conditions are appropriate. Practitioners who carefully assess cloudy-day risk do not get swayed by the appearance of annual figures and instead confirm “under what weather assumptions this generation is based.” This attitude prevents post-installation disputes and expectation gaps.

# Item 2: Check monthly generation drops

Checking monthly generation is indispensable for concretely understanding cloudy-day risk. Even with the same annual generation, systems that generate steadily each month and systems that drop sharply in certain months are very different in practice. Solar PV generation simulations should always show how generation evolves month by month, not just annual totals.

Monthly generation reveals periods with many cloudy or rainy days, short daylight hours, and susceptibility to snow or fog. Generally, generation tends to increase from spring to early summer and drop during the rainy season and winter. However, regional differences exist, so relying on a national image is risky. Pacific-side and Sea of Japan-side climates, plains versus mountainous areas, and urban versus suburban environments all show different monthly generation patterns.

When assessing cloudy-day risk, focus on the month with the lowest generation. Checking how much the lowest month falls relative to the average month makes the impact of low-irradiance periods clear. For example, even if annual generation is sufficient, a large winter or rainy-season drop may increase power purchases during that time. In commercial facilities, a mismatch between seasonal demand (air conditioning, lighting, equipment operation) and generation can reduce expected self-consumption benefits.

Do not be distracted by months with abundant generation. Even if a sunny month generates a lot, if the demand-heavy months have little generation, the system’s intended purpose may not be met. For instance, if you want to reduce summer air-conditioning load, check how stable summer generation is. Facilities with high winter electricity use should focus on winter low-irradiance risk.

Also, when reviewing monthly generation graphs, check whether the seasonal variation is smooth or whether specific months drop sharply. If there are sharp drops, multiple factors—clouds, rain, snow, surrounding shading, solar altitude, and installation angle—may overlap. If the simulated monthly values look unnaturally high or low, review input conditions and irradiance data settings.

For practitioners, it is important to read monthly generation as a “seasonal generation calendar.” Understanding which months see increases and which see drops and how that relates to demand makes it easier to explain cloudy-day risk in advance. To avoid being told after installation that “generation was lower than expected in certain months,” always check monthly generation drops.

# Item 3: Check the impact of consecutive cloudy periods

A commonly overlooked aspect of cloudy-day risk is the impact of consecutive cloudy periods. Solar generation does not collapse the whole plan because of one cloudy day. However, if cloudy or rainy conditions persist for days to weeks, the shortfall accumulates. This is a significant operational risk, especially when self-consumption or battery operation is assumed.

Annual and monthly generation are often shown as totals or averages over a period, so the day-to-day shortfalls from consecutive cloudy days can be masked. For example, a month’s total may look average, but if sunny days were concentrated in the first half and cloudy days in the second half, daily operations can be significantly affected. Even if monthly totals present no problems, actual operations may see increased purchased energy or insufficient battery state of charge.

To assess consecutive cloudy-day risk, daily and hourly generation simulations are effective. By looking at daily generation you can understand how many low-generation days may occur in a row and how far generation can drop on the worst days. Especially when PV is introduced for emergency power, peak shaving, or improving self-consumption rates, focus on operation during extended low-generation periods rather than maximum clear-sky days.

The impact of consecutive cloudy periods also affects battery planning. Batteries store generated electricity, but if low irradiance continues, charging itself will be insufficient. Even if a battery can be charged on sunny days, consecutive cloudy days make it hard to replenish state of charge. Therefore, when sizing batteries consider not only single-day generation but also multi-day generation shortfalls.

In commercial facilities, consecutive cloudy periods can increase weekday purchased energy. Facilities with steady operational power demand may suppress purchased power with self-consumption on sunny days, but prolonged clouds reduce savings. In such cases, evaluate PV as an auxiliary distributed power source that includes weather variability, not as a primary power source.

When explaining consecutive cloudy-day risk, do not use only “on average this much is generated.” Clearly communicate that “generation may fall if low irradiance persists.” Sharing downside scenarios at the simulation stage helps keep post-installation evaluations calm. Since PV is a long-term asset, how far you assume unfavorable conditions affects the plan’s credibility.

# Item 4: Check generation tendencies at dawn/dusk and under low irradiance

When considering cloudy-day risk, it is important to see how generation changes throughout the day. PV output is highest when solar altitude is high during daytime and is lower in the morning and evening. Under cloudy conditions, periods that resemble dawn/dusk low-irradiance states can lengthen, depressing the entire daily generation curve.

On clear days, the generation curve is typically peaked around midday. Under cloudy conditions, the peak is lower and the curve may be flatter. On days with thick clouds, output may not increase much even at midday, and low output can persist from morning through evening. If a simulation allows viewing generation by time of day, check not only maximum clear-sky values but also behavior under low-irradiance conditions.

For self-consumption systems, morning and evening generation shortfalls often translate directly into increased purchased power. For example, facilities where lighting, air conditioning, and equipment start in the morning will have demand before PV has ramped up. In the evening, operations may continue while generation falls. On cloudy days, lower daytime peaks further reduce the amount of energy available for self-consumption.

In residences, mismatches between morning/evening usage and generation times are also an issue. Households that are at home during the day and those that are away and use power at night will feel cloudy-day impacts differently. Combining generation simulation with hourly usage data allows a more accurate assessment of practicality under cloudy conditions.

Panel installation conditions also affect low-irradiance generation tendencies. Shadows from nearby buildings, trees, roof steps, and equipment can further worsen generation drops at dawn/dusk and on cloudy days. Even if shadows seem negligible at noon on a sunny day, they lengthen when solar altitude is low and may fall on generation surfaces. When assessing cloudy-day risk, check whether shadows overlap during low-irradiance periods as well as cloud effects.

Hourly checks also help make proposals more persuasive. Annual generation alone does not show when generation occurs. If you can explain hourly generation tendencies, you can more concretely communicate compatibility with load patterns, battery needs, surplus generation potential, and time windows of shortage under cloudy conditions. When handling cloudy-day risk in practice, do not underestimate low-irradiance generation.

# Item 5: Check short-term fluctuations caused by clouds

Cloudy-day risk includes not only daily or monthly generation declines but also short-term fluctuations. When clouds block the sun, generation rises and falls quickly. Thin clouds may cause only small drops, but thick or fast-moving clouds can change output over minutes. These short-term fluctuations are easy to miss if you look only at totals.

Short-term fluctuations matter when you want to closely balance generation and consumption. In self-consumption systems, times when generation exceeds or falls below demand can switch frequently. Even if self-consumption is stable on sunny days, cloudy days can make the balance between purchased and generated power unstable. As a result, expected peak shaving and power reduction effects may be limited in practice.

Short-term fluctuations also affect system control and power management. When output suddenly drops, the deficit must be supplied by the grid or batteries. Conversely, when clouds clear and generation surges, surplus exceeding demand may occur. Even if the system can operate overall, facilities that emphasize fine-grained power management need to understand the fluctuation range.

Even if a PV simulation cannot directly show short-term fluctuations, check hourly or daily data as much as possible when considering cloudy-day risk. If generation varies widely on an hourly basis, the site may be susceptible to cloud impacts. For more detailed operational planning, measured data or generation trends from similar facilities can be useful.

When explaining cloud-driven short-term fluctuations, it’s more accurate to say “generation output varies with cloud thickness and movement” rather than simply “no generation on cloudy days.” PV can generate under cloudy skies, but you cannot expect the same stable output as on sunny days. Especially in weather with moving clouds, output fluctuates frequently and must be evaluated according to operational objectives.

Short-term fluctuations relate not only to the amount of generation but also to how power is used. For example, facilities with many daytime constant loads may absorb fluctuations and still self-consume total energy, while rapid generation increases during periods of low demand easily produce surplus. To assess cloudy-day risk correctly, consider both the generation and demand side variability.

# Item 6: Check how orientation and tilt affect generation under cloudy conditions

In PV generation simulations, orientation and tilt significantly influence generation. Generally, the more optimally oriented and angled the panels are relative to the sun, the greater the generation. However, when assessing cloudy-day risk, consider not only optimal conditions under clear skies but also how generation tends to behave under cloudy conditions.

Under clear skies, the sun’s position relative to the panel face strongly affects output. When sunlight strikes the panel at favorable angles, generation increases. Under cloudy skies, direct irradiance weakens and the relative share of diffuse light from the whole sky increases. Thus, orientation and tilt differences may not be as pronounced as on sunny days, though total generation falls. Misunderstanding this can lead to overestimating actual cloudy-day generation.

When checking orientation, do not use south-facing as the sole standard; also examine east- and west-facing and multi-aspect installations. East-facing arrays tend to favor morning generation, west-facing arrays afternoon. Because total generation drops under cloudy conditions, the distribution by time of day and its fit with demand becomes more important. For example, west-leaning generation may be meaningful for facilities with high afternoon demand, but the effect may be limited on cloudy days.

Tilt angle relates to seasonal solar altitude. In winter the sun is lower, so tilt affects received irradiance. Regions with many cloudy winters can see winter generation doubly reduced—shorter daylight hours plus cloud or snow and low solar altitude overlapping. In simulations, check not only angles that look optimal annually but also how much generation is obtained in low-generation months.

Tilt also affects soiling, snow, and drainage. Low-angle installations may not shed dirt easily in rain, causing long-term output loss. In snow-prone regions, the time that snow remains affects generation. Even if you focus on cloudy-day risk, soiling, snow, humidity, and surrounding shading can overlap to reduce generation. Confirm how much these factors are reflected in simulation conditions.

The purpose of checking orientation and tilt is not necessarily to seek an ideal mounting surface. It is to judge how much cloudy-day risk you can accept within existing roofs or site constraints. In practice, roof shape, structure, load, maintenance access, and neighboring environment impose limits. Within those constraints, consider not only maximizing generation but also configuring arrays to deliver realistic expectations under low-irradiance conditions—this leads to more robust simulations.

# Item 7: Check effects on self-consumption and battery operation

The ultimate impact of cloudy-day risk appears not only in generation amounts but in how electricity is used. If PV is introduced for self-consumption, it’s important to know how much purchased power can be reduced under cloudy conditions. When batteries are used, key questions are how much they can be charged during cloudy periods and whether they can discharge when needed. Therefore, solar PV simulations should examine generation and consumption together.

Self-consumption rate indicates the proportion of generated electricity used within the facility or home. Under cloudy conditions, generation is lower, so generated electricity is more likely to be consumed locally and self-consumption rate can appear high. But a high self-consumption rate does not necessarily mean large power savings. If total generation is small, the coverage ratio of consumption is low. When assessing cloudy-day risk, separate checks for self-consumption rate, generation, and changes in purchased energy are essential.

The same applies when combining batteries. On sunny days you can charge during the day and discharge in the evening. But if cloudy days persist, daytime charging is insufficient and the energy available for evening or night use decreases. Batteries do not completely eliminate cloudy-day risk. To use batteries effectively, check generation on sunny, cloudy, and consecutive cloudy days separately.

In commercial facilities, alignment between business hours and generation times is important. Facilities with steady daytime demand tend to self-consume PV more easily. However, cloudy days increase the time when generation falls below demand, so savings depend on weather. Simulations should confirm expected reductions not only for sunny days but also for months with many cloudy days and low-irradiance days.

In residences, perception of cloudy-day risk depends on lifestyle. Households using much power during the day benefit more from PV, while those with concentrated nighttime usage need to consider battery presence and operation. Combining generation simulations with hourly consumption data provides a more realistic decision basis.

When translating cloudy-day risk into self-consumption and battery operation scenarios, avoid fixing a single expectation. Consider optimistic (many sunny days), standard, and downside (many cloudy days) scenarios separately to facilitate post-installation evaluations. Especially for internal approvals and customer proposals, explaining the variability range rather than showing only favorable results increases credibility.

Ultimately, PV is weather-dependent. You cannot eliminate cloudy-day risk entirely, but you can identify it beforehand and incorporate it into operational plans. By carefully checking generation, consumption, storage, and purchased power relationships, you can make realistic and convincing installation decisions.

# How to proceed with simulation checks considering cloudy-day risk

When assessing cloudy-day risk, following a fixed check order helps keep decisions consistent. Start with annual generation, then move to monthly generation, daily or hourly generation tendencies, low-irradiance generation, relationship with demand, and impacts on battery operation. This flow from totals to distribution to operational impact makes it easier to organize the overall picture and to build explanatory materials. It is easier to construct rationale by going from aggregate figures to distribution and then to operational impacts than to start with detailed data.

First, confirm that annual generation is reasonable relative to system capacity. At this stage, aim to identify any extremely high or low values. Next, check monthly generation and identify months with drops. Assess whether this aligns with regional characteristics and seasonal factors. Consider low-generation factors such as winter, rainy season, typhoon season, and snowfall according to the site.

Then, within low-generation months, check daily and hourly tendencies. See how much generation drops if cloudy conditions persist and how the daily generation curve changes in mornings, afternoons, and evenings. If hourly data is available, overlay it with demand curves. If generation and demand align, self-consumption improves; if they misalign, surplus or purchased power is likely.

Also confirm installation conditions. Make sure orientation, tilt, surrounding shading, roof surface splits, panel layout, and maintenance spaces are reflected in the simulation. Cloudy-day risk changes not only with weather but also with installation conditions. In particular, shading and low-irradiance generation declines can compound cloud effects.

When explaining simulation results, avoid concluding with a single generation figure. Supplement the standard estimate with verbal notes on downside potential when cloudy conditions increase. Even without detailed numbers, explain that generation falls under low irradiance, batteries may not charge during consecutive cloudy days, and purchased energy may rise seasonally. This helps prevent post-installation misunderstandings.

Simulations are not one-off. The more detailed the site information, the more accurate the results. It is desirable to increase precision stepwise: rough estimates for initial studies, detailed analysis reflecting orientation and shading after site inspection, and a final check including demand and operation data before contracting. For cloudy-day risk, focus on regional characteristics at the initial stage and verify hourly behavior and prolonged low-irradiance impacts in detailed stages.

What practitioners need is the ability to interpret assumptions and risks, not to accept simulation outputs at face value. If you can carefully check cloudy-day risks, you can preemptively explain downside generation and more easily revise system capacity and operational policies. Presenting both expected benefits and variability risks in PV installation decisions leads to trusted proposals.

# Summary

To assess cloudy-day risk in solar PV generation simulations, annual generation alone is insufficient. You must comprehensively check annual irradiance and regional differences, monthly generation drops, consecutive cloudy periods, generation tendencies at dawn/dusk and under low irradiance, short-term cloud-driven fluctuations, the effects of orientation and tilt, and impacts on self-consumption and battery operation. Reviewing these in sequence helps organize downside factors and adjust post-installation expectations realistically.

Cloudy-day risk is not meant to find weaknesses in PV. Instead, it is a set of preconditions you should grasp to enable long-term stable operation. Relying only on sunny-day generation in installation decisions makes discrepancies likely during the rainy season, winter, consecutive cloudy days, and low-irradiance times. Conversely, checking low-irradiance tendencies allows more realistic planning of system capacity, batteries, power usage strategies, and explanatory materials.

In practice, it is important not only to present simulation numbers but also to explain what regional conditions, installation conditions, and weather assumptions those numbers are based on. Practitioners who can explain cloudy-day risk address pre-installation concerns more readily and maintain consistency in post-installation evaluations. Use PV generation simulations as decision tools that link site conditions and operational conditions, not just generation forecasts.

For that, accurately understanding site orientation, tilt, surrounding shading, available mounting surfaces, and equipment layout is indispensable. Desktop simulations alone may not fully reflect site-specific steps, obstacles, site shape, roof orientations, or surrounding environment. To improve analysis accuracy, combine generation simulations with on-site measurements and make input conditions precise.

If you want to streamline site surveys and layout checks, leveraging high-precision positioning—such as LRTK (iPhone-mounted high-precision GNSS positioning device)—makes it easier to capture location information around roofs and within premises on site. The accuracy of solar PV generation simulations depends not only on irradiance data but also on how accurately site conditions are reflected. To make sound installation decisions that include cloudy-day risk, combine simulations and on-site positioning and build plans based on solid evidence.