Five approaches to calculating solar power generation considering cloudy and rainy conditions

When calculating solar power output, looking only at generation under clear-sky (sunny) conditions tends to result in large discrepancies with actual operational results. This is especially true in regions with many cloudy or rainy days, areas susceptible to the effects of the rainy season or typhoon season, and locations with large weather variability such as mountainous or coastal areas, where how you account for decreases in solar irradiance affects calculation accuracy.

Solar power generation works by converting sunlight into electricity, but the amount generated is not determined solely by the weather. Even on cloudy days, scattered light produces a certain amount of power, and on rainy days panels can generate electricity during brighter periods. Conversely, when thick clouds, prolonged rain, dirt on the panel surface, temperature, installation angle, surrounding shadows, and equipment conversion losses combine, the output can appear lower than expected. Therefore, when calculating generation in practice, it is important not to rely only on ideal clear-sky values but to realistically incorporate cloudy and rainy conditions, seasonal variations, and equipment conditions.

Table of Contents

• Understand the assumption that power generation will not drop to zero on cloudy or rainy days.

• Lay the groundwork for calculations by analyzing solar irradiance data according to weather conditions.

• Consider annual power generation taking into account monthly and seasonal variations

• Use loss coefficients to approximate actual power output

• Review the calculation conditions by comparing them with actual performance data.

• Summary

Understand the assumption that power generation does not drop to zero on cloudy or rainy days

One key point to grasp when calculating solar power generation is that output does not necessarily drop to zero on cloudy or rainy days. Solar panels generate electricity not only from strong direct sunlight on clear days but also from light diffused by clouds and the atmosphere. Therefore, on an overcast day when the whole sky is bright, generation will be lower than on a sunny day but some output can still be expected. The same applies to rainy days: generation falls significantly during dark periods under thick rain clouds, but as long as some daylight remains, panels can still produce a small amount of power.

A common practical problem is performing calculations based on extreme assumptions such as "it doesn't generate any power because it's cloudy" or "because it's raining, the power generation will be nearly zero." Conversely, calculations that use sunny-day generation as the baseline and do not adequately discount for the effects of cloudiness or rain also require caution. Both tend to diverge from actual power generation and can lead to incorrect conclusions in pre-installation simulations, monthly reports, and investigations into causes of reduced power generation.

When roughly estimating solar power generation, you approximate it by combining the installed capacity of the generation equipment, the solar irradiance, and the overall system efficiency. The important point is the idea that differences in weather are mainly reflected in solar irradiance. On sunny days the irradiance is high, on cloudy days it is low, and on rainy days it tends to be even lower. However, even among cloudy conditions, thin clouds and thick clouds create very different conditions. Similarly, for rain, whether it is a brief shower or a day-long, dark rain will change the amount of power generated.

For example, a day that is cloudy in the morning and has sunny intervals in the afternoon and a day that is covered in thick clouds all day would both be classified as cloudy, but the power generation would be very different. Even on rainy days, if it only rains in the morning and evening and there are bright periods during the daytime, power generation does not drop completely. Conversely, even on sunny days, yellow sand (Asian dust), snowfall, shading, soiling of panels, or equipment outages can prevent generation from reaching expected levels.

Rather than treating the weather simply as sunny, cloudy, or rainy, it is important to pay attention to the actual intensity and duration of solar irradiance reaching the panels. Especially for practitioners who search for "太陽光発電量 計算" (solar power generation calculation), memorizing the formulas alone is not enough. You need to confirm what conditions the irradiance values used in the calculations represent—whether they are based on clear-sky conditions, long-term averages, measured values, or estimates.

When accounting for cloudy or rainy conditions, the key point is not to treat the maximum generation on sunny days as an absolute benchmark. Sunny-day generation is a reference for when equipment is operating well and solar irradiance conditions are favorable. When calculating annual or monthly generation, it is more realistic to use averaged conditions that include not only sunny days but also cloudy days, rainy days, mornings and evenings with weak solar irradiance, and seasonal differences in solar elevation.

Also, when considering power generation on cloudy or rainy days, it is important not to judge solely by panel capacity. Even systems with the same capacity can produce different amounts of power depending on the installation angle, orientation, surrounding environment, condition of the panel surface, and system configuration. Because solar irradiance is inherently weaker on overcast days, slight shading, dirt, poor connections, or differences in conversion efficiency can become more noticeable. Small losses that are hard to detect in sunny conditions can show up as reduced generation on cloudy or rainy days.

Therefore, in power generation calculations that take clouds and rain into account, you should not end with the generalization "power generation drops on bad-weather days"; instead, you need to separate how much solar irradiance decreases, when during the day that decrease occurs, and whether it overlaps with equipment-side losses. Clarifying these points makes it easier, when comparing calculated results with on-site actual performance, to distinguish whether the cause is weather or a problem on the equipment side.

Lay the groundwork for calculations by analyzing solar irradiance data by weather

When calculating solar power generation while accounting for cloudy or rainy conditions, handling solar irradiance data is central. Generated output is not determined solely by installed capacity; it is influenced by the amount of solar energy reaching the panel surface. Therefore, if the irradiance used as the basis for calculations does not match reality, no matter how meticulous the formulas you use the results will be off.

There are different ways to view solar irradiance depending on the purpose, such as horizontal-plane irradiance, tilted-plane irradiance, and global irradiance. Because solar panels are installed to match the angle of roofs or mounting racks, when estimating actual power generation it is important to consider irradiance under conditions as close as possible to the panel surface. Looking only at horizontal-plane data can fail to fully reflect differences caused by installation angle and orientation.

When considering cloudy and rainy days, not only the average solar irradiance but also day-to-day variability is important. The monthly average solar irradiance is a value that evens out sunny days and bad-weather days. It is convenient for estimating annual power generation, but it can be too coarse for assessing drops in generation in specific months or for verifying performance during extended rainy periods. In regions where the rainy season, typhoon season, or winter sunlight shortages are problematic, looking at daily and hourly variations as well as the monthly average provides a more realistic assessment.

For example, if monthly solar irradiance is lower than the long-term average, it is natural for that month's electricity generation to be lower than expected. However, if solar irradiance is at the long-term average while generation alone is significantly lower, you should suspect other factors such as equipment outages, shading, soiling, wiring, metering equipment, or power conversion devices. To distinguish between these causes, it is essential to use solar irradiance data as the baseline rather than judging the weather by feel.

When considering different weather conditions, it is important not to treat sunny, thinly cloudy, heavily cloudy, and rainy days uniformly. On thinly cloudy days, even if direct sunlight weakens, scattered light from the whole sky can still allow for a certain level of power generation. On the other hand, days covered by thick clouds or with long-lasting rain clouds see solar irradiance drop significantly even during daytime. Short periods of rain may have only a limited impact on a day's total generation, but if it rains all day it can lead to a substantial decrease.

Practically speaking, it is safer to check time-series data of solar irradiance and actual power generation performance than to calculate based solely on the wording of weather forecasts. Even if the forecast says "cloudy", there may actually be sunny breaks that increase generation. Conversely, even if it is "sunny with occasional clouds", if clouds cover the peak generation hours the day's total generation can be lower than expected. In solar power generation, what matters is how much solar irradiance was received during the generation-prone hours from morning to afternoon.

Be careful about the data period used for calculations. Judging only from short-term data makes results prone to being skewed by transient weather. If you check power generation after a few days of rain, the system may appear to have a problem. However, if the latter half of the same month has continued sunny weather, the monthly total may come closer to expectations. Conversely, even if the annual picture looks fine, an unusually low generation in a specific month may hide season-specific shading, snow cover, soiling, or equipment outages.

When using solar radiation data, pay attention to the distance to the target site. When using nearby observation stations or general regional data, local microtopography, fog, mountain shadows, sea breezes, snow cover, and shadows from surrounding buildings cannot be fully reflected. Especially in mountainous areas, sunlight conditions can change even within the same municipality. In coastal areas, the movement of clouds and humidity can have an effect. In urban areas, the influence of building shadows and reflections is added. Therefore, publicly available solar radiation data are a useful reference, but it is necessary to consciously adjust them in light of actual on-site conditions.

A common approach for a rough estimate of power generation is to multiply solar radiation by the system capacity and a loss coefficient. If you separately assume a large impact from clouds or rain, you need to check whether weather effects are already included in the solar radiation data. When using long-term average solar radiation or measured solar radiation, average variations due to weather are to some extent already reflected. Applying an additional overly conservative bad-weather correction on top of that can lead to underestimating the power generation.

On the other hand, when calculations are based on ideal solar radiation conditions under clear skies, if you do not separately account for the effects of cloudy or rainy weather, you will overestimate power generation. In other words, the need for correction depends on which data you are using. Before inputting values into the formula, checking the type, period, and location of the solar radiation data, and whether it is an average or an actual measured value, is the first step in performing calculations that take clouds and rain into account.

Consider annual power generation accounting for monthly and seasonal variations

When calculating solar power generation, the effects of clouds and rain appear not only on a daily basis but also on a monthly and seasonal basis. When estimating annual generation, simply multiplying the average daily generation by 365 does not adequately reflect seasonal solar irradiance conditions and weather biases. In practice, it is effective to aggregate annual generation month by month while taking into account monthly solar irradiance, sunshine hours, solar altitude, temperature, and the frequency of rain and cloudiness.

Solar power generation tends to increase during periods of high solar irradiance and decrease when irradiance is low. However, summer is not always the season with the highest output. Although summer has longer sunshine hours, high temperatures can reduce the output of solar panels. In some regions, the rainy season, typhoons, sudden evening showers, and moisture-laden clouds can also prevent generation from increasing as much as expected. Spring and autumn, with their relatively mild temperatures and more stable sunlight conditions, can sometimes produce favorable generation.

When considering rain and cloudiness, special attention should be paid to the effects of the rainy season and prolonged rain. When cloudy or rainy conditions persist, daily power generation drops significantly. In the short term, it is easy to perceive this as a period of "low power generation," but over the course of a year it can often be partly compensated by other sunny periods. Therefore, it is important to separate assessments made on a monthly basis from those made on an annual basis. While a monthly decline can often be explained by weather factors, if low output persists on an annual basis for a long time, it becomes necessary to review the equipment and operating conditions.

Winter is also a season with many calculation considerations. In winter, daylight hours are shorter and the sun's altitude is lower, so even with the same system capacity, electricity generation tends to decrease. In snowy regions, if snow remains on the panel surface the panels cannot receive sunlight and generation drops significantly. In areas where cloudy or snowy days persist, estimating winter generation based on clear-sky conditions will lead to overestimation. Furthermore, if shadows from surrounding buildings or terrain extend longer in winter, generation may not increase much even when it is sunny.

On the other hand, in winter, because temperatures are lower, the reduction in output caused by the panels' own temperature rise tends to be smaller than in summer. In other words, declines in winter generation are more likely to be driven by solar irradiance, hours of sunlight, solar altitude, shading, and snowfall rather than by temperature. Thus, seasonal factors are not limited to a single cause. Looking at not only clouds and rain but also temperature and the way shadows fall makes it easier to interpret the calculation results.

When considering monthly electricity generation, it is important not to simply divide the annual generation equally by twelve. Solar power generation varies by month. Some months have higher solar irradiance and others lower, and even with the same equipment there are periods when generation is easier and periods when it is harder. Even if the annual expected value is the same, an incorrect monthly allocation can make one month appear excessive and another month appear insufficient. Especially when evaluating the effects of cloudiness or rain, it is necessary to compare with the month's long-term average and with the actual weather.

When an operations staff member prepares a monthly report, simply summarizing low power generation in one word as "bad weather" may be insufficient. Checking how much the bad weather led to a reduction in solar irradiance, how many rainy days there were, whether there were many clouds during the generation peak hours, and how it compared with the same month last year or the long-term average will improve the accuracy of the explanation. Conversely, if generation was close to expectations despite many cloudy or rainy days, that can be taken as evidence that the equipment is operating stably.

When calculating annual power generation, a practical approach is to aggregate monthly generation. Multiply each month's solar irradiation by the system capacity and the loss factor to derive the estimated generation for each month. Then assess seasonal characteristics. Months affected by the rainy season or typhoons can be expected to have lower solar irradiation; in winter, check sunshine hours, shading, and snowfall. Spring and autumn are generally relatively stable periods, but depending on the region you should also consider effects such as prolonged rain, yellow sand, falling leaves, and dust from agricultural work.

The important thing here is not to be satisfied with looking only at the annual total. Calculating annual power generation is necessary for project evaluation and business planning, but in actual operation monthly variations are what matter. For example, even if the annual total is close to expectations, if there is a significant drop in a particular month you need to check that month’s weather and the condition of the equipment. Conversely, if only one month falls short of expectations and there is a clear reason such as prolonged rain or a typhoon, you don’t need to immediately conclude that there is an equipment fault.

When making calculations that account for cloudy and rainy conditions, it's important to separate the seasonally "normal variability" from abnormal declines. Normal variability refers to the reductions in solar irradiance observed in that region or season. An abnormal decline is when generation is lower even compared with years or months with similar weather conditions. Distinguishing between the two stabilizes the assessment of power generation and prevents over-attributing underperformance to either the weather or the equipment.

Use loss coefficients to approximate actual power generation

When calculating solar power generation, you need to account not only for solar irradiance and installed capacity but also for losses across the entire system. In theory, with sufficient irradiance and ideally operating equipment, high generation can be achieved. However, in the field the actual generation is reduced by various factors such as temperature rise, conversion losses, wiring losses, dirt on the panel surface, shading, aging, equipment control, and measurement errors. To account for this difference, the concepts of loss factors and system efficiency are used.

On cloudy or rainy days, solar irradiance is low, so the appearance of losses differs from that on sunny days. On sunny days, generation is high and some losses may be less noticeable, but on cloudy days baseline generation is lower, so shadows, dirt, and equipment standby conditions can appear relatively larger. Rain can wash some dirt off the panel surface, but bird droppings, oily contaminants, fallen leaves, mud, and accumulated dust may not be completely removed. It is not safe to assume that panels will necessarily be clean just because it rained.

When using loss coefficients, it's important not to squash all conditions into a single number. In simplified calculations you may treat the system's overall loss as a lumped value, but in practical root-cause analysis you need to separate which losses are dominant. For example, reduced solar irradiance due to clouds or rain is a weather-related factor. In contrast, inverter shutdowns, wiring faults, panel soiling, shading, and measurement device drift are equipment- or operation-related factors. Confusing these makes explanations of reduced power generation ambiguous.

Losses due to temperature should not be overlooked. Solar panels generally tend to produce less output as panel temperature rises. On sunny summer days, although the solar irradiance is high, the panel temperature increases, so generation may not rise as much as the increase in irradiance. On cloudy or rainy days, ambient and panel temperatures may fall, but because the irradiance itself is low, power generation is suppressed. In other words, the main reason for low generation on cloudy or rainy days is usually a lack of irradiance rather than temperature. However, when making seasonal comparisons, it is safer to consider both irradiance and temperature.

Shading losses also affect cloudy and rainy days. On overcast days without strong direct sunlight, shadows may seem less noticeable, but when evaluating power generation you cannot ignore the influence of the surrounding environment. If shadows appear only during certain hours on sunny days, generation during those hours can drop significantly. In winter, because the sun’s altitude is low, shadows from buildings, trees, mounting structures, handrails, utility poles, and the like extend far. When a season with frequent rain and clouds overlaps with a season prone to shading, the cause of reduced power generation becomes difficult to identify as a single factor.

The condition of the panel surface also affects the difference between calculated and actual performance. Rain can wash away light dust from the surface, but adhered dirt, bird droppings, fallen leaves, pollen, and mud may remain. When calculating power generation for cloudy or rainy conditions, looking only at the reduction in solar irradiance can overlook additional losses due to soiling. In particular, if some dirt remains after the rain, it can continue to affect power generation even after the weather clears.

Losses in conversion equipment and wiring also need to be considered. The direct current power generated by solar panels incurs losses during the process of being converted into a form suitable for use or grid connection. Differences also arise depending on wiring distance, connection condition, equipment efficiency, and operational control. Under cloudy conditions, because the input is small, the apparent efficiency can change depending on the equipment’s operating conditions. In calculations these are often treated as average losses, but if actual results differ significantly, it is advisable to check the equipment’s operating logs and shutdown history.

Degradation over time should also be included as a factor in power generation calculations. Because solar power generation systems are intended for long-term operation, their output may gradually decline as years pass. If you base estimates on the first-year output and assume the same generation for many years, long-term calculations can become overestimated. However, degradation rates vary depending on the equipment, installation environment, and maintenance conditions, so it is important not to treat them as definitive and to estimate while checking specifications, inspection records, and historical performance trends.

When calculating power generation that accounts for cloudy or rainy conditions, be careful not to double-count corrections to solar irradiance and loss factors. For example, if you are using measured solar irradiance, the weather-related reduction in irradiance is already reflected. If you then further subtract a large "rain correction" from the generation, the result can be unnecessarily low. On the other hand, if the calculation is based on ideal clear-sky conditions, you need to separately account for weather-related reductions in irradiance.

A safe way to proceed with calculations is to first reflect weather effects using solar irradiation, and then appropriately account for equipment-side losses. By treating weather and equipment losses separately, it becomes easier to explain the calculation results. If actual performance is lower than expected, you can check, in order, whether the solar irradiation was low, the assumptions about loss coefficients were too optimistic, or there is an abnormality in the equipment.

Review calculation conditions by comparing with actual performance data

Calculations of solar power generation that take clouds and rain into account are not something you create once and then finish. Calculated values are merely estimates, and their accuracy improves by revising assumptions while comparing them with actual generation. Especially for systems in operation, it is important to cross-check generation performance, solar irradiance, temperature, weather, and equipment operating status. Rather than relying solely on formulas, linking calculations to field data yields generation assessments that are practical for real-world use.

When comparing actual performance, the first thing to check is the relationship between solar irradiance and power generation over the same period. It is natural for power generation to be low on days with low solar irradiance. If generation drops during a stretch of cloudy or rainy days, first confirm whether this can be explained by weather factors. On the other hand, if solar irradiance is sufficient but power generation is low, suspect an equipment-side problem. Rather than looking at power generation alone, examining the ratio to solar irradiance and the changes by time of day makes it easier to isolate the cause.

Time-of-day data are also useful. Solar power generation generally increases during the daytime and is lower in the morning and evening. On clear days, the generation curve rises relatively smoothly, peaks around midday, and falls in the evening. On cloudy days, output tends to fluctuate depending on cloud movement, and on rainy days it tends to be generally low. If output suddenly drops during a specific time period even on a clear day, you should check for shading, equipment control, shutdowns, or measurement anomalies.

Month-by-month comparisons with the same month of the previous year or with the long-term average are useful. However, simply comparing with the same month last year is not sufficient. If the same month last year benefited from unusually sunny weather while this year is much rainier, a decrease in generation is to be expected. Conversely, if this year’s weather is comparable to last year’s but only the generation is lower, that provides grounds to suspect equipment-related changes. When evaluating generation, it is important to align the weather conditions of the comparison targets.

When reviewing performance data, it is important to pay attention to time offsets in measuring instruments and data loggers. If the timestamps of solar irradiance data and power generation data are offset, you may think you are comparing the same time period but are actually looking at different conditions. The impact of timestamp misalignment is especially large on days when clouds move quickly or when rainfall changes rapidly over short periods. Before analyzing a drop in power generation, check the data timestamps, aggregation intervals, missing data, communication outages, and recording methods to avoid misjudgments.

Also, actual power generation records include the effects of equipment stoppages and control. Inspections, power outages, output curtailment, protection actions, communication failures, and measurement loss can cause generation to be recorded as low regardless of the weather. If equipment shutdowns occur on days with cloudy or rainy conditions, the reduction in generation can appear to be caused by the weather. When comparing actual and calculated values, it is safer to also check shutdown history and alarm history.

When reviewing calculation assumptions, first confirm whether the initially used solar irradiance, loss coefficients, system capacity, installation angle, orientation, and shading conditions match reality. Pre-installation simulations may not adequately reflect surrounding buildings and tree growth, seasonal shading, soiling buildup, snow accumulation, or maintenance frequency. Once operational performance data have been accumulated, adjusting the assumed conditions based on those results will make subsequent forecasts and reports more realistic.

However, you should avoid changing calculation conditions too readily just to match observed results. If you significantly lower the annual loss factor because one month happened to be particularly rainy, the calculations will no longer match once the weather returns to normal. A useful approach is to explain short-term weather variability on the solar irradiance side, and to review equipment conditions and loss factors for differences that persist in the long term.

When power generation is lower than expected, a step-by-step approach to checking causes is helpful. First, check whether solar irradiance during the period was low. Next, see whether the ratio of generated power to the same solar irradiance has declined compared with the past. Then check for equipment outages, shading, soiling, snow cover, measurement anomalies, and aging-related degradation. Following this sequence reduces the risk of overestimating the impact of clouds or rain, or conversely overlooking equipment abnormalities.

By continuing to compare actual performance, the characteristics of each installation become apparent. Even installations in the same area will have different power output on cloudy or rainy days if their installation angle or surrounding environment differs. Some installations generate relatively stable output on partly cloudy days, while others tend to produce lower output due to shadows or dirt. Accumulating performance records for your own or managed installations and understanding trends by weather, season, and time of day will improve the accuracy of calculation conditions.

Calculating power generation with consideration for cloudy and rainy conditions is useful not only for pre-installation estimates but also for post-installation improvements. This is because, when generation is low, you can determine whether the weather reasonably explains it or whether an inspection is necessary. If you routinely review calculation assumptions using actual performance data, your reports will be more persuasive and it will be easier to explain the results to stakeholders.

Summary

When calculating solar power generation with cloudy and rainy conditions in mind, it is important not to use generation during clear skies as the sole baseline. Solar power can still produce some electricity on cloudy or rainy days from diffuse and weak irradiance, but output tends to fall significantly compared with clear-sky conditions. Therefore, instead of judging the weather by intuition, you should construct your calculation conditions around solar irradiance data.

To bring power generation estimates closer to reality, consider a combination of solar irradiance, system capacity, and loss factors. In this context, it is important to confirm whether the solar irradiance data already includes weather effects or uses ideal clear-sky conditions. The adjustments required differ when using measured values or long-term average values versus correcting from ideal conditions. Applying too many corrections leads to underestimation, while insufficient corrections lead to overestimation, so clarifying the assumptions is essential.

Furthermore, the effects of cloud cover and rain appear not only on a daily basis but also on a monthly and seasonal basis. The rainy season, typhoons, lack of sunshine in winter, snowfall, prolonged rain, and other factors greatly affect power generation. When considering annual generation, it is more realistic to aggregate monthly solar irradiation and reflect seasonal characteristics. Rather than looking only at the annual total, understanding monthly variations makes it easier to explain differences from actual performance.

Furthermore, it is important not to attribute all declines in power generation to the weather. Equipment-related factors—conversion losses, wiring losses, dirt on panel surfaces, shading, equipment outages, measurement anomalies, and degradation with age—also affect generation. During periods with frequent clouds or rain, generation tends to be lower, which can make equipment problems harder to detect. Comparing solar irradiance and power output, and separating weather-related factors from equipment-related factors when assessing performance, is a prudent and safe approach in practice.

For operating facilities, it is essential to continuously compare calculated values with actual results and review the conditions. By looking at power generation, solar irradiance, temperature, weather, stoppage history, alarm history, and inspection records together, it becomes easier to determine whether a decline is a natural drop due to clouds or rain, or a decline that requires equipment inspection. Explain short-term poor weather by changes in solar irradiance, and address long-term persistent discrepancies by reviewing loss coefficients and equipment conditions; doing so stabilizes the accuracy of the calculations.

Calculating solar power generation is not just a simple mathematical exercise; it's a process of interpreting weather, seasons, equipment, and on-site conditions together. Properly accounting for cloudy or rainy conditions improves the quality of pre-installation simulations, monthly generation checks, root-cause isolation during low-output periods, and maintenance decisions. By organizing site-specific irradiance conditions and generation performance and continuously verifying the relationship between irradiance and generation, calculation results become easier to use as practical decision-making material.