6 Solar Simulation Items to Calculate Annual Electricity Generation Yourself

When calculating solar power generation, the first thing people often struggle with is “which numbers should I input to get how close to reality?” Annual generation is not determined by system capacity alone. It is determined by a combination of factors such as solar irradiance, tilt angle, orientation, shading, temperature, conversion losses of the power conditioner, losses from wiring and soiling, downtime, and so on. This article organizes, in order, six items that practitioners should check when performing solar power generation calculations themselves. It does not completely replace specialized simulations, but it summarizes a way of thinking that can be used to check the plausibility of rough estimates, provide explanations within the company, make preliminary assessments before site surveys, and verify the actual performance of existing installations.

Table of Contents

• Grasp the basic formula for annual electricity generation simulations

• Align assumptions for system capacity and panel output

• Check irradiance data by region and installation surface

• Anticipate generation differences due to azimuth and tilt angle

• Decompose loss coefficients to approximate realistic values

• Validate calculation results using monthly generation and actual performance data

• Prevent common mistakes when calculating by yourself

• Summary

Understand the basic formula for simulating annual power generation

When calculating annual energy production yourself, it's important to first reduce complex conditions to a simple formula. As a rough estimate, the annual energy production of a solar power system is obtained by multiplying the "solar panel capacity", the "irradiance on the installation surface", and a "loss factor" that accounts for losses. In practice, the workflow is to clarify what the installed capacity (in kW) is, how much solar irradiance the installation site receives, and how much loss occurs across the entire system.

The basic idea is that annual electricity generation, relative to installed capacity, reflects how much solar energy can be received over the year. For example, with the same installed capacity, annual generation will differ between regions with good solar irradiance and regions with frequent cloud cover. Even within the same region, a roof that faces nearly south and a roof oriented east-west will show differences in the time of day they generate power and in their annual output. Moreover, because factors such as soiling of the panel surface, wiring losses, conversion losses, temperature increases, shading, and equipment downtime come into play, you cannot treat the catalog-rated output as the annual generation.

As a rough formula, it is easier to organize if you consider the annual power generation as "solar PV capacity kW × annual insolation on the installation surface kWh/m2 equivalent × performance ratio or loss factor." Here, solar PV capacity means the rated output obtained by summing the solar PV modules. For annual insolation, it is desirable to use the annual total of solar radiation incident on the installation surface, because judging only by the horizontal-plane insolation can overlook differences due to tilt angle and orientation. The performance ratio or loss factor collectively anticipates the losses from the solar irradiance received by the PV to the AC electrical energy actually available.

However, if you combine too many coefficients into one, it becomes difficult to explain why that result was obtained. When using this in practice, it is safer to first grasp the overall picture with a simplified formula and then separately check the loss factors. If you try to perform detailed calculations from the outset, the number of input items increases and it becomes harder to notice inconsistencies in the assumptions. Conversely, if you rely solely on a simple formula, you may overlook site-specific conditions such as shading or downtime.

In calculating solar power generation, what matters is clarifying the assumptions used to derive the numbers, rather than the calculation results themselves. Even when expressed as the same "annual generation," the meaning changes depending on whether the calculation used irradiance on the panel surface, a simplified correction of horizontal-plane irradiance, or the extent of losses included. When using this in internal documents or explanations to customers, keep the calculation formula, input values, and the way losses are treated together in the same document so it is easier to review later.

Also, annual power generation is not a prediction that the figure will inevitably be achieved in the future, but a simulated value under certain conditions. Weather varies from year to year, and equipment condition also changes over time. Therefore, the calculated results should be treated only as expected values or guidelines, and it is necessary to adjust them by comparing with actual results. In particular, when evaluating the power generation of existing facilities, do not judge a condition as abnormal based solely on a single year's performance; it is essential to check monthly trends, comparisons with nearby facilities, solar radiation conditions, and outage histories together.

Align assumptions for system capacity and panel output

The first item to check when calculating annual power generation is the installed capacity. Installed capacity may appear to be a straightforward figure at first glance, but in practice the "total capacity of the photovoltaic modules" and the "capacity of the power conditioner" are sometimes confused. In the basic calculation of annual power generation, the sum of the rated outputs of the photovoltaic modules is generally used. For example, the panel-side installed capacity is the value obtained by multiplying the rated output per module by the number of modules installed.

What should be noted here is that rated output is a value measured under specific test conditions, and it does not mean that the same output will always be produced outdoors. Output varies with solar irradiance, panel temperature, shading, dirt, and aging. For this reason, system capacity is a reference value used to calculate annual generation and is not a figure that guarantees actual annual generation. While larger system capacity tends to increase generation, poor installation conditions or large losses may prevent it from rising as expected.

When calculating existing equipment, check as-built drawings, single-line diagrams, the equipment ledger, and module layout drawings to verify that the actual number of installed modules matches the rated output. For equipment that has undergone partial removal or replacement in the past, the original design capacity may differ from the current equipment capacity. Also, for expanded installations, old and new panels may coexist, and treating them simply as a single capacity can misrepresent the actual situation. In such cases, dividing and calculating capacity by system or by power conditioner unit makes later verification easier.

When checking panel output, you need to be aware not only of the DC-side capacity but also of the AC-side output limits. In designs where the power conditioner (inverter) capacity is smaller than the solar array capacity, output can become capped during periods of strong sunlight. This is not necessarily a fault and may be adopted as a design approach. However, if this effect is not accounted for at all when calculating annual generation, peak generation on clear days may be overestimated.

On the other hand, it is not appropriate to estimate annual generation excessively low by looking only at peak output limits. The periods during which output is capped vary depending on region, azimuth, tilt angle, panel capacity, power conditioner (inverter) capacity, and season. It is important to check how long during the year this effect occurs and, if necessary, to examine monthly or hourly generation curves. In the preliminary estimation stage you may account for it as a coefficient, but if generation affects revenue or contractual decisions, it is safer to verify under more detailed conditions.

When aligning assumptions about system capacity, you must not overlook how units are handled. kW refers to output (power), while kWh refers to electrical energy. Annual generation is typically expressed in kWh. If you confuse system capacity in kW with annual generation in kWh, calculations and explanatory materials are likely to contain errors. For example, saying "a 10 kW system" indicates the scale of instantaneous output capacity, whereas "how much it will generate in a year" is expressed in kWh, which takes into account solar irradiance and time. Clarifying this difference helps prevent misunderstandings during internal reviews and when explaining to customers.

Check solar radiation data by region and mounting surface

The second item is checking solar irradiance data. In solar power generation calculations, solar irradiance has a large impact on the results. Solar irradiance varies by region and can change greatly by season even within the same area. When estimating annual energy production, use meteorological conditions as close as possible to the installation site, and check not only the annual total but also monthly trends to make comparisons with actual performance easier.

There are several ways to characterize solar irradiance, including horizontal irradiance, tilted-surface irradiance, direct (beam) irradiance, and diffuse irradiance. Simple calculations sometimes use horizontal irradiance, but actual solar panels are mounted on roofs or racks at an angle, so it is necessary to consider the irradiance incident on the mounting surface. When panels face south and are close to an optimal tilt angle, annual power generation tends to be higher; east- or west-facing orientations or low tilt angles change the time-of-day profile of generation and the annual total.

When handling solar irradiance data, also check which period’s average is being used. Using a long-term average makes it easier to estimate generation for an average year. On the other hand, when comparing with actual values for a specific year, you need to consider whether that year’s weather was sunnier than normal or had more rain and clouds. Even if the annual power generation is lower than expected, if the solar irradiation conditions themselves were poor that year, it does not necessarily indicate equipment malfunction.

If there is no solar radiation data close to the site, you will refer to data from nearby locations. In doing so, consider not only proximity but also terrain and climatic characteristics such as mountainous areas, coastal areas, snowy regions, and urban areas. Even within the same prefecture, solar radiation conditions can differ between areas affected by mountains and plains. Especially in regions where winter solar radiation and snowfall have a large impact, if seasonal differences are not reflected in the annual power generation calculations, discrepancies with actual results tend to be large.

Performing monthly calculations allows you to verify the impact of solar irradiance in a more practical way. If you only look at the annual total, you can't tell which months have insufficient generation. By comparing monthly solar irradiance and monthly generation side by side, it becomes easier to distinguish declines during the rainy season, reduced solar irradiance in winter, output decreases from temperature rise in summer, and effects from snow or soiling. Even when calculating annual generation, having a monthly breakdown in practice improves your ability to explain the results.

When entering solar radiation data, you also need to pay attention to the units. Solar radiation data can come in different formats, such as daily averages, monthly totals, or annual totals. If you use an average daily solar radiation value, you must check how it relates to the number of days in a month or year. Mistakenly using a monthly total as an annual total, or treating a daily average value as an annual value, can cause calculated results to be significantly off. It is basic but very important to verify the meaning of input values before putting them into formulas.

Estimate differences in power generation due to orientation and tilt angle

The third item is orientation and tilt angle. The amount of electricity a solar panel generates changes depending on the angle at which it receives sunlight. In general, in Japan, the closer a panel faces south the more sunlight it receives during the day, and the higher the annual power generation tends to be. However, depending on roof shape, site conditions, and intended use, installations may also face east, west, or have a low tilt. In those cases, you should consider not only the annual total but also differences in the generation curve, such as generation being concentrated in the morning or evening.

When considering the impact of orientation, it's important not to dismiss a site as "bad simply because it's not south-facing," but to evaluate it in light of the installation's purpose. For systems that prioritize self-consumption, it's important not only to maximize total generation but also to ensure that the times when electricity is used align with the times when it is generated. East-facing arrays tend to increase generation in the morning, while west-facing ones tend to preserve generation into the afternoon. Even if annual generation estimates are lower than for a south-facing system, the operational value depends on the pattern of electricity use.

Regarding the tilt angle, the appropriate angle varies depending on the region and season. A larger tilt angle can be advantageous for the low sun altitude in winter, while a smaller tilt angle can make it easier to receive solar radiation in summer. However, for roof-mounted installations the tilt is often matched to the roof pitch, so you may not be able to set the angle freely. For ground-mounted installations the angle is easier to design, but adjustments are needed for inter-row shading and land-use efficiency.

When running your own simulations, you may treat azimuth and tilt angle as correction factors. For example, this is a way to estimate how much power generation will change for east- or west-facing orientations or low-tilt angles compared with the reference condition of south-facing with a standard tilt angle. However, correction factors vary by region, month, and time of day, so it is important not to overtrust them as fixed values. For rough estimates, organize things by coefficients, and where accuracy is required it is realistic to examine them by month or by time of day.

If a roof is divided into multiple surfaces, it is necessary to calculate the capacity, azimuth, and tilt angle separately for each surface. If an installation has panels distributed across south-, east-, and west-facing surfaces and you treat them as a single average azimuth, the generation curve and monthly generation characteristics become harder to discern. Calculating by surface is especially effective when the power conditioner’s input circuits are separated by surface or when shading affects each surface differently.

When checking orientation and tilt angle, we look not only at the orientation shown on the drawings but also at the actual installation conditions. Even if the drawings indicate a south-facing orientation, on-site measurements may reveal a slight deviation to the east or west. The roof's tilt angle can also differ between the documentation and the on-site measurement. For rough estimates this may not be a major issue, but when verifying a decrease in power output of existing systems or comparing multiple proposals, reflecting the actual site conditions increases reliability.

Decompose the loss coefficient to bring it closer to realistic values

The fourth item is the loss factor. In calculating solar power generation, this is the part where practical differences are most likely to appear. Not all of the solar irradiance received by the panels becomes AC electrical energy as-is. Generation is reduced by multiple factors such as increases in panel temperature, conversion in the power conditioner, wiring resistance, losses at connection points, shading, dirt, degradation over time, equipment downtime, and output control. The loss factor summarizes and anticipates these.

Putting the loss factor into a single number makes calculations simple, but in practice it is safer to consider it broken down. For example, conversion loss depends on the equipment specifications and operating conditions. Wiring loss is affected by cable length, thickness, current, and connection condition. Temperature loss tends to be larger in summer and is also influenced by ventilation and the installation method. Soiling loss varies with the surrounding environment, bird droppings, yellow sand, pollen, fallen leaves, dust, and so on. Shading loss changes depending on buildings, trees, utility poles, spacing between racking rows, and the arrangement of nearby equipment.

Output reduction due to temperature is a factor that cannot be overlooked when considering the annual energy yield of solar power generation. In general, crystalline silicon solar cells tend to exhibit reduced output as panel temperature increases. Therefore, even in summer when solar irradiance is strong, energy production does not necessarily rise in direct proportion to irradiance alone. Installations close to the roof often have limited heat dissipation, so their temperature conditions differ from installations with adequate ventilation. When checking monthly energy output, note that months with high irradiance but lower-than-expected generation cannot always be judged as abnormal.

The effects of shading must be handled especially carefully when calculating annual energy production. Even short-duration shading can affect energy production more than expected, depending on the string configuration and the location of the shade. In winter, when the solar altitude is lower, shadows from surrounding objects that were not a problem in summer can have a significant impact. Also, morning and evening shading may have a limited effect on the annual total, but can be significant for self-consumption or time-of-day evaluations. Because shading is highly site-specific, it is important not to rely solely on simplified calculations; combine on-site verification with time-of-day analyses.

Dirt and snowfall also vary by region and environment. Some dirt is naturally washed away by rain, but bird droppings and mud can persist locally. On low-tilt panels, dirt is less likely to wash off and can accumulate near the frames. In snowy regions, power generation can drop significantly for the period when snow remains. When calculating annual power generation yourself, handling these conditions with only general coefficients can lead to results that differ from actual site conditions.

It is also necessary to be clear about whether to include downtime and output control. Hours when equipment was stopped for inspection or failure, hours when data were missing due to communication anomalies, and hours when output was curtailed for grid-side reasons all affect annual energy production. While simulations as future forecasts may assume a standard availability rate, for performance evaluations of existing facilities it is important to review outage histories separately. Confusing declines caused by downtime with declines in equipment performance can lead to incorrect root-cause analysis.

It is important not to set the loss coefficient either too high or too low. If the loss is set too low, the calculated annual power generation will be higher, but the discrepancy with actual performance tends to increase. If the loss is set too high, the estimate will be conservative, but it will underestimate the equipment’s true potential. In practice, it is advisable to provisionally apply a standard loss, adjust it according to site conditions, and document the reasons for any adjustments.

Verify calculation results with monthly power generation and actual values

The fifth item is verification based on monthly power generation and actual performance. A simulation of annual power generation is not complete merely by performing the calculation. To determine whether the calculated results are realistic, it is necessary to break the generation down by month and compare it with actual values and with facilities that have similar conditions. Even if the annual total is close, if the monthly breakdown deviates significantly, the assumptions may be incorrect.

When viewed by month, the effects of solar irradiance, temperature, shading, snowfall, soiling, and downtime become easier to see. For example, if power generation is lower than expected only in winter, consider shading caused by the decline in solar altitude, snow accumulation, and the effects of azimuth and tilt angles. If it is lower than expected only in summer, check for temperature rise, power clipping, thermal protection of equipment, soiling, and shading from weeds or surrounding objects. A decline during the rainy season may be largely due to weather factors, but this cannot be determined without comparing it to solar irradiance data.

When comparing actual results, it's useful to look not only at energy generation but also at metrics approximating energy yield per unit of insolation. A simple kWh comparison will naturally show lower output in months with poor weather. Looking at how much energy is produced relative to insolation makes it easier to assess the condition of the system. However, this metric is not foolproof: it is also affected by temperature, shading, and downtime. Combining multiple viewpoints improves the precision of isolating causes.

Because there are no actual performance values at the planning stage of a new project, we refer to historical weather data and existing systems under similar conditions. In doing so, we check how closely the installed capacity, orientation (azimuth), tilt angle, region, shading conditions, and operational methods match. Even if only the capacity is the same, energy production will differ if the mounting surface or surrounding environment is different. When selecting comparators, we prioritize the degree of match of conditions rather than simply the magnitude of annual energy production.

For existing installations, arranging actual results from the past several years makes it easier to grasp trends. If generation is low in only one year, weather or a temporary shutdown might be the cause. On the other hand, if it declines gradually year by year, accumulation of dirt, growth of trees, equipment degradation, poor connections, or faults in measuring instruments should be considered. By using the calculated annual generation as a baseline and comparing by month, year, and by installation, it becomes easier to distinguish ordinary variability from anomalies.

When using actual measured values, also verify the reliability of the measurement data. Remote monitoring readings, power conditioner display values, electricity meter readings, and records related to sold and purchased power may differ in measurement location or aggregation method. If you compare them without deciding which value to treat as the annual power generation, discrepancies can occur not because of the equipment but because of differences in data definitions. When comparing measured values with calculated values, it is important to align the definitions as much as possible.

Prevent common mistakes when doing calculations yourself

The sixth item is the prevention of calculation errors and errors in assumptions. In calculations of solar power generation, errors can become larger due to mixing up input values or omissions in assumptions than because of the formula itself. In particular, confusing kW with kWh, monthly values with annual values, horizontal-plane irradiance with tilted-plane irradiance, and panel capacity with power conditioner capacity are mistakes that commonly occur in practice.

First, standardizing units is fundamental. Equipment capacity is in kW, generated energy is in kWh, and solar irradiance can be represented as daily averages or monthly totals—so the way the data are recorded differs. When creating an input table, include not only the item names but also the units, as this makes it easier to spot errors when reviewing later. In particular, when using monthly solar irradiance to calculate annual power generation, check whether you have accounted for the number of days in each month.

Next, avoid averaging the conditions of the installation surfaces too much. In systems with multiple roof surfaces or multiple power conditioners, the solar irradiance and shading conditions can differ for each surface. If you calculate everything in bulk using only the total capacity, you won't be able to tell which surface is suppressing the power output. Separating by surface, by circuit, and by power conditioner increases the calculations slightly, but produces results that are easier to verify.

Also, it is important not to overlook shading and downtime. In simulations of annual energy production, calculating under ideal conditions produces attractive figures. However, in actual sites, surrounding buildings, utility poles, trees, railings, equipment, snow, dirt, and vegetation affect performance. When using the calculation results to make decisions, you need to reflect the risks found during on-site inspections as losses or supplementary conditions.

Avoiding excessive assertions is also important in practical documentation. Because annual power generation is affected by weather, the calculated value may not necessarily be realized. Avoid expressions such as "will definitely generate," "will certainly be recouped," or "if it falls below this value it is a fault," and make it clear that the figures are guidelines based on assumptions. When judging equipment abnormalities, confirm them by combining not only power generation but also solar irradiance, shutdown history, alarm history, on-site conditions, and measured values.

Furthermore, it's useful to decide the timing for updating the calculations. Simulations at the time of new installation may be based on provisional conditions from the design stage. If, after construction, actual installation angles, wiring, or equipment configuration change, recalculating to match the as-built conditions will better reflect reality. After operations start, reviewing the calculation assumptions based on a certain period of actual performance makes it easier to establish reference values suited to that equipment.

Finally, how calculation results are stored is also important in practice. Keeping the input values, calculation formulas, loss coefficients, the solar irradiation conditions referenced, the update date, and the author will be helpful when reviewing the work months or years later. If only the numerical results are preserved, you cannot trace why that annual energy production value was obtained. Treating solar power generation calculations not as a one-off task but as management documentation that links design, construction, maintenance, and improvement increases their value.

Summary

In a solar simulation where you calculate annual energy production yourself, it is important to check six items in order: installed capacity, solar irradiance, azimuth, tilt angle, loss coefficients, and performance verification. Rather than just memorizing the equations, clarifying the assumptions behind the numbers makes the simulation usable in practical work.

Regarding system capacity, it is important not to confuse the total capacity of the solar PV modules with the capacity of the power conditioner. For solar irradiance, check regional differences, monthly variations, and the incidence conditions on the installation surface. For orientation and tilt angle, consider not only the annual totals but also differences in generation time periods. For loss factors, avoid lumping together temperature, conversion, wiring, shading, soiling, downtime, output control, etc., and organize them by factor as much as possible. When comparing monthly generation and actual values, assess not simply by the amount of generation but also include solar irradiance conditions and stoppage history.

Calculations of solar power generation, even without a precise dedicated analysis, can be useful for practical estimates and plausibility checks if the assumptions are aligned. On the other hand, at sites with complex shading, systems where panels are spread across multiple surfaces, or installations heavily affected by output control or shutdown histories, it can be difficult to judge using only a simple annual factor. In such cases, it is essential to check by month, by time of day, and by individual equipment unit, and to compare the results with on‑site conditions.

If you are using power generation calculations for internal explanations or maintenance decisions, it is important to record not only the calculation results but also the input values, units, assumptions about losses, and the date of verification. If the basis of the calculations is preserved, when there is a discrepancy with actual performance it will be easier to determine whether it is due to weather factors, installation conditions, or equipment or operational issues.

If you want to verify annual power generation in a way that is closer to on-site conditions, it is effective to review it not only with desk calculations but also by combining the site’s installation conditions and operational data. Rather than taking calculated values at face value, checking them together with solar irradiance, shutdown history, alarm history, inspection results, and on-site photographs makes it easier to translate the calculated solar power generation results into practical decisions.