7 Criteria for Correctly Interpreting Power Generation Simulation Results

Calculations and simulations of solar power generation are useful materials for pre-installation decisions, verification of design conditions, and post-operation performance evaluation. However, simulation results are not, by themselves, numbers that guarantee future generation. They are estimates calculated by combining multiple assumptions such as solar irradiance, installation angle, shading, equipment efficiency, degradation, weather conditions, and loss rates. Therefore, when using them in practice, you need to interpret not only the total annual generation but also the conditions under which it was calculated and how wide a range the figures may have.

Table of Contents

• Criterion 1 Examine not only the annual power generation but also the month-by-month variations

• Criterion 2 Verify the validity of calculation conditions and input values

• Verify the assumptions of Standard 3 solar radiation data

• Criterion 4 Prevent underestimation and overestimation by examining the breakdown of loss rates

• Criterion 5: Verify how well shadows and the surrounding environment are reflected.

• Criterion 6 Read the results in a form that can be compared with actual values

• For Criterion 7, treat the numbers used for decision-making and the reference values separately

• Summary: Power generation simulations can be used in practical work if you read the assumptions.

Criterion 1: Look at monthly variations, not just annual power generation

When looking at power generation simulations, the first thing people tend to check is the annual power generation. The expected annual generation is an important figure for equipment planning and installation decisions. However, judging solely by the annual generation can easily overlook seasonal variations and monthly imbalances that occur in actual operation. Solar power systems do not generate uniformly throughout the year. They are affected by solar irradiance, hours of sunshine, temperature, snowfall, the rainy season, typhoons, and shading from surrounding objects, which cause differences in monthly generation.

For example, even with the same annual generation, a system whose output tends to increase from spring to summer and a system whose winter decline is comparatively small have different operational implications. When prioritizing self-consumption, it is more important to ensure that the periods of high electricity use align with periods of high generation than to focus on the annual total. Even when considering selling power or utilizing surplus electricity, judging solely by the annual figure without checking monthly generation can easily lead to a mismatch with the expected results.

In practice, after checking the annual power generation, we examine the monthly generation trends as much as possible. If a particular month shows an unusually high or low output, it is important to investigate the cause. We distinguish whether it is a natural fluctuation due to seasonal differences in solar irradiance, an effect of the installation angle or orientation, or a reflection of snow or shading conditions. Reading the monthly figures makes it easier to determine whether the simulation aligns with on-site conditions.

Also, in power generation simulations, the expected annual power generation is sometimes presented as a single number. However, actual generation varies from year to year due to weather variability. In some years there may be more sunny days and output can be higher than projected, while prolonged rain or snowfall can cause it to fall below projections. Therefore, annual generation should be treated not as a fixed value but as a guideline with a certain range of variation.

When reviewing monthly power generation, rather than simply comparing which months are higher or lower, check what factors are present in months with lower generation. Check whether site-specific factors are included, such as insufficient solar irradiance in winter, decreased solar elevation, snowfall, dirt on the panel surface, shadows from nearby buildings, and morning/evening shading from mountains or trees. If the monthly decline does not match on-site observations, the input conditions or shadow settings may have been simplified.

The purpose of using power generation calculations in practice is not simply to check large numbers, but to develop an operational outlook. Annual values are used to grasp the overall picture, while monthly values are used to verify the accuracy of plans. By reading these two separately, you can avoid overreliance on simulation results and turn them into decision-making information that can be used on site.

Criterion 2: Verify the validity of calculation conditions and input values

The accuracy of power generation simulations is heavily influenced not only by the calculation method itself but also by the input conditions. Calculating solar power generation involves many factors: installed capacity, installation orientation, installation tilt angle, solar irradiance, panel output characteristics, power conditioner efficiency, various losses, and the surrounding environment. If any one of these conditions deviates from reality, it will affect the final power output.

Specifically, we want to check the installed capacity and the installation conditions. Installed capacity is the fundamental figure for power generation calculations. Verify that the entered capacity matches the total capacity of the photovoltaic modules actually to be installed. During the design phase, the number of panels and their layout may change. If calculations are performed based on the initially assumed capacity, the simulation results will not correspond to the actual installation.

Installation orientation and tilt angle are also important. In solar power generation, the amount of electricity generated changes depending on the angle at which sunlight is received. For rooftop installations, roof pitch and the orientation of each roof plane affect power output. Even for ground-mounted systems, it is necessary to verify that the racking tilt and layout direction are correctly reflected in the calculation parameters. If orientation or angle are entered as estimates, there can be differences from the actual layout.

Also, when panels are installed across multiple surfaces, check whether the conditions are calculated separately for each surface. South-facing surfaces and east- and west-facing surfaces produce different generation profiles. If these are combined and calculated under a single condition, the monthly and time-of-day trends may not match reality. This is especially important at sites that prioritize self-consumption, because differences in the times when power is generated affect operational planning, so confirming the conditions for each surface is important.

When checking the validity of input values, pay attention to whether the conditions are unrealistically favorable. If calculations assume no obstructions, little dirt or degradation, and minimal temperature losses, the results tend to be biased high. Conversely, assumptions that are overly conservative can produce power estimates that are too low, causing the benefits of installation to be underestimated. What matters is not making the numbers look better or worse, but reading them with assumptions that closely reflect on-site conditions.

When reviewing simulation results, check not only the final power generation figure but also the input conditions that produced that figure. Results with unclear input conditions are difficult to use as a basis for decisions. What practitioners should confirm is not only "how many kWh will be generated" but also "under what assumptions that number was obtained." Adopting this perspective makes it possible to handle the results of power generation calculations safely.

Criterion 3 Verify the assumptions of solar radiation data

In calculations of solar power generation, solar irradiance data is a central assumption. Even if the equipment performs well, if sufficient sunlight does not reach it, power output will not increase. Therefore, when interpreting simulation results, it is important to verify which location, which period, and which conditions the irradiance data used are based on.

Solar irradiance varies by region. Even within the same prefecture, coastal areas, mountainous areas, basins, and urban areas can have different weather conditions. Even when using the nearest observation station, the actual installation site may differ in elevation, terrain, likelihood of cloud cover, and snow conditions. If the location settings in a simulation are coarse, this can be a factor causing discrepancies between simulated and actual power generation.

Also, some solar irradiance data use average weather conditions. Calculations using mean values are useful for making long-term projections, but they do not accurately predict generation for a specific year. Because weather varies from year to year, it is natural that simulated values and actual results do not exactly match. When interpreting the results, check whether the values assume an average year or are based on meteorological data for a specific period.

Solar irradiance can be treated in different ways, such as horizontal-plane irradiance and tilted-plane irradiance. Because solar panels are normally installed at a fixed angle, it is necessary in practice to consider the irradiance incident on the panel surface. In calculations, confirming whether the irradiance has been adjusted to the tilted plane to reflect the installation angle and orientation makes interpretation of the results more consistent. If power generation is judged solely by simple sunshine duration, the generation estimate can be rather crude.

Power generation simulations are also affected by the granularity of solar irradiance data. Calculations based on monthly averages versus those that reflect hourly variations lead to different interpretations of shading, peak shaving, and temperature effects. This is especially true for sites where building shading changes throughout the day, or for sites where you want to assess the timing of self-consumption; monthly or annual totals alone may not be sufficient.

Practitioners should not only check whether the solar radiation data is reliable, but also whether it fits the decision-making purpose at hand. For preliminary assessments, average data may be sufficient. By contrast, when data will be used for detailed design, financial planning, or post-operation performance evaluation, data that more closely reflects site conditions is required. If the granularity of the solar radiation data is insufficient for the intended purpose, it can lead to misinterpretation of simulation results.

Solar radiation is the foundation of power generation. If that foundation is unclear, scrutinizing only the power output will not improve the accuracy of your judgments. To correctly interpret power generation simulations, it is essential to check the location, period, format, and correction methods of the solar radiation data and to understand the background behind the figures.

Criterion 4: Prevent underestimation and overestimation by examining the breakdown of loss rates

In power generation simulations, the expected actual power output is sometimes calculated by taking the theoretically obtainable generation and accounting for various losses. The loss rates used here are an important item that greatly affects the results. If the loss rate is estimated to be large, the power generation will be lower; if it is estimated to be small, the power generation will be higher. Therefore, when loss rates are presented only as a single aggregated figure, it is necessary to check their breakdown.

Losses to be considered in solar power generation include reduced output due to temperature rise, conversion losses in power conditioners (inverters), wiring losses, soiling of the panel surface, effects of snow or fallen leaves, shading losses, degradation over time, and equipment downtime or output curtailment. These vary depending on site conditions. Even when treating a loss rate as a fixed value, it is important to confirm what kind of site that value assumes.

Temperature loss is an item that is easy to overlook. While solar panels tend to generate more power with stronger solar irradiance, their output decreases as panel temperature rises. Even in summer, when solar radiation is high, generation may not increase as much as expected due to ambient temperature and panel temperature effects. When reviewing simulation results, check whether temperature effects, not just solar irradiance, are reflected.

Losses caused by dirt and deposits also vary by site. Typical residential roofs, factory roofs, areas around farmland, roadsides, coastal areas, and snowy regions experience different patterns of soiling and types of adhered materials. The effects of dust, yellow sand, bird droppings, fallen leaves, salt, and snow can be difficult to represent with simple uniform conditions. Long-term power generation also changes depending on whether cleaning and inspection operations are carried out.

Wiring losses and conversion losses are related to the design and equipment configuration. If wiring distances are long, losses can become significant depending on the design conditions. The efficiency of the power conditioner does not always operate at its maximum. Efficiency varies with input voltage, load conditions, and solar irradiance. Confirming what efficiency the simulation assumes makes it easier to avoid misreading the power output.

Handling degradation over time is also important. The power generation in the first year is not the same as that several years or a decade later. Confirm whether the simulation results are estimates for the first year, long-term averages, or values that account for degradation over a given period. If you base long-term planning only on first-year generation, you may overestimate future output.

When evaluating loss rates, it is important not to judge solely by the numbers. Rather than simply viewing a low loss rate as good and a high one as bad, check whether it fits the site conditions. If the assumptions about losses are reasonable given the roof shape, surrounding environment, weather conditions, maintenance plan, and installation method, the simulation results are more trustworthy. Conversely, if a high power output is shown without a clear breakdown, you should read it cautiously.

Criterion 5: Assess how well shadows and the surrounding environment are reflected

One of the factors that often leads to discrepancies in solar power generation calculations is shading. Shading may occur only during certain times of day, and its extent can change with the seasons. Causes of shading vary by site and include nearby buildings, trees, utility poles, signs, mountains, rooftop equipment, railings, and lightning protection equipment. When interpreting simulation results, it is important to check to what extent shading has been accounted for.

The effect of shadows cannot be judged solely by the "area that is shaded." Because the sun's position changes with the season and time of day, the way shadows fall from the same obstacle differs between summer and winter, and between morning and evening. In winter, the sun's altitude is lower, so shadows from distant obstacles tend to stretch farther. Although solar generation is relatively small in the morning and evening, shadows can be meaningful for self-consumption planning. Shadows that look minor in the annual total can still affect operations during specific times of day.

Some simulations treat shading simply as a loss rate. While this method is convenient for rough estimates, it may not capture the timing of shading or seasonal variations in detail. If you want to examine this more closely, check to what extent the location of shadows, the time of day, and seasonal differences are taken into account. This is especially important in urban areas with nearby buildings or in locations where trees may grow, because shading assessment can significantly affect expected power generation.

For rooftop installations, obstacles on the roof must also be taken into account. Even small protrusions or pieces of equipment can affect power generation depending on panel placement and circuit configuration. In actual construction, maintenance spaces and safety clearances are also required, so the area shown as available on drawings may not be directly usable for power generation. It is important to confirm that simulation results are based on the actual layout.

For ground-mounted installations, shadows cast between rows of panels should also be checked. Depending on the tilt angle and row spacing, shadows from the front rows may fall on the rear rows during winter or in the morning and evening. Packing many panels into a limited site increases installed capacity, but can be disadvantageous in terms of shading and maintainability. In power generation simulations, you need to check whether losses due to layout are considered, not just the result of increasing capacity.

The surrounding environment is not necessarily fixed at the time of installation. Changes can occur, such as new buildings being erected nearby, trees growing, or surrounding land use changing. Simulations are typically based on the conditions at the time of calculation, so they cannot fully capture future environmental changes. Precisely because equipment is to be used over the long term, it is desirable to treat possible future changes as practical items to verify, not just the current shadows.

Verifying shadows and the surrounding environment is the process of anchoring the power generation figures to the actual site. No matter how well the calculation formulas are prepared, if on-site obstacles are overlooked, the results will diverge from reality. When reading power generation simulations, it is important to compare them with site photos, layout drawings, orientation, and surrounding conditions, and to confirm that shading has been handled adequately.

Criterion 6 Read the results in a form that can be compared with actual performance values

Power generation simulations are useful not only before installation but also after operation. However, to compare them with actual results after operation, the simulation outputs need to be presented in a form that makes comparison easy. Annual energy production alone makes it difficult to identify where differences from actual performance arise. It is important to make the results readable in units suited to the purpose, such as by month, by day, or by time of day.

When comparing actual values with simulations, first confirm that you are comparing under the same conditions. Simulations assume fixed weather conditions, while actual values are affected by the weather in that year. A year with many sunny days and a year with a lot of rain will result in different power generation from the same equipment. Therefore, it is not appropriate to immediately conclude equipment failure just because actual results fall below the simulation. You need to check weather differences, downtime, output curtailment, snow accumulation, soiling, inspection history, and so on.

Monthly comparisons are useful for narrowing down causes. Even if there appears to be little difference over the year, a specific month may show lower actual performance. In such cases, consider factors such as adverse weather, snowfall, soiling after typhoons, equipment outages, or seasonal changes in shading. Conversely, if low performance continues over several months, you should check for deviations in input conditions, equipment efficiency, wiring, panel faults, or problems with measurement methods.

In performance comparisons, the measurement location of power generation is also important. The DC generation on the panel side, the AC generation after passing through the power conditioner, and the surplus electricity remaining after the facility’s consumption all represent different figures. If you do not align which measurement point the simulation’s generation refers to with where the actual measurements were taken, you cannot make a correct comparison. When reading power generation calculations, you need to make the differences in measurement points clear.

Also, actual values may include missing data or measurement errors. If there are communication failures or instrument outages, generation may actually be occurring even though the recorded output appears low. Conversely, shifts in aggregation periods can make monthly figures not directly comparable. When comparing actual performance with simulations, verify the aggregation period, measurement units, and whether any data are missing.

To make power generation simulations useful for operations management, it is important to record the results from the outset in a format that makes comparison easy. Rather than leaving only annual values in the documentation, recording monthly estimated values, calculation conditions, loss rates, equipment capacity, installation conditions, and the update date will make post-operation verification easier. When conducting root-cause analysis later, if the original assumptions are clear, you can calmly assess the difference from actual performance.

Simulations serve not only as decision-making material before installation but also as reference values during operation. By reviewing them in a comparable format, when you feel that power generation is low you can verify it based on conditions rather than on intuition. This reduces unnecessary anxiety and misjudgments, and makes it easier to prioritize inspections and improvements.

Criterion 7: Treat numbers used for judgments and reference values separately

Power generation simulations involve a large number of figures. The more items there are—annual generation, monthly generation, generation per unit of installed capacity, loss rates, assumed capacity factor, generation after degradation, shading losses, generation after conversion, etc.—the harder it becomes to know which numbers to use for decision-making. In practice, it is important not to treat all figures with equal weight, but to separate the numbers used for decisions from those kept as reference values.

Numbers used for decisions on adoption or design should be based on assumptions that are clear and can be reconfirmed. For example, when using annual power generation as a basis for judgment, installed capacity, installation conditions, solar irradiance, loss rates, and degradation conditions must be clearly specified. Power generation figures presented without clarification of these factors may be treated as reference values but are insufficient as practical decision-making criteria.

On the other hand, during the initial assessment stage, rough estimates can also be useful. When comparing potential installation sites or getting a general sense of scale, simple power generation calculations can be enough to indicate the right direction. However, if you use the figures from that stage as-is as the basis for detailed design or long-term planning, discrepancies are likely to emerge later. Treat rough estimates as rough estimates, and when moving on to detailed decisions, review the assumptions and conditions.

Also, simulation results are not a single correct answer. Small changes to the input conditions will change the outcomes. By changing the loss rate, using different solar irradiance data, adding shading conditions, or reflecting degradation rates, you can obtain multiple results depending on the assumptions. Therefore, it is important to view the estimated power generation not as a single fixed value but as an expected value that varies according to the conditions.

In practice, results are sometimes considered separately for standard conditions, for a conservative (safety-oriented) case, and for favorable conditions. Providing such a range makes it easier to clarify expectations and risks. However, even when presenting a range, be explicit about which condition corresponds to which result. Listing multiple numbers with conditions mixed together only makes decision-making more ambiguous.

When deciding on the figures to use in decision-making, it is also important to align understanding among stakeholders. If design, construction, operations, and management personnel are each looking at different figures, expectations for power generation will diverge. By sharing whether the figures shown in the documents refer to first-year generation, long-term averages, post-degradation values, or include losses, you can prevent misunderstandings later.

Reading power generation simulations correctly is not just about scrutinizing the numbers. It means organizing which figures to use for decision-making and which to treat as reference information. Numbers used for judgment require clear assumptions, consistency with on-site conditions, and comparability. Reference values should be positioned as inputs for initial assessment or for grasping trends. Making this distinction makes it easier to translate simulation results into practical operations.

Summary Power generation simulations can be used in practice by reading the assumptions

To correctly interpret the results of power generation simulations, it is important not to focus solely on the magnitude of annual generation. By checking monthly variations, input conditions, solar irradiance data, loss rates, shading and the surrounding environment, methods for comparing with actual performance, and the role of the figures used for decision-making, the simulation results become a more practical resource.

The calculation of solar power generation cannot be completed by simple multiplication alone. Even with the same system capacity, power output varies depending on installation location, orientation, tilt angle, weather conditions, shading, temperature, equipment configuration, and operation and maintenance. That is why, when viewing simulation results, you need to check the conditions behind the numbers and interpret them in light of the actual site conditions.

For practitioners, it is important neither to over-rely on simulation results nor to be unduly skeptical. When used with an understanding of their underlying assumptions, simulations provide valuable information that can assist with decisions on adoption, design verification, operations management, and performance evaluation. Conversely, using them without checking the assumptions can lead to mismatches between expected and actual outcomes and to insufficient explanations.

Even if you feel that power generation is lower than expected, it is important first to align the simulation conditions with the actual conditions and verify them. By isolating whether the cause is different weather, shading effects, equipment downtime, soiling or snow accumulation, or differences in measurement methods, you can take appropriate countermeasures. The ability to interpret the results of power generation calculations is useful not only before installation but also for improving operations afterward.

When reviewing power generation simulations, it is important to carefully check not only the final generation figures but also the consistency between the calculation conditions and the site conditions. Power generation simulations do not definitively predict future output; they should be used as a decision-making aid while confirming the underlying assumptions. Organizing the context behind the numbers makes them easier to use both for pre-installation comparisons and for verifying actual performance after operation.