Five checkpoints to avoid failure in photovoltaic generation simulations

Photovoltaic generation simulation is an indispensable task for planning, designing, evaluating profitability, internal explanations, and forming consensus with stakeholders for solar power systems. By forecasting generation in advance, it becomes easier to organize installation capacity, panel layout, azimuth, tilt angle, shadow impacts, loss conditions, and annual generation trends. On the other hand, because simulation results are highly dependent on input conditions, incorrect assumptions can yield figures that diverge significantly from actual generation.

Many practitioners who search for "solar power generation simulation" are not only seeking calculation methods but also want to know which conditions to check to prevent failures and how detailed the inputs need to be to produce results useful in practice. In particular, for projects with complex site conditions, constrained roof shapes, or ground-mounted installations affected by surrounding features, small differences in input values can greatly affect annual and monthly generation.

This article organizes five points to check from a practical perspective to avoid failures in photovoltaic generation simulations. Rather than taking simulation numbers at face value, we examine them in terms of meteorological data, installation conditions, shadows, losses, and on-site surveying, so they can be used as evidence-based decision-making materials.

Table of Contents

• Simulation results change depending on assumptions

• Checkpoint 1: validity of irradiance and meteorological data

• Checkpoint 2: input accuracy for installation azimuth and tilt angle

• Checkpoint 3: evaluate shadow impacts according to site conditions

• Checkpoint 4: do not underestimate loss conditions

• Checkpoint 5: improve planning accuracy with on-site surveying and coordinate information

• How to use simulation results in practice

• Summary

Simulation results change depending on assumptions

Photovoltaic generation simulation estimates how much solar irradiance strikes panels, how much of that is converted to electricity, and how much usable electrical energy remains after various losses. Typically, inputs include installation location, irradiance, azimuth, tilt angle, installed capacity, equipment characteristics, surrounding shadows, temperature effects, wiring and conversion losses, etc., to calculate annual and monthly generation.

However, simulation does not determine future generation with certainty. It merely forecasts generation based on certain assumptions. Therefore, if input conditions differ from actual site conditions, the results will naturally deviate. For example, if a site actually receives building shadows in the afternoon but the calculation assumes no shadows, generation will be overestimated. Conversely, if overly strict loss assumptions are used, generation will be underestimated and may lead to wrong decisions about system installation.

What matters in practice is confirming the assumptions behind the simulation numbers rather than focusing solely on the numbers themselves. Rather than only checking how many kWh will be generated annually, you should verify whether the irradiance data is appropriate, whether the installation angles are close to measured values, whether shadow conditions reflect the site, and whether losses have been properly accounted for.

Also, photovoltaic simulations are used at multiple stages: initial planning, detailed design, internal approval, pre-construction checks, and post-operation performance comparison. Early-stage planning may only require rough estimates, but stages that support investment decisions or design finalization demand higher-accuracy input settings. The required accuracy varies with the simulation’s purpose.

A common failure is carrying over assumptions used in an initial rough estimate into detailed analysis without revision. Even if early-stage calculations used map-based positions and standard irradiance data, final decisions require reflecting on-site obstructions, actual roof slopes, surrounding buildings, trees, terrain, equipment layout, and maintenance space. Simulations are convenient, and results can be produced even with vague inputs, so it is important to guard against the numbers taking on a life of their own.

Therefore, to avoid failure in photovoltaic generation simulations, it is important to clearly distinguish which conditions are treated as fixed values and which as assumptions. If many conditions are not yet fixed, it is more practical to compare multiple scenarios and view generation as a range rather than fixing on a single figure.

Checkpoint 1: validity of irradiance and meteorological data

The first thing to confirm in a photovoltaic generation simulation is the validity of irradiance and meteorological data. Since photovoltaics convert irradiance to electricity, irradiance conditions form the foundation of generation forecasts. If the installation site’s latitude and longitude, regional characteristics, seasonal weather trends, and temperature conditions are not appropriate, no amount of fine-tuning of installation parameters will sufficiently improve result reliability.

Irradiance data may be based on long-term regional averages, interpolated from nearby observation stations, or derived from satellite data. In practice, it is important to confirm which type of data is being used. In mountainous areas, coastal areas, snowy regions, fog-prone areas, or regions affected by localized cloud cover, averages from nearby stations may not adequately represent local conditions.

Temperature also affects generation. While strong irradiance generally increases generation, higher panel temperatures reduce conversion efficiency. Thus, even in regions with high summer irradiance, failing to account for temperature conditions can lead to overestimated generation. Conversely, in winter, while sunlight hours are shorter, lower temperatures can relatively improve conversion efficiency. When examining monthly trends, it is important to check both irradiance and temperature.

Additionally, check whether the monthly peaks and troughs align with regional characteristics, not just the annual total. Even if the annual total seems plausible, an unnatural monthly breakdown may indicate problems in data settings, azimuth, tilt angle, or shadow conditions. For instance, if a snowy or low-sun-angle region shows excessively high winter generation, site conditions may not be properly reflected.

When checking irradiance data, consider the simulation’s purpose. For internal preliminary studies, standard regional data may suffice for a rough estimate. However, when judging profitability or system scale, use conditions closer to the actual site. Selection of meteorological data should not be overlooked, especially for projects where small differences in generation affect project viability.

Another important point is understanding the difference between single-year weather conditions and long-term averages. In operation, one year may be unusually sunny and produce more generation, while another may have extended rain or cloud cover and produce less. When comparing simulation results with actual performance, it is risky to judge the simulation as right or wrong based only on first-year performance. Distinguish whether the prediction is based on long-term averages or on a particular year’s weather.

To avoid failure in photovoltaic simulations, do not assume that automatically loaded irradiance data is necessarily correct. Simply checking whether the data is close to the installation point, matches regional characteristics, and shows no odd monthly trends can greatly improve forecast reliability.

Checkpoint 2: input accuracy for installation azimuth and tilt angle

Next in importance are the installation azimuth and tilt angle of the panels. In photovoltaics, the direction the panel faces and the angle at which it is installed determine the amount of irradiance it receives. Azimuth and tilt may seem like simple inputs, but in practice they are prone to errors and can greatly influence generation forecasts.

Azimuth refers to the direction the panel surface faces. Generally, orientations closer to south tend to secure higher annual generation, but an ideal south-facing arrangement is not always possible. Roof shape, site layout, building orientation, surrounding obstructions, racking layout, constructability, and maintenance flow can result in east, west, southeast, or southwest orientations.

A common input error for azimuth is mistaking the top of a drawing for north or confusing true north on site with the reference direction on a plan. On architectural drawings or site plans, the top of the page is not always north. A quick on-site azimuth check may still leave an offset of several to more than ten degrees. Because small azimuth changes can alter monthly generation balance, accurate azimuth verification is necessary at the design stage.

Tilt angle is equally important. Changes in tilt affect seasonal irradiance reception: a shallow tilt favors summer irradiance, while a steep tilt may better capture low winter sun. However, the optimal angle depends on region and objectives: whether annual generation or winter generation is prioritized, whether roof constraints apply, or whether ground-mounted racking allows adjustment.

For retrofitting existing building roofs, confirm that the slope on drawings matches actual roof slope. Older buildings may have drawings that do not reflect current conditions, and renovations or additions may have altered roof shapes. Simulating without on-site measurements and relying solely on old documents can produce generation forecasts that deviate from actual installation angles.

For ground-mounted systems, row spacing and front-to-back shading in addition to tilt matter. Increasing tilt may benefit winter irradiance acquisition but can increase shading from front rows onto rear rows. Decisions should not be based solely on power efficiency; consider land-use efficiency, shading, constructability, and maintainability.

When verifying azimuth and tilt in simulations, clearly state which documents the input values are based on: drawing values, on-site measurements, or assumptions. The way results are treated differs accordingly. If accurate surveying has not yet been performed, check sensitivity across multiple azimuths and tilt angles to understand how generation varies and reduce rework later.

Checkpoint 3: evaluate shadow impacts according to site conditions

Shadows are often overlooked in photovoltaic generation simulations. Even with appropriate irradiance and installation angles, actual shadows on panels reduce generation. Shadows may seem like a minor, temporary issue, but depending on the time of occurrence and season, they can cause large differences in annual generation.

Causes of shadows include surrounding buildings, utility poles, trees, signs, fences, rooftop equipment, chimneys, railings, adjacent rows of solar panels, and terrain undulations. On roofs, rooftop protrusions and shadows from adjacent blocks are common issues; on ground mounts, surrounding trees, slopes, hills, and inter-rack shading are frequent concerns. In winter, when sun angles are low, obstacles that were not problematic in summer can cast long shadows.

When checking shadows, do not judge based only on the time of your site visit. For example, if a midday visit shows few shadows, other buildings or trees may cast significant shadows in the morning or evening. If you visit in summer, you may overlook low-sun-angle winter shadows. Simulations should consider the sun’s movement throughout the year and check shadow effects by season and time of day.

Shadow impacts cannot be assessed simply as “present or absent.” It is important to know where, at what times, and how frequently shadows occur. The effect on generation differs greatly between a short-duration, partial shadow and a large-area shadow lasting many hours daily. Panel and circuit configurations can also cause a small shadowed area to reduce generation more than anticipated.

Existing drawings or maps may not capture small obstacles that cause shadows. Surrounding trees grow, and adjacent properties or temporary structures can influence shading. Rooftop equipment positions and heights, railing shapes, and heights of adjacent structures may not be fully reflected in drawings. To accurately reflect shadow conditions, combine on-site verification with surveying information.

In simulation, input the height, position, and distance of obstacles correctly. Even a shift of tens of centimeters (several in) to several meters (several ft) in an obstacle’s position can change the time and area affected by its shadow. Especially for installations on limited roof areas or tight sites, shadow input accuracy directly affects the reliability of generation forecasts.

Shadow assessment also leads to layout revisions, not just loss estimation. For heavily shaded areas, avoid placing panels, adjust row spacing, disperse placements, review tilt angles, and secure maintenance access. Use simulation results as design decision-making material rather than treating shadows merely as a loss item.

To avoid failure in photovoltaic simulations, do not underestimate shadow conditions. Rather than deciding "no shadow" based on a single impression at the site, confirm shadows across seasons, times of day, surrounding obstacles, and potential future changes to achieve a prediction closer to reality.

Checkpoint 4: do not underestimate loss conditions

In photovoltaic simulations, panels receiving irradiance do not produce ideal power without losses. In reality, losses arise from temperature rise, soiling, wiring, conversion, equipment characteristics, aging, snow, mismatch, downtime, and more. If these loss conditions are not properly accounted for, simulation results tend to be optimistic.

First check temperature-related losses. Panels generate more under strong irradiance but conversion efficiency decreases as panel temperature rises. Panels mounted close to the roof behave differently from those on well-ventilated racks. Consider not only ambient temperature but also installation method and ventilation conditions.

Next, consider soiling losses. Dust, pollen, bird droppings, fallen leaves, exhaust, sea spray, and dust from nearby farmland adhere to panel surfaces and impede irradiance transmission. Rain can wash them away, but shallow-roof slopes or environments prone to soiling can reduce generation more than expected. Soiling varies greatly with surrounding environment, so determine loss rates with site characteristics in mind rather than relying solely on standard loss percentages.

Do not overlook wiring and conversion losses. Generated DC power goes through wiring and conversion equipment before becoming usable power, and losses occur in that process. Losses are more critical when wiring distances are long, equipment layout is constrained, or capacity design leaves little margin. Standard values may be used in initial design, but review wiring plans and equipment configurations in detailed design.

Also account for degradation over time. PV systems are used over long periods, so generation after several years is important in addition to first-year generation. Components’ performance changes with time and will not maintain initial output indefinitely. For long-term financials and operation planning, include expected degradation in simulations.

In snowy regions, snow losses are a major point. Snow remaining on panels reduces irradiance reception and generation. Effects depend on snowfall frequency, whether the tilt promotes snow shedding, ambient temperatures, irradiance conditions, and whether snow removal is performed. Set conditions appropriate to regional characteristics to avoid overestimating winter generation.

A common mistake in loss settings is using all standard values. While standard figures may suit preliminary studies, they may not be appropriate for atypical site environments or projects requiring high generation accuracy. Consider surrounding environment, installation method, operation regime, and maintenance frequency to judge whether loss assumptions are realistic.

Underestimating losses can lead to "it generates less than expected" after installation. Optimistic simulation assumptions may produce attractive figures for internal presentations and investment decisions, but cause large discrepancies with operational performance. Conversely, overly pessimistic assumptions may cause undue caution and forgo viable projects. The important thing is to set evidence-based loss assumptions, neither optimistic nor pessimistic without basis.

Checkpoint 5: improve planning accuracy with on-site surveying and coordinate information

To bring photovoltaic simulations to a practical level of accuracy, on-site surveying and use of coordinate information are important. No matter how carefully you consider irradiance, azimuth, tilt, shadows, and losses, simulation reliability is limited if the positional relationships of the site, roof, and obstacles remain vague.

For ground-mounted photovoltaic systems in particular, many factors affect generation and layout: site boundaries, terrain elevation differences, slopes, existing structures, surrounding trees, access paths, drainage facilities, and maintenance spaces. Judging from site maps or aerial photos alone may fail to capture actual terrain undulations and obstacle heights. Elevation changes influence row-to-row shading, feasible installation areas, and the need for earthworks.

On roofs, surveying is also important. If you do not correctly grasp roof surface dimensions, slopes, azimuths, steps, equipment, railings, lightning protection, inspection routes, and roof material conditions, the number of panels that can actually be installed and the layout may change. Even if drawings show sufficient area, in reality obstacles and maintenance space can reduce usable area.

Coordinate information becomes important to link layout planning with simulation conditions. If obstacle positions and heights, panel row positions, site boundaries, and building orientations are organized as coordinates, shadow analysis and layout precision improve. Conversely, vague location information leads to mismatches between simulated obstacles and real obstacles, making shadow evaluation inaccurate.

On-site surveying also yields information useful for construction planning and maintenance. Confirming installation positions, racking layout, access routes, equipment locations, delivery paths, and maintenance routing are practical elements inseparable from generation simulation. Even if the generation-only approach is maximized, impractical layouts for construction or inspection will create operational problems.

Photovoltaic simulation may seem like a desk exercise, but it heavily depends on the quality of site information. By accurately measuring the site and grasping azimuths, heights, distances, and obstacle positions, simulation assumptions become concrete. As a result, explanations to stakeholders become easier and the risk of design changes and rework decreases.

In practice, it is realistic to perform preliminary simulations with approximate information and then update conditions as on-site surveying is reflected. It is not necessary to measure everything at high precision from the start, but as decision importance increases, recalculating based on measured data is desirable. Especially for projects where shading is significant, terrain is complex, or feasible installation area is limited, the accuracy of site information will determine the results.

How to use simulation results in practice

Simulation outputs provide more than just annual generation. You can check monthly generation, generation efficiency relative to irradiance, loss breakdowns, comparisons by installation conditions, shadow impacts, and generation relative to system capacity. In practice, review these comprehensively to judge plan validity.

First, annual generation is the clearest indicator. However, judging solely on annual totals can miss seasonal variations or significant declines in specific months. By viewing monthly generation, check whether winter drops are excessive, whether summer temperature losses are too large, or whether shadows concentrate in certain seasons. Even with equal annual totals, different monthly distributions affect power usage planning and operational decisions.

Second, comparing conditions is important. Compare multiple patterns—slightly different azimuths, varied tilt angles, alternative panel layouts, or avoiding shaded areas—to evaluate the balance between generation and constructability. Simulation is a tool not just for producing one answer, but for comparing multiple options to make rational decisions.

This article does not present multiple configuration proposals; rather, it explains the practical importance of condition comparisons. In real projects, before narrowing to a final plan, examine several conditions and comprehensively consider generation, number of panels, maintainability, shading impacts, and construction difficulty. Choose a layout suited for long-term operation rather than simply maximizing generation.

Also, do not expect excessive accuracy from simulations. Generation forecasts cannot perfectly predict future weather or operational conditions. Actual generation fluctuates with weather, soiling, equipment condition, inspection status, and changes in the surrounding environment. Thus, treat simulation outputs as baseline values for decision-making, not as definitive numbers.

After operations begin, comparing simulated and actual generation helps monitor system condition. If generation is significantly lower than expected, separate whether it is due to weather, changes in shading, soiling, or equipment issues. If you preserve the simulation assumptions, it becomes easier to analyze causes when comparing results.

Practitioners should avoid relying on simulation results alone. Combine them with on-site surveys, drawings, survey data, construction constraints, and maintenance plans to clarify result meaning. Present numbers together with assumptions and verified items to aid internal and external consensus building.

Summary

To avoid failure in photovoltaic generation simulations, do not chase numbers alone; carefully confirm the assumptions supporting those numbers. By verifying that irradiance and meteorological data match the site, that azimuth and tilt are correctly input, that shadow impacts are assessed by season and time of day, that loss conditions are not underestimated, and that on-site surveying and coordinate information are used to improve planning accuracy, you can significantly enhance simulation reliability.

Photovoltaic simulation is not only for judging whether to install equipment. It is a practical foundation to confirm design validity, explain to stakeholders, reduce pre-construction rework, and support post-operation performance comparisons. Therefore, do not stop at initial rough estimates; reflect site conditions as planning progresses and recompute as necessary.

Conditions such as shadows, azimuth, tilt, site shape, and obstacle positions depend on the accuracy of site information. Many elements cannot be captured from drawings or maps alone, so combining positioning and on-site verification enables simulations that more closely match reality.

If you want to improve planning accuracy for solar power, obtaining precise on-site position information and reflecting it in design and simulation is essential. By using LRTK (iPhone-mounted GNSS high-precision positioning device), you can more easily grasp site conditions and surrounding environments based on high-precision position information obtained on site. Improving positioning accuracy is a meaningful way to move photovoltaic generation simulations beyond desk calculations toward plans that reflect actual site conditions.