Nine Items to Check Before a Solar Power Generation Simulation

Solar power generation simulations are not just a task to produce numbers for generated power. They are important decision-making materials to assess the validity of equipment planning, profitability, design conditions, construction conditions, and operational risks in advance. In practice, if decisions are made by looking only at the numerical results of simulations, actual generation after installation may fall below expectations, cash flow plans may deviate, and explanations to stakeholders may become difficult.

To improve simulation accuracy, it is essential not only to use advanced calculation tools but also to perform checks before inputting data. If input conditions remain ambiguous, no matter how detailed the calculations are, the results may diverge from actual site conditions. This is because solar power generation is determined by a stack of many factors such as irradiance, installation angle, surrounding shading, equipment specifications, loss conditions, degradation, and operational conditions.

This article organizes nine items that practitioners searching for information on "solar power generation simulation" should check before running simulations. It explains these as a way of thinking useful in various situations such as early-stage project feasibility, rooftop installations, ground-mounted projects, self-consumption systems, and reassessments of existing equipment.

Table of Contents

• Confirm the purpose of the simulation

• Confirm the scope and evaluation period

• Confirm the location information and terrain conditions of the installation site

• Confirm assumptions for irradiance and weather conditions

• Confirm panel capacity and layout conditions

• Confirm azimuth and tilt angle settings

• Confirm shading impacts and surrounding obstacles

• Confirm loss conditions and degradation rates

• Organize how to use output results and methods for site verification

Confirm the purpose of the simulation

Before starting a solar power generation simulation, the first thing to confirm is the purpose: why are you calculating generation output? Although generation numbers may appear similar at first glance, required accuracy, input conditions, and indicators to be evaluated vary depending on the purpose. Whether you want to check profitability, determine equipment capacity, compare design options, or verify the poor performance of existing equipment, the way you build the simulation differs significantly.

For example, at the early stage of a business plan, the main goal is to grasp a rough estimate of annual generation to get a sense of the investment direction. At this stage, it is important to confirm a broad revenue-and-expenditure picture based on the candidate site's irradiance conditions, installable area, rough equipment capacity, and major loss factors. On the other hand, when design progresses, it is necessary to reflect panel layout, tilt, azimuth, surrounding shading, equipment specifications, and wiring losses in greater detail to calculate generation closer to actual design conditions.

For self-consumption solar systems, not only the simple annual generation but also the hourly generation and how it overlaps with electricity usage are important. Facilities with high daytime demand can make effective onsite use of generated power, but if usage varies greatly on holidays or by season, handling of surplus power also needs to be checked. In such cases, annual totals alone are insufficient; monthly, daily, and hourly perspectives are necessary.

When simulations are used to explain results to banks, investors, internal approval bodies, or clients, it is important to be able to explain the basis of the simulation results. Organizing which weather data were used, which losses were assumed, and how conservative the conditions were increases the credibility of the results. Rather than choosing conditions that simply make generation look larger, it is crucial in practice to use realistic and explainable assumptions.

If you start simulations with an unclear purpose, questions are likely to arise later such as "Can this number be used in revenue calculations?", "Is this sufficient as a basis for design comparison?", or "To what extent are site conditions reflected?". Clarifying at the outset who will decide what and what level of accuracy is required is the starting point for a high-accuracy solar power generation simulation.

Confirm the scope and evaluation period

The next item to check is the simulation’s scope and evaluation period. In solar power generation simulations, the meaning of results changes depending on what is included in the calculation target. If the target scope is ambiguous, different people may see different numbers even for the same power plant.

First, confirm whether the target is the entire generation facility or only a portion of it. For ground-mounted plants, you may evaluate the layout of the whole site or examine sections separately where earthworks or shading conditions differ. For rooftop installations, be clear whether the entire building is the target or only specific roof surfaces. If a roof has multiple orientations or slopes, the generation characteristics vary by surface, and evaluating them together may misrepresent reality.

The evaluation period is also important. Annual generation is commonly used, but in practice you may need multiple views such as monthly generation, seasonal generation, first-year generation, long-term average generation, and cumulative generation over equipment lifetime. For profitability assessments in particular, long-term generation including annual degradation must be considered, not just first-year output. If first-year generation looks high but degradation rates or maintenance assumptions are optimistic, long-term cash flow plans will be overly optimistic.

When setting the evaluation period, align it with the project plan’s timeframe. Because generation equipment operates over the long term, judging by short-term generation alone may fail to sufficiently account for maintenance costs, equipment replacements, output decline, regulatory changes, or shifts in usage. Conversely, doing overly detailed long-term calculations in the initial feasibility stage when assumptions are not yet firm may lead to numbers that take on a life of their own. It is necessary to change the calculation granularity by project stage: rough estimate, basic design, detailed design, and operational evaluation.

Also confirm whether the evaluation target is the electrical energy at the generation side or the energy actually available for use. The power produced by generation equipment does not always match the power usable at the grid interconnection point or on the demand side due to losses and control. For self-consumption systems, it is important to separate the portion of generated power that can actually be used, the surplus, and the controlled portion. Clarifying the target scope allows you to correctly connect simulation results to revenue calculations and design decisions.

Confirm the location information and terrain conditions of the installation site

Location information of the installation site is extremely important in solar power generation simulations. Irradiance, solar altitude, azimuth, shading behavior, and weather conditions vary by location, and if location information is ambiguous, accurate calculations are impossible. There is a difference in calculation reliability between roughly specifying a site by address and precisely capturing the actual installation area by coordinates.

In particular, for ground-mounted solar plants, elevation differences and slope directions may vary even within a site. Even within the same address, north-facing slopes, south-facing slopes, valley terrain, ridge areas, and locations with nearby trees will have different irradiance and shading impacts. Before simulation, it is important to capture as accurately as possible the candidate site's latitude and longitude, elevation, terrain undulation, site boundaries, and installable area.

For rooftop installations, you also need to confirm the building location and roof surface shapes. Building drawings alone can miss rooftop equipment, handrails, parapets, adjacent buildings, rooftop structures, and HVAC equipment. You must confirm how much installable area actually exists on the roof and how many panels can be placed while securing inspection paths and maintenance spaces; otherwise, generation assumptions may be overestimated.

Checking terrain conditions requires more than just looking at the planar area. On sloped ground, the post-development ground surface, mounting structure height, row spacing, and drainage planning also affect generation. If the ground surface is irregular, panel row heights and angles may vary locally, affecting inter-row shading and maintainability. Even if a simulation treats the site as an ideal plane, the real site may not allow the planned arrangement.

Misidentification of site boundaries or installable areas is also a practical risk. If the entire candidate site is assumed to be installable but in reality slopes, access paths, drainage structures, setbacks from neighboring land, maintenance spaces, and electrical equipment zones must be preserved, installable panel area can be significantly reduced. This difference directly affects equipment capacity and annual generation. Before simulating, organize site location information and terrain conditions as accurately as possible to minimize differences between desk calculations and field reality.

Confirm assumptions for irradiance and weather conditions

One of the most fundamental factors affecting solar power generation is irradiance. Simulations calculate generation based on the assumption of how much sunlight reaches the installation site. Therefore, you cannot judge the validity of results without confirming which irradiance data and weather condition assumptions were used.

Irradiance data come in various granularities such as annual averages, monthly averages, and hourly data. At the rough estimate stage, monthly or annual averages may suffice for a broad judgment, but to check shading impacts, self-consumption rates, peak outputs, and seasonal variations, finer time-resolution data are required. Especially for self-consumption systems, because the overlap between generation time and electricity usage time is critical, annual totals alone may be insufficient.

Weather conditions such as ambient temperature, wind speed, snowfall, rainfall, humidity, and cloudiness also affect generation. Solar panels lose output as temperature rises, so regions with high irradiance can still have reduced generation efficiency due to temperature effects. High summer irradiance does not directly translate to maximum generation efficiency. Conversely, when temperatures are low and irradiance is sufficient, generation can be relatively efficient.

In snowy regions, it is important to account for generation stoppages or reductions caused by snow. When snow covers panel surfaces, generation can drop significantly. Whether snow naturally slides off, accumulates nearby, or is cleared operationally will change outcomes. Judging by annual irradiance alone may underestimate winter generation declines.

Weather data are typically based on past observations and statistics, but actual yearly weather varies. One year may have many sunny hours, another may have more cloudy or rainy days. Therefore, simulation results should be treated as forecasts based on certain assumptions, not as guarantees of future generation. In practice, checking not only a standard case but also conservative and upside/downside scenarios helps judge the safety of revenue plans.

Irradiance and weather assumptions form the foundation of simulation results. If they are overestimated, generation will be overestimated; if underestimated, the plan may be too conservative. Confirming which regional data to use, which period’s trends to reflect, and how much variability to assume leads to simulations that stand up in practice.

Confirm panel capacity and layout conditions

Checking panel capacity and layout conditions is also indispensable in solar power generation simulations. Although generation is strongly influenced by equipment capacity, it is not enough to simply fill every available area with panels. In practice, you must consider panel dimensions, installation angle, row spacing, maintenance pathways, mounting conditions, electrical equipment placement, and building or land constraints.

First check whether the assumed panel capacity is realistically installable. On paper it may seem possible to install a large capacity, but actual restrictions such as clearance distances, inspection routes, roof load-bearing capacity, ground conditions, and interference with surrounding equipment can reduce the number of panels. On rooftops especially, complex roof shapes or many existing installations can shrink the installable area compared to theoretical area.

For ground-mounted systems, row spacing is important. If rows are too close, shadows from the front row will fall on the rear rows in winter or at dawn and dusk, reducing generation. Widening row spacing reduces shading but decreases the number of panels that can be installed on the same site. In other words, there is a trade-off between increasing equipment capacity and suppressing shading losses. Before simulation, consider not only a simple maximum capacity plan but also layout options that account for actual generation and maintainability.

Layout conditions should also consider electrical groupings. Treating surfaces with different orientations or tilts as if they have the same conditions can fail to reflect differences in generation characteristics. Evaluating by roof surface, slope, and shading condition produces a simulation closer to reality. For projects spanning multiple roof surfaces, check not only summed annual generation for south-, east-, and west-facing surfaces, but also hourly generation patterns.

A larger capacity is not always advantageous. Optimal capacity depends on how you size conversion equipment relative to generation capacity, how you handle output control, and the relationship with power consumption. For self-consumption systems, installing excessive capacity can increase surplus power and reduce expected economic benefits. Conversely, undersizing capacity may fail to make full use of usable roof or land.

Before simulation, check panel capacity, number of panels, layout drawings, row spacing, pathways, maintenance space, and electrical equipment zones together. Generation numbers only make sense when based on a layout that can actually be constructed. Simulating an ideal layout rather than one reflecting actual site conditions increases later rework.

Confirm azimuth and tilt angle settings

Azimuth and tilt angle settings are often overlooked in solar power generation simulations. The direction a panel faces and the angle at which it is installed change the irradiance it receives. While orientations and angles that receive sunlight efficiently are generally preferred, actual sites face constraints such as roof shape, site geometry, mounting conditions, wind loads, landscape considerations, and constructability.

Azimuth indicates the direction panels face. The closer to south-facing, the more annual generation tends to be obtained, but east- and west-facing orientations also have practical meaning. East-facing arrays generate more in the morning and west-facing more in the afternoon. For self-consumption facilities, matching generation timing to the facility’s usage time can matter; facilities using more power in the afternoon may benefit from westward-biased generation characteristics.

Tilt angle indicates the panel surface angle. Tilt affects seasonal irradiance reception. Increasing tilt helps capture lower winter sun but requires consideration of wind effects, mounting structure, and inter-row shading. Lower tilt makes rooftop or low-mount installations easier but affects how dirt flows off, snow sliding, and generation characteristics.

On rooftops, installations often follow existing roof pitch, so the ideal angle cannot always be freely chosen. Installation methods vary for standing-seam roofs, flat roofs, and sloped roofs; whether you tilt panels using mounts or lay them along the roof changes generation and construction conditions. On flat roofs, adding tilt can improve efficiency, but inter-panel shading, wind loads, and attachment methods must be considered.

For ground-mounted systems, azimuth and tilt can be adjusted to some degree in design, but site shape and earthwork conditions may impose constraints. If a site is narrow and long, you may not be able to orient all rows in the ideal direction. If matching terrain slope, panel angles may vary slightly by location. Failing to reflect such conditions in simulation will cause discrepancies with actual generation.

Azimuth and tilt affect not only generation but also constructability, maintenance, shading, wind, snow, and drainage. Settings that maximize generation alone are not necessarily optimal overall. Before simulation, clarify the range of azimuth and tilt that can be adopted in design and set realistic azimuth and tilt values.

Confirm shading impacts and surrounding obstacles

Shading impacts are particularly important in solar power generation simulations. Because panels generate electricity from sunlight, shadows cast by buildings, trees, utility poles, signs, mountains, rooftop structures, fences, adjacent equipment, and so on reduce generation. Shadows may occur only during certain hours or vary widely by season. If you fail to check surrounding obstacles before simulation, generation may be overestimated.

Shading impact is more than just part of a surface being dark. If part of a panel is shaded, depending on electrical connections, output may drop more than the shaded fraction. Thus, assuming that a small shadow is negligible is risky. Especially at low solar altitudes in the morning and evening, shadows from distant buildings or trees can extend long distances, and shadow extent tends to increase in winter.

On rooftops, rooftop equipment shadows are easy to overlook. HVAC equipment, piping, chimneys, handrails, rooftop structures, lightning protection, and adjacent taller buildings may cast shadows on panels during parts of the day. Items that look small on drawings may still shade panels for some time. It is important to identify potential shading sources using on-site checks, photos, and survey data.

For ground-mounted projects, shadows from surrounding trees and terrain may be an issue. A site that looks sunny before earthworks may experience shading from southern trees or slopes when the season changes and solar altitude lowers. Trees growing in the future can also expand shadow extents. Consider not only the state at installation but also changes in shading conditions during the operational period.

Inter-row shading is also important. Insufficient row spacing allows front rows to shade rear rows. In winter mornings and afternoons when the sun is low, inter-row shadows extend. Packing panels tightly to increase generation capacity can increase shading losses so that despite larger capacity, actual generation falls short. Confirm the balance between equipment capacity and inter-row shading in simulation.

Three-dimensional understanding of the site helps with shading checks. Plan views alone cannot fully capture height differences and the spatial relationship of obstacles. Confirm surrounding buildings, trees, ground elevation, and rooftop equipment heights to assess shading risks realistically. Overlooking shading often leads to generation shortfall, so checking shading before simulation is a high-priority item.

Confirm loss conditions and degradation rates

In solar power generation simulations, it is important to set loss conditions and degradation rates, not just irradiance and equipment capacity. Solar panels do not always produce theoretical maximum output under sunlight. Actual generation is reduced by various factors including temperature rise, soiling, wiring and conversion losses, equipment characteristics, shading, aging, and downtime.

Temperature loss is a representative loss. As panels absorb sunlight, their temperature rises and output decreases above certain temperatures. In summer, while irradiance is high, panel temperature also tends to rise, so you cannot judge generation by irradiance alone. Ventilation conditions differ by installation method, and installations close to roof surfaces may trap heat.

Soiling losses cannot be ignored. Dust, pollen, bird droppings, fallen leaves, exhaust, coastal salt, and industrial dust vary by environment. Rain may wash some away, but low-tilt installations tend to retain dirt. If cleaning frequency and maintenance policy are not considered and soiling losses are set too small, a gap with actual generation is likely.

Wiring and conversion losses should also be confirmed. The DC power generated by panels becomes usable AC power through wiring and conversion equipment, during which losses occur. Losses may increase if cable distances are long, equipment layout is complex, or capacity design is strained. Before simulation, confirm equipment layout and electrical design assumptions and avoid excessively optimistic loss rates.

Aging is indispensable for long-term evaluations. Solar panels gradually lose output over years. Judging by first-year generation alone can overestimate long-term generation. In practice, determine how much degradation to assume annually and how to reflect this in long-term cumulative generation. Degradation rate assumptions vary by equipment specifications, installation environment, and maintenance status.

Downtime and operational losses are also important. Inspections, failures, equipment replacement, output control, grid constraints, disasters, and communication failures mean equipment does not always operate ideally. In simulations, decide in advance how much operational loss to assume. Setting losses too small to make generation look high will create a large gap with actual performance and be difficult to explain later.

Loss conditions and degradation rates determine the realism of simulation results. Rather than making results look good, it is important to reflect realistic potential losses. Being too conservative hinders project progress, but being too optimistic creates risks after implementation. In practice, it is desirable to separate standard and conservative cases and share assumptions that stakeholders find acceptable.

Organize how to use output results and methods for site verification

The final item to check is how you will use simulation results and how to link them to site verification. Solar power generation simulation is not finished by producing calculation results. You need to organize whether the results will be used to revise the design, create revenue plans, obtain internal approval, explain to clients, or compare with post-construction actuals.

First, clarify what you will check in the output. Besides annual generation, different items should be reviewed according to purpose: monthly generation, hourly generation trends, equipment utilization rates, loss breakdowns, shading impacts, peak output, and generation after long-term degradation. For profitability assessments, check not only total generation but also when generation occurs, how much is usable, and whether revenue holds up under downside scenarios.

When using results to compare designs, clearly define differing conditions. If comparing options that change azimuth, tilt, capacity, or row spacing, organize which conditions are varied and which are fixed; otherwise, comparisons are invalid. If differences in generation among options are small, consider constructability, maintainability, cost, risk, and future operation in decision-making.

Organizing methods for site verification is indispensable. Simulation input conditions gain credibility only after on-site verification. Confirm on-site installation areas, roof surfaces, terrain, obstacles, surrounding shading, existing equipment, azimuth, tilt, and maintenance routes and check they match desk assumptions. Keeping site photos, positioning data, survey results, drawings, and equipment information organized makes it easier to explain simulation conditions later.

In practice, discrepancies between simulation assumptions and site conditions lead to rework later. For example: an assumed installable area actually had obstacles; rooftop equipment not shown on drawings existed; trees cast larger shadows than expected; site boundary recognition differed; or ground elevation differences changed layout. Identifying these discrepancies early allows design changes and revenue adjustments to be made sooner.

Simulation results can also be used for post-installation performance management. Comparing actual generation with forecasts helps determine whether differences are due to weather, equipment faults, soiling, or shading. For this, it is important to record the simulation assumptions. Without recorded assumptions, comparing actuals with forecasts makes it hard to analyze causes of differences.

Solar power generation simulation can serve as a common language connecting planning, design, construction, and operation, not merely as a forecasting task. For that, it is important to organize not only output numbers but also input conditions, site verification, and decision criteria. The more thorough the pre-simulation checks, the higher the explanatory power and decision accuracy in later stages.

Summary

Items to check before a solar power generation simulation are more than simple input checks. By organizing the purpose, target scope, location information, irradiance, layout, azimuth, tilt, shading, losses, degradation, and site verification methods, the credibility of simulation results changes significantly. In practice, it is important to be able to explain not just the generation numbers but the assumptions under which those numbers were calculated.

Be particularly careful not to over-rely on simulation results. Calculations are forecasts based on assumptions, and if inputs deviate from field reality, results will too. Irradiance and weather vary year to year, and factors such as shading, soiling, equipment degradation, and downtime affect actual generation. That is why careful pre-calculation checks and realistic assumptions are indispensable.

For practitioners performing solar power generation simulations, it is more effective to increase accuracy progressively according to the stage of consideration than to seek perfect numbers from the start. In early feasibility, grasp rough potential; in basic design, specify layout and capacity; in detailed design, scrutinize shading and losses; after operation, compare with actuals and improve. Following this flow makes simulations not just predictive work but decision-making tools that improve the overall quality of generation projects.

Also, the accuracy of site condition capture directly affects simulation accuracy. Accurately recording installation coordinates, site boundaries, roof surface locations, surrounding obstacles, terrain elevation differences, and shading factors reduces discrepancies between desk calculations and the field. Maintaining precise site location information and reflecting it in design and simulation frameworks greatly enhances the reliability of solar power plans.

If you focus on improving efficiency of site verification and accuracy of location information, using LRTK—a GNSS high-precision positioning device that can be attached to an iPhone—can also be effective. If you can accurately record the location, boundaries, obstacles, and terrain conditions of candidate sites before simulation, it becomes easier to clarify the basis of simulation assumptions. To improve prediction accuracy, it is important not only to set parameters in calculation software but to measure the site correctly, record it accurately, and reflect it properly in design conditions. Incorporating LRTK into site surveys and installation planning helps make solar power generation simulations more useful as practical decision-making materials.