Seven Loss Items to Check in Solar Power Generation Simulations

Solar power generation simulations are not simply about predicting annual generation. In practice, what matters is understanding under which assumptions the estimated generation was calculated and where generation opportunities are being lost. Even with the same installed capacity, actual generation can vary greatly depending on insolation conditions, installation angle, shading, temperature, equipment configuration, wiring, soiling, aging, and downtime.

For practitioners who search for information using terms like "solar power generation simulation," understanding loss items is involved in design decisions, financial assessments, contract terms, post-construction verification, and operational improvements. Judging only by the simulation’s annual generation number makes it hard later to answer “why is generation lower than expected?” or “which conditions should be revised to improve it?” This article organizes seven representative loss items that you should always check in solar power generation simulations and explains how to view them in practice.

Table of contents

• The meaning of checking loss items in solar power generation simulations

• Loss item 1: Losses due to insolation and meteorological conditions

• Loss item 2: Losses due to azimuth, tilt, and layout

• Loss item 3: Losses due to shading

• Loss item 4: Losses due to temperature rise

• Loss item 5: Losses due to equipment conversion and output control

• Loss item 6: Losses due to wiring, connections, and mismatch

• Loss item 7: Losses due to soiling, snow, aging, and downtime

• How to compare loss items and use them in design decisions

• Accurately reflecting site conditions improves simulation accuracy

The meaning of checking loss items in solar power generation simulations

In solar power generation simulations, you first calculate how much solar energy reaches the panels based on the insolation and meteorological conditions at the installation site. However, not all the incoming solar energy can be used as electricity. Generation decreases bit by bit due to various factors: panels not being at optimal angles, shadows from surrounding objects, panel temperatures rising in summer, losses during power conversion, and so on.

Those “bit-by-bit decreases” are organized as loss items. By examining loss items, you can identify design weaknesses and operational improvement opportunities that are not visible from the annual generation number alone. For example, if annual generation is lower than expected, the countermeasures will differ completely depending on whether the cause lies in the insolation assumptions, shading impacts, temperature losses, or equipment configuration.

In practice, it is important not to judge simulation results simply as “high or low,” but to separate which losses are large, whether those losses can be reduced in design, and whether they must be accepted as site conditions. Confusing reducible and irreducible losses can lead to setting unrealistically high expectations or overlooking design elements that could be improved.

Loss items also help explain the plan to stakeholders. Developers, designers, contractors, maintenance staff, landowners, and financiers each focus on different points. Instead of presenting only the annual generation number, explaining which conditions and to what extent losses are expected makes it easier to convey the plan’s validity. Checking loss items is the foundation for turning a simulation from a mere calculation result into a practical document for decision-making.

Loss item 1: Losses due to insolation and meteorological conditions

The first loss to check in solar power generation simulations concerns insolation and meteorological conditions. Since solar power converts solar irradiation from the sun into electricity, the forecast of total generation changes dramatically if the assumed insolation input is off. When confirming the basis for annual generation, you need to check which location the insolation data represents, which period’s weather trends are reflected, and whether an average year is being assumed.

Losses related to insolation are not determined simply by whether a region has many sunny days. Direct irradiance, diffuse irradiance, cloud cover, humidity, precipitation, temperature, and wind speed all interact. In mountainous areas, terrain can block morning and evening sun; coastal areas are affected by cloud patterns and humidity; in urban areas, surrounding buildings and local atmospheric conditions can combine so that generation conditions vary by site even within the same region.

In practice, pay attention to the “representativeness” of meteorological data. Even if you use the nearest observation point or standard weather data, site-specific conditions—such as being on a mountainside, in a valley, along the coast, in a snowy area, or in a fog-prone location—may not be properly reflected. If the simulation’s annual generation looks high but site insolation is harsher than the data assumed, the gap between predicted and actual generation can be large.

Monthly generation is also important when examining insolation and weather-related losses. Annual totals can look reasonable but seasonal generation patterns may not match local experience. For example, regions prone to rainy seasons or typhoons see depressed generation in specific months. Snowy regions may experience significant winter declines. Because annual values can smooth these effects, checking month-by-month variation helps grasp losses due to meteorological conditions more realistically.

This item is difficult to change significantly later through equipment-side improvements. Therefore, it is important to estimate conservatively at the pre-survey stage. In particular, adopting optimistic insolation assumptions in a business feasibility assessment can overestimate overall financial projections. When reviewing a solar power generation simulation, the basic step is to first confirm whether the insolation data are appropriate for the site, and then evaluate the other loss items.

Loss item 2: Losses due to azimuth, tilt, and layout

Next to check are losses due to panel azimuth, tilt angle, and layout. Solar panels’ generation depends on the angle at which they receive sunlight. Generally, orienting panels close to the appropriate azimuth and tilt for the installation area yields more annual generation, but on actual sites roof shapes, landform, mounting conditions, aisle widths, wind loads, constructability, and surrounding constraints often prevent ideal layouts.

Azimuth losses occur depending on which direction panels face relative to the sun’s movement. South-facing orientations tend to generate more over the year in many cases, while east-west orientations bias generation to mornings and evenings. On roofs, you must follow the roof surface orientation, so azimuth may not be freely chosen. On ground-mounted systems, land shape and civil engineering constraints may cause deviation from optimal orientation.

Tilt losses relate to the angle at which panels receive sunlight. Low tilt can be advantageous in summer but deliver less in winter when the sun is low. Conversely, steep tilt may help in winter but can require wider spacing and be more susceptible to wind. In simulation, it is important to check tilt validity by looking not only at annual generation but also seasonal generation balance.

Layout losses involve spacing between panels, inter-row shading, and land utilization efficiency. On ground-mounted sites, packing panels too closely to increase capacity can increase inter-row shading and reduce efficiency. Conversely, spacing too far apart reduces installed capacity per land area, affecting overall generation and project economics. Thus layout is not simply about minimizing losses; decisions must balance land use, constructability, maintenance access, and generation.

Roof installations face similar constraints from eaves, equipment, lightning protection, and inspection space. Even if panels appear placeable in the simulation, safe construction or inspection might not be possible in some locations. Ignoring such site constraints when planning layout can lead to design changes that reduce generation and create gaps from the original simulation.

Losses due to azimuth, tilt, and layout offer relatively large leeway for adjustment during design. Therefore, simulation results should compare multiple conditions to judge which layout is most rational. Rather than aiming solely for maximum generation, choose a layout that is easy to construct, easy to maintain, minimizes shading impacts, and enables stable long-term operation—this leads to good practical design decisions.

Loss item 3: Losses due to shading

Shading losses are often the most overlooked in solar power generation simulations. Shadows are caused by surrounding buildings, utility poles, trees, fences, mountains, roof protrusions, and between panel rows, among other factors. Although shading may look minor at first glance, it can have a significant effect on generation. Even when shading affects only some panels, the connection topology can cause output reduction to spread beyond the shaded area.

When assessing shading losses, you must consider the sun’s movement throughout the year. In summer the sun is high and shadows tend to be short, while in winter the sun is low and morning and evening shadows extend longer. A single site visit may not capture seasonal shading changes. Especially if shading occurs in winter mornings and evenings, it may be inconspicuous when looking only at annual generation but will affect monthly and hourly generation.

Shading from adjacent buildings is a common problem in urban areas, factory roofs, and warehouse roofs. Nearby structures, rooftop rooms, signage, and HVAC equipment can cast shadows depending on time of day. Tree shading is difficult to judge from a single visit because trees change leaf cover seasonally; trees also grow, so an initially small shading problem can worsen after a few years.

For ground-mounted systems, inter-row shading is important. Narrowing inter-row spacing to increase capacity leads to the front rows casting shadows on the back rows during winter and at sunrise/sunset. Even if the design permits a certain level of shading, larger-than-expected inter-row shading reduces generation. Inter-row shading is also affected by land slope and grading accuracy. A site simulated as flat may have subtle elevation differences that change shading patterns.

When checking shading losses, it is important to identify “where,” “when,” and “for how long” shadows occur. It’s not just whether shading exists but whether it falls during high-generation hours or is limited to low-generation morning/evening periods that determines the impact. Also, if shading concentrates on certain circuits, redesigning the electrical connections can mitigate the impact.

Shading losses are one item where the accuracy of the site survey directly affects simulation accuracy. Judging from drawings alone may overlook the heights, positions, seasonal changes of surrounding objects, and terrain undulations. Even if a simulation estimates shading losses as small, you should verify site photos, survey results, and the relative positions of surrounding objects to ensure compatibility with actual installation conditions.

Loss item 4: Losses due to temperature rise

Solar panels generate more when irradiance is strong, but their output decreases as panel temperature rises. Losses from temperature rise are an item that must always be checked in solar power generation simulations. Summer appears favorable due to high irradiance, but panel temperatures can get high enough that output does not increase as much as expected. When assessing annual generation, irradiance and temperature losses should be considered together.

Temperature losses depend not only on ambient temperature but also on ventilation, mounting method, roof material, rack height, and heat dissipation conditions at the panel rear. Ground-mounted systems with good airflow and roof-mounted systems placed close to the roof have different heat dissipation characteristics. On roofs, panels may heat more if the roofing material retains heat or if airflow behind the panels is poor.

In practice, it is important not to underestimate temperature losses. Judging solely by ambient air temperature in weather data can miss the difference between that and actual panel surface temperature. Panels under direct sunlight get hotter than the surrounding air. Simulations typically estimate panel temperature and resulting output reduction based on air temperature, irradiance, wind speed, and installation conditions. If these assumptions do not match site conditions, summer generation forecasts can differ.

Temperature losses have a larger impact on total generation for projects with larger installed capacity. Even a few percent loss per unit becomes a non-negligible difference when converted to annual generation and revenue. Because temperature losses vary seasonally, it’s important to look at month-by-month generation trends as well as annual averages. In high-irradiance regions with large summer insolation, large temperature losses will reduce efficiency.

Design measures to suppress temperature losses include ensuring ventilation, structuring installations so heat does not accumulate behind panels, and avoiding overly dense layouts. However, changing racks or layouts primarily to reduce temperature loss can affect constructability, wind resistance, costs, and maintenance. Therefore, temperature loss must be evaluated in balance with other design considerations.

Temperature rise losses are not visually obvious at the site. Unlike shading or soiling, they aren’t easy to see, so they are easily overlooked unless simulation assumptions are checked. When explaining seasonal generation variations, temperature loss is an important reason why output can plateau in summer despite abundant insolation. When reading solar power generation simulations, it is essential to confirm how temperature loss is handled alongside meteorological conditions.

Loss item 5: Losses due to equipment conversion and output control

Electricity generated by solar panels is not used as-is. DC power is converted to AC and used in systems and loads appropriate to the grid or facility. Losses that occur during this conversion are equipment conversion losses. Solar power generation simulations should consider not only panel generation but also the final usable electrical energy.

Conversion losses depend on converter efficiency, load factor, and operating conditions. Converters have operating ranges where efficiency is higher, and they do not always run at maximum efficiency. When input varies—during low irradiance at dawn/dusk, cloudy weather, or partial shading—efficiency changes. If simulation treats conversion efficiency uniformly, differences can arise from actual operating conditions.

The relationship between panel capacity and converter capacity is also important. It is common to size panel capacity somewhat larger than converter capacity, but during high irradiance periods output may be limited by converter capacity. This creates losses from peak output clipping. Even if such a design is rational in terms of annual generation, excessive output clipping can result in lost generation opportunities.

Losses from output control should also be checked. Grid-side constraints, connection agreements, or regional supply-demand conditions may require curtailment, where output is reduced even if generation is possible. Confirm whether the simulation includes assumptions about output control and, if so, to what extent. Evaluating generation without accounting for expected curtailment can lead to discrepancies between projected and actual sellable or usable energy.

For self-consumption systems, the relationship with demand is important. If generation is high when demand is low, the handling of surplus power affects the actual usable energy. Confusing generation simulation with self-consumption simulation can lead to misunderstanding the amount the panels generate versus how much the facility can use. In practice, it is important to distinguish among panel generation, post-conversion electrical energy, and effectively utilized energy.

Since losses from equipment conversion and output control depend on design and operational conditions, checking them during planning is important. Even with high annual generation, a configuration with low conversion efficiency or large output restrictions can reduce practical value. When reviewing simulation results, confirm whether the displayed electrical energy refers to generation at the panel terminals, after conversion, or at the point of receipt—because the meaning of the number changes accordingly.

Loss item 6: Losses due to wiring, connections, and mismatch

In solar power systems, electricity generated by panels is sent via wiring to conversion equipment. This process causes wiring resistance losses and losses originating from connection configurations. When wiring distances are long, currents are high, or cable selection is inappropriate, part of the electricity is lost as heat. Simulations need to specify how much wiring loss is assumed.

Wiring losses may seem like a small proportion individually but accumulate into non-negligible generation loss over long-term operation. Especially in large ground-mounted sites or when distances from rooftop panels to electrical equipment are substantial, designing wiring routes is important. If simulations use standard wiring loss values, ensure they match actual wiring lengths and voltage conditions.

Losses from connection configurations are also important. Panels are combined into circuits, but differences in individual panel output, shading patterns, and variations in azimuth or tilt can make overall output uneven. Such output variation causes mismatch losses. Even panels of the same model are not identical due to manufacturing tolerances, soiling, degradation, and temperature differences.

Mismatch losses are closely related to shading and layout conditions. For example, grouping panels from differently oriented roof surfaces into the same circuit creates time-dependent mismatches. If one roof face receives sun while the other is shaded, overall generation efficiency declines. On ground-mounted systems, terrain slope and inter-row shading differences change per-circuit generation conditions.

Proper connection design can mitigate mismatch losses. You can separate shaded and unshaded areas, separate faces with different azimuths or tilts, and group panels with similar generation conditions to reduce losses. Conversely, deciding connections without reflecting actual site conditions may make simulations underestimate losses that appear in real operation.

Wiring, connections, and mismatch losses are easy to overlook at the drawing stage. Even if panels appear neatly arranged on layout drawings, without considering actual wiring routes, junction box locations, distances to electrical equipment, azimuth differences, and shading, generation estimates will differ. When reviewing solar generation simulations, check whether standard loss ratios are applied automatically or adjusted to match site-specific design.

Loss item 7: Losses due to soiling, snow, aging, and downtime

Finally, check losses from soiling, snow, aging, and downtime that occur during the operation period. Solar power systems operate outdoors for long periods, so the as-installed condition does not remain forever. Panel surfaces accumulate dust, pollen, bird droppings, leaves, exhaust-related grime, salt, and other deposits. Accumulated soiling reduces how much sunlight reaches the panels and lowers generation.

Soiling losses vary by region and installation environment. Some locations are easily washed by rain, while dry areas, dusty sites, agricultural or industrial surroundings, and bird-populated areas retain more dirt. Low tilt angles impede rainwater runoff and allow dirt to accumulate on panel surfaces. Simulations often assume a fixed proportion for soiling loss, but you must confirm whether that assumption is appropriate for the site.

Snow losses are particularly important in snowy regions. When snow covers panel surfaces, there are periods with no generation. Factors include not only snowfall amount but how long snow remains, whether panels shed snow naturally due to tilt, and whether accumulated snow nearby creates additional shading. In regions with low winter insolation, the baseline generation is small and annual impact may appear limited, but monthly planning for revenues and power use can’t ignore it.

Aging losses are indispensable in long-term assessments. Panels and peripheral equipment gradually decline in performance after years of use. Planning based only on first-year generation can overestimate long-term generation. Check how the simulation assumes annual degradation rates. For long-term financial plans, you must examine the generation trend across the entire operation period rather than initial-year generation alone.

Downtime losses are also important in practice. Equipment inspections, component failures, grid-side work, natural disasters, communication faults, and safety checks can cause the system to stop even when conditions would otherwise allow generation. Some simulations assume continuous normal operation, but in reality it is difficult to make downtime zero. Weak maintenance and monitoring systems delay anomaly detection and expand downtime losses.

This item can be improved not only at the design stage but also through operational management. Regular inspections, generation monitoring, anomaly detection, cleaning schedules, snow-response measures, and spare-part replacement planning reduce losses. To achieve the generation assumed in a simulation, you must include post-installation operational management. Solar power generation simulations are both planning documents and benchmarks for post-operation comparison.

How to compare loss items and use them in design decisions

In solar power generation simulations, it is important not only to view loss items individually but to compare which losses are largest overall. If you want to improve generation, it is more effective to prioritize the largest losses. For example, in a project with large shading losses, spending effort to refine conversion efficiency will have limited overall improvement. Conversely, in a site with little shading and favorable layout conditions, reviewing temperature loss, wiring loss, and equipment configuration may be more important.

When comparing loss items, separate reducible losses from those you must accept. Insolation and regional weather conditions are generally unchangeable by design. Meanwhile, layout, azimuth, inter-row spacing, wiring routes, connection configuration, and maintenance planning can be improved by design or operation. You cannot make all losses zero, but you can identify where to implement measures.

Reducing losses is not always optimal. For example, enlarging panel spacing to reduce inter-row shading can decrease installed capacity per land area. Changing structures substantially to reduce temperature loss can affect constructability and durability. Altering equipment layout to reduce wiring loss may affect maintenance access and safety. In practice, decisions must balance generation with constructability, maintainability, safety, and long-term operational stability.

Comparing a baseline case with improvement cases is an effective way to view simulation results. Compare generation under the current layout, how much improves if shading is avoided, how monthly generation changes with different tilt, and how much wiring loss reduces if routes are revised. Such comparisons clarify the basis for design decisions. A single result alone makes it difficult to explain why a design is appropriate.

Also organize simulation results to explain them to stakeholders. If you can present annual generation, monthly generation, major loss items, assumptions, site constraints, and improvement potential in a logical flow, the plan’s credibility increases. Practitioners should not accept simulations from designers uncritically; they should verify which assumptions affect generation.

Understanding loss items also helps post-construction verification. If actual generation is below simulation, you can avoid immediately assuming equipment failure and instead separate weather differences, shading, soiling, downtime, and temperature conditions. Carefully setting loss items during simulation makes later comparisons easier. The value of checking loss items lies in improving planning-stage accuracy and enabling operational improvements.

Accurately reflecting site conditions improves simulation accuracy

To improve solar power generation simulation accuracy, it’s important not only to refine calculation methods but also to correctly reflect site conditions. Many loss items—insolation, azimuth, tilt, shading, temperature, wiring, soiling, snow, downtime—are deeply linked to site specifics. Simulations created using only standard desktop conditions may be useful for initial studies but insufficient for detailed design or financial decisions.

Shading, layout, terrain, and equipment positioning are particularly affected by the precision of site surveying and measurements. If the positions and heights of surrounding buildings and trees, site boundaries, roof shapes, installable areas, and distances to electrical equipment remain ambiguous, the loss settings in the simulation will also be ambiguous. Small positional or height oversights can affect shading ranges and wiring plans. If you plan to use generation simulations in practice, aligning site survey data and design data is essential.

Simulations should not be one-off. It is desirable to update input conditions at each stage—initial study, basic design, detailed design, pre-construction confirmation, and post-construction verification. Use rough generation estimates at the initial stage, reflect site surveys and layout plans in detailed design, and compare with actual equipment positions and operational data after construction. Creating this flow turns the simulation from a mere forecast into a decision-making standard linking design and operation.

The seven loss items to check in solar power generation simulations are: insolation and meteorological conditions; azimuth, tilt, and layout; shading; temperature rise; equipment conversion and output control; wiring, connections, and mismatch; and soiling, snow, aging, and downtime. Checking these in order makes it easier to understand the assumptions underpinning the annual generation number. In practice, it is essential to confirm not only the size of the generation but also the loss breakdown and the potential for improvement.

A key factor in improving the accuracy of loss items is obtaining accurate site positional information and reflecting it in the design and simulation. Accurately capturing site boundaries, equipment positions, surrounding objects that cause shading, panel layout, and inspection routes reduces the gap between desktop assumptions and field reality. By utilizing LRTK, an iPhone-mounted GNSS high-precision positioning device, you can more easily use high-accuracy positional data collected on-site for layout considerations, post-construction verification, and maintenance. If you want to improve simulation accuracy, it is important to consider not only understanding loss items but also establishing a system to measure site conditions correctly.