Ten essential input items for solar power generation simulation

Solar power generation simulation is not just a matter of entering the system capacity and calculating the annual energy output. To produce results usable in practice, you need to prepare many input items such as the installation location, solar irradiance, azimuth, tilt, shading, module performance, equipment configuration, loss conditions, and operational conditions. If inputs are coarse, the simulation results will also be coarse, causing large discrepancies in generation forecasts, business viability assessments, design comparisons, and post-construction verification.

This article organizes the input items required for generation simulations into ten items for practitioners who search for "solar power generation simulation", and explains what to check for each item, what kinds of mistakes are likely to occur, and how to handle them to improve accuracy.

Table of contents

• Why input items matter in solar power generation simulation

• Input item 1: Location information of the installation

• Input item 2: Solar irradiance and meteorological data

• Input item 3: Installation azimuth and tilt angle

• Input item 4: PV module specifications

• Input item 5: System capacity and module count configuration

• Input item 6: Conditions for power converters such as inverters

• Input item 7: Shading conditions and surrounding obstacles

• Input item 8: Wiring losses and electrical losses

• Input item 9: Losses due to soiling, degradation, and temperature

• Input item 10: Assumptions about operational conditions and output curtailment

• Practical notes when organizing input items

• Summary

Why input items matter in solar power generation simulation

The goal of solar power generation simulation is to estimate future generation as realistically as possible. Generation is not determined solely by the capacity of the PV modules. Even with the same capacity, results change depending on the installation site's irradiance conditions, the orientation and tilt of the roof or racking, surrounding shading, temperature, equipment efficiency, wiring length, soiling, aging, and operational restrictions.

In practice, simulation results are used for investment decisions, design comparisons, explanations to authorities or internal stakeholders, construction planning, and post-completion performance evaluation. Therefore, if many input items are ambiguous, the results will be difficult to explain in later stages. Simulations that do not sufficiently reflect site conditions often look good on paper but tend to diverge from actual generation performance.

Also, simulation results are not absolute truths but forecasts based on assumptions. It is therefore important to make clear which input items were used, on what basis, and at what level of accuracy. Proceeding with default values without understanding the meaning of input items can lead to overestimation of generation or, conversely, overly conservative results.

In solar power generation simulation, treat input items not as mere data fields but as a checklist of conditions that affect generation. Only by linking site surveys, design drawings, equipment specifications, electrical design, and operational conditions will the simulation become useful in practice.

Input item 1: Location information of the installation

The first required input is the location information of the solar power system installation. Location information is the basic data that determines irradiance, solar altitude, solar azimuth, and meteorological conditions. For generation simulations, latitude, longitude, elevation, and regional classification are important.

A change in latitude alters the seasonal solar elevation and daylight hours. Longitude relates to solar time and referencing regional data. Elevation can affect temperature and atmospheric conditions; mountainous or highland areas may exhibit different generation trends than flatlands. Regional characteristics—coastal, inland, snowy, urban, etc.—also influence generation.

A common practical mistake is setting a location roughly based on an address alone. In large sites, factories, warehouses, forests, or reclaimed land, the actual installation location can be far from the address reference point. Using a site entrance or representative point may cause discrepancies in elevation or surrounding terrain conditions relative to the actual installation location.

For rooftop installations, accurately identifying the building location is necessary. In facilities with multiple buildings, each building can have different orientations and shading conditions. For ground-mounted systems, the shading from nearby trees, slopes, and buildings varies depending on where panels are placed within the site.

Location information is the starting point of the simulation. If this is off, even carefully set subsequent inputs will yield lower overall accuracy. Cross-check address, coordinates, site drawings, survey data, aerial photos, and on-site confirmation, and input conditions that closely match the actual installation location.

Input item 2: Solar irradiance and meteorological data

One of the most important inputs for solar power generation simulation is solar irradiance and meteorological data. Since PV systems convert energy from the sun into electricity, the amount of solar irradiance available at the site directly affects generation.

Irradiance concepts include horizontal plane irradiance, tilted plane irradiance, direct irradiance, and diffuse irradiance. What practitioners should first consider is whether the meteorological data used reflect the reality of the target site. Whether you use regional average data, data from a nearby observation point, or long-term averages changes the meaning of the results.

Meteorological data may include not only irradiance but also temperature, wind speed, snowfall, and humidity. Temperature in particular affects PV module output. Generally, module output decreases as module temperature rises. Therefore, even if summer irradiance is high, output may not increase as much as expected because of temperature rise.

When handling irradiance data, be careful not to be overly influenced by a single year’s weather. If one year had exceptionally long sunshine or little rain, that year’s output will be high. For business planning and long-term forecasts, long-term average trends are needed. Conversely, for performance evaluation, you must check how that year’s weather compared to the average to determine whether lower outputs were due to equipment issues or weather.

In snowy regions, consider not only winter irradiance but also generation stoppages due to accumulated snow and effects of albedo/reflection. Coastal areas may experience soiling from salt-laden winds; mountainous areas may have terrain-induced morning and evening shading; urban areas may have shading from surrounding buildings. Meteorological data represent representative regional values and do not automatically reflect all site-specific conditions.

In simulation, understand what the irradiance and meteorological data represent, not just select data. When explaining differences in generation, the reason "why two systems with the same capacity generate different amounts" is often attributable to irradiance or temperature conditions.

Input item 3: Installation azimuth and tilt angle

The installation azimuth and tilt angle of PV modules are input items that greatly influence generation. Azimuth indicates the direction the module surface faces. Tilt angle indicates how much it is inclined relative to the horizontal plane.

Generally, the closer the orientation and tilt are to conditions that receive more sunlight, the higher the generation. However, in practice you cannot always install under ideal conditions. Roof shape, building orientation, site shape, racking layout, wind loads, snow loads, maintenance access, and aesthetic considerations can constrain optimal azimuth and tilt.

For rooftop installations, accurately input the roof surface azimuth and slope. Because the azimuth shown on drawings can differ from the actual building azimuth, on-site confirmation or measurement is important. For ground-mounted systems, enter the designed racking orientation and tilt, but consider the slope of reclaimed land and construction tolerances.

Low tilt angles can reduce wind loads and fit better with roof details, but may cause soiling to accumulate and reduce winter generation when solar altitude is low. High tilt angles can improve winter irradiance but require attention to wind loads, inter-row shading, and racking structure.

Don’t judge azimuth only by the principal direction. For example, an east-facing bias may be advantageous for facilities with high morning demand. A west-facing bias may suit facilities with large afternoon demand. Design decisions involve not only annual generation but also the timing of generation.

In simulation, small changes in azimuth and tilt can alter generation. When comparing multiple proposals, ensure azimuth and tilt conditions are clearly aligned. If input conditions are ambiguous for each design, you cannot determine which proposal is truly advantageous.

Input item 4: PV module specifications

PV module specifications are central input items for generation simulation. Main inputs include nominal peak power, conversion efficiency, temperature characteristics, voltage, current, dimensions, weight, and power tolerance. These affect system capacity, generation efficiency, temperature-related output reduction, and electrical combinations.

Nominal peak power is the module output measured under standard test conditions. However, in real outdoor environments modules face varying irradiance, temperature, wind, soiling, shading, and aging, so they will not continuously generate at nominal values. In simulation, input the module specifications and then reflect losses appropriate to the site environment.

Temperature characteristics are especially important. PV modules tend to lose output as ambient temperature rises and module surface temperature increases. On sunny midsummer days, irradiance is high but module temperature is also high, so you cannot judge generation by irradiance alone. Incorrect temperature coefficient inputs can lead to significant differences in summer generation forecasts.

Module dimensions are important for layout planning. How many modules can be placed on a roof or site, row spacing, and maintenance aisle provision depend on module dimensions. Differences between the actual installable number of modules and the number assumed on paper change both system capacity and generation.

Even modules with the same capacity can have different generation tendencies depending on installation area, temperature characteristics, low-irradiance behavior, and power tolerance. In simulation, do not enter capacity alone; set conditions close to the planned module specifications.

In practice, it is common to perform rough estimates with candidate specifications during early design and update to final specifications once equipment selection is decided. If you continue to use simulation results based on old specifications, they may not align with the final design. Module specifications should be reviewed as design progresses.

Input item 5: System capacity and module count configuration

System capacity and module count configuration are basic items that greatly determine simulation results. System capacity is calculated by multiplying module output by the number of modules. For example, in the same site, increasing the number of modules increases system capacity and potentially generation.

However, larger system capacity is not always advantageous. Overcrowding modules on a roof or site can increase shading, reduce maintenance access, and complicate equipment configuration. Insufficient row spacing can cause front-row shading of rear rows, especially reducing generation in winter and during mornings and evenings.

In module count configuration, it is important to specify how many modules are placed on each surface. When roofs are divided into multiple surfaces, generation tendencies differ for south-, east-, west-facing, and north-leaning surfaces. Treating all modules as a single aggregated capacity does not reflect per-surface differences. In practice, it is desirable to input azimuth, tilt, and shading conditions separately for each installation surface.

Also, the number of modules in series and circuit configuration affect generation. If modules electrically connected in the same circuit have markedly different conditions, partial shading or orientation differences can affect overall output. When roof surfaces are divided or shading affects certain areas, confirm not only the module count but how modules are grouped electrically.

At the early simulation stage, you may enter estimated capacity for a rough generation estimate. As you approach detailed design, reflect module counts based on layout drawings, per-surface conditions, and circuit configurations. To improve generation accuracy, understand not just the capacity number but how that capacity is constituted by layout and configuration.

Input item 6: Conditions for power converters such as inverters

The electricity generated by PV modules is not immediately usable by facilities or the grid. It passes through devices that convert DC to AC or adjust voltage, and losses occur in that process. In simulation, you need to input converter rated capacities, conversion efficiencies, allowable input range, quantity, and circuit configuration.

Particularly important is the relationship between module capacity and converter capacity. If converter capacity is smaller than module capacity, output can become capped during times of strong irradiance. This is not necessarily a poor design, but you need to understand the extent of output limitation.

Conversely, simply increasing converter capacity is not always the solution. Appropriate configuration depends on operational conditions, connection conditions, load usage, installation space, and grid interconnection rules. In simulation, reflect capacity ratios and efficiencies that match the design intent.

Conversion efficiency is not constant. Efficiency can vary during low-output periods, near-rated output periods, and under severe temperature conditions. In conditions with frequent low-power operation, such as mornings, evenings, or cloudy days, rated efficiency alone may not adequately represent actual behavior.

Also confirm that the converter input range matches module voltage conditions. Module voltage increases at low temperatures and decreases at high temperatures, so the design must keep voltages within equipment tolerances year-round. This affects safety and equipment protection, making it important for both generation estimates and design verification.

Do not leave converter conditions at default values; set them according to the planned equipment configuration. Capacity ratio, conversion efficiency, quantity, and circuit partitioning are inputs that strongly affect generation results.

Input item 7: Shading conditions and surrounding obstacles

Shading conditions are easy to overlook in solar power generation simulation and are a frequent source of divergence from actual performance. PV generation depends on sunlight hitting the module surface. Therefore, shadows from buildings, trees, utility poles, signs, mountains, adjacent structures, and rooftop equipment reduce generation.

The effect of shading cannot be judged solely by the shaded area. Because modules are electrically connected, shading on a part can affect output of the whole circuit. Long narrow shadows or shadows that move during morning and evening can affect generation even for short periods.

On rooftops, chimneys, HVAC equipment, railings, penthouses, and adjacent buildings cause shading. On ground-mounted systems, nearby trees, slopes, elevation differences of reclaimed land, fences, neighboring buildings, and mountain shadows are influential. For new construction or reclaimed land projects, simulations are sometimes performed without reflecting post-completion surrounding structures.

On-site confirmation is indispensable for inputting shading conditions. Drawings alone may not accurately capture tree heights, actual equipment positions, impacts of surrounding buildings, or terrain undulations. Seasonal changes in solar altitude mean that shading irrelevant in summer may have a large impact in winter.

In simulation, it is helpful to separate near-field and far-field shading. Near-field shading is caused by obstacles close to the system such as rooftop equipment or adjacent buildings. Far-field shading comes from mountains, hills, or distant buildings. Both affect generation but require different input and checking methods.

Underestimating shading leads to overestimation of generation. Conversely, overestimating shading can unfairly disadvantage a design. Input shading conditions based on site surveys, photos, surveys, drawings, and solar trajectory checks, and keep a rationale that can be explained.

Input item 8: Wiring losses and electrical losses

In PV systems, electricity generated by modules incurs losses while being transmitted to converters and receiving equipment. In simulation, you must appropriately input wiring losses, connection losses, and electrical losses between devices.

Wiring losses depend on cable length, gauge, current, voltage, and routing method. For large ground-mounted sites, distances from module rows to collection equipment can be long, increasing wiring losses. Rooftop installations may also require checking losses when internal routing is long or multiple buildings are consolidated.

A practical point to watch is that wiring conditions often change between the conceptual and detailed design phases. While early studies may assume short wiring, actual routing may become longer due to equipment panel locations, interactions with existing equipment, fire compartmentation, maintainability, and safe access routes. When wiring lengths change, losses change, so re-enter wiring conditions as design progresses.

Electrical losses also include losses from module-to-module variance, connector losses, transformer and protective device losses, etc. Each individual loss may seem small but can sum to a non-negligible difference across the entire system. For large systems, loss assumptions have a significant impact on generation forecasts.

When entering wiring losses, avoid overly optimistic values. Setting losses too small to make generation look better will make it difficult to explain divergences from actuals later. Conversely, entering large losses without solid grounds can unfairly lower a design’s evaluation.

Loss values used in simulation must be consistent with electrical design. Once layout diagrams, single-line diagrams, equipment placement, cable routes, and panel locations are decided, revisiting wiring loss conditions is important in practice.

Input item 9: Losses due to soiling, degradation, and temperature

In solar power generation simulation, you must input losses due to soiling, long-term degradation, and temperature. These are losses that are difficult to avoid during actual operation. They are particularly important when estimating long-term generation, not only ideal first-year conditions.

Soiling losses arise from dust, pollen, yellow sand, bird droppings, fallen leaves, exhaust, salt, and soiling after snow melt. Low tilt angles can reduce rain-wash-off of soiling. The type and tendency for soiling attachment differ near factories, agricultural land, busy roads, and coastal areas.

When inputting soiling losses, consider regional characteristics along with maintenance plans. Assumptions about whether cleaning will be performed regularly or left to natural rainfall change expected losses. Some roof or ground-mounted installations are easy to clean, while others are difficult to clean frequently for safety reasons.

Long-term degradation is the gradual decline in PV module output over the years. For long-term business planning, consider generation declines over multiple years, not just the first year. Inputs differ depending on whether you are focusing on first-year generation or long-term financials.

Temperature losses occur when module temperature rises and reduces output. When modules are installed close to the roof surface with poor ventilation, module temperature tends to increase. Ground-mounted systems with good ventilation may have different temperature conditions even at the same ambient temperature.

These losses are often overlooked because they are not easily visible. However, they are important for explaining differences between simulation and actual generation. In simulation, set realistic soiling, degradation, and temperature losses according to the installation environment, maintenance policy, and operational life.

Input item 10: Assumptions about operational conditions and output curtailment

Finally, assumptions about operational conditions and output curtailment are important. PV systems do not always generate at maximum whenever there is sunlight. Grid constraints, facility load conditions, equipment downtime, maintenance and inspections, communication failures, output control, and contractual conditions can prevent all generated power from being used or exported.

In self-consumption systems, the relationship with facility electricity demand is important. In facilities with low daytime demand, there may be periods when generation exceeds demand. In such cases, reflect assumptions about handling surplus power and output control in the simulation. It is important to see not only annual generation but when generation occurs and how much of it can be utilized.

For grid-connected systems, interconnection conditions and operational rules may limit output. Particularly for large systems, region- or connection-specific conditions may require assuming output curtailment even during otherwise generatable times. Simulations that ignore output curtailment can overestimate actual sellable or usable energy.

Also consider downtime due to maintenance and equipment replacement. Although it may not be a large proportion, certain stoppages or performance reductions can occur over long-term operation. When systems consist of multiple converters, checking the impact of partial outages aids risk assessment.

Operational conditions are inputs not only of a technical nature but of operational management. Who will manage the system, how quickly can they respond to anomalies, the frequency of cleaning and inspections, and whether facility power demand will change in the future all affect actual delivered generation.

When using simulations for business decisions, separate potentially generable energy from usable energy. Even if generation appears high, heavy output curtailment or unused power may prevent expected benefits.

Practical notes when organizing input items

When preparing input items for solar power generation simulation, first clarify the purpose. Required input accuracy varies depending on whether it is a rough assessment, design comparison, internal explanation, pre-construction check, or post-completion performance verification. It is not necessary to input detailed data at all stages from the start, but at decision-making stages you must update conditions to ones supported by evidence.

A common practical problem is reusing results even though simulation assumptions have changed. For example, an initial plan assumed south-facing arrays but the final plan splits them onto east- and west-facing roof surfaces due to roof shape; generation will change. If module type, number, converter capacity, shading conditions, or wiring routes change, re-calculation is needed.

Input items are linked to design drawings, site surveys, equipment specifications, electrical design, and operational conditions. Therefore, do not treat generation simulation as an isolated task; create a process to update input conditions when design changes occur. Recording the input date, inputter, referenced drawings, chosen meteorological data, and basis for loss rates makes later explanations easier.

When reviewing simulation results, do not focus solely on a single annual generation number. Reviewing monthly generation, hourly trends, loss breakdowns, presence of output curtailment, shading impacts, and temperature losses together makes it easier to judge result validity. Even if annual generation is high, it may be seasonally biased or misaligned with demand.

Improving input accuracy requires accurately grasping site conditions. Drawings alone can miss rooftop obstacles, surrounding elevation differences, shading causes, actual azimuth, and constructible areas. Reflecting on-site information in the simulation increases result reliability.

In particular, location information, elevation differences, installation area, and obstacle positions are directly linked to simulation accuracy. Preserve such information not only as photos or notes but as positioning data or on-site measurements so designers, contractors, and clients can share a common understanding.

Summary

The input items required for solar power generation simulation range widely: installation location, irradiance, azimuth, tilt, module specifications, system capacity, converters, shading, wiring losses, soiling and degradation, and operational conditions. Accurately inputting just one item while leaving others ambiguous will not yield results you can rely on in practice.

The important point is not to treat simulation as a simple calculation to produce generation figures. Solar power generation simulation is a practical tool to organize site conditions, design conditions, equipment conditions, and operational conditions and to verify how they affect generation. The more carefully you prepare input items, the easier it becomes to compare design proposals, make investment decisions, perform pre-construction checks, and evaluate post-construction performance.

In particular, site location information, azimuth and tilt of installation surfaces, causes of shading, and elevation differences of the site or roof are critical assumptions for simulation. Accurately obtaining these data during site surveys reduces discrepancies between desk studies and actual conditions.

In planning PV systems, reliably linking coordinates and site location information obtained on site to design and simulation leads to improved generation forecast accuracy. If you want to streamline on-site positioning and location confirmation, using LRTK (iPhone-mounted GNSS high-precision positioning device) can make it easier to record installation areas, obstacles, survey points, and site conditions with high accuracy. To improve the input accuracy of solar power generation simulation, accurately collect site information and retain it in a form that can be applied to design and operation.