Solar power generation simulations are not just for seeing "how much electricity can be generated annually." In practice, they are used to determine what capacity of solar PV should be introduced by considering building electricity usage, roof or site conditions, orientation, tilt, shading, how electricity is used, and even future equipment expansions. Increasing capacity raises generation, but it is not always optimal. Conversely, if capacity is too small, self-consumption, electricity bill savings, and decarbonization effects may not be achieved sufficiently.

This article explains, in six steps, the approach for determining required capacity for practitioners searching for "solar power generation simulation." The basic flow is common whether the target facility is a residence, store, factory, warehouse, or public facility. By organizing not only generation but also demand, installation conditions, monthly variations, losses, and operational objectives, you can design capacity with fewer shortages or excesses.

# Table of Contents

• The meaning of determining required capacity with solar power generation simulations

• Step 1: Understand electricity usage and how it is used

• Step 2: Clarify the purpose of introduction and set upper and lower capacity limits

• Step 3: Organize available installation area and orientation/tilt conditions

• Step 4: Check generation per 1 kW in simulation

• Step 5: Reconcile monthly generation and monthly demand

• Step 6: Adjust final capacity accounting for losses and future changes

• Common failures when deciding required capacity

• Why site data accuracy becomes important in capacity studies

• Summary

# The meaning of determining required capacity with solar power generation simulations

Determining the required capacity of solar PV is not simply installing as many panels as can fit on a roof or site. In practical capacity studies, it is important to set a scale that matches the building or business objectives while balancing how much can be generated and how much can be used. Solar power generates during daytime and not at night. Also, the relationship between generation and electricity demand changes on clear versus cloudy days, summer versus winter, and weekdays versus holidays. Therefore, deciding capacity solely by annual total generation can lead to too much surplus or inability to cover power needs at required times.

When considering required capacity, you must first clarify "why you are introducing solar PV." Appropriate capacity varies depending on whether you prioritize electricity bill reduction, increasing daytime self-consumption, securing power during disasters, or introducing it for environmental value and decarbonization initiatives. For example, factories or stores with high daytime electricity use tend to be able to self-consume even relatively large capacities. On the other hand, residences with few people during daytime or facilities with little weekend operation may have times when generated electricity cannot be fully used.

Solar power generation simulations are a tool for organizing these decisions numerically. They reflect site solar irradiance, orientation, tilt, shading effects, panel capacity, conversion losses, etc., allowing you to check projected annual and monthly generation. By cross-checking with electricity usage data, you can see which capacity can be used without strain, from which capacity surplus tends to increase, and how much loss to expect.

An important point in capacity studies is not to fix on a single capacity from the start. Set multiple candidate capacities and compare each candidate’s annual and monthly generation, ease of self-consumption, and tendency for surplus. Although generation increases with capacity, the match rate with demand can fall. Because installation area, electrical equipment, structural conditions, and operational policy also matter, simulation results should be read as "materials for capacity decision-making" rather than merely "predicted generation values."

# Step 1: Understand electricity usage and how it is used

The first step in determining required capacity is to understand how much electricity the target building or equipment uses. Even if you run a solar power generation simulation first, you cannot judge the appropriateness of capacity unless you know how much of the generated electricity can actually be used. Generation is supply-side information, and electricity usage is demand-side information. Required capacity only becomes apparent when you consider these two together.

First, confirm annual electricity usage. Annual usage helps grasp the rough amount of electricity that solar PV could potentially cover. However, deciding capacity based solely on annual usage is risky. Facilities with the same annual usage can have very different compatibility with solar PV depending on whether they use more electricity during daytime or at night. Because solar generates during daytime, the more daytime demand there is, the easier it is to self-consume.

Next, check monthly electricity usage. Monthly demand varies greatly depending on operation of cooling and heating, lighting, manufacturing equipment, refrigeration, HVAC, hot water supply, charging equipment, and so on. Some facilities see higher HVAC demand in summer, others see increased heating, snow-melting, or hot-water-related loads in winter. Because solar generation changes seasonally, it is important to examine the match between monthly demand and monthly generation.

In practice, having time-of-day usage data increases the accuracy of capacity decisions. Facilities with stable daytime usage can more easily self-consume solar generation. Conversely, facilities with demand concentrated in the evening or nighttime often find it hard to align generation and demand with solar only. In such cases, increasing capacity may not raise self-consumption rate as much as expected. Unless combined with storage or operational changes, it is realistic to base capacity studies on daytime demand when considering solar alone.

When reviewing electricity usage, it is preferable to check trends over multiple years rather than just the most recent year. If a particular year had fewer operating days, equipment replacements, extreme heat or cold events, or changes in occupancy or operations, single-year data may misrepresent typical demand. Especially for corporate facilities, future changes—such as increased production, changes to operating hours, HVAC upgrades, introduction of electric vehicles, or equipment additions—can change future electricity usage.

For residences, required capacity also varies depending on family composition, time spent at home, hot water system, HVAC habits, presence of electric vehicles, and lifestyle changes. You should consider the possibility of increased electricity demand in a few years, not just match current usage exactly. However, overestimating future demand may create excessive surplus in the short term. When considering future uncertainty, reviewing multiple scenarios—standard, conservative, and demand-growth scenarios—makes decision-making easier.

What matters in this step is not only "how many kWh are used annually" but also "when, which equipment, and how much is used." Simulation results for solar generation are meaningful only when combined with demand data. Instead of deciding capacity by generation alone, narrowing candidate capacities by back-calculating from electricity usage is the first step to avoid mistakes.

# Step 2: Clarify the purpose of introduction and set upper and lower capacity limits

After understanding electricity usage, next organize the purpose of introducing solar PV. Required capacity varies significantly by purpose. Whether you prioritize self-consumption, maximize annual generation, strengthen emergency backup, or make contributions to environmental goals visible, the appropriate capacity approach differs. If the purpose is unclear and you proceed with simulations, you may end up with large generation that cannot be used, unused available installation area making investment decisions difficult, or inconsistent evaluation criteria among stakeholders.

If self-consumption is the main objective, consider capacity based on daytime electricity demand. Installing large capacity despite small continuous daytime usage can create surplus. How surplus power is handled depends on regulations, contract conditions, and facility policy, but in practice many cases emphasize "using generated power on-site as much as possible." Therefore, in self-consumption–focused capacity studies, the overlap with daytime demand is more important than maximum generation.

Conversely, if you want to make effective use of roof or site area to maximize annual generation, consider capacities up to the installable area. Even then, more generation is not always better. You must check surplus handling, electrical acceptance capacity, grid-connection conditions, maintainability, shading impact, and structural constraints. The larger the capacity considered, the more important it becomes to check electrical equipment and construction conditions in addition to generation simulation.

If emphasizing use during disasters or power outages, organize not only PV capacity but also which loads and capacity you want available during emergencies, the scope of daytime usage, and whether storage and transfer equipment are present. Solar PV is strong during generation hours, but you cannot necessarily use all equipment during outages as in normal operation. When emergency use is an objective, it is important to consider "normal-period generation" separately from "power needed during emergencies."

If environmental goals and decarbonization efforts are prioritized, confirm the share of annual generation relative to electricity usage. Determine what proportion of electricity you aim to supply from renewables, what percentage of the facility’s total usage you’re targeting, and whether the numbers will stand up to organizational reporting and explanation. Even here, do not simply increase capacity; verify how much generation is realistically expected, whether there are large monthly imbalances, and whether the plan aligns with operational reality.

After clarifying objectives, tentatively set lower and upper capacity bounds. The lower bound is a capacity that is not too small to produce meaningful benefits. If installed capacity contributes only minimally to electricity usage and the administrative burden outweighs benefits, the objective will be hard to achieve. The upper bound is the realistic maximum capacity considering installable area, daytime demand, electrical equipment, structural conditions, and acceptable surplus. Setting several candidate capacities within these bounds and comparing them via simulation makes decisions easier.

Avoid deciding "this capacity is final" from the start. In practice, capacities are not only segmented by round numbers like 10 kW, 30 kW, 50 kW, 100 kW but also vary by roof-face layout, number of panels, and electrical constraints. Creating multiple patterns before narrowing to one allows comparison of how generation increases, how surplus appears, monthly imbalances, and construction difficulty. Solar power generation simulations are effective for making these comparisons.

# Step 3: Organize available installation area and orientation/tilt conditions

Understanding installable area is indispensable when considering required capacity. Theoretically you may want to choose capacity to match electricity demand, but in reality the capacity that can be installed is limited by roof or site size, shape, structure, orientation, tilt, shading, maintenance space, and safety walkways. Especially for roof installations, the apparent area and the area where panels can actually be placed often differ, so you need to organize site conditions early.

For roof installations, first check orientation and tilt for each roof face. Generally, roof faces that receive more solar irradiance yield greater generation. However, optimal conditions vary by building shape, region, and surrounding environment. Slight deviations in orientation can still yield adequate generation, and shallow-tilt roofs can achieve practical generation depending on installation methods. Conversely, a roof face with large area but long-duration shading may not deliver expected generation.

When considering installable area, checking obstacles is important. Roofs may have outdoor HVAC units, ventilation equipment, inspection hatches, piping, lightning protection, skylights, antennas, railings, snow guards, drainage routes, etc. Since panels must be arranged around these, judging capacity from plan-view roof area alone tends to overestimate. Also, if you do not secure walkways and workspaces for maintenance inspection, future inspections, cleaning, and equipment replacement may become difficult.

For ground-mounted systems, check usable site area, terrain, slope, need for site preparation, shading from nearby trees or buildings, snow and drainage, maintenance paths, fences, boundaries, regulations, and future land-use plans. Ground installations offer more freedom than roofs but require coordination with overall site use. Maximizing generation without regard to vehicle access, maintenance routes, drainage, mowing, or distances to nearby facilities can cause operational issues.

Orientation and tilt directly affect solar generation simulations. For the same capacity, annual and monthly generation change with installation angle and direction. For example, you may prioritize morning generation, midday peak, or afternoon demand depending on objectives; evaluation changes accordingly. It is important to consider not only the orientation that maximizes annual generation but also whether that orientation matches the facility’s high-demand hours.

Shading also strongly affects capacity studies. Shadows from surrounding buildings, trees, utility poles, mountains, signboards, and rooftop equipment change by time of day and season. Because solar altitude is lower in winter, shading that is negligible in summer may have a large winter impact. If you fill shaded areas to increase capacity, not only may generation not increase much, but adding low-efficiency areas can lower the overall evaluation.

At this stage, consider both the "capacity when panels are prioritized on high-efficiency surfaces" and the "capacity when area is used to the maximum" separately. The former is suited to self-consumption and efficiency-focused studies, while the latter helps when maximizing generation or planning for future expansion. By comparing these multiple patterns in solar generation simulation, you can concretely grasp the relationship between area use and required capacity.

# Step 4: Check generation per 1 kW in simulation

After organizing installation conditions, next check the generation per 1 kW. This is a very important indicator for reverse-calculating required capacity. For example, a 10 kW PV system in a location with good irradiance and little shading will generate differently from the same 10 kW in a shaded or unfavorably oriented location. When estimating capacity from required annual generation, you must know how much generation you can expect per 1 kW to estimate capacity properly.

Generation per 1 kW is affected by regional irradiance, installation orientation, tilt angle, temperature, shading, equipment losses, and more. Deciding capacity based on general rules of thumb can yield results that do not match actual installation conditions. Especially when roof faces are divided or some faces have poor orientation or partial shading, generation differs by face. Averaging over the whole can obscure differences between good and bad faces, so if possible simulate per roof face or per layout pattern.

The purpose of checking generation per 1 kW is to make it easier to compare generation among candidate capacities. For instance, if a site yields about 1,100 kWh per year per 1 kW under certain conditions, you can estimate roughly 22,000 kWh for 20 kW and 55,000 kWh for 50 kW. However, this is only a rough calculation; as capacity increases, you may not always place panels only in the best locations. While the first few kW may fit on the best roof faces, as capacity increases you may need to use shaded or unfavorably oriented faces, which can reduce kWh per 1 kW.

Therefore, it is important to look at changes in generation efficiency by capacity. When comparing small, medium, and large capacity options, check whether generation increases proportionally with capacity or whether the marginal generation efficiency of the later additions drops. If a large-capacity option shows a significant decline in kWh per 1 kW, the added capacity may contribute little generation relative to the area used. Conversely, if kWh per 1 kW does not fall much with increased capacity, it may indicate efficient use of area.

In generation simulations, pay attention not only to annual generation but also to the breakdown of expected losses: temperature-related losses, conversion losses, wiring losses, soiling, shading, orientation/tilt impact, etc. If loss settings are overly optimistic, capacity assessments will be optimistic. If overly conservative, you may tilt toward increasing capacity unnecessarily. In practice, it is effective to compare a standard case with a conservative case after clearly listing assumptions.

By checking generation per 1 kW, you can create an initial capacity estimate. For example, if you aim for about 30,000 kWh per year, you can derive a capacity guideline from the annual generation per 1 kW. Then adjust while confirming installable area, daytime demand, monthly generation, and surplus occurrence. Repeating this reverse-calculation and verification moves you from intuitive capacity decisions toward evidence-based capacity decisions.

# Step 5: Reconcile monthly generation and monthly demand

A commonly overlooked step when deciding required capacity is reconciling monthly generation and monthly demand. Looking only at annual generation can make it seem that there is sufficient generation, but generation-heavy months and demand-heavy months may not match. Solar generation varies by season. Monthly generation differs due to irradiance, temperature, weather, snow accumulation, rainy season, typhoons, and regional characteristics. Meanwhile, electricity demand also varies seasonally with HVAC and equipment operation. Checking whether these two variations align is important for capacity decisions.

For example, facilities with high summer cooling loads often have demand that aligns with months of high solar generation. In such cases, up to a certain capacity it is easier to self-consume and explain benefits. Conversely, facilities with high winter heating demand may be in regions where winter solar generation is low; even if annual generation seems sufficient, winter demand may not be adequately covered. Without monthly reconciliation, you may overlook such seasonal gaps.

When comparing monthly generation and monthly demand, check not only totals but also which months tend to have surplus and which months tend to have shortages. If there are many months where generation exceeds demand, increasing capacity may not significantly raise self-consumption rates. Conversely, if generation is always below demand, there may be room to increase capacity to use more on-site. Note, however, that even in months when monthly demand is lower than generation, temporary daytime surpluses can occur on sunny days. For more precise decisions, also check the overlap of hourly demand and generation.

For corporate facilities, differences between weekdays and weekends are also important. A facility with high weekday daytime demand may see surplus generation on weekends when equipment is shut down. Monthly demand alone won’t show weekday-weekend differences, so consider operating calendars. Especially in factories, schools, public facilities, offices, and warehouses, weekday and seasonal operating patterns change self-consumption potential. Comparing simulation results with operational calendars yields more realistic capacity decisions.

In residences, seasonal living patterns and time at home affect results. Households with occupants at home during the day differ from those absent during the day and concentrating demand in the evening; the same capacity can have very different self-consumption shares. If hot water, HVAC, appliances, and vehicle charging can be shifted to daytime, solar PV is easier to utilize. When deciding required capacity, consider not only current usage but whether usage patterns can be changed after installation.

If monthly reconciliation indicates generation is insufficient relative to demand, it does not always mean you should immediately increase capacity. Due to installable area and shading constraints, increasing capacity may lower generation efficiency. Also, if demand is concentrated at night, capacity increase alone may not solve the issue. In such cases, consider combinations of increasing PV capacity, adding storage, shifting usage times, energy efficiency, and equipment upgrades.

Reconciling monthly generation and monthly demand is also useful for explaining to stakeholders. Presenting seasonal supply-demand balance clarifies effects that are hard to see from annual totals alone. When deciding capacity, verify not only "how much is generated annually" but "how much is generated each month and how much of that power can be used."

# Step 6: Adjust final capacity accounting for losses and future changes

Once you have checked the relationship between generation and demand for candidate capacities, finally adjust the capacity accounting for losses and future changes. Solar power generation simulation is a forecast based on input conditions. Actual generation varies with weather, soiling, aging, changes in the surrounding environment, equipment operation status, and maintenance conditions. Therefore, treat simulation values not as fixed numbers but as estimates with a reasonable range.

When estimating losses, avoid deciding capacity under overly ideal conditions. Calculating based on the pristine condition immediately after installation, assuming almost no shading, or assuming negligible soiling and temperature effects can lead to actual performance falling short of expectations. Especially in locations subject to dust, falling leaves, snow, bird damage, salt damage, nearby construction, or new adjacent buildings, consider elements that could affect generation in advance.

Consider aging as well. Solar PV systems are used for the long term, so anticipate not only first-year generation but performance degradation in later years and decades. If you decide required capacity based only on the first year's ideal generation, you may face insufficient generation later in long-term operation. Conversely, assuming excessively large margins can result in excessive short-term surplus; choose appropriate safety margins according to objectives.

Future changes in electricity demand are also important. Electricity usage can change due to equipment additions, HVAC upgrades, introduction of electric vehicles, changes in operating hours, changes in employee numbers, production volume alterations, or changes in building use. If daytime demand is likely to increase, keeping capacity too small now may miss future benefits. On the other hand, introducing very large capacity based on uncertain future demand may lead to significant surplus in the near term.

When deciding final capacity, balance current optimality and future flexibility. If you prioritize current self-consumption rates, base capacity on daytime demand. If future demand increases are very likely, choosing slightly larger capacity can be an option. Alternatively, if there is room on the roof or site for future expansion, keeping initial capacity moderate and planning later expansion is also valid. Which approach suits best depends on electrical equipment, constructability, building use plans, and operational policy.

Also, when adjusting capacity check the coherence of equipment configuration, not just generation. Number of panels, circuit layout, inverter capacity, balance across installation faces, and handling of shaded areas determine practical, buildable capacities. Even if simulation can vary capacity finely, in the field the optimal increments may differ due to equipment unit sizes. The final decision requires reconciling simulation values with design and construction realities.

The final capacity is not necessarily the capacity that maximizes generation. Required capacity is the capacity that, considering objectives, demand, installation conditions, losses, and future changes, minimizes shortages and excesses, is explainable, and is easy to operate. If you can verbalize reasons for increasing, limiting, or allowing margin in capacity based on simulation results, it is easier to build stakeholder consensus.

# Common failures when deciding required capacity

There are several typical failures in capacity studies using solar power generation simulations. The most common is judging solely by annual generation. Large annual generation can appear to yield big benefits, but if generation times and electricity usage times do not match, self-consumption becomes difficult. When deciding capacity, you must consider annual generation, monthly generation, and time-of-day demand together.

Another common mistake is equating the maximum capacity that fits on a roof or site with required capacity. Installable capacity and required capacity are not the same. Using every installable area can be effective, but if you use heavily shaded or low-efficiency areas, generation may not increase commensurately with capacity. Also, layouts that do not secure maintenance space or safety walkways can hinder operation after installation.

Deciding capacity with insufficient electricity usage data also leads to failures. Relying only on annual usage or only the last few months can miss seasonal variation and operational differences. Especially for corporate facilities, demand can vary greatly by busy and slow seasons, weekdays and weekends, and daytime and nighttime. To improve simulation accuracy, carefully verify demand-side data as well as generation-side conditions.

Underestimating shading impacts is another major problem. Even partial shading can affect generation depending on layout and circuit configuration. Low solar altitude in winter, shadows from nearby buildings, rooftop equipment shadows, and tree growth are often overlooked. Insufficient on-site verification or plan review can create gaps between simulated generation and actual performance.

Not considering future changes is also a failure. If you set capacity based only on current electricity usage and later expand equipment, introduce electric vehicles, or upgrade HVAC, solar capacity may become insufficient. Conversely, if you overestimate future demand and install too much capacity, you may experience large near-term surplus and reduced operational benefits. Do not fix on a single future prediction; check multiple scenarios.

Finally, failing to share simulation assumptions is problematic. If you share only results without clear assumptions—irradiance, orientation, tilt, shading, losses, equipment capacity, demand data, operating days—stakeholders may misunderstand the numbers. In practical capacity decisions, be clear not only about the numbers but also the conditions under which they were calculated.

# Why site data accuracy becomes important in capacity studies

The accuracy of solar power generation simulations is greatly influenced by the precision of input site data. While irradiance and equipment specifications are important, site-specific conditions that affect installability and generation—roof-face shape, orientation, tilt, obstacles, shading, site boundaries, and surrounding environment—have large impacts. If drawings are outdated, do not reflect extensions or added equipment, have shifted rooftop equipment positions, or if nearby trees or buildings have changed, differences will arise between simulation results and reality.

Particularly for existing buildings, many pieces of information are not discernible from drawings alone. Roof level changes, slopes, deterioration, waterproof layers, actual equipment positions, inspection routes, railing heights, and shadows from adjacent buildings are often difficult to accurately grasp without on-site checks. Capacity studies must confirm not only theoretical generation values but whether the planned layout can be operated safely and continuously.

The same applies for ground-mounted installations. If information on site elevation differences, drainage, ground conditions, existing structures, trees, maintenance routes, and vehicle routes is insufficient, installable capacity can be overestimated. A site that looks large on a plan may actually be limited by slopes, steps, pathways, drainage routes, or planned future use. Accurately obtaining site information in the initial capacity study reduces rework later.

Site data accuracy also matters for stakeholder explanations. When proposing capacity, you need evidentiary site data to explain why a certain roof face is used or not used, and why you propose a capacity below the maximum. If you can clearly show areas with large shading impact, areas reserved as inspection routes, or areas to avoid for structural reasons, you can more easily justify capacity choices.

Solar power generation simulation should not remain a desk calculation; it becomes practical only when it reflects site conditions. At the stage of deciding required capacity, it is important to have both electricity data and site data. If you can accurately grasp roof or site dimensions, locations, slopes, obstacles, and shading causes and reflect them in simulation conditions, layout accuracy improves and capacity comparisons approach reality.

For such site checks, positioning devices that can acquire high-precision location data are useful. LRTK is a GNSS high-precision positioning device that can be attached to an iPhone and is suitable for efficiently recording on-site verification points and structure positions. When deciding required capacity through solar power generation simulation, accurately identifying positions of roof surroundings, site boundaries, obstacles, and shading-causing objects makes it easier to organize installable area and layout conditions. Connecting desk-based simulations with on-site measured data clarifies the grounds for capacity decisions.

# Summary

To determine required capacity with solar power generation simulations, do not judge by generation alone; sequentially organize demand, purpose, installation conditions, monthly variations, losses, and future changes. First understand electricity usage and how it is used, then clarify the introduction purpose. Next confirm installable area, orientation, tilt, and shading conditions and use simulation to grasp generation per 1 kW. Reconcile monthly generation with monthly demand, and finally adjust capacity considering losses and future changes.

Required capacity is neither the maximum nor the minimum capacity but the capacity with minimal shortages or excesses relative to the objective. Focusing only on increasing generation can create large surplus or force use of low-efficiency areas. Conversely, keeping capacity too small can fail to meet objectives like self-consumption, decarbonization, or emergency use. In practice, compare multiple capacity proposals and check each one’s annual generation, monthly generation, overlap with demand, installation conditions, and operational issues.

Also, simulation results depend on assumptions. If irradiance, orientation, tilt, shading, losses, electricity usage, operating days, and future demand assumptions are unclear, numbers can be misinterpreted. When deciding capacity, be able to explain why that capacity is appropriate. Accurately grasping site conditions and reflecting them in simulations reduces misunderstandings among stakeholders and rework later.

Solar PV capacity design achieves higher accuracy only when desk-based calculations and on-site verification are combined. If you accurately record roof faces, site boundaries, obstacles, shading-causing objects, and equipment positions and reflect them in simulation conditions, capacity decisions become more practical. If you want to improve on-site survey accuracy, using LRTK, an iPhone-mounted GNSS high-precision positioning device, helps leverage on-site position data in capacity and layout studies. To turn generation simulations from mere estimates into evidence-based design decisions, evaluate required capacity from both electricity data and site data.