6 Points to Review When Calculated Solar Power Generation Is Low

When calculating solar power generation, you may sometimes be surprised to get figures that are considerably lower than expected. It is not uncommon in practice to encounter cases where the annual kWh does not scale with the installed capacity, where a roof that should have enough area produces less power than anticipated, or where the numbers make the financial calculations hard to justify.

However, just because the calculation results are low, it is premature to conclude that the project itself is unfeasible. In practice, simply revisiting a few assumptions—how equipment capacity is placed, how usable area is assessed, how azimuth and tilt are treated, corrections for shading and loss rates, the choice of regional conditions, and the interpretation of self-consumption assumptions—can significantly change how the numbers look. The important thing is not to accept low numbers at face value, but to isolate, in order, where the causes of the low results lie.

For practitioners who search for "solar power generation calculation", the important thing is not to dismiss a low calculation result as a gut feeling, but to have a reproducible way of determining which conditions should be reviewed. Therefore, this article organizes and explains six points you should prioritize when solar generation calculation results are low. If you review them in order—from the system's input conditions, through correction coefficients, to operational assumptions—the causes of low figures will become much clearer.

Table of Contents

• What to consider first when calculation results are low

• Point 1 Reexamine the assumptions about system capacity

• Point 2 Reexamine how effective area and the number of panels are determined

• Point 3 Reexamine the assessment of orientation, tilt, and shading conditions

• Point 4 Reexamine regional solar radiation conditions and the handling of seasonal variations

• Point 5 Reexamine how loss rates and correction factors are applied

• Point 6 Reexamine the interpretation of evaluation objectives and self-consumption assumptions

• Order in which to carry out the review in practice

• Summary

What to consider first when the calculation results are low

When the calculated solar power generation is low, the first thing to clarify is what that number represents. The generation figure can be an input number close to the theoretical value of the system's installed capacity, or a practical figure that includes orientation, shading, losses, and self-consumption conditions; if you confuse these two, it's difficult to judge whether the result is too low or reasonable. In other words, when a low result appears, you should first check which stage the number corresponds to.

For example, the figure obtained by multiplying the system capacity in kW by the region-specific annual generation estimate per kW is only the initial annual kWh. If you then apply orientation correction, shading correction, and loss correction, the figure will, of course, decrease. You need to determine whether that decrease is within a normal range or whether some assumption is too strict; otherwise you risk being left with nothing but the impression that the result is “low.” In other words, a figure that looks low may not be due to a calculation error but rather to a misunderstanding of the role of the corrections.

Also, when a low result appears, it is important to separate the system size in kW and the actual energy generation in kWh. When people hear “a 5 kW system,” they tend to expect roughly 5,000 kWh per year, but in reality that fluctuates with regional and installation conditions. Conversely, even if the annual result is 5,000 kWh, you cannot determine whether that is an appropriate figure for a 5 kW system or low for a 7 kW system without looking at the assumed system capacity. In other words, whether a result is low is determined not by the absolute value but by its relation to the assumptions.

Furthermore, we should clarify whether the low power generation is truly a problem. For example, in projects that prioritize self-consumption, the kWh that overlap with daytime demand can be more important than the annual total. Conversely, in projects that emphasize electricity sales or recovery of investment, a low annual total may become a major issue. In other words, the same low figure can mean different things depending on the purpose for which the equipment is being evaluated. Keeping this perspective makes interpreting the numbers much more straightforward.

When calculation results are low, the important thing is not to feel immediate anxiety about the numbers, but to distinguish where they appear low — in the input conditions, the correction conditions, or the evaluation objective. Once that is organized, it will naturally become clear what to review next.

Point 1 Review the assumptions regarding equipment capacity

The first point to review is the assumption about the system capacity. In calculating solar power generation, the system capacity in kW is the starting point. If this is set too low, the resulting annual kWh, monthly kWh, self-consumption, and surplus will all be small. Conversely, if it is set high, the figures will be higher across the board. In other words, when low generation is observed, you should first check whether the way the system capacity was set is reasonable.

A common practical situation is that after deriving the theoretically installable capacity from the roof area, the installed capacity is set much smaller by being overly conservative. For example, if you leave too much margin at a stage when the detailed layout has not yet been decided, you end up assuming fewer kW than actually possible, and the subsequent estimated power generation tends to come out lower. In other words, taking a conservative approach to installed capacity is not wrong in itself, but if it is smaller than necessary the overall estimate becomes weak.

Also, the assumed output per panel can make a difference. For example, whether you look at 0.4 kW per panel, 0.42 kW, or 0.45 kW, the total installed capacity changes increasingly as the number of panels grows. With 20 panels a small difference is minor, but with 100 or 200 panels it becomes a significant difference. In other words, errors in system capacity are affected not only by how you assess the roof area but also by how you treat the panel specifications.

Furthermore, with roofs that have multiple faces it’s easy to overlook that the capacities for each face are summed. If you focus heavily only on the number of panels on the south face and don’t sufficiently capture the additions on the west and east faces, the total installed capacity will appear smaller. Conversely, if you judge the east and west faces too harshly and assume they won’t be used, you’ll miss out on kW that could actually be obtained. In other words, when estimating installed capacity, it’s better to examine each face carefully as well as the total to avoid underestimating.

When reviewing this point, it helps to put into words whether the assumed equipment capacity is the theoretical maximum, the practically expected value to be adopted, or a fairly conservative assumption. When generation is low, it is important first to check whether the kW itself is too small. If the input kW is small, then however favorable the subsequent conditions, the resulting kWh is unlikely to be large.

Point 2 Reassess how effective area and the number of panels are determined

The second point to review is how the usable area and the number of panels are determined. One cause of low generation output can be that, even before considering the system capacity itself, the estimate of the usable area is too conservative. Even if the roof area or the planned installation area looks large, if the actually usable area is underestimated excessively, the resulting number of panels and system capacity — and therefore the annual energy generation — will all be low.

The important thing here is to distinguish between total area and usable area. Roofs and mounting surfaces have zones where panels cannot be placed, such as edge clearances, maintenance access paths, equipment, skylights, upstands, parapets, and obstructions from columns and beams. Subtracting these to calculate the usable area is correct, but if those deductions are too large, they will cut into the number of panels that could actually be installed. In other words, being overly cautious can itself lead to underestimation.

For example, in detached houses you may reduce the number by a few when taking the roof ridge and eaves into account, but in reality it can often be secured through clever equipment placement. In warehouses and factories, skylights and ventilation equipment are sometimes overestimated, causing the usable area to be assumed much smaller. Even for carports, being overly strict about relationships with beams and columns can cause the number that could actually be accommodated to be missed. In other words, estimating usable area is not necessarily better when biased toward the safe side; it should be based on realistic layouts.

Also, the number of panels changes depending on how they are arranged. Whether they are placed horizontally or vertically, how much space is left between rows, and where aisles are positioned can significantly affect the number of panels that can be installed. In discussions about detecting insufficient area, cases judged as "not enough" have mainly been the focus until now, but conversely there are cases where it only appears to be insufficient because the assessment is too strict. When low energy output is observed, it is worth questioning whether the chosen layout is being judged too harshly.

When reviewing this point in practice, it is easier to understand if you organize total area, usable area, assumed number of panels, and adopted capacity in sequence. If you can see where the major reductions are occurring, it becomes easier to judge whether they can be improved by adjusting the layout or should be accepted as constraints of the equipment/site conditions. If you feel the power generation is low, it is important to first check whether the assumptions about usable area and the way the number of panels is determined are reasonable.

Point 3 Review how to assess orientation, slope, and shading conditions

The third point to review is how you evaluate orientation, tilt, and shading conditions. If the input value for annual energy production is not extremely low but the adjusted figure drops considerably, you may be applying overly strict assessments to these conditions. Of course orientation, tilt, and shading are important factors for energy production, but if the way they are aggregated or the way coefficients are applied is crude, the resulting value can become unnecessarily small.

Regarding orientation, the basic rule is that the closer to south-facing the better, east and west are somewhat disadvantageous, and north-leaning orientations should be viewed cautiously. However, in practice east- and west-facing surfaces are sometimes uniformly estimated quite low. In reality, east- and west-facing surfaces can still secure sufficient system capacity and can be meaningful in terms of annual totals. Especially in projects that prioritize self-consumption, they can have value by overlapping with morning or afternoon demand. In other words, orientation correction is necessary, but it is important not to underestimate east- and west-facing surfaces wholesale.

The same applies to roof pitch. If the pitch changes, the incident light conditions change, but that effect also varies by season. If you estimate the pitch too steeply because you focus strongly on the low solar altitude in winter, the annual value can be reduced more than necessary. Conversely, being overly optimistic by looking only at summer is also a problem. What’s important is to consider the meaning of the pitch over the entire year, or at least across spring, summer, autumn, and winter.

Regarding shading, estimates can sometimes end up lower when shading is overestimated rather than underestimated. If on-site verification is insufficient, it's easy to make a conservative adjustment—reducing estimates because "there might be shading." However, because the impact of shading changes with time of day and season, treating shading that occurs only in the morning, only in winter, or only on part of a surface as a major effect on the entire installation will unduly reduce estimated power generation. In other words, shading conditions are not uniform, and it's better to distinguish which surfaces are affected and by how much.

To review this point, it is useful to check whether the entire installation is being processed with a single coefficient. If you separate the south, west, and east faces, consider the effects of shading by face and by season, and clarify how you treat tilt over the year, it becomes easier to see whether the estimated generation is being made unnecessarily low. When low figures appear, be sure to check whether the azimuth, tilt, and shading adjustments are too strict.

Point 4 Reassess the treatment of regional solar radiation conditions and seasonal variations

The fourth review point is the treatment of regional solar irradiation conditions and seasonal variations. Even if equipment capacity and layout conditions are appropriate, if regional coefficients or the chosen solar irradiation values are too conservative, the annual power generation tends to come out lower overall. In particular, when using sunshine duration or solar irradiance as average input values, it is important how the characteristics of the region and the seasonal differences are incorporated.

For example, if you set the annual generation estimate per 1 kW using a rather low regional coefficient, the annual kWh will fall substantially even with the same system capacity. If this truly reflects the realities of that region, there is no problem, but if the region is only slightly below the national average and you use a much lower value, you will already be underestimating the annual generation from the outset. In other words, the way regional conditions are set can itself be the cause of low results.

Also, if you try to deal with monthly or seasonal differences with a single annual average, it can actually look lower. For example, if you focus strongly on winter conditions and significantly lower the annual average, you end up pulling down the spring and autumn periods when generation is easier. Conversely, if you look only at summer, you overlook high‑temperature losses. In other words, the more you compress everything into a single annual average, the harder it becomes to see errors caused by seasonal differences. Checking by month or by season can reveal areas that have been underestimated.

Same applies to projects that are evaluated on the basis of sunshine duration. Sunshine duration is useful as an entry point for assessing regional differences and the likelihood of clear skies, but directly linking it to power generation tends to be crude. It is important to consider not only the length of sunshine but also the strength of solar irradiance and seasonal variations. If necessary, adopting the idea of first converting sunshine duration into solar irradiance will make the way you set the input value much more stable.

To review this point, it is advisable to check not only the annual coefficient but also the monthly patterns or the seasonal patterns by spring, summer, autumn, and winter. Figures that appeared low on an annual basis may actually be skewed by an overemphasis on winter, while spring and autumn may be at adequate levels. Revisiting how regional coefficients and seasonal differences are applied is very effective for reevaluating low power generation results.

Point 5 Reexamine how loss rates and correction factors are set

The fifth review point is how loss rates and correction coefficients are applied. In generation estimates, it is common to multiply the input value derived from system capacity and regional conditions by orientation correction, shading correction, loss correction, and so on. This is the correct approach, but the more correction factors there are, the more the final kWh becomes significantly smaller, even if you intended each to be only slightly conservative. In other words, when a low figure appears, you should always suspect the accumulation of correction factors.

For example, if you slightly reduce the values for orientation, shading, losses, high temperature, and soiling—essentially pushing everything toward the conservative side—the result can fall considerably from the input value. Of course this may be reasonable depending on site conditions, but you need to verify whether the meanings of the individual corrections overlap or whether the same risk is being counted twice. In other words, correction factors may each look reasonable when considered individually, but when multiplied together they can produce figures that are much harsher than expected.

Also, even when the loss rate is summarized as a single number, if you do not understand its components, errors are likely to occur. If it is unclear which of the converter losses, wiring losses, high-temperature losses, soiling, and aging are treated as general losses and which are treated as site-specific adjustments, overlap with equipment conditions can easily arise. For example, if high-temperature losses are considered separately but the loss rate also strongly includes them, you will end up double-correcting.

Furthermore, there are cases where corrections that should be considered on a monthly or seasonal basis are applied too strongly as an annual aggregate. While it may be reasonable to give strong weight to winter shading, applying that as a large uniform coefficient across the entire year will depress generation in spring, summer, and autumn as well. In other words, when applying corrections it is important to consider not only the magnitude of a single number but also "which time axis the correction applies to."

To review this point, it is useful to break the correction coefficients down once. If you write down in words what each coefficient is for and what each represents, overlaps and excessive safety margins become easier to spot. When low power output occurs, it is very often the case that the cause is not the formula itself but the accumulation of correction factors.

Point 6 Reassess how to interpret evaluation objectives and assumptions regarding self-consumption

The sixth review point is how to interpret the evaluation purpose and the assumptions about self-consumption. This is more likely to cause a misreading of what a seemingly low figure means than to be an error in the generation amount itself. Even if the annual kWh seems smaller than expected, the assessment will differ depending on whether that is a problem with the system’s capacity, the result of an approach that prioritizes self-consumption, or an accounting that excludes sold electricity. In other words, when a low figure appears, you need to confirm what that figure represents.

For example, for projects evaluated on the assumption of self-consumption, the kWh that coincide with daytime demand are more important than the total generation. In this case, even if the annual total generation is not very large, it can still be meaningful as self-consumption. Conversely, if a project should be viewed by the total including power sales, but one focuses too much on self-consumption alone, the value of the installation can be underestimated. In other words, the reason a figure looks low may sometimes lie not in the amount of generation but in the way it is being evaluated.

Also, it is risky to judge something as “low” based solely on annual figures without looking at differences by month or time of day. For example, even if the annual figures are modest, if the installation can generate enough power to meet daytime summer demand, it may be effective for self-consumption. A system that produces surpluses in spring and autumn but tends to be insufficient in winter can still be perfectly viable depending on the application. In other words, whether something appears “low” depends greatly on what you are evaluating it for.

Furthermore, assumptions about battery storage and operational improvements are sometimes omitted. If there is an assumption that daytime surplus will be shifted to nighttime, a simple self-consumption rate alone may underestimate the value of the installation. Conversely, for a home that is often unoccupied during the day and has no battery, overestimating the self-consumption rate will lead to an overvaluation. In other words, the evaluation of generation should be done not in isolation but together with the assumptions about how it will be used.

To review this point, it is easier to understand if you keep annual generation, self-consumption, and surplus energy separate and clarify what each figure is for. When a low number appears, it is important to determine whether that number reflects low equipment capability or merely appears low because of how the data were scoped for the evaluation. In practice, the quality of equipment decisions varies significantly depending on whether this distinction is understood.

Order to proceed with reviews in practice

Taking the six points covered so far into account, you can also organize the order in which to review items when the calculated power generation is low. First, confirm whether the assumptions about system capacity are reasonable. If the kW value is too small, it will be difficult to achieve a significant improvement even after revising other items. Next, check whether the effective area and the method for determining the number of panels are overly conservative. At this stage, verify that the initial input to the system capacity is not being set smaller than necessary.

After that, review orientation, tilt, and shading conditions by surface. Check whether you are treating the entire installation in aggregate, overestimating shading, or being too strict with east- and west-facing surfaces — doing so will make the causes of excessively low annual kWh much clearer. Next, review how regional solar radiation conditions and seasonal variations are represented. Check whether you are compressing everything into a single annual average or overemphasizing winter conditions; if so, it will be easier to see where improvements can be made.

Next, break down the loss rates and correction factors. Confirm what each correction is for, whether there is any duplication, and whether they are being deducted too much as an annual lump sum. Finally, review whether the purpose of evaluating the generation output is appropriate, because the meaning of the numbers changes depending on whether you want to look at total generation, self-consumption, or include surplus and sold electricity.

If you follow this order, rather than judging a low number as "odd" based on intuition, you can sequentially isolate which part is causing it to appear low. In practice, simply keeping this sequence of checks will make reviewing estimates much more efficient.

Summary

The six points to review when the calculated output of a solar power system is low are assumptions about system capacity; how usable area and the number of panels are determined; how orientation, tilt, and shading conditions are assessed; regional insolation conditions and the handling of seasonal variations; how loss rates and correction factors are applied; and how the evaluation purpose and self-consumption assumptions are interpreted. Any one of these can cause a large difference on its own, but in practice multiple factors often overlap, making the estimate appear low.

The important thing is not to immediately conclude that the installation is unfeasible just because the numbers are low. By checking in order whether the input kW is too small, the correction factors are too strict, the handling of month-to-month differences has been over-averaged, or whether there is a problem with how the evaluation was sampled, you will surprisingly find room for improvement. In other words, consider a low result not as a sign of failure but as a figure that points to what should be reviewed.

To reduce such errors and overly low estimates, it is essential to accurately capture the site conditions. If roof edges, obstacles, elevation differences, equipment, and the way shadows fall remain ambiguous, no matter how much you refine the formulas the results will tend to vary. In particular, effective area and shading conditions are aspects where the on-site spatial relationships directly affect equipment capacity and annual kWh.

From that perspective, LRTK, an iPhone-mounted GNSS high-precision positioning device, is extremely effective as a means of accurately grasping on-site positional relationships. Because it makes it easier to accurately record the positions of roof edges and obstacles on site, it helps improve the accuracy of power generation estimates that take usable area and shading conditions into account. If the calculated solar power output is low and you want to reliably reassess the causes in practice, having a method like LRTK to properly capture on-site conditions is a major advantage.