Five ways to interpret PVSyst's monthly generation comparisons

Table of contents

• Why comparing PVSyst monthly generation is important

• Perspective 1: Compare monthly differences after aligning comparison conditions

• Perspective 2: Focus on months where differences appear, not the annual totals

• Perspective 3: Separate the influences of meteorological conditions and installation conditions by month

• Perspective 4: Break down the monthly impacts of shading, temperature, PCS, and loss coefficients

• Perspective 5: Link monthly generation differences to design decisions and on-site verification

• How to turn PVSyst monthly comparisons into practical results

Why comparing PVSyst monthly generation is important

When running PV power simulations in PVSyst, many practitioners first look at the annual generation. The annual output is an easy-to-understand indicator for grasping the overall scale and business viability of a plan, and it is convenient for internal presentations. However, looking only at annual values makes it easy to miss in which seasons design differences appear and which conditions affect which months. If you use PVSyst in practice, it is critically important to conduct a careful monthly generation comparison before focusing on the annual total.

In real projects, two proposals can have similar annual generation but very different monthly characteristics. One proposal may perform strongly in summer while another suffers less decline in winter. Or they may be similar on an annual basis but show clear differences only in spring and autumn. These differences arise because azimuth, tilt, shading conditions, temperature losses, PCS behavior, and how various loss coefficients are set manifest differently by season. The annual difference alone reveals little of this background.

Monthly generation comparisons are not just information to decide which proposal is superior. Rather, they are information to locate design features and weaknesses. If only winter is low, you might suspect shading or tilt effects; if only summer is low, you might need to revisit temperature or PCS limits. By comparing months, you can more easily work backward from generation differences to causes. PVSyst presents results from multiple perspectives, so to leverage those features you need a monthly viewpoint.

Moreover, monthly generation comparisons also help internal decision-making. If you show only annual values, decision makers tend to judge proposals solely by which number is larger. But if monthly differences are clear, you can compare proposals including their intended design emphasis—this proposal prioritizes summer peak, this one prioritizes winter stability. In practice, sharing the character of proposals in this way can be more important than a simple highest-value comparison.

What is required when comparing PVSyst monthly generation is not casually scanning graphs to sense more or less. You must align comparison conditions, identify which months exhibit differences, systematically organize the design factors creating those differences, and, if necessary, return to on-site conditions to verify. Only then do monthly generation data become practical material for judgment. Below, I organize five perspectives for that purpose from the practitioner’s viewpoint.

Perspective 1: Compare monthly differences after aligning comparison conditions

The first thing to do when comparing monthly generation is to align the comparison conditions. This may seem basic, but in practice it is the part most easily distorted and therefore most likely to cause misunderstanding. Monthly graphs make differences visually easy to see, so when multiple condition differences are mixed together they can still be read plausibly. That is why, when doing monthly comparisons in PVSyst, you must clearly state at the outset what you are changing and what you are fixing.

For example, if you want to see the effect of azimuth differences but the meteorological data location differs between cases or PCS capacity and DC/AC ratio also change, you cannot interpret the monthly differences as effects of azimuth. If you want to compare shading conditions but only one case uses different availability loss or wiring loss assumptions, the meaning of the differences shown in the graph becomes ambiguous. The same problems occur for annual comparisons, but monthly graphs can concentrate differences in particular months and thereby make assumption mismatches harder to detect.

In practice, managing conditions becomes more difficult as you increase the number of comparison cases. As you derive many similar variants, you can even become unclear yourself about what was changed. Monthly comparisons made in such a state may produce results but be hard to use for decisions. What you really want from PVSyst comparisons is not volume of numbers but the meaning of the differences. To clarify that meaning, focus on one or two variables and keep everything else fixed.

Aligning comparison conditions also makes internal explanations easier. If the same meteorological data, module conditions, and PCS conditions are used and only row spacing is changed, then the resulting monthly differences can be explained directly as the influence of row spacing. Conversely, if comparison conditions are mixed, the numbers may look impressive but the explanation becomes lengthy and the audience will find it harder to follow. In practice, the clarity of a comparison is itself valuable.

As a countermeasure, before starting monthly comparisons write one sentence stating what you want to observe in this comparison. Decide in advance whether you are examining azimuth, shading conditions, or PCS behavior, and align conditions irrelevant to the topic. If you want to leverage PVSyst's monthly generation in practice, design the comparison conditions before looking at the graphs.

Perspective 2: Focus on months where differences appear, not the annual totals

When comparing monthly generation, merely seeing which bar is higher is not sufficient. What truly matters is which months show differences and whether those differences are concentrated or spread across the year. The annual total is a convenient indicator, but whether its difference appears evenly throughout the year or opens up in certain seasons changes the design implications substantially. PVSyst's monthly graphs provide the material for reading how differences appear.

For example, if differences are large only in winter, the main causes might be shading at low solar elevations, tilt differences, or azimuth effects on winter irradiance. If differences are large only in summer, temperature losses, PCS output limits, or DC/AC ratio choices may be strongly influencing results. If differences appear only in spring and autumn, check the meteorological monthly distribution, morning/evening shading, and compatibility with angle conditions. These readings are hardly possible from annual totals alone.

Focusing on months with differences also reveals proposal personalities. One proposal may be slightly advantageous in annual total but suffer a large winter decline. Another may be slightly disadvantaged by annual totals but be stable in winter, which could be easier to manage for long-term operation. Judging only by annual totals makes it easy to lose sight of such character. By examining monthly differences carefully, you can infer the design intent behind the numbers.

Additionally, identifying months with differences helps prioritize improvements. If winter differences are large, re-evaluating shading and tilt might be the priority. If summer differences dominate, reviewing temperature loss settings or PCS parameters may be more valuable. Rather than randomly changing settings after seeing PVSyst results, start from the months with the largest differences and investigate their causes to efficiently guide design improvements.

A practical approach is: when you view the monthly graph, first find the month with the largest difference and then consider, one by one, which conditions are likely affecting that month. Even simply checking whether differences are uniform or concentrated in certain months will narrow the candidate causes significantly. In PVSyst monthly comparisons, focusing on the months where differences appear is the basic practical reading.

Perspective 3: Separate the influences of meteorological conditions and installation conditions by month

When interpreting monthly generation differences, you need to separate meteorological influences from installation influences. In PVSyst, meteorological data, azimuth, tilt, array layout, and shading conditions overlap and reflect in the monthly graph. Therefore, simply noting that a month is low or high does not readily lead to design improvements. By considering which conditions are likely to be strongly affecting each month, monthly comparisons gain practical meaning.

For instance, if winter differences are large, you should suspect not only differences in the meteorological irradiance distribution but also how azimuth and tilt differences, building shading, or self-shading act at low solar elevations. If summer differences are large, temperature conditions, temperature losses, PCS behavior, and ventilation conditions may be involved. If differences appear only in spring or autumn, check morning/evening shading and the compatibility between angle conditions and meteorological distribution. Use PVSyst monthly comparisons to form such hypotheses.

It is also important to confirm whether installation conditions match the site. A case with ideal azimuth and tilt may produce a neat monthly curve on paper, but in the actual site constraints such as aisles, slopes, or existing structures might make that layout impractical. As a result, shading or row spacing may be shifted and appear as monthly differences. What you thought was a meteorological difference might actually be caused by impractical installation conditions. When using PVSyst, develop the habit of reading monthly differences as the intersection of meteorology and installation.

With this perspective, the meaning of comparison cases deepens. One proposal may be meteorologically favorable but difficult to install. Another may be naturally installable but perform less well in a particular season. Which is better depends on the project's priorities, but distinguishing whether monthly differences are meteorological or installation-driven is essential for that judgment. When comparing monthly generation in PVSyst, it is important to read not only where differences occur but the layers of their causes.

As a practical measure, before looking at the monthly graph, hypothesize whether meteorological or installation conditions are more likely to produce differences in that project. With that preconception, you can better check which hypothesis matches the results. To connect PVSyst monthly comparisons to practice, cultivate the intent to read meteorological and installation influences separately.

Perspective 4: Break down the monthly impacts of shading, temperature, PCS, and loss coefficients

When comparing monthly generation, it is important to separate the monthly impacts of shading, temperature, PCS, and various loss coefficients. In practice, when practitioners see differences in monthly graphs they tend to jump to a single cause. However, PVSyst results arise from multiple overlapping losses, so explaining a month’s difference by a single reason can lead to misinterpretation. Organizing in your mind which losses act strongly in which months greatly advances the ability to separate causes.

For example, winter differences tend to reflect shading strongly. With lower solar elevations, the impact of building shading and self-shading becomes more noticeable than in the annual total. Summer differences often show temperature losses and PCS output limitations strongly. Differences that accumulate gradually throughout the year may be associated with wiring losses, soiling losses, or availability loss assumptions. To use PVSyst monthly comparisons effectively, read with the seasonality of loss factors in mind.

The same loss can also act differently depending on the proposal. In one case the DC side may be heavy relative to PCS capacity, making summer limits noticeable. In another case high array density may make temperature losses look stronger in summer. If shading layout differs, winter differences will grow. If you only look at graph heights without organizing these differences, it will be unclear what to improve. When comparing monthly results in PVSyst, translate differences into types of loss as you read.

It is also useful to cross-check with the loss tree and individual settings. When you find a month with a large difference, review shading conditions, temperature settings, PCS parameters, and loss coefficient assumptions in turn; doing so will clarify the background of that difference considerably. Don't try to conclude from the monthly graph alone—switch between PVSyst screens to deepen the meaning of the numbers. In practice, the ability to make that back-and-forth is what distinguishes effective analysis.

As a practical step, when you see a monthly difference, list candidate loss factors likely affecting that month and compare them to PVSyst’s settings and loss tree. This shifts the conversation from “the numbers differ” to “why they differ,” a design discussion. To make PVSyst monthly generation comparisons a strong analysis, you need the perspective of separating loss factors by month.

Perspective 5: Link monthly generation differences to design decisions and on-site verification

Finally, it is important to connect monthly generation differences to design decisions and on-site verification. Simply viewing PVSyst graphs and noting differences is only half the job in practice. What really matters is identifying which design conditions produced those differences, checking whether they are plausible against site conditions, and, if necessary, returning to revise the design. Monthly comparisons should be used not only to evaluate numbers but to determine the next design actions.

For example, if differences are large only in winter, verify whether building locations, slope directions, and morning obstacles on site would actually produce such effects. If differences are large only in summer, recheck whether array density, ventilation conditions, and PCS capacity choices align with site intuition. If monthly differences and site impressions disagree, there may be mismatches in meteorological assumptions, shading conditions, or layout conditions. Returning to the site is essential to make PVSyst monthly comparisons useful.

Monthly comparisons also help build the rationale for adopting a proposal. Even with a small annual difference, if one proposal is strong in winter and another in summer, you can more easily discuss which to prioritize based on project objectives. Including metrics such as low shading, maintainability, and aisle conditions can reveal strengths not visible from annual rankings. In practice, what matters is not choosing the highest-value proposal but explaining why a proposal fits the site.

As a practical measure, after confirming monthly differences always return to site conditions, drawings, 3D scenes, and aisle/maintenance conditions. If necessary, expand comparison cases and check how well the difference patterns align with site intuition. The meaning of comparing monthly generation in PVSyst is not to gaze at graphs but to convert those differences into design-language and link them to the site.

How to turn PVSyst monthly comparisons into practical results

What the five perspectives above have in common is treating monthly generation not as a simple list of monthly numbers. Align comparison conditions, find months with differences, distinguish whether meteorological or installation conditions are driving those differences, separate loss factors by month, and finally link results to site conditions and design decisions. When this workflow is established, PVSyst’s monthly graphs become not just supplemental material to the annual generation but practical documentation that supports design improvement and proposal explanation.

For practitioners, the important task is not merely to stare at which months are high or low. The true value is being able to explain why those monthly differences arise. Even with identical annual totals, a proposal with strong winter shading, large summer temperature losses, or PCS limitations appearing in specific periods will differ in on-site manageability and adoption value. By reading monthly generation carefully, you can organize a proposal’s character—hidden by annual totals—into practical terms.

Improving the quality of monthly comparisons also requires not completing the work with desk simulations alone. If site information is vague—site boundaries, slopes, buildings, trees, aisles, maintenance paths, existing conditions—then the meaning of monthly differences becomes vague too. To connect PVSyst numbers to practice, continuously cross-check site understanding and simulations to determine which monthly differences seem natural and where there are inconsistencies. Monthly generation is not just a graph; it reflects site conditions.

In that sense, when you need more reliable on-site position confirmation or coordinate acquisition, using high-precision GNSS devices that attach to an iPhone, such as LRTK, can be effective. If site position data and conditions gathered on site are easier to organize, assumptions about layout, obstacles, and aisle conditions used in PVSyst monthly comparisons become clearer. If you can raise the accuracy of desk comparisons in PVSyst and support on-site understanding with LRTK, monthly generation comparisons cease to be mere number comparisons and move closer to site-rooted design decisions. Reading monthly generation carefully not only deepens understanding of annual generation but also enhances the practical capability to connect desk work and on-site work.