3 Steps to Recalculate Solar Power Generation Using Remote Monitoring Data

Calculations of photovoltaic power generation do not end with pre-installation simulations. Once the actual generation equipment begins operating, site-specific conditions such as solar irradiance, temperature, shading, equipment outages, output curtailment, soiling, and aging are reflected in the generated output. Therefore, it is important to regularly compare the projected generation produced during planning with the actual values obtained via remote monitoring.

By leveraging remote monitoring data, you can not only check power generation by day, month, and time of day, but also gain clues to isolate reasons why generation is lower than expected. However, merely looking at the collected figures as they are will not lead to accurate recalculation. It is necessary to organize and normalize issues such as missing data, measurement units, equipment capacity, weather conditions, and outage history, and put them into a comparable format.

This article explains, in three steps, the process of recalculating power generation using remote monitoring data for practitioners searching for information on "solar power generation calculation." Use it as a reference when you want to check differences between pre-installation estimates and measured values, when you want to organize the causes of decreased power generation, or when you want to create calculation-based justification for internal reporting or maintenance decisions.

Table of Contents

• Key considerations to keep in mind before recalculating with remote monitoring data

• Step 1: Prepare the power generation data and make it comparable

• Step 2: Re-evaluate power output by separating weather conditions and equipment status

• Step 3: Incorporate the recalculation results into operational improvements and the next calculation

• Precautions when using remote monitoring data

• Summary: Update solar power generation calculations based on measured values

Key Considerations Before Recalculating Using Remote Monitoring Data

In calculating solar power generation, generation is generally estimated using system capacity, solar irradiance, loss factors, installation orientation, tilt angle, surrounding environment, and so on. At the pre-installation stage, annual and monthly generation are estimated based on historical weather data and design conditions. However, once actual operation begins, the calculated conditions rarely match the actual site conditions exactly.

The purpose of recalculating with remote monitoring data is not simply to check whether the forecast was right or wrong. What matters is to break down the difference between the assumptions made at planning and the actual values, and to organize that information into a form that can be used for future operational decisions. For example, even if a month's power generation was lower than expected, the response to take depends on whether that shortfall was caused by weather, equipment downtime, panel soiling, or shading.

In such cases, remote monitoring data becomes a useful basis for decision-making. If you can check generation on a daily or hourly basis, it becomes easier to see which time periods have reduced output, whether output on sunny days is close to the expected level, and whether only specific circuits are showing reduced performance. The advantage is that it makes isolating the cause easier than looking only at the monthly total.

On the other hand, remote monitoring data are not infallible. Communication failures of monitoring devices, missing data, differences in measurement intervals, differences in recording units, or discrepancies in time settings can lead to misinterpretation of calculation results. Before using the data for recalculation, you need to verify what the acquired values actually represent. If you confuse whether the values are generated energy, instantaneous power, the amount of electricity sold, or the surplus after self-consumption, your conclusions can change dramatically.

In practice, the term "generated energy" is often used with multiple meanings. It can refer to the amount of electrical energy generated by the entire solar power installation, or it can refer to the amount of electrical energy sent to the grid. In self-consumption systems, part of the generated electricity is used within the building, and the remainder may be recorded as surplus. In such cases, remote monitoring data and the utility's metering data may not match. Therefore, in recalculation, it is important to first clarify which measurement point's data is being used.

In recalculations using remote monitoring data, it is more helpful to adjust planned values based on measured data than to recreate theoretical values. Rather than using the planning formulas unchanged, revise expected generation to better reflect actual generation trends, downtime, weather conditions, and equipment condition, bringing the estimates closer to on-site reality. Performing this process regularly leads to earlier detection of anomalies, revision of maintenance plans, and improved accuracy of generation reporting.

Step 1: Prepare the power generation data and make it comparable

The first step is to prepare remote monitoring data for comparison rather than using it directly in calculations. A common mistake when recalculating power generation is comparing planned and actual values without thoroughly checking the meaning and period of the acquired data. Unless the date, time, units, the equipment in question, and the presence or absence of missing data are aligned, you cannot correctly determine the reason for any discrepancy.

First, what you need to confirm is the period to be recalculated. Whether you are reviewing annual generation, checking month-by-month, or investigating anomalies on a specific day, the required data granularity will differ. Even when recalculating annual generation, reviewing monthly or daily data makes it easier to detect whether there has been a large drop confined to a specific period. This is because monthly totals alone can make it hard to see stoppages or communication losses lasting a few days.

Next, check the unit for generated energy. Generated electricity is usually treated as the amount of electricity produced over a certain period of time. On the other hand, the remote monitoring screen may display instantaneous output. Instantaneous output is the output at a specific point in time and is not, by itself, the amount of electricity generated in a day. When recalculating generated energy, you need to confirm whether the value is the sum of outputs for each hour or whether it has already been aggregated by day or by month.

Also, matching the data to the system capacity is important. For example, in systems with multiple power conditioners or multiple circuits, you need to confirm whether the monitoring data are totals for the entire system or values for only part of the equipment. If you are looking at only some circuits but compare them to the design values for the whole system, a large discrepancy will naturally appear. Conversely, if you evaluate performance by dividing the total system generation by a partial capacity, you may overstate the generation efficiency.

Checking for missing data is also essential. Because remote monitoring is affected by the communication environment and equipment condition, there may be periods when data cannot be obtained. Whether you treat a missing period as zero generation or exclude it as missing changes how monthly and annual generation appear. It is necessary to distinguish whether generation actually stopped or only the communication did. If the loss is due to communication, it may be possible to supplement it with other metered values or on-site records.

Be careful about time offsets. If the timestamps in monitoring data are offset from the actual local time, you can draw incorrect conclusions when analyzing generation by time of day. In particular, when checking morning and evening effects or peak periods, a time offset can affect root-cause analysis. Looking only at daily totals may not be a major issue, but when recalculating using hourly output curves, it is safer to verify the time settings.

When preparing the data, the basic rule is to match the aggregation units used in the generation calculations at the planning stage. If monthly generation was calculated during planning, aggregate the remote monitoring data on a monthly basis as well. If you want to compare on a daily basis, prepare the planned or baseline values in a form that is close to daily. Aligning the units of comparison makes it easier to explain the differences.

As a preprocessing step before recalculation, it is also important to check for obviously anomalous values. Data such as power generation being recorded at night, large generation on equipment downtime days, suddenly dropping to zero on sunny days, or the same value persisting for long periods may indicate measurement or communication problems. Mechanically aggregating these can reduce the reliability of the recalculation results.

At this stage, the goal is not to produce clean numbers but to create a dataset usable for decision-making. If there are missing values or outliers, instead of forcibly removing them, record what problems occurred and when. This is because later, when explaining differences in power generation, you can make explicit the limitations of the data.

After organizing the data, divide the energy generated during the period of interest by the installed capacity and check it as generation per unit of capacity; this makes comparisons easier. When comparing multiple sites with different scales, expressing values per unit of capacity also makes trends easier to see. However, do not judge performance solely by generation per unit of capacity; it should be considered together with solar irradiance conditions and installation conditions.

By the end of Step 1, the goal is to have clearly established "when", "which facility", "which measurement point", and "which unit" of data will be used. If this organization is completed, it will be easier in the next step to separate and interpret meteorological conditions and equipment status. Conversely, if this preprocessing remains ambiguous, you may be able to produce recalculation results, but the numbers will be difficult to use for operational decision-making.

Step 2: Reassess power output by separating weather conditions and equipment status

In the next step, using the organized remote monitoring data, re-examine differences in generated power by separating them into weather conditions and equipment condition. Because solar power generation is heavily influenced by solar irradiance, it is not appropriate to immediately conclude an equipment fault just because generation is low. Months with many cloudy or rainy days will see reduced generation even with properly functioning equipment. Conversely, if output does not increase on sunny days, it becomes more likely that the cause lies with the equipment or the surrounding environment.

When recalculating, first check the weather trends for the target period. If solar irradiance data can be obtained, viewing it together with generation makes it easier to determine whether a drop in generation is within a natural range. Even if irradiance data are not available, roughly classifying days as clear, cloudy, and rainy and simply comparing the output curves for clear days is still effective. In practice, rather than trying to match every condition perfectly, it is important to separate factors to the level necessary for making a judgment.

When re-evaluating power generation, pay attention not only to the monthly total but also to the hourly output on clear days. The output curve on clear days is useful for checking the condition of the equipment. If output is low only in the morning, shadows on the east side or problems in some circuits may be suspected. If output is low only in the afternoon, it provides a prompt to check for shadows on the west side, surrounding structures, temperature rise of equipment, or effects of output control. If output levels off around midday, you need to check the equipment capacity and control settings.

What should be noted here is not to attribute differences in power output to a single cause. In actual field situations, meteorological conditions, panel temperature, soiling, shading, equipment downtime, curtailment, and measurement errors can overlap and affect generation. When recalculating, even if it is difficult to completely separate each factor, it is important at least to distinguish between "differences explainable by weather" and "differences that warrant checking equipment condition."

For example, if monthly power generation is lower than planned, first check how many sunny days there were in the same month. If there were many rainy days, the monthly shortfall may be mainly due to weather conditions. However, if generation on sunny days is lower than on past sunny days, the condition of the equipment needs to be checked. Conversely, if output on sunny days is stable and there are simply more cloudy or rainy days, the likelihood of equipment abnormalities is relatively low.

When checking equipment status, compare at the granularity available — by power conditioner unit, by circuit, by string, etc. Even if the facility’s total power generation is low, the cause differs depending on whether all systems are similarly low or only some are. If only some are reduced, check for poor connections, equipment shutdowns, panel soiling, shading, open/disconnected wiring, or protection operation. If the reduction is overall, check weather conditions, temperature conditions, overall soiling, output control, and differences in measurement points.

In recalculation, it's important not only to recompute the total generation but also to clarify the approach to adjustments. For example, actual generation that includes periods of equipment downtime is important for evaluating actual project financial performance and utilization. On the other hand, if you want to assess the generation capacity when the equipment was operating normally, you need to exclude downtime periods or treat the downtime hours separately. Both values are meaningful, but they serve different purposes.

In internal reports, explaining "actual power generation" and "reference values that take outages and losses into account" separately helps prevent misunderstandings. Actual power generation is the result actually obtained, while the reference value is used to understand equipment capacity and potential for improvement. If the two are confused, it becomes difficult to tell whether the equipment performed poorly, whether operational stoppages had an impact, or whether the weather was the cause.

Also, when recalculating power generation, it is important not to estimate loss factors too finely. In practice, there are limits to the accuracy of measurement data and the information that can be obtained. Trying to strictly quantify all losses—shading losses, temperature losses, soiling losses, and equipment losses—can actually make the basis more ambiguous. It is more realistic to first take an approach of making adjustments, within an explainable range, based on facts that can be confirmed from remote monitoring data.

Comparing by time of day is also effective. Because solar power generates during daytime, looking at how output behaves in the morning, at noon, and in the evening can reveal changes in the installation environment. If afternoons used to be stable but recently only the afternoon output has fallen, it can prompt checks for nearby trees or structures, snow accumulation, uneven soiling, and the like. By regularly comparing sunny days with the same conditions, you can verify whether the assumptions used for generation calculations have changed.

Don't forget to account for seasonal differences. In summer, although the hours of sunlight are longer, panel temperatures tend to rise and there can be periods when output does not increase as much. In winter, the solar incidence angle is lower, and some locations are more susceptible to shading. In snowy regions, snow on the panels and the surrounding reflective conditions can also affect power generation. When recalculating using remote monitoring data, it's better to separate trends by month or by season, as this makes it easier to understand on-site conditions than looking only at the annual total.

In this step, the important thing is to attach explanations to the recalculated results. Simply stating that a value is "a certain percentage lower than the planned value" does not lead to next actions. By separating and organizing differences caused by weather, differences caused by stoppages, and differences that require equipment inspections, you can link them to maintenance inspections, cleaning, verification of settings, and revision of future forecasts. Remote monitoring data should be used not only to gather numbers but to prioritize decisions.

Step 3: Reflect the recalculation results in operational improvements and in the next calculation

The final step is to incorporate the recalculated power generation into operational improvements and the next calculation. Recalculating power generation is not something that ends with creating a table once. The trends revealed by measured values only have meaning when they are incorporated into inspection plans, reporting materials, revenue-and-expenditure forecasts, and equipment management standards. The advantage of using remote monitoring data is that it enables continuous verification of actual performance.

First, organize the recalculation results as management indicators on a monthly or quarterly basis. If you keep the planned values, actual values, adjusted reference values, and the main causes of differences in the same format, it will be easier to compare them in future periods. For example, if low power generation in a given month was due to the weather, record that fact. If it was caused by equipment downtime, record the outage start time, the affected equipment, the recovery time, and the estimated impact. Having such records makes it easier to explain annual power generation when reviewing it later.

Next, identify operational improvements from the recalculation results. If output for some systems remains low even on clear days, you can narrow down inspection targets. If morning and evening effects are larger than expected, check sources of shading and seasonal changes. If soiling, bird damage, fallen leaves, or snow are suspected, use this to prompt on-site verification or decisions about cleaning. Rather than determining the cause solely from remote monitoring data, it is practical to use the data as a basis for prioritizing on-site inspections.

The recalculated power generation results can also be reflected in future power generation forecasts. Pre-installation simulations are estimates based on design assumptions. However, once several months to several years of actual performance have been accumulated, the generation trends specific to that equipment become apparent. By adjusting the planned values based on measured data, monthly and annual power generation for the following year and beyond can be estimated in a way that more closely reflects on-site conditions.

However, you should be careful about using actual historical values alone for future forecasts. If a given year had particularly unfavorable weather, using that year’s generation as the baseline could cause you to underestimate the outlook for the following year. Conversely, using only years with favorable weather as the baseline could lead to overestimating the outlook. When recalculating, you can reduce the impact of extreme years by emphasizing actual values while separately examining meteorological conditions and outage history.

Recalculating power generation helps create benchmarks for anomaly detection. By accumulating past clear-sky day data, you can determine the expected power output for the same season and under similar solar irradiance conditions. If output deviates significantly from that benchmark, you can promptly investigate. Establishing benchmarks not only for the overall facility's power generation but also at the equipment and circuit level can help detect localized anomalies.

What is important for practitioners is to present the results of recalculations in a form that is easy to explain. Simply listing technical formulas may not be easily understood by internal stakeholders or managers. It is important to organize in writing which period was used, which data were used, what was adjusted, and what judgment was reached. If the calculation basis is clear, it becomes easier to use for decisions on maintenance costs, prioritizing equipment improvements, and explanations to customers.

When saving recalculation results, record not only the numbers but also the underlying assumptions. By recording the target equipment's capacity, the target period, the types of remote monitoring data used, how missing data were treated, how downtime was handled, and the approach to weather correction, the next person responsible can review using the same criteria. The ability to compare with the previous analysis using the same approach, even when the person responsible changes, is highly significant for continuous equipment management.

Also, when recalculation reveals a trend of decreased power generation, it is important not to rush to conclusions and to proceed with additional verification steps. Even if remote monitoring data show a drop in output, on-site inspection may reveal that it was caused by a communication failure or a problem at the measurement point. Conversely, a small difference in remote monitoring may correspond to progressing soiling or shading of some panels at the site. Remote monitoring data should not replace on-site inspection, but be positioned as information to help prioritize and make on-site checks more efficient.

The frequency of recalculation depends on the scale of the installation and its operational purpose. For large installations or systems where power generation directly affects business revenue, it is worthwhile to check on a monthly basis. Even for small installations, reviewing them seasonally or whenever an anomaly is suspected can lead to early detection of problems. The important thing is not to wait until generation has dropped significantly and then hurriedly check, but to have a baseline you can regularly compare against.

The objective of Step 3 is to shift recalculation from a task performed merely for reporting into management that drives further improvements. By utilizing remote monitoring data, changes in power generation can be continuously tracked. Reflecting those changes in the calculations and, when necessary, linking them to inspections or operational adjustments makes it easier to improve the management accuracy of solar power generation facilities.

Precautions When Using Remote Monitoring Data

When recalculating solar power output using remote monitoring data, there are caveats despite its convenience. The largest caveat is not to regard the displayed figures as the correct actual values as they are. The numbers on the monitoring screen can vary in meaning depending on the measurement instruments, communication paths, aggregation methods, and display settings. Before using them for recalculation, you need to confirm the definitions of the data.

Especially for systems that include self-consumption, generation, consumption, purchased electricity, sold electricity, and surplus are easily confused. If the objective is to recalculate generation, the basic approach is to use the actual amount of electricity generated by the photovoltaic system. Looking only at the amount sold can fail to reflect the electricity consumed within the building and may lead to underestimating generation. Conversely, if you want to assess the effect of reducing electricity consumption, you need to check not only generation but also changes in self-consumption and purchased electricity.

Care must also be taken when handling missing data. If you aggregate periods missing due to communication failures as zeros, energy production may appear lower than it actually is. Conversely, naively filling in missing periods can produce figures with little justification. When there are missing data, it is safer to explicitly indicate the missing periods and treat the cases with and without imputation separately.

Handling output curtailment and equipment shutdowns is also important. During periods when output curtailment occurred, generation may not increase even under favorable solar irradiance conditions. When equipment is shut down or taken offline for inspection, actual generation can fall for reasons unrelated to the plant’s capacity. If these factors are not considered and one concludes that "generation performance is low," it can lead to incorrect conclusions. In recalculations, it is desirable to check the history of shutdowns and control actions as thoroughly as possible and include them in the explanation for differences in generation.

Also, caution is required when judging aging-related degradation based solely on remote monitoring data. Even if power generation appears to be declining over the long term, weather, soiling, the surrounding environment, shading, equipment replacement, and changes in measurement conditions may be influencing it. When evaluating long-term changes, it is important to compare data from the same season, under similar solar irradiance conditions, and with the same measurement conditions. Comparing only simple annual totals can lead to misidentifying the cause.

Care should also be taken in how calculation results are presented. Rather than stating definitively the reasons for low power generation, record verifiable facts and assumptions separately. For example, "power generation was low during this period," "there was a communication outage during this period," and "there may have been an equipment malfunction during this period" each have different meanings. In recalculation reports, separating facts, how they were treated in the calculations, and items to be confirmed makes it easier for stakeholders to decide on next actions.

Furthermore, when comparing remote monitoring data across multiple installations, it is necessary to take differences in site conditions into account. Even with the same installed capacity, power generation will vary depending on installation orientation, tilt angle, surrounding shading, local solar irradiance conditions, the presence or absence of snow, the timing of operation start, and equipment configuration. Judging superiority or inferiority solely by generation per unit of capacity can lead to comparisons that ignore on-site conditions.

In recalculating solar power generation, balancing precision and practicality is also important. Trying to quantify every factor completely makes the calculations complex and difficult to put into operation. In practice, a realistic workflow is to first check the quality of remote monitoring data, then isolate the major contributing factors to differences, and proceed to detailed investigations as needed. Rather than chasing down tiny errors, prioritizing early detection of generation declines and signs of anomalies is more useful for equipment management.

Remote monitoring data is not only material for calculations but also a record for understanding the site. By accumulating daily power generation, changes in output, shutdown history, abnormal notifications, and recovery status, trends for each facility become apparent. If those trends are reflected in power generation calculations, you can create management indicators that are close to actual site conditions rather than mere desk-based estimates.

Summary: Update solar power generation calculations starting from measured values

Recalculating solar power generation using remote monitoring data is an important task for verifying the differences between planned and actual values and leveraging them for equipment management. The first step is to organize the generation data and make it comparable. Checking the target period, units, measurement points, equipment capacity, and whether there are any missing data stabilizes the basis for recalculation.

Next, reassess power generation by separating meteorological conditions from equipment status. Even if generation is lower than expected, it is important to determine whether this is due to weather, shutdowns or output curtailment, or whether equipment inspection is required. Not only looking at monthly totals, but also examining hourly output on sunny days and comparisons at the equipment-unit level makes it easier to pinpoint the cause.

Finally, incorporate the recalculation results into operational improvements and into the next calculations. The recalculated figures can be used for internal reporting, maintenance inspections, cleaning decisions, revising future forecasts, and establishing criteria for anomaly detection. It is important to record not only the calculation results but also the underlying assumptions and factors causing deviations. This makes it possible to verify power generation using the same criteria going forward and makes it easier to improve the accuracy of equipment management.

Calculating solar power generation is not a one-time task performed before installation. By continuously using remote monitoring data, you can conduct reviews based on actual measurements and more quickly detect signs of declining output and operational issues. It is important to organize planned values, actual results, and adjusted values, and to update generation management to match site conditions.

When recalculating power generation using remote monitoring data, it is effective to consider not only numerical aggregation but also on-site verification and record management. If you want to efficiently carry out reviews of generation, assess equipment condition, and reconcile with on-site information, it is important to combine remote monitoring data, local records, and inspection results to update power generation calculations while preserving supporting evidence.