How to Increase Power Generation and Cost-Effectiveness | 6 Decision Criteria to Consider

Table of Contents

• Basics for Increasing Power Generation and Evaluating Cost-effectiveness

• Decision Axis 1: Identify Improvement Potential from Power Generation Data

• Decision Axis 2: Separate Weather and Seasonal Factors from Site-specific Factors

• Decision Axis 3: Compare the Effects of Cleaning, Weeding, and Shading Countermeasures

• Decision Axis 4: Confirm Losses from PCS, Connection Points, and Cable Abnormalities

• Decision Axis 5: Include Recurrence Prevention and Ease of Inspection in the Assessment

• Decision Axis 6: Verify Cost-effectiveness Using Records Before and After Measures

• How to Proceed Without Misprioritizing When Improving Power Generation

• Summary

Basics of Increasing Power Generation and Evaluating Cost-Effectiveness

When considering how to increase the power output of a solar power generation system, the first important thing is not to rush into major measures. If you feel that output is low, not increasing as expected, or has dropped compared with before, you may be tempted to hastily consider panel cleaning, weeding, equipment inspections, or facility upgrades. However, if you implement countermeasures without confirming the cause of the output decline, the improvement effect may be small relative to the workload. From a cost-effectiveness perspective, it is important to first isolate the causes of generation loss and then address the areas that have the greatest impact on output.

In solar power generation, you cannot increase the solar irradiance itself at the site. You cannot increase the number of sunny days or change the seasonal solar altitude. However, you can move closer to a state in which the incident solar radiation is converted into electricity with as little waste as possible. In other words, in practical terms, increasing generation means identifying the causes of lost potential generation and reducing those losses.

The causes of reduced power generation are not singular. Dirt on the panel surface, bird droppings and fallen leaves, shading from weeds or trees, faults in connections, cable damage, PCS stoppages, output curtailment, temperature increases, poor drainage, and insufficient inspection records—various factors can combine. Even if panels look dirty, shading in the morning and evening may actually be the primary cause. Even when grass is overgrown, the main reason for reduced output might be short-term PCS stoppages. Conversely, even if the site looks normal, it may be that only a specific string is underperforming.

To improve cost-effectiveness, you need to correlate power generation data with on-site conditions. Determine when output is low, which equipment is underperforming, whether there is a difference compared with equipment under the same conditions, whether output is low even on sunny days, and whether it becomes unstable after rain. Based on that, prioritize cleaning, weeding, shading countermeasures, checking connections, PCS checks, drainage measures, and record management. Simply knowing that generation is low does not tell you where to start.

When judging cost-effectiveness, what's important is not simply the burden a measure imposes, but which power generation losses it can reduce and by how much. Even if the operational burden is small, the effect will be limited if the impact on power output is small. Conversely, if you can accurately identify the causes of major power generation losses, comparatively small improvements can lead to a recovery in power output. When improving power output, alignment with the cause is more important than the scale of the measure.

Evaluation Axis 1: Identify improvement potential from power generation data

The first metric to check when evaluating cost-effectiveness is the power generation data. Before starting cleaning or weeding on site, identify which time periods, which equipment, and what kinds of declines are occurring. Looking only at monthly or annual generation hides the timing of generation losses and differences at the equipment level. Even if nothing appears abnormal on a monthly basis, generation may drop only during certain hours of sunny days, or be low only for a specific row, a specific string, or the areas connected to a specific PCS.

If morning generation is low, shadows from trees on the east or southeast side, slopes, weeds, surrounding structures, or adjacent equipment may be involved. If generation is low in the evening, check for shadows on the west or southwest side, nearby terrain, and tree growth. If the midday peak does not develop, possible causes include dirt on the panel surface, temperature rise, PCS restrictions, output curtailment, equipment shutdowns, or string-level anomalies. If the generation curve drops suddenly even on sunny days, the PCS shutdown history and alarm history need to be cross-checked with the timestamps.

When reviewing power generation data, use sunny days as the baseline whenever possible. On cloudy or rainy days, generation fluctuates significantly due to moving clouds, making it difficult to determine whether a change is caused by equipment abnormalities or by weather. On the generation curve for a sunny day, time-of-day dips from shading, plateauing due to output curtailment, sudden drops from equipment shutdowns, and per-equipment differences caused by string anomalies are easier to see.

It is also important to compare with facilities under the same conditions. Compare installations with similar azimuth, tilt, number of panels, shading conditions, and connection configurations, and look for spots that are consistently lower among installations that should have similar power output. If you only look at the plant-wide aggregate, some anomalies can be masked by the average. When only a specific area is underperforming, there is a high likelihood that there is room to improve its power generation.

From a cost-effectiveness perspective, data verification itself is a critically important process. By narrowing the range of decline using power generation data, you can narrow the targets for on-site inspections and countermeasures. Rather than inspecting a large plant indiscriminately, focusing inspections on equipment that is experiencing generation losses allows you to find the causes that lead to improvements more quickly. The first step in improving power generation output is not on-site work, but identifying where improvements can be made from the data.

Decision Axis 2: Separate weather and seasonal factors from site-specific factors

When you notice a drop in power generation, it is risky to immediately conclude there is a problem on site. Solar power generation is greatly affected by solar irradiance, so during periods with many cloudy or rainy days, generation will fall even if the equipment is functioning properly. In winter, systems are particularly affected by solar altitude and shorter hours of sunlight, and in summer high temperatures can make it harder for power output to reach expected levels. If you ignore these natural variations and take measures regardless, you may end up performing work with poor cost-effectiveness.

On the other hand, you must avoid blaming the weather or season and overlooking abnormalities on site. If the entire power plant is declining in the same way in line with local weather, the influence of solar irradiance conditions is likely significant. However, if only part of the plant is lower while other equipment at the same plant is operating normally, or there is a clear difference compared with equipment under the same conditions, the weather alone cannot explain it. In that case, you need to check for causes that can be remedied on site, such as soiling, shading, poor connections, PCS shutdown, or output curtailment.

To separate weather effects from site factors, compare sunny days with each other and days with similar weather. Cloudy or rainy days have large fluctuations in power generation, which makes it harder to discern the characteristics of anomalies. By checking the power generation curves on sunny days, it becomes easier to find shadows that fall at the same time each day, string anomalies where only specific equipment shows low output, and equipment shutdowns that drop output for a limited period. Do not isolate only low-generation days; it is important to compare them with days that have similar conditions.

Seasonal causes are also considered. In spring, panels are prone to soiling from pollen, yellow sand, and dust. From the rainy season to summer, weeds can grow and cast shadows on the front of the panels. In summer, be aware of output reductions due to high temperatures and poor ventilation. After typhoons or heavy rain, check for fallen debris, sediment, drainage problems, and the condition around cables. In autumn, watch for fallen leaves; in winter, watch for shadows from the low sun angle, frost, and snow accumulation.

For cost-effectiveness, it is essential to separate natural declines in power output from on-site generation losses that can be corrected. If weather is the main cause, cleaning or repairs will not significantly improve power output. Conversely, if a specific area remains low even on sunny days, there may be room for improvement on site. Before considering ways to increase power output, it is important to first determine whether the decline is one that can be improved.

Evaluation Axis 3: Comparing the Effectiveness of Cleaning, Weeding, and Shade Countermeasures

Measures often considered to improve power output include panel cleaning, vegetation control, and shading countermeasures. These are relatively easy to inspect on site and, if performed appropriately, can potentially lead to recovery of power generation. However, before carrying out cleaning or vegetation removal, it is necessary to confirm that the cause of the power decline corresponds to the planned scope of work. Just because dirt or vegetation is visible does not necessarily mean it is the primary cause of the reduced power output.

Contamination on the panel surface is a common factor that reduces the amount of light received. Soil dust, pollen, yellow sand, bird droppings, fallen leaves, sap, and surrounding dust particles can adhere to the panel surface and may reduce power output. In particular, banded dirt remaining at the lower edge of a panel or around the frame can affect power generation even if it is not noticeable from a distance. When deciding whether to clean, check whether the equipment with low power output corresponds to the area of contamination.

Shadows from weeds and trees are also important. Even if grass is not touching the panels, at the low sun angles in the morning and evening shadows can stretch and reduce power generation. Even if an on-site inspection at noon shows no problems, shadows may appear in the morning or evening. Trees that did not cause problems at the time of installation can grow over several years and cast shadows in winter or at sunrise and sunset. For shadow mitigation, it is important to check the site at the times when power generation data shows a decline.

To improve cost-effectiveness, ensure you can compare power generation before and after cleaning or weeding. Record photos before and after cleaning, the work area, the work date, weather conditions, and changes in power generation. If power generation improves after cleaning, soiling may have had a significant impact at that site. If morning and evening power generation improve after weeding, it is likely that shading from weeds was contributing to generation loss. If no effect is observed, it is necessary to investigate other causes.

Cleaning and weeding are not tasks to improve appearance; they are measures to reduce power generation losses. Even if you tidy areas that have little impact on generation first, cost-effectiveness will not improve. It is important to prioritize installations with low power output, shadows with long duration, rows with concentrated dirt, and places prone to weed regrowth. Linking the scope of work to power generation data makes it easier to explain the effectiveness of the measures.

Decision Axis 4: Verify losses from PCS, connection points, and cable abnormalities

If cleaning or weeding does not restore power output, or if there is a sharp drop or plateau in the generation curve, it is necessary to check for abnormalities in the PCS, connections, cables, and strings. Even if the solar panels are generating normally, if there is a fault in the path that extracts the electricity or in the conversion equipment, the power output will not increase. Even when there are no visible abnormalities, generation losses may appear in the data.

When checking PCS, first compare the power generation of each PCS unit. If a specific PCS is lower compared to PCS under the same conditions, you need to inspect the PCS unit itself, the input side, the output side, and the surrounding environment. If the generation curve suddenly drops partway, correlate the shutdown history and alarm history with the timestamps. Even a brief stoppage can cause large losses if it occurs during daytime when generation is high.

Also check for output curtailment and saturation. If the top of the generation curve flattens on sunny days, possible causes include PCS output limits, equipment capacity ceilings, temperature rise, input-side shortages, and measurement anomalies. This does not necessarily indicate equipment failure, but if it occurs during periods that have a large impact on generation, it should be prioritized for inspection. Make an assessment by combining historical records, the generation curve, and differences from equipment under the same conditions.

Strings, connection points, and cables are also important items to check. If only a particular string shows low output, consider dirt, shading, panel abnormalities, poor connections, or cable damage. If anomalies tend to appear after rain, suspect water ingress or issues around the connection points. In areas with heavy weeds, cables can become hard to see, increasing the likelihood of overlooking damage from mowing or animal activity.

In inspections of electrical equipment, safety is the top priority. Even if you want to increase power output, on-site personnel should avoid forcibly opening equipment or touching connection points to make an assessment. First, organize the equipment suspected of abnormalities, the time of occurrence, changes in power output, historical records, on-site photos, and the surrounding environment, and, as necessary, arrange for a professional inspection. When assessing cost-effectiveness, it is important to prioritize checking abnormalities that have a large impact on power output and are related to safety.

Evaluation Criterion 5: Make judgments that include recurrence prevention and ease of inspection

From a cost-effectiveness perspective, you need to evaluate not only the immediate recovery in power generation but also measures to prevent recurrence and to make inspections easier. Even if cleaning temporarily restores power output, if the same spots become dirty again quickly, that does not constitute a fundamental improvement. If you remove weeds but they grow back in the same places, generation losses from shading will be repeated. Even if you repair connection points, if causes such as moisture, puddles, or exposed cables remain, abnormalities may occur again.

Drainage and terrain may seem unrelated to power generation. However, places where water tends to pool, where sediment washes in, paths that easily become muddy, slope failures, and areas where cables are likely to be exposed can lead to soiling, weed growth, connection faults, and reduced ease of inspection. If, after rain, the same locations see grass growing, sediment accumulating, or paths becoming difficult to use, drainage and terrain should be checked.

Ease of inspection also affects cost-effectiveness. On sites that are difficult to inspect, anomalies are discovered late. If grass has overgrown and paths are impassable, the ground is too muddy to approach, equipment numbers are hard to read, or photos alone don't convey location, inspections and repairs take longer. Even if low-generating equipment is identified from the data, corrective action will be delayed if it is hard to reach the corresponding spot on site.

If you want to prevent recurrence, you check the underlying factors behind the measures. You don't just clean dirt; you look at why that spot gets dirty easily. You don't just cut the grass; you check why grass tends to grow in that location. You don't just inspect around the PCS; you manage the area so that grass and deposits that impede ventilation do not recur. The cost-effectiveness of improving power generation depends not only on the immediate effect of the work itself but also on how much recurrence can be reduced.

Under this decision criterion, measures that do not immediately appear as increases in power generation are also important. Improving drainage, ensuring clear access routes, making equipment identification numbers easy to read, inspection records with location information, and sharing locations of recurring problems may seem mundane in the short term. However, over the long term they reduce missed inspections, duplicated work, and delays in anomaly detection, helping to keep generation losses small. If you consider cost-effectiveness over the long term, it is important not to neglect recurrence prevention and ease of inspection.

Evaluation Axis 6: Verify cost-effectiveness using pre- and post-measure records

To judge the cost-effectiveness of measures to improve power generation, records from before and after the measures are indispensable. Even if you perform cleaning, weeding, pruning, inspections of connection points, PCS checks, and drainage measures, you cannot determine whether those actions were effective unless you have recorded the condition before the measures and the power generation after the measures. Relying only on the subjective feeling "it seems better" makes it difficult to use for decision-making next time.

What should be recorded are the locations of equipment with low power generation, the characteristics of the generation curves, photos before countermeasures, the work area, the work performed, photos after the work, weather conditions, and changes in power generation. If cleaning was performed, comparing cleaned and uncleaned areas makes it easier to confirm the effect. If weeding was performed, check whether power generation in the morning and evening improved. If ventilation around the PCS was improved, check whether there were any stoppages or alarms and whether the daytime generation curve changed.

When comparing power generation, take weather conditions into account. If the weather differs significantly before and after measures are implemented, a simple comparison is not possible. As much as possible, compare sunny days with sunny days and systems under the same conditions. Even if a clear difference does not appear immediately, observing trends over multiple days makes it easier to judge. Combining power generation data with on-site records makes it easier to explain the effects of the measures.

Measures that had a large effect will be given higher priority in future. For example, if power output improved after spring cleaning, then spring dirt management is important at that site. If morning and evening power output improved after summer weeding, then shading from weeds becomes an important maintenance item. If the PCS stoppage history matched the decline in power output, prioritize regular checks of the equipment history. Measures that had a small effect should lead to a reexamination of the causes.

Without records, you end up searching for the same problem from scratch each time. When the person in charge changes, it becomes unclear where dirt accumulates easily, which lanes are prone to shadows, and which PCS experience frequent stoppages. If you record location information, photos, equipment numbers, and work histories together, stakeholders can more easily verify the same locations. To improve cost-effectiveness, it's necessary not only to implement countermeasures but also to verify their effectiveness and apply the findings to future decisions.

How to Avoid Misprioritizing When Improving Power Output

To avoid mistakes in prioritization when improving power generation, first identify the areas with the largest generation losses. Rather than addressing the most conspicuous problems in order, prioritize equipment or time periods where a decline is clearly shown in the generation data. Equipment that has a large impact on generation output, shadows that affect for long periods, soiling that recurs, PCS that experience frequent stoppages even for short periods, and connection points that become unstable after rain should be checked as priorities.

Next, evaluate the ease of implementation of countermeasures and the likelihood of recurrence. Cleaning and weeding are relatively easy measures to carry out, but their effect is limited unless they address the actual cause of the power output decline. Checking connection points and the PCS may require specialist judgment, but if generation losses are large, their priority increases. Improvements to drainage and inspection access routes may not immediately appear as increases in power output, but they are important for preventing recurrence.

In improving power generation, it is also important to separate short-term effects from long-term management effects. Panel cleaning and weeding can produce relatively quick effects when they are the underlying causes. On the other hand, drainage improvements and record management may not be visible as short-term increases in power output, but in the long term they help prevent the same generation losses from recurring. When judging cost-effectiveness, it is necessary to consider not only immediate power output but also recurrence prevention and inspection efficiency.

Also, it is important not to try to complete measures in a single attempt. A solar power plant is an outdoor facility, and its condition changes with the seasons, weather, surrounding environment, and the aging of equipment. Even if you clean it, dirt will return; even if you remove weeds, they will grow back; trees will grow; and PCS and connection points will also change condition. To steadily increase power generation, operations that repeat inspection, measures, verification of effectiveness, and record updates are necessary.

Sharing priorities on-site is also essential. At large power plants, photos alone can make it difficult to convey location. By linking equipment numbers, location information, photos, work histories, and power generation data, on-site staff, managers, inspection staff, and repair staff can more easily identify the same location. When priorities are shared, missed checks and duplicated work are reduced, making it easier to improve the cost-effectiveness of measures to increase power output.

Summary

When considering ways to increase power generation and cost-effectiveness, it is important not to decide on the measures themselves first, but to identify the causes of generation losses and prioritize addressing the areas with the greatest potential for improvement. In solar power generation, you cannot increase the solar irradiance itself at the site. However, you can improve generation by bringing the system closer to a state in which the received sunlight is converted into electricity without waste. To do so, it is necessary to check, in order, power generation data, weather and seasonal factors, dirt and shading, PCS and connection points, drainage and ease of inspection, and records before and after measures.

To improve cost-effectiveness, first narrow down the time periods and the equipment areas of the output decline using power generation data. Next, distinguish whether the decline is a natural decrease due to weather or season, or generation loss that can be improved on site. Then consider cleaning, weeding, shading countermeasures, checking connections, checking the PCS, and drainage measures. Rather than deciding to clean simply because there is dirt or to weed simply because there is grass, it is important to confirm whether the scope and timing of the output decline match the cause.

Also, cost-effectiveness cannot be verified without records from before and after the measures. After performing cleaning, weeding, repairs, equipment checks, and drainage checks, record the power generation before and after the work, on-site photographs, the scope of work, and weather conditions. Prioritize measures that produced large effects in future instances, and suspect other causes for measures that produced small effects. Through this repetition, improvement in power generation becomes not a one-off task but a continuous operational improvement.

Especially at large power plants, a system for accurately sharing problem locations is essential. If you record soiling-prone rows, shaded areas, places where water accumulates, abnormal strings, PCS shutdown locations, spots suspected of connection abnormalities, cleaning areas, repair locations, and inspection photos together with location information, stakeholders can more easily verify the same spot. By combining power generation data with on-site location information, it becomes easier to explain the priority of countermeasures and more efficient to confirm whether issues recur on subsequent inspections.

If you want to continuously assess how to increase power generation and cost-effectiveness based on field data, utilizing LRTK can also be effective. As an iPhone-mounted GNSS high-precision positioning device, LRTK is useful for recording inspection locations within solar power plants, areas prone to soiling, shadow occurrence points, spots with poor drainage, abnormal equipment, areas around PCS, cleaning coverage, repair locations, and on-site photos together with high-precision location information. By organizing the six decision axes with location information, it becomes easier to proceed with power generation improvements based on field data rather than on intuition.