How to Handle Batteries in PVSyst | 6 Basic Setup Steps

Table of Contents

• Basics to Understand Before Handling Batteries in PVSyst

• Step 1: Determine the System’s Purpose

• Step 2: Organize Load Conditions and Consumption Patterns

• Step 3: Set Battery Capacity and Operating Range

• Step 4: Confirm Charge/Discharge Control and Priorities

• Step 5: Input Losses, Efficiencies, and Constraint Conditions

• Step 6: Check the Indicators to View on the Results Screen

• Common Mistakes and Checkpoints in Battery Configuration

• Approaches to Improve Simulation Accuracy by Reflecting Site Conditions

• Summary

Basics to Understand Before Handling Batteries in PVSyst

When handling batteries in PVSyst, the first thing to understand is that a battery is not a device that increases generation but a device that changes how generated electricity is used. The photovoltaic system’s own generation is determined by irradiance, weather conditions, module capacity, orientation, tilt, temperature losses, shading losses, wiring losses, conversion losses, and so on. Adding a battery does not increase the irradiance that the solar panels receive. What changes is the flow of electricity: whether generated power is used on-site or later, whether surplus is stored instead of being discarded, or whether the amount sent to the grid is adjusted.

Therefore, in battery settings you need to look not only at how many kWh are generated annually, but also at how much surplus power is produced, how much of the load can be met by self-consumption, whether the battery spends too much time fully charged or nearly empty, and how large the losses from charging and discharging are. It is not simply a matter of increasing capacity; it is important to set an appropriate capacity and control strategy based on load timing, generation peaks, seasonal variations, and operational objectives.

In PVSyst, depending on the configuration of the photovoltaic system, you combine and evaluate concepts such as grid-connected, self-consumption, standalone, and battery-coupled setups. In practice, the approach to settings differs depending on the objective—for example, when you want to increase the self-consumption rate at a residential or commercial site, when you want to shift daytime surplus power to nighttime, when you want to reduce the contractual peak demand, when you want to assess backup capability during outages, or when you are considering an off-grid power supply for a remote location.

What is especially important to note is that even in simulations labeled "with battery," the results that should be evaluated differ depending on the objective. If you prioritize self-consumption, the important metrics are the proportion of generated energy that was usable on-site and the reduction in the amount of energy purchased from the grid. If you prioritize measures against output curtailment, you need to look at how much surplus or discarded energy was reduced. If you are considering an operation close to an off-grid mode, the important metrics are the time during which the load could not be supplied and the energy shortfall. In other words, clarifying "what you consider a good result" before configuring is the first step to handling batteries correctly in PVSyst.

Step 1: Determine the system's purpose

The first step in battery configuration is to define the system’s purpose. Before opening the settings screen in PVSyst, clarify what kind of operation the target project intends to pursue. If you enter capacity and efficiency while this remains unclear, you will likely find later, when reviewing the results, that you can’t tell whether they are good or bad.

For example, at facilities where daytime demand at the site is high, most of the solar generation can potentially be consumed on site. In this case, the battery's role is to shift daytime surplus to the evening and nighttime. On the other hand, at facilities with low daytime demand and high electricity use at night, the battery plays a larger role. Because generation during the day cannot be used immediately, excess power is likely without a storage battery, and installing one can significantly change the self-consumption rate.

Also, when the objective is peak shaving, it is important not only to look at annual energy totals but also to reduce the maximum demand during specific time periods. In this case, the battery should not always be kept fully charged; control is required so it can discharge during peak demand periods. This differs from the simple approach of charging with surplus power and discharging at night.

Moreover, when considering blackout countermeasures or emergency power, you also need to decide how much battery capacity to reserve during normal operation. Operations that deeply discharge the battery every day to maximize self-consumption and operations that maintain a certain reserve for emergencies require different simulation conditions. How detailed you reproduce this in PVSyst depends on the project, but at minimum, as an assumption for the assessment, you need to be clear about the battery’s intended purpose.

A common mistake in practice is to proceed with a vague request such as "I want to see the power generation if a battery is added." Whether you are looking at the generation itself, the self-consumption rate, surplus reduction, or the ability to supply power during an outage changes the required input conditions and how the results should be interpreted. In PVSyst, you should first appropriately select the project type and system configuration, and proceed with the settings while being conscious of whether the battery's role is on the generation side, the load side, or the grid side.

At this stage, it makes subsequent processes smoother if you can state the project's objective in a single sentence. For example, "redirect daytime solar surplus to evening and later loads to increase the self-consumption rate", "store power curtailed by output limits for later use", "reduce the hours of shortage for remote loads". When the objective is clear, the required load data, battery capacity, control methods, and result verification items naturally fall into place.

Step 2: Organize Load Conditions and Consumption Patterns

When dealing with batteries, load conditions are as important as the generation side. In simulations of solar power generation alone, you can make a reasonable assessment by focusing on the amount of power generated. However, when a battery is included, the timing of when the generated power is used has a large impact on the results. Therefore, it is important to make the temporal variation of power consumption as close to reality as possible.

Load conditions refer to information about how much power a given facility uses at different times of day. Annual energy consumption alone is not sufficient. Even with the same annual energy consumption, the effectiveness of a battery can differ greatly between a facility that uses more during the daytime and one that uses more at night. If daytime demand is high, a larger share of solar generation can be used directly, and a battery can be effective even with a smaller required capacity. Conversely, for facilities with high nighttime demand, battery capacity becomes important to store daytime surplus.

When performing practical studies in PVSyst, prepare hourly—and if not possible, at least monthly or representative-day—load patterns. Hourly data make it easier to check the overlap between the PV output curve and the load curve. This is particularly important for facilities where demand differs greatly between weekdays and weekends, where HVAC loads vary significantly with the seasons, or where operating hours are limited; evaluating only with averages can easily lead to results that diverge from reality.

When organizing load data, check not only the annual totals but also the trends by time of day. Determine whether the peak occurs in the morning, at midday, in the late afternoon to evening, or if there is a steady base load during the night. Because a battery is a device that fills the time gap between generation and demand, the extent of that time gap is the basic factor in capacity planning.

Also, you need to pay attention to the units and time granularity of load data. How you handle the data depends on whether the input values are power or energy, and whether they are 1-hour values, 30-minute values, or daily averages. Before importing into PVSyst, check for missing values, anomalies, time shifts, the presence of daylight saving time, and differences in the target year, as doing so will reduce the likelihood of being troubled by unexplained results later.

In practice, detailed load data may not be available in the early stages of design. In such cases, representative load patterns by usage are assumed and explicitly stated as premises before running simulations. However, because the effectiveness of battery storage strongly depends on the load pattern, it is safer to avoid using preliminary estimates directly for final decisions. It is preferable to update the settings and recalculate once measured data or more detailed demand forecasts become available.

Before configuring a battery in PVSyst, first grasp the overall load profile and check how much it overlaps with the solar generation periods. When the mismatch between generation and consumption becomes apparent here, the reasons a battery is needed, the capacity likely required, and the periods when it should discharge become concrete. Organizing the load conditions is a mundane task, but it is an important step that affects the accuracy of the battery simulation.

Step 3: Configure battery capacity and operational range

After organizing the load conditions, the next step is to set the battery capacity and operational range. Here, "capacity" includes not only the total capacity listed in the catalog but also the concept of usable capacity. A battery cannot be used from 0% to 100% at all times; the usable state-of-charge range is determined by considerations such as lifetime, safety, and control conditions. When configuring in PVSyst, you need to consider the operational upper and lower limits as well as the nominal capacity.

For example, even a battery that appears to have a large total capacity will have a smaller usable capacity in the simulation if the range over which it can actually be discharged is limited. Conversely, configuring the system to allow deeper discharges can make on-site self-consumption appear higher in the short term, but in actual operation it may affect service life and warranty conditions. In PVSyst, it is important to set a realistic usable range that matches the design intent.

When deciding on capacity, first compare the excess electricity generated during the daytime with the load you want to supply after storing the energy. If daytime surplus is small but you select a large battery, there may be few days when it reaches full charge and the system may not be utilized effectively. Conversely, if the surplus is large but the capacity is small, the battery will reach full charge quickly and cannot store any additional surplus. In this case, it is important to check on the results screen the amount of time the battery spends at full charge and the amount of surplus energy that cannot be stored.

Also, when setting capacity, consider not only daily but also seasonal variations. In spring and autumn, generation is high and loads are low, so surpluses tend to occur, whereas in summer and winter some facilities see increased HVAC loads. A capacity that appears appropriate on an annual basis may still have large surpluses or deficits in certain seasons. It is important to check PVSyst results by month and determine in which seasons the battery is effectively operating.

When defining the operating range, verify the maximum state of charge, minimum state of charge, and initial state of charge. The choice of initial values can alter short-term simulation results. In annual simulations these effects may be averaged out, but caution is required when comparing specific periods or representative days. In particular, if emergency power is a consideration, you should carefully consider how deeply to discharge during normal operation.

Furthermore, when considering capacity, note that a "too large capacity" does not necessarily lead to better outcomes. Increasing capacity increases the room to absorb surplus power, but charge–discharge losses also occur. Because power supplied directly to the load without passing through the battery is more efficient, the basic idea is that the battery should be used only to the extent necessary to bridge the time difference between generation and consumption. When comparing multiple cases in PVSyst, set them incrementally—such as small, medium, and large capacity—and judge by checking at what point the self-consumption rate and the amount of surplus reduction plateau.

Step 4: Confirm charge/discharge control and priorities

Simply setting the battery capacity is insufficient for a simulation. In practice, the control conditions—when to charge and when to discharge—greatly influence the results. When handling batteries in PVSyst, you also need to understand and configure the charge/discharge priorities.

As a basic concept, solar power is first supplied directly to the load; if there is surplus, it charges the battery, and if there is still surplus it is sent to the grid or treated as excess. Conversely, if generation is insufficient for the load, the battery discharges, and if that is still insufficient the grid supplies power or the shortage is treated as a deficit. However, actual control depends on the objective: whether you maximize self-consumption, prioritize peak shaving, or maintain an emergency reserve, the outcomes can differ even with the same capacity.

In a setting that prioritizes self-consumption, the basic control is to charge as much of the daytime surplus as possible and to discharge for loads in the evening and at night. In this case, what should be evaluated is how much reverse flow to the grid and surplus energy have been reduced, and how much the electricity purchased from the grid has been reduced. However, if a large surplus occurs after the battery becomes fully charged, this may indicate insufficient capacity or a large time mismatch with the load.

When the objective is peak shaving, it is different from simple surplus charging. You must secure a sufficient state of charge in advance so that you can discharge during the demand peak periods. If you immediately discharge power generated during the day, you may not be able to respond to evening or other specific time-of-day peaks. In such cases, you need to confirm that the timing of the load peak and the battery’s discharge timing are aligned.

From the perspective of emergency power supply, a control strategy that fully drains the battery during normal operation may be inappropriate. Operating so as to preserve a certain remaining charge may slightly reduce the self-consumption rate, but it secures spare supply capacity for emergencies. Whether PVSyst can fully represent such an operation depends on the configuration settings, but at minimum it is important to include the concept of maintaining a remaining charge as a simulation assumption.

You also need to confirm the charging priority. Whether charging is only from solar PV or charging from the grid is considered changes the meaning of the results. If the objective is to effectively utilize surplus from solar generation, charging will basically focus on solar PV. Conversely, in operations that take electricity tariffs and peak control into account, the option of charging from the grid may be examined. However, in that case the analysis becomes more of a power-operation simulation than a solar-generation simulation, so care is needed when interpreting the results.

When comparing results in PVSyst, it's easier to understand if you create multiple cases with different control conditions. Even with the same capacity, simply changing the discharge timing or priority will alter the self-consumption rate, grid purchase amount, surplus energy amount, and battery utilization rate. In practice, it's important not only to compare "with battery" and "without battery" but also to clarify what kind of "with battery" operation is being modeled.

Step 5: Enter losses, efficiencies, and constraint conditions

In systems that include batteries, in addition to losses on the photovoltaic side, losses on the battery side must also be taken into account. To obtain realistic results in PVSyst, check the charge/discharge efficiency, conversion efficiency, standby losses, input/output limits, temperature conditions, and the approach to degradation.

First, the important factor is charge and discharge efficiency. The power put into a storage battery cannot all be retrieved as-is. Losses occur during charging, discharging, and power conversion. Therefore, when you store surplus power to use later, you will have less energy than if you supplied it directly to the load. Even if the self-consumption rate increases, charging and discharging losses can reduce the final usable amount of energy, so you need to be careful when interpreting the results.

Next, there are input/output constraints. Batteries have not only capacity but also a maximum charging power and a maximum discharging power over a given period. Even if capacity is sufficient, if the available charging power is low, the system may not be able to absorb sudden daytime generation peaks. Conversely, if the available discharging power is low, the battery may not be able to discharge sufficiently against demand peaks, limiting its peak-cutting effect. If judgments are made based solely on capacity, it is easy to overlook these kinds of constraints.

Also, the efficiency of conversion equipment is important. Between solar power generation, batteries, loads, and the grid, conversions between DC and AC may occur. Depending on where the battery is connected, the conversion path that the power takes changes, and the losses change accordingly. In practice, checking the system configuration diagram and mapping which conversions the generated power passes through before it reaches the load, or before it enters the battery and then reaches the load again, makes it easier to avoid configuration mistakes.

Standby losses and self-consumption cannot be ignored. Battery systems can consume power for control devices and auxiliary equipment even when they are not charging or discharging. In small-scale systems or cases with low battery utilization, such losses can stand out relatively more. The items that can be configured in PVSyst depend on the system configuration, but when reading the results you should always check the losses that increase as a result of adding the battery.

Temperature conditions also affect battery performance. In high- or low-temperature environments, efficiency, usable capacity, and the progression of degradation may change. A detailed degradation assessment may be performed separately, but at a minimum you should clarify as prerequisites whether the installation site is outdoors, indoors, in a climate-controlled space, in a cold region, or in a hot region. Do not over-rely on PVSyst results; it is important to make conservative decisions that account for the actual installation environment.

Furthermore, how to account for battery degradation is an important practical consideration. Battery performance changes with years of operation and the number of charge–discharge cycles. Even if a first-year simulation appears to show sufficient benefits, usable capacity may decline after a few years. When conducting long-term assessments in PVSyst, you need to consider not only PV module degradation but also reductions in battery capacity and any operational constraints.

When entering losses and efficiencies, it is important not to use overly optimistic values. If you set high efficiencies, low losses, and a wide operating range, the simulation results will look good. However, if those settings do not match actual operation, the discrepancy between projected and actual performance after installation will be large. PVSyst is a tool that calculates based on specified conditions, and if the input conditions are not realistic, the output results will also deviate from reality.

Step 6: Review the metrics to check on the results screen

In simulations after configuring the battery, it is important not only to look at generation output but to break down and examine the flow of power. In PVSyst's result screens and reports, photovoltaic generation, the energy supplied to the load, the energy charged to the battery, the energy discharged from the battery, interactions with the grid, surplus, losses, and so on are checked.

First, what you should look at is how much of the solar power generation was used directly by loads. Power used directly has fewer losses because it does not pass through the battery, making it the most efficient use. Next, check how much of the surplus power was charged into the battery. If there is a large surplus but only a small amount is charged, there may be constraints in the battery capacity, charging power, or control settings.

Next, check the amount of discharge from the battery. Even if the battery is charged a lot, if it remains charged without discharging for long periods, the storage battery may not be being used effectively. For example, if it is charged during the day but nighttime demand is low, the state of charge can remain high until the next day, making it difficult to accept new surplus energy. In this case, possible causes include the capacity being too large, the load conditions not being appropriate, or the discharge control not being aligned with its intended purpose.

It is also necessary to understand the difference between the self-consumption rate and the self-sufficiency rate. The self-consumption rate is a concept that indicates the proportion of generated electricity that was used on-site. In contrast, the self-sufficiency rate is a concept that indicates the proportion of the load that was covered by solar and batteries. In systems with high generation, the self-sufficiency rate tends to be higher, while a large surplus can cause the self-consumption rate to fall. Adding a battery can increase the self-consumption rate, but it is important to also check how much that contributed to improving the self-sufficiency rate for the overall load.

Also check the battery’s state-of-charge trends. If it spends long periods at full charge throughout the year, the capacity may be unable to absorb surplus, or there may be insufficient demand to discharge into. Conversely, if it is almost always near empty, the capacity may be too small, there may be too few charging opportunities, or generation may be insufficient for the load. The ideal condition depends on the objective, but observing state-of-charge trends makes it easier to judge whether capacity and control are well matched.

Don't overlook the breakdown of losses. Adding batteries increases charge/discharge losses and conversion losses. If you only look at improvements in the self-consumption rate, you may miss the impact of increased losses. In particular, the more energy that passes through the storage battery, the greater the losses. In terms of effectively using the power generated, it is necessary to comprehensively look at the balance among direct consumption, use of storage, surplus, and losses.

Checking monthly results is also important. Even if annual values look favorable, viewing them by month can reveal trends such as large surpluses only in certain seasons, significant shortages only in winter, or the discharge being unable to keep up with summer peaks. Because batteries are equipment involved in daily operations, checking not only annual totals but also monthly, representative-day, and hourly results will bring you closer to a realistic operational picture.

Common Mistakes and Checkpoints in Battery Settings

One common mistake when handling batteries in PVSyst is judging the effect solely by changing capacity. Capacity is important, but if the load pattern, charge/discharge power, control settings, efficiencies, and operating range are not aligned, you will not achieve the expected results. If you increase capacity but the self-consumption rate does not rise as much as expected, possible reasons include there being little surplus power in the first place, small nighttime loads, or mismatched discharge control.

Another common mistake is making detailed judgments based on crude assumptions about load data. When estimating using only annual energy consumption, the effect of batteries can be significantly misestimated. Because batteries deal with time-shifting, the temporal variation of load is important. At minimum, it is desirable to understand a representative daily demand pattern, the differences between weekdays and holidays, and seasonal variations.

Also, there are cases where the initial state of charge and the lower operational limit are set without careful consideration. In short-term comparisons, differences in initial values can influence the results. Even in annual assessments, setting the minimum state of charge too low can make the usable capacity appear larger than it actually is. Because real-world control restricts the usable range to ensure safety margins and preserve lifespan, input values need to be adjusted to realistic ranges.

Insufficient understanding of conversion pathways is also a point to watch. The power supplied directly from solar PV generation to the load, the power used to charge the battery, and the power discharged from the battery each pass through different equipment and incur different losses. If you input efficiencies without correctly understanding the system configuration, losses may be underestimated or overestimated. In particular, configurations connected on the DC side and those connected on the AC side require caution because the flow of power differs.

There are also pitfalls in how results are interpreted. Adding a battery can increase the self-consumption rate, but that alone does not necessarily indicate a good design. It is necessary to comprehensively check whether charge/discharge losses have increased too much, whether the equipment is being utilized sufficiently, whether full-charge or empty states last too long, and whether there remains any energy that could not be supplied to the load.

Furthermore, when explaining simulation results as performance forecasts, it is important to make the assumptions clear. If the meteorological data, load data, degradation conditions, operational control, or installation environment change, the results will change. Batteries in particular are greatly affected by the mode of operation, so it is necessary to explain, “under these conditions, this is what will happen.” When sharing PVSyst results internally or with customers, do not simply present the numbers; convey them together with the operational assumptions on which the results are based to avoid misunderstandings.

Approaches for Improving Simulation Accuracy by Incorporating Local Site Conditions

When conducting simulations that include batteries in PVSyst, not only the software settings but also understanding the on-site conditions has a large impact on accuracy. Solar power generation output is affected by the site's solar irradiance conditions, nearby shading, terrain, orientation, tilt, installation height, and the influence of surrounding buildings and trees. Even when a battery is included, if the accuracy of the underlying generation estimate is low, evaluations of charging amounts and self-consumption rates will also be skewed.

The impact of shading, in particular, is also relevant to battery assessment. If shadows occur during specific periods of the daytime, the surplus power during those periods decreases and the amount of charge delivered to the battery also changes. If evening shading is significant, sufficient charging before sunset may not be achieved, and supply to nighttime loads may be insufficient. It is important to consider not only annual generation but also the generation curve for each time period.

It is also important to record the exact location, elevation, and surrounding environment of the installation site. During the design phase, simulations are often based on drawings and map data, but on-site there may be obstacles not shown on the drawings, differences in ground elevation, post-development shapes, changes in equipment layout, and so on. If these on-site differences are not reflected, results may look favorable in PVSyst yet actual power generation and battery operation may differ from the assumptions.

In studies that include batteries, leveraging accurate location information and point cloud data acquired on site makes it possible to carry out design verification that is closer to reality. For example, if the layout of the solar equipment, surrounding structures, the slope of the terrain, and the locations of obstructions can be determined with high accuracy, it becomes easier to establish the assumptions for shading analysis and power generation simulations. The more accurate the assumptions on the generation side are, the more realistic the assessment of how much surplus will flow into the battery and which time periods are likely to experience shortages becomes.

In practical work, it is important not to separate desk-based simulations and on-site verification but to update them iteratively. In the initial stage, use PVSyst with approximate conditions, and after the site survey update orientation, tilt, obstructions, topography, and layout conditions. Re-examining battery capacity and control settings thereafter will yield more convincing results. In particular, when deciding on the introduction of battery storage, reflecting site conditions should be done carefully, since it affects the scale of investment and operational policies.

Summary

Handling batteries in PVSyst is not simply a matter of entering the storage battery capacity. First, determine the system’s objectives, organize the load conditions and consumption patterns, and set the battery capacity and operating range. Then verify the charge/discharge control, losses, efficiencies, and input/output limits, and on the results screen you need to read comprehensively not only the energy production but also direct consumption, charged energy, discharged energy, surplus, losses, self-consumption rate, self-sufficiency rate, and the state-of-charge trajectory.

Battery storage is a key element in enhancing the value of solar power generation. However, it is not a device that increases generation output; rather, it adjusts the timing of how generated electricity is used. Therefore, if load data and operational objectives are left ambiguous, calculations in PVSyst will yield results that are difficult to use for practical decision-making. It is important to clarify whether you want to increase self-consumption, reduce surplus, suppress peak demand, or use the system as an emergency power supply, and to configure settings and verify results that match the intended purpose.

Also, the effectiveness of batteries is strongly influenced by the conditions on the generation side. If solar irradiance, shading, azimuth, tilt, terrain, or the surrounding environment change, the amount of surplus power generated will also change. In other words, to improve the accuracy of battery assessments, it is essential to correctly understand the on‑site conditions, not just the inputs in PVSyst.

By reflecting obstructions and terrain differences that are hard to see on drawings, as well as deviations in equipment layout, simulations of power generation and battery operation will be closer to reality.

If you want to streamline on-site position checks and terrain assessment, using LRTK, an iPhone-mounted GNSS high-precision positioning device, is also effective. At planned solar power facility sites, because it enables easy positioning, current-condition assessment, point cloud acquisition, and verification of equipment locations, it helps organize the prerequisites for input into PVSyst and assists with on-site checks after design. For photovoltaic systems that include batteries, linking power generation simulation, battery operation, and site conditions together leads to reliable assessments in practice.