How to Enter Battery Conditions in PVSyst｜6 Essential Design Tips

Table of Contents

• Things to organize before entering battery parameters in PVSyst

• Basics for determining battery capacity

• Considerations when entering charge/discharge power

• Points to consider when setting SOC and operating range

• How to enter charge/discharge efficiency and loss parameters

• Settings by operational purpose: self-consumption, peak shaving, emergency backup, etc.

• Metrics to check in simulation results

• How to collect on-site information to improve the accuracy of battery parameter inputs

• Summary

What to clarify before entering battery conditions in PVSyst

The purpose of entering battery conditions in PVSyst is to grasp, as realistically as possible, the generated energy, charging amount, discharging amount, surplus power, purchased electricity, sold electricity, losses, and operational effects when combining a battery with a solar power generation system. In simulations of solar power generation alone, the focus is on whether the generated power is used directly by the load, fed into the grid, or curtailed because it cannot be used. On the other hand, when a battery is added, an element that absorbs the time difference between generation and consumption is introduced, so the meaning of the input conditions changes significantly.

When entering battery storage parameters, the first important thing is to clarify why you are installing the battery. Depending on whether you want to increase the self-consumption rate, use solar-derived power in the evening or at night, reduce the peak of contracted demand, or consider backup during outages, the capacity, output, control settings, and how SOC is used will change. Even with the same battery capacity, the simulation results you should examine differ between an operation that stores surplus power during the day for use at night and an operation that discharges only during peak periods.

When dealing with batteries in PVSyst, you first need the generation-side conditions to be reasonably well-defined. If you add a battery while items such as the installation site, meteorological data, azimuth, tilt angle, array configuration, PCS capacity, various losses, and shading conditions are still ambiguous, you will not be able to correctly assess the battery’s effects. For example, if PV generation is overestimated, the amount charged to the battery will also be overestimated, making the self-consumption rate and the reduction in purchased electricity appear better than they actually are; conversely, if shading losses or soiling losses are overestimated, the battery may not be sufficiently charged, causing its capacity to appear oversized.

Also, battery parameters are not determined in isolation but are decided in relation to the load data. At facilities with large daytime loads, generated power tends to be consumed on site, so the surplus power available to charge the battery may be small. At facilities with large nighttime loads, storing daytime surplus in the battery for use at night is more likely to be effective. For facilities whose loads vary greatly due to holidays or seasons, it is important to examine not only annual averages but also monthly, daily, and hourly trends.

Before entering battery parameters in PVSyst, it's helpful to have at least the PV system capacity, PCS capacity, load profile, the approach to grid interconnection, whether feed-in or reverse power flow is allowed, the battery's intended use, operating time periods, and whether it will be used during outages organized in advance to make data entry smoother. In practice, rather than trying to input perfect conditions from the start, it's more realistic to create a baseline case and compare multiple cases by varying battery capacity and control settings.

One thing beginners particularly tend to get tripped up on is judging effectiveness solely by battery capacity. A battery being large doesn't necessarily make it better. If there is little surplus power available for charging, even a high-capacity battery can't make use of its available capacity. If the load that will consume the discharged power is small, you won't be able to use up the stored energy. If the charge/discharge output is too low, it won't be able to respond to short-term surplus or peaks. In other words, you need to consider capacity, output, load, generation, and control together.

As a way to use PVSyst, we recommend always creating a no-battery case before adding a battery. Using the no-battery results as a baseline lets you see how much each parameter changes when you add the battery. By comparing how much purchased electricity decreases, how much surplus power decreases, how much the utilization rate of generated power increases, and how much battery loss occurs, it becomes easier to assess the validity of the battery conditions.

Basics for Determining Battery Storage Capacity

Among battery parameters, capacity tends to draw the most attention. Capacity indicates how much electrical energy can be stored, and it directly affects how much surplus power from solar generation can be absorbed and how much can be discharged during nighttime or peak periods. However, when entering data into PVSyst, you need to clarify not only the numerical value of the capacity but also whether that figure refers to the total capacity or the usable capacity, and whether it includes operational restrictions.

Batteries have a nominal capacity and an actually usable capacity. The nominal capacity is often shown as the capacity in catalogs, but in real operation the usable SOC range is restricted to avoid overdischarge and overcharge. For example, operating a battery to be completely emptied or always using it until it is fully charged may be avoided from the perspectives of degradation and safety. Therefore, in simulations it is important to be aware of the effective capacity that includes the SOC upper and lower limits, not just the simple capacity.

When sizing capacity, the basic rule is to look at both the amount of surplus electricity and the amount of load to which it will be discharged. If daytime solar generation encounters low loads and produces a large surplus, there is room to charge the battery. However, if nighttime loads are small, the stored energy may not be discharged sufficiently and may remain until the next day. If the battery is near full charge when the next day's generation period begins, it will be unable to accept new surplus power, which ultimately leads to surplus energy or output curtailment.

Conversely, even if nighttime loads are large, if daytime surplus power is small the battery cannot be charged sufficiently. In this case, increasing capacity will have only limited effect. Before increasing battery capacity, it is necessary to consider whether to increase solar PV capacity, change how loads are used, or change control settings. In PVSyst, creating multiple cases and varying capacity stepwise while checking charged energy, discharged energy, unused energy, and the SOC profile makes it easier to judge.

When specifying battery capacity, it is easier to understand if you imagine the energy balance on a daily basis. Look at how much surplus electricity is generated during the daytime per day, how much of that can be routed to the battery, and how much electricity you want to use in the evening and at night. If you judge only by annual totals, differences between summer and winter, weekdays and holidays, and sunny and cloudy days become hard to see. Because batteries deal with time shifts, load data with time resolution is extremely important, not just annual values.

In practice, it is effective to compare several capacity patterns—smaller, medium, and larger. With a smaller capacity, the number of charge/discharge cycles increases and the storage battery is used more frequently, but it may fail to capture surplus power. With a larger capacity, it may be able to absorb more surplus power, but the frequency of reaching full charge becomes lower and the effectiveness of the investment may appear diminished. With an intermediate capacity, it can be easier to balance surplus absorption and discharge utilization.

After entering the capacity in PVSyst, check the results screen to see how much the battery is being utilized. If the annual discharged energy is extremely small relative to the capacity, the capacity may be oversized. Conversely, if the battery frequently reaches full charge and a large amount of surplus power still remains, there may be insufficient capacity or insufficient discharge opportunities. However, before concluding that capacity is insufficient, it is also necessary to check whether charging is simply being prevented by charge/discharge output limits or SOC control.

Battery capacity is a condition for changing how generated electricity is used, not a condition for increasing the amount of power generated. If this point is misunderstood, it can appear as though installing a battery will increase generation itself. In reality, some losses occur when electricity is routed through a battery. Even if on-site self-consumption increases, the amount of usable electricity is slightly reduced by the battery’s charge/discharge losses. Therefore, when setting capacity it is important to consider the balance between the surplus-reduction effect, the self-consumption-improvement effect, and the increase in losses.

Considerations when entering charge/discharge output

In battery storage specifications, the charging and discharging power is as important as capacity. If capacity is the container for energy, the charging and discharging power determines how quickly you can put electricity into that container and how quickly you can take it out. Even if capacity is sufficiently large, low charging power cannot absorb surplus power that occurs over short periods. If discharging power is low, it cannot supply enough power for peak loads.

When configuring a battery in PVSyst, it is very important to set the charge and discharge power to realistic values. Solar PV output can vary greatly with weather and time of day. Around noon on a sunny day, a large surplus can occur for a short period. If the charging power is too small at that time, the battery cannot absorb the surplus even if there is available capacity, and some of it will go unused. As a result, increasing capacity may not be as effective as expected.

On the other hand, discharge power affects how the load side is used. If you only need to cover a steady load from evening to night, large discharge power may not be necessary. However, at facilities where large load peaks occur over short periods, insufficient discharge power will limit the peak-cutting effect. When evaluating peak reduction and suppression of grid purchases in PVSyst, you should not simply look at annual discharged energy; you need to confirm whether the required output can be provided during peak periods.

When considering charging and discharging output, you also look at the ratio to the battery capacity. If the output is large relative to the capacity, charging and discharging can be done in a short time, but the SOC will change rapidly. If the output is small relative to the capacity, operation will involve slow charging and discharging. Which is better depends on the application. For the purpose of improving self-consumption, it may be sufficient to have output that can absorb daytime surplus and discharge it from the evening onward. For the purpose of peak shaving, output capable of responding to short-term maximum demand may be required.

Also, battery storage systems have constraints not only from the battery itself but also from the power conversion equipment and the connection method. Whether the system is connected on the DC side or the AC side, and how the PV generation and the battery interact, will change what output conditions should be entered and how losses are considered. When configuring PVSyst, it is important to confirm that the configuration assumed in the actual design is not significantly different from the model in the software.

Increasing the charging output makes it easier to absorb surplus power, but that alone does not necessarily increase effectiveness. If the battery storage capacity is small, it will reach full charge quickly and cannot be charged further. Even if you increase the discharging output, the power will not be used if there is no load to discharge to. In other words, charging and discharging outputs need to be evaluated together with capacity, load, and control conditions.

In simulation results, it is useful to examine the surplus power that could not be charged, the demand that could not be discharged, and any instances of SOC sticking. If the SOC frequently sticks at the upper limit, this may indicate insufficient discharging, too small capacity, or too little load. If the SOC frequently sticks at the lower limit, this may indicate too small capacity, insufficient charging, or excessively large discharge requests. Because constraints on charge/discharge power can prevent the SOC from behaving as expected, it is important not to judge the results by a single metric.

When beginners input charge/discharge power, they should first enter values based on the actual equipment specifications, and then create cases with slightly larger and smaller values as a sensitivity analysis to deepen their understanding. If changing the power hardly changes the results, capacity or load may be the main constraints. If changing the power significantly alters surplus power or the amount of purchased electricity, the charge/discharge power is likely an important design constraint.

Key Points to Consider When Setting SOC and Operational Scope

A parameter that is easy to overlook when entering battery conditions is SOC. SOC is a concept that indicates a battery’s state of charge, expressing how charged it is as a percentage. When dealing with batteries in PVSyst, the SOC upper and lower limits, initial value, and control settings have a major impact on simulation results. Even if capacity and output are entered correctly, if the SOC range differs from reality, the available energy and the number of charge/discharge cycles will not match actual conditions.

The SOC lower limit is the condition that determines how far the battery may be discharged. Setting a lower SOC limit increases usable capacity, but in actual operation excessive discharge is sometimes avoided for reasons of degradation and protective control. Setting a higher SOC limit makes it easier to ensure an emergency reserve, but reduces the capacity available for normal operation. If backup during a power outage is prioritized, it may be necessary to configure the system to reserve a certain amount instead of using the full capacity for everyday self-consumption.

The SOC upper limit is the parameter that determines how far to charge. Raising the upper limit increases the amount that can be charged, but operating constantly near full charge is not always desirable. Slightly lowering the upper limit can bring the setting closer to one that accounts for degradation and operational stability. In simulations, a higher upper limit may appear to increase energy storage utilization, but if it does not align with actual control specifications, this will be an overestimate.

Initial SOC is surprisingly important. In short-term simulations or comparisons of specific days, results can change depending on the initial SOC. In annual simulations the influence of the initial value may be less pronounced, but when looking at seasonal or representative days, the SOC at the start affects the amount of charging, discharging, and purchased electricity. In practice, recording what initial SOC was set makes it easier to explain the results later.

By looking at SOC behavior, you can clearly understand how the battery is being used. If it is charged up to the upper limit every daytime and discharged down to the lower limit at night, the battery is being well utilized. However, if it is constantly oscillating between the upper and lower limits, there may be a capacity shortage. If the SOC remains high all the time, there may be little load to discharge to, discharge control may be limited, or the capacity may be oversized. If the SOC remains low all the time, there may be insufficient surplus available for charging.

When reviewing PVSyst results, it's important to check not only the annual totals but also the time variation of SOC. In particular, for battery storage design, even if the total annual discharged energy is the same, operational stability can differ. In one case, the battery may be used steadily throughout the seasons, while in another it may be used mainly in summer and hardly at all in winter. Whether the system meets the facility's operational objectives cannot be judged without looking at how it is used over time.

If the battery storage system is also used as an emergency power source, normal self-consumption operation and reserving capacity for emergencies will compete. If you try to maximize self-consumption, the battery will discharge at night and the SOC will drop. However, to prepare for a blackout you need to keep a certain amount in reserve. In this case, it is important to check to what extent emergency operation can be represented in PVSyst, and to organize any aspects that cannot be represented separately as conditions. When explaining the simulation results, you should also make clear whether you are discussing normal operational evaluation or the evaluation of duration in an emergency.

SOC settings are not merely input fields but conditions that express the operational philosophy of the battery. Design engineers need to be able to explain why they chose those upper and lower limits, why they set that initial value, and which operational priorities they are favoring. As a way of using PVSyst, comparing not only cases with a fixed SOC range but also slightly wider and slightly narrower cases makes it easier to grasp the sensitivity of the battery's effect.

How to enter charge/discharge efficiency and loss conditions

When electricity is routed through a battery storage system, losses occur during charging, discharging, conversion, standby, and so on. When entering battery conditions in PVSyst, it is important to appropriately account for these losses. While adding a battery increases the self-consumption rate, the amount of usable energy can decrease by the portion that passes through the battery. Setting loss conditions too leniently can lead to overestimating the battery's effectiveness.

Charge–discharge efficiency is a parameter that determines how much of the energy put into a storage battery can be retrieved. For example, when energy charged during the daytime is discharged at night, the amount of energy charged and the amount that can be discharged are not the same. In addition to the battery’s own efficiency, factors such as the efficiency of power conversion equipment, the number of conversions caused by the connection scheme, and standby consumption during control affect the outcome. You need to check which losses are treated in which input fields in PVSyst and ensure there is no double counting or omission.

What you should pay particular attention to is that the way losses are considered changes depending on whether the battery is handled on the DC side or the AC side. In configurations where the photovoltaic system and the battery are integrated on the DC side, you need to understand at which stage the generated power enters the battery and which conversions it goes through during discharge. In configurations connected on the AC side, the solar generation may be converted to AC before charging the battery, which can increase the number of conversion steps. If you input efficiencies based on assumptions that differ from the actual configuration, losses will be underestimated or overestimated.

Battery losses may not appear large when viewed as an annual total, but they still affect design decisions. For example, the more energy that passes through the battery, the greater the charge/discharge losses. Even if the self-consumption rate seems to improve, the benefit may be smaller than expected when looking at the effectively utilized energy including battery losses. In PVSyst results, it is important to check charged energy, discharged energy, losses, and unused energy together.

Standby losses and self-consumption are also easy to overlook. Even during periods when the battery is not charging or discharging, control units and power conversion devices can consume electricity. In particular, in designs where the battery is used infrequently, the impact of standby losses can become relatively large. In cases where capacity is increased but the battery is seldom discharged, these losses can become conspicuous compared with the effective utilization of the battery.

When entering efficiency values, you need not only to input the catalog or specification numbers as-is, but also to confirm that they match the definitions used in the simulation. The meaning differs depending on whether a value refers to the efficiency of an individual battery cell, the efficiency of the entire battery system, or the round-trip efficiency including conversion equipment. If you enter numbers into PVSyst’s input fields without clarifying which scope of efficiency should be used, it will be difficult to explain the results.

Practically, it is recommended not to fix the efficiency assumption to a single value but to create a standard case and a conservative case. In the standard case, input values close to the expected specifications; in the conservative case, set the efficiency slightly lower and compare the resulting differences. This lets you understand how much the battery’s effect is influenced by the efficiency assumptions. Especially at the proposal stage, showing results that account for realistic losses rather than presenting only the best-case conditions increases credibility.

The handling of battery losses is one of the aspects of using PVSyst that most often leads to practical discrepancies. In generation simulations, attention tends to focus on irradiance, temperature, shading, and wiring losses, but when a battery is included you need to track which path the electricity takes to reach the load. Whether generated power is used directly, charged into the battery before use, or purchased from the grid, the locations where losses occur differ. Understanding these differences and entering them correctly prevents misinterpretation of the results.

Settings by operational purpose such as self-consumption, peak shaving, and emergency use

When entering battery parameters, you need to change your approach to the settings depending on the operational objective. A battery intended to increase self-consumption, a battery intended for peak shaving, and a battery kept as an emergency power supply require different optimal control strategies even with the same capacity. When creating design cases in PVSyst, it is important to either focus on a single objective or organize multiple objectives with priorities.

When the aim is to increase self-consumption, the basic operation is to charge a storage battery with surplus daytime electricity and discharge it during periods of low generation. In this case, what matters is how much surplus is produced during the day and how much load there is from the evening onward. At facilities where daytime load is high and there is almost no surplus, the amount of energy that can be charged into a battery is limited. Conversely, at facilities that tend to generate surplus during holidays or lunch breaks, a battery can potentially reduce unused electricity.

When aiming for peak shaving, the relationship between the time periods when maximum demand occurs and the discharge power is important. If peaks occur only for short periods, discharge power can be more effective than capacity. If a peak lasts for a long time, capacity is also necessary. When evaluating peak reduction effects in PVSyst, you cannot judge based only on the annual discharged energy. You need to check how much the maximum demand was reduced in which time periods, and whether the battery was sufficiently charged at the times it was needed.

Planning for emergency use requires a different approach from normal, economically driven operation. You should clarify which loads will be limited to those needed in an emergency, how many hours you want to sustain them, and what level of SOC to secure in the event of a blackout. If the battery is used too deeply during normal operation, there may be insufficient remaining charge during an outage. Therefore, in designs that prioritize emergency use, it is common to set a higher SOC lower limit or to operate so that a certain portion of capacity is not used during normal times.

Also, when there are constraints on selling electricity or reverse power flow, the way the battery is used changes. If surplus power can be exported to the grid, there are cases where selling it is better than charging the battery. If reverse power flow is restricted, charging surplus power into the battery may help reduce output curtailment. In PVSyst, if the relationship with the grid and the handling of surplus power are not correctly reflected, the value of the battery will be misjudged.

When considering electricity use by time of day, the accuracy of the load profile is crucial. Monthly consumption alone does not indicate which times of day a battery is needed. With data at time resolutions such as 30-minute or 1-hour values, you can evaluate the mismatch between solar PV generation and the load more accurately. In practical work configuring batteries in PVSyst, it is not an exaggeration to say that the preparation of load data determines simulation accuracy.

When there are multiple operational objectives, it is important to set priorities. Maximizing the self-consumption rate, suppressing peaks, and ensuring an emergency reserve can sometimes conflict. For example, if you discharge at night for self-consumption, the SOC the next morning will be lower. If you prioritize emergency reserves, you need to keep a certain amount in reserve. If you prioritize peak shaving, you may need control strategies that preserve SOC until the peak period.

When creating multiple cases in PVSyst, it is easier to manage them if you name each case according to its operational purpose. By separating them into, for example, a self-consumption-priority case, a peak-shaving-priority case, and an emergency-reserve-preservation case, you can tell what each setting was intended to achieve when comparing results. Rather than simply lining up cases with different capacities, clarifying differences in control philosophy also makes it easier to explain to stakeholders.

Batteries are not equipment that will be automatically optimized simply by being added later to a photovoltaic system. It is necessary to design which power to store, when, and how much, and when and where to discharge it. Entering the battery conditions in PVSyst is the process of quantifying that operational policy. Creating the conditions with design intent, rather than merely filling in the fields on the input screen, leads to simulations that are usable in practice.

Indicators to Check in Simulation Results

After entering the battery storage conditions, interpreting the results is extremely important. In PVSyst, you should check not only energy production and losses but also the amount charged into the battery, the amount discharged from the battery, changes in SOC, surplus power, purchased electricity, and self-consumption. Because it is difficult to judge the results as good or bad by looking only at the case with a battery, the basic practice is to compare them with a baseline case without a battery.

First, what I want to confirm is how the total solar PV generation is handled when a battery is added. Because a battery is not equipment that increases generation itself, we focus on the destinations of the generated electricity rather than changes in the amount generated. By separating the electricity used directly by loads, the electricity charged into the battery, the electricity exported to the grid, and the electricity that could not be used, you can see what role the battery is playing.

Next, review 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 within the facility. Adding a battery can increase the self-consumption rate because daytime surpluses can be used at night. The self-sufficiency rate is a concept that looks at the proportion of the facility’s electricity consumption that was covered by solar power generation and batteries. Even if the self-consumption rate is high, the self-sufficiency rate may not be very high if that corresponds to only a small share of the overall load.

The difference between a storage battery’s charged energy and discharged energy is also important. If the discharged amount is smaller than the charged amount, possible causes include large charge/discharge losses, inability to fully use the battery due to SOC constraints, or insufficient discharge destinations. Of course, it is natural for the discharged amount to be smaller than the charged amount for efficiency reasons, but if that difference is larger than expected, you need to review the loss conditions and operating conditions.

The time variation of SOC is very useful for assessing the validity of battery storage design. Even if annual totals look good, there can be imbalances such as being used only in certain seasons, being hardly charged in winter, remaining stuck at full charge in summer, or becoming depleted early at night. If SOC remains stuck at the upper or lower limit for long periods, there may be constraints in capacity, power output, control, or load.

You should also check changes in surplus power. If you installed a battery storage system but the surplus power has hardly decreased, possible reasons include insufficient charging output, insufficient capacity, the SOC being fully charged and unable to accept more, or control conditions not aligned with the intended purpose. Conversely, even if surplus power has decreased significantly, if battery losses have increased too much, an evaluation of efficiency is necessary.

Reduction in purchased electricity is also an important metric in practical operations. You check how much battery discharge reduced purchased electricity during periods when there is no solar power generation. However, even if purchased electricity decreases, it is necessary to see which time periods the decrease occurred in. Whether purchased electricity during peak hours decreased, purchased electricity at night decreased, or only low-load periods changed has different implications for design.

The utilization rate of the storage battery is another item to check. If the annual discharge amount is small relative to the capacity, the storage battery may not be used sufficiently. Of course, in designs that reserve remaining capacity for emergency use, a low utilization rate during normal times can still be meaningful. However, if the purpose is self-consumption or peak shaving and the utilization rate is low, this may indicate oversized capacity, insufficient load, or inappropriate control.

When explaining results, it is important not to judge by a single metric alone. Even if the self-consumption rate has increased, losses may have increased. Even if surplus power has decreased, it may not be having much effect on reducing purchased electricity. Even if the amount of discharge is large, it may not be discharging during the required peak periods. PVSyst results only make sense when viewed comprehensively, considering generation, load, battery, and grid flows.

How to Collect On-Site Information to Improve the Input Accuracy of Battery Storage Conditions

To correctly enter battery conditions in PVSyst, the accuracy of on-site information as well as the specifications on paper is important. Photovoltaic systems and batteries are greatly influenced by the site's solar irradiation, shading, site conditions, equipment layout, and how loads are used. No matter how precisely battery capacity and output are specified, if the site conditions differ from reality, the reliability of the simulation results will decrease.

First and foremost, the conditions of the installation site are important. The power output of a solar photovoltaic system varies depending on azimuth, tilt angle, shading, surrounding obstructions, terrain, and the condition of the mounting surface. Because a storage battery stores the electricity that is generated, if the generation-side conditions are off, the battery's charge level will also be affected. In sites particularly affected by shading, daytime surplus power may be lower than expected, reducing the utilization of the storage battery.

Next, obtaining load data is important. For energy storage system design, annual consumption alone is not sufficient. If possible, check power usage by time of day and understand the differences between weekdays, holidays, seasons, and operating hours. Load profiles vary greatly among factories, warehouses, offices, commercial facilities, and public facilities. For facilities with daytime-dominant loads and those with large nighttime loads, the appropriate battery capacity will differ even with the same solar PV capacity.

On-site surveys also verify the available installation space, equipment layout, wiring routes, and the relationship with existing incoming power equipment. For batteries, it is necessary to consider not only capacity and output but also the installation location, ventilation, maintenance space, connection points, metering points, and the relationship with the control panel. PVSyst is primarily used for energy simulation, but in actual design, construction conditions and maintenance conditions can also become constraints.

Also, when considering the layout of a photovoltaic system, the accuracy of on-site location and topographical information is important. If site boundaries, building locations, obstacles, ground elevation, and the tilt of the installation surface remain ambiguous, they will affect the assessment of shading conditions and the feasible installation capacity. As a result, the power generation conditions and array configuration entered into PVSyst may deviate from reality.

When collecting on-site information, combining photographs, positioning data, simple surveys, and point cloud data makes it easier to organize the assumptions for design. Especially for outdoor solar power installations, accurately understanding the site's coordinates, terrain, and the locations of obstacles leads to improved simulation accuracy. The battery conditions themselves are values entered into software, but the power generation and surplus power that underlie them depend heavily on local conditions.

In using PVSyst, a practical workflow is to create a baseline case based on information obtained from the site survey, and then change conditions for comparison. If you change the presence or absence of shading, differences in load, battery capacity, charge/discharge power, SOC range, and efficiency conditions all at once, it becomes difficult to determine which condition affected the results. It is important to change conditions one at a time and check the differences in the results.

Even when on-site information is insufficient, you can update it later as long as you clearly state the assumed conditions. For example, if load data are only available on a monthly basis, assume representative time-of-day patterns for the initial assessment and later replace them with measured data. When shading conditions are unknown, compare a no-shade case and a shaded case separately. The important thing is not to hide assumptions and to record which conditions are provisional.

Summary

When entering battery parameters in PVSyst, it is important to organize them around six basics: capacity, charge/discharge power, SOC range, efficiency, operational purpose, and result indicators. A battery is not equipment that increases the generation output of a photovoltaic system itself, but equipment that adjusts when and where the generated power is used. Therefore, even if you enter battery parameters in detail, if the generation conditions and load conditions are ambiguous, the results will not be usable in practice.

The first step is to create a baseline case without a battery. On that basis, compare cases with different battery capacities, different power outputs, different SOC ranges, and a case that treats efficiency conservatively. By comparing these cases, you can determine whether increasing battery size will yield greater benefit, whether the capacity is already excessive, whether power output is the limiting constraint, or whether the way the load side is used is the constraint.

When deciding capacity, consider daytime surplus energy and nighttime or peak-period loads together. When determining charge/discharge output, check whether it can handle short-term surpluses and peaks. When setting SOC, think separately about the range used for normal operation and the portion reserved for emergencies. When entering efficiencies and losses, organize your thinking for the whole system, including not only the battery itself but also converters and standby consumption.

Operational objectives also need to be clarified. If the battery is intended to increase self-consumption, it is important to know how much surplus power can be shifted to nighttime use. If the goal is peak shaving, check whether there is sufficient SOC and discharge power during the time when peak demand occurs. If emergency backup is prioritized, carefully set how far the battery may be discharged during normal operation. If the objectives differ, the appropriate input conditions change even for the same battery.

In the simulation results, we comprehensively check the self-consumption rate, amount of purchased electricity, surplus power, battery charging amount, discharge amount, losses, and SOC transitions. Judging based on a single value can lead to design errors. In particular, if the battery spends long periods stuck at full charge or at its lower limit, it is necessary to review the capacity, output, control, or the loads.

Furthermore, improving input accuracy in PVSyst requires a thorough understanding of on-site conditions. Accurately identifying the installation site's orientation, tilt, shading, obstructions, site layout, and temporal variations in load as precisely as possible will also enhance the accuracy of battery condition assessments. In combinations of solar PV and batteries, correctly linking the site's generation potential with consumption patterns determines the quality of the design.

During on-site surveys and pre-design information organization, utilizing LRTK, a high-precision GNSS positioning device that can be attached to an iPhone, can streamline layout planning and on-site verification of solar power generation equipment. You can obtain the planned installation site's location information, surrounding obstacles, current-condition photos, and basic surveying information in the field, making it easier to organize the basis for design conditions. As a preliminary step before entering battery conditions into PVSyst, accurately understanding the site's power generation and installation conditions is highly important for enhancing the reliability of simulation results.