Solution Services: Energy Storage Systems

Energy Storage in SolarNexus

SolarNexus allows you to add an energy storage system to a customer solution. This enables you to analyze the energy impact and economic value of installing storage along with PV, and to include storage in your sales proposals and contracts.

 

Professional Grade Analysis

Energy storage systems are used for a variety of residential and commercial applications, including backup, self consumption maximization, time-of-use optimization, demand shaving, etc. Properly assessing the value of adding storage under the different operating assumptions of these various applications requires sophisticated, hour-by-hour modeling of a site's energy use combined with projected hourly PV production, efficiency savings and detailed battery performance. To ensure our modeling and analysis is as accurate as possible, SolarNexus has incorporated the industry-validated System Advisor Model (SAM) from the National Renewable Energy Lab (NREL) for running the behind-the-scenes battery simulations that drive our performance estimates. (SAM also powers the popular PVWatts service that SolarNexus uses for estimating PV output for a given system.) 

Defining a Storage System

A solution may have one and only one energy storage system. When adding a storage system, you can simply select a pre-defined service offering, or if your administrative settings allow, you may configure it from scratch by adding a generic storage system. SolarNexus strongly recommends creating reusable storage service offerings - each representing a specific manufacturer's offering so that each has its own equipment items, operational parameters, and pricing -- so you can add a fully-configured storage system to a customer solution with a single click.

Defining a Storage System - Process

The basic storage system definition steps include:

1. Specify post-project electricity tariff (needed if maximizing self-consumption or time-of-use)
2. Select an energy storage service offering (or manually adding battery and possibly inverter and charge controller from your Company Catalog)
3. Review battery bank configuration
4. Review PV coupling configuration
5. Configure battery charge/discharge modeling parameters
6. Review battery performance details

The sections below cover each of these steps in more detail.

Once you've completed these steps to add a storage system, you can use the Energy Analysis graphs to visualize how the storage system impacts grid usage on an hourly/daily/monthly basis and proceed to the Analysis screen to understand the financial costs and benefits of adding storage.

Specifying Post-Project Tariff

When you add a storage system, if you haven't yet specified the customer's expected post-project tariff AND if the customer's utility has any time-of-use rates, SolarNexus may first prompt you to specify the post-project tariff.

SolarNexus needs to know the post-project tariff in order to choose the correct default dispatch strategy for the battery. For load shifting applications, you will typically want to model battery performance using a time-of-use optimization strategy when using a tariff with time-of-use rates, but if NOT using a time-of-use tariff, you'll more likely be using a dispatch strategy that maximizes self consumption. See the Battery Charge/Discharge Modeling section below for more details on dispatch strategy.

Note: If the customer's utility doesn't have any time-of-use rates, you won't see this step.

Selecting Equipment

If you're adding a storage system from a pre-defined storage offering, the default storage unit model should already be pre-selected, and if that's the model you want to quote, you can simply click Save, otherwise you can select an alternate battery model.

IF you are defining a generic storage system, SolarNexus will prompt you to select the storage unit (battery) model and quantity for the proposed storage system.

Tip: If you don't see the model you need in the list, an administrator for your SolarNexus account can add the needed model to your Company Catalog. 

After you select the storage unit and quantity, the storage system will be added to the solution. If you selected a standalone DC battery and need to add a battery inverter and/or charge controller to the system, you can do so using the Add Inverter and Add Charge Controller buttons. You can also click the edit icon next to the battery to change the battery selection.

System Configuration - Battery Bank

The Battery Bank area of the system configuration section shows the total capacity and estimated annual throughput of the storage system.

Annual throughput is the total kWhs charged and then discharged by the storage system over the course of a year. The normalized annual throughput is the throughput divided by capacity, showing the throughput per kWh of capacity. 

The normalized throughput makes it easy to understand the battery utilization at a glance. A normalized throughput of 365 would indicate that the battery is projected to fully cycle once per day, with no efficiency losses. This is the theoretical maximum for most residential installs where the battery bank is charging only from PV. More typically, the normalized throughput will be somewhat less than 365 because the battery bank might not fully charge/discharge in each cycle, might not cycle every day, and will usually be subject to efficiency losses causing the amount of energy discharged to be lower than the amount of energy charged. A normalized throughput much lower than 365 indicates that the battery bank might be underutilized.

Note: Throughput is estimated by simulating charge/discharge behavior for every hour of the year, given the site's energy usage, projected PV output, battery performance characteristics and discharge strategy. It is heavily dependent on the PV coupling and storage modeling parameters described below. As you change the PV and storage configuration, you'll see the throughput numbers recalculate.

System Configuration - PV Coupling

The PV Coupling area of the system configuration is where you can see and configure how the storage system is coupled to the PV system.

PV Coupling Types:

• AC Coupled: the PV system and the storage system each have their own inverter(s). To charge the battery from excess PV, DC power from the PV system is first converted to AC with the PV inverter(s), then it is converted back to DC with the battery inverter.
• DC Coupled: The PV system and the storage system share an inverter. The battery is charged from DC power directly from the PV system. A charge controller or hybrid inverter with MPPT is often used to convert and optimize the voltage coming from the PV system.

Here are a couple of articles describing the pro's and con's of AC vs. DC coupling:

• AC or DC coupling: Which to use for your next storage project? (Solar Power World, Mar. 2018)
• Solar battery system types - AC Vs DC coupled (Clean Energy Reviews, Apr. 2018)

SolarNexus needs to know how the storage system is coupled to the PV system in order to estimate the roundtrip conversion losses involved in charging/discharging the battery. An AC coupled system involves more trips through an inverter during a roundtrip and so typically has lower roundtrip efficiency than a DC coupled system, and thus lower storage throughput for the same PV output.

Configuring the PV coupling type

Depending on the particular equipment selected for the PV system and storage system, SolarNexus may either be able to automatically determine the implied PV coupling type or it may assume a default but allow you to configure it. When SolarNexus can't automatically determine the coupling type, or if your chosen setup allows either type, you can click the Switch to AC or Switch to DC link to toggle the coupling method.

Here are some typical scenarios and the implied or assumed PV coupling type:

PV and Storage Configuration	Coupling Type
Storage system configured to use a standalone DC battery with battery-based inverter and PV system configured to use a string inverter.	AC coupling is implied.
PV system configured to use micro-inverters.	AC coupling is implied. The storage system will need to use its own inverter(s).
Storage system configured to use an AC battery like a Tesla Powerwall, Sonnen eco or Enphase AC Battery.	AC coupling is implied. The PV system will need to use its own inverter(s).
Storage system configured to use a standalone battery like an LG Chem RESU10H, and PV system is configured to use a hybrid inverter like a StorEdge.	DC coupling is assumed.
Storage system configured to use an integrated storage system like a SimpliPhi ACCess with integrated MPPT charge controller.	DC coupling is assumed. User can change to AC coupling if they will not be using the integrated charge controller.
Storage system configured to use an integrated storage system like a SimpliPhi ACCess without integrated MPPT charge controller.	AC coupling is assumed. User can change to DC coupling if they will be installing with a separate charge controller.

PV coupling details

Click the Show Details link in the PV Coupling section to see the coupling details.

This popup shows the inverters/charge controllers and associated conversion efficiencies for both the PV-storage link and the storage-AC link.

For an AC coupled system, the overall PV-to-storage-to-AC conversion efficiency is calculated by multiplying the efficiency of each of the three conversions:

AC coupled efficiency = PV-to-AC efficiency * AC-to-storage efficiency * storage-to-AC efficiency

For a DC coupled system, the overall PV-to-storage-to-AC conversion efficiency is simpler:

DC coupled efficiency = PV-to-storage efficiency * storage-to-AC efficiency

If you added the requisite inverter/charge controller equipment to the PV and storage system definitions, the efficiencies come from the data sheets for the selected equipment as captured in the SolarNexus catalog. However, if for some reason you want to modify the assumed efficiency of the selected equipment, you can click the Edit link next to each efficiency value to override it.

If you did NOT add the requisite inverter/charge controller equipment to the PV and storage system definitions, SolarNexus will use the default inverter/charge controller efficiency values from your account preferences. You can click the Edit link to change the assumed efficiency value for the particular configuration your are proposing.

Battery Charge/Discharge Modeling

The Storage Modeling section shows a summary of the key charge/discharge modeling parameters.

A newly added storage system will start with default modeling parameters and you can customize as necessary. The defaults can be set in a couple of ways:

• When defining a reusable storage offering, you can specify the default modeling parameters for all systems created from the offering.
• If the storage offering used to add a storage system doesn't specify default parameters, or if you start from a generic storage system (i.e. no storage offering), the storage system will use the default storage modeling parameters from your SolarNexus account settings. Go to Administration > Project Settings > Storage Modeling to edit the default parameters (requires admin privileges).

Note: when defining defaults, you specify the default dispatch strategy for two different scenarios: one where the project will be using a time-of-use tariff and one where it will NOT be using a time-of-use tariff. The default value that's used for a particular system depends on the post-project tariff specified for the solution. If you don't typically encounter time-of-use tariffs in the regions you operate, you can ignore the default value for the time-of-use tariff scenario.

Click the edit icon to customize the modeling parameters for a system.

Dispatch Strategy

The dispatch strategy specifies the charge/discharge program expected to be used by the storage system. SolarNexus has three built-in dispatch strategies that cover most residential use cases:

1. Backup Power-Only: Storage system is used only for backup power during outages and has no impact on day-to-day energy usage or costs. In this case, annual throughput and self-consumption will both show as 0.
2. Load Shifting - Maximize Self-Consumption. Storage system is used to maximize the amount of solar energy that's directly consumed on site. The battery charges whenever PV production exceeds consumption and discharges to meet load whenever consumption exceeds production. This strategy makes sense for non-time-of-use tariffs where exports are compensated at below retail rate (or not compensated at all, for example in Hawaii). Storing excess solar and discharging to offset grid usage makes sense at any time of day in this scenario because doing so will always increase the value of the excess PV.
3. Load Shifting - Optimize Time of Use. Storage system is used to reduce utility usage during peak times, when rates are the highest. The battery charges from excess solar only during OFF PEAK hours and discharges to meet load when consumption exceeds production only during PEAK hours. This strategy is only available for selection when using a time-of-use tariff. This is the standard strategy for most residential projects in California.

NOTE: You can combine either of the Load Shifting strategies with backup by simply increasing the default minimum threshold for state of charge. For example, allowing the load shifting to only use 50% of the battery charge, and reserving 50% in case of backup needs. Customers value backup energy, and you can incorporate that value of backup as an incentive. See Energy Storage- Value of Backup Energy.

Custom Dispatch Strategies

You can also define custom dispatch strategies for more advanced scenarios. There are two ways you can do this. To create a one-off custom strategy for a particular project, or to experiment with how customizing the dispatch strategy impacts ROI, select a dispatch strategy to start with (e.g. Maximize Self Consumption), click the down arrow next to the strategy selector to show the details, and the click the Customize button. If you want to reuse a custom strategy across many projects, you (or an account administrator) can go to Administration > Storage Dispatch Strategies and create your own dispatch strategies to use in your account. You can create strategies from scratch or clone one of the SolarNexus-defined strategies and customize it from there.

For example, let's say you want to define a custom dispatch strategy where the battery can charge from PV at any time, can charge from the grid from 8am-10am, and can only discharge to meet load from 5pm-9pm. This is how such a strategy would look:

 

 

Follow these steps to create this strategy:

1. Give your dispatch strategy a custom name (if defining a reusable strategy) and description.
2. Set the type to Custom Schedule.
3. We'll assume we're starting with the default strategy where every hour in every month is set to Period 1 (light blue). For Period 1 (whole day), we want to allow charging from PV but not charging from the grid or discharging. So in the Charge/Discharge Rules section, for Period 1, check Allow Charging from PV and uncheck Allow Charging from Grid and Allow Discharging.
4. Now we want to define the rules for the 8-10am period. First, click the green square labeled "2" in the upper right above the schedule table. Now, drag the cursor over the 8am and 9am cells for every month. You'll see the cells turn green as you click or drag the mouse over them. Then, go up to the Charge/Discharge Rules section and specify the rules for Period 2: uncheck Allow Charging from PV, check Allow Charging from Grid and uncheck Allow Discharging.
5. Lastly, we want to define the rules for the 5pm-10pm period. Similar to what we did before, first click the Period 3 square (yellow), then drag the mouse over the 5pm-9pm cells for all months until you have a block of yellow squares. Then, go up to the Charge/Discharge Rules section and specify the rules for Period 3: uncheck Allow Charging from PV, uncheck Allow Charging from Grid and check Allow Discharging.
6. That's it! Just click Save to save the custom dispatch schedule.

Other Types of Dispatch Strategies

As of December 2018, SolarNexus only supports schedule-based dispatch strategies, with the goal of reducing consumption charges. Dynamic dispatch strategies aimed at reducing demand charges, like peak shaving, are not yet supported.

Battery Replacement Policy

Most batteries on the market today have lifetimes of around 10 years or less, so customers will need to replace their batteries at least once or twice over the course of the PV system lifetime. As a battery degrades, its retained capacity (effective capacity at full charge) diminishes, so its expected throughput goes down each year. SolarNexus takes this into account when modeling lifetime performance.

You can specify how SolarNexus should model the replacement interval when calculating lifetime ROI. For example, if the battery is projected to be replaced in year 11, SolarNexus will model the effects of battery degradation for the first ten years, and then will start over at full capacity in year 11 and model degradation again from there.

Replacement policy options include:

• No Replacement: The battery is assumed to never be replaced. SolarNexus continues modeling battery degradation for the full analysis period (e.g. 25 years). Depending on battery chemistry, the battery may effectively degrade to the point of becoming unusable before the end of the analysis period, at which point it would no longer contribute to bill savings.
• Capacity Based: The battery is assumed to be replaced once the retained capacity reaches a given threshold. Enter a value for Replace at Capacity (%) to specify the threshold.
• Interval Based: The battery is assumed to be replaced at fixed intervals. Enter the number of years in the replacement interval.

Tip: You can use the warranty information for the selected storage unit as a guideline for specifying the replacement policy. If the manufacturer guarantees the battery will retain at least 70% capacity after 10 years, you can probably set the replacement policy to either Capacity Based at 70% threshold, or Interval Based at 10 years.

Min/Max State of Charge

The minimum and maximum state of charge determine the usable capacity of the battery. For example, if the minimum state of charge is 20% and the maximum state of charge is 95%, the usable capacity is 75%. When modeling the charge/discharge behavior of the battery, SolarNexus won't let the battery discharge below the minimum state of charge and won't let the battery charge above the maximum state of charge.

Leave these blank to use the default values for the selected storage unit in the storage system.

If you are installing a battery to use for both self consumption and backup, you may want to configure the modeling to assume the battery will never be discharged below, say, 50%, so that it always maintains a reserve in case of a power outage. Even if the power outage occurs right after the battery finishes its daily peak time-of-use discharge cycle in the evening, it will still have 50% capacity for powering backed up loads. You would set the Minimum State of Charge to 50% in this case.

Room Temperature

Battery performance is highly sensitive to the outside temperature. You can increase the accuracy of the modeling by specifying the expected average room temperature. This value defaults to 20℃ (68℉).

Inverter/Charge Controller Efficiency

As described in the PV Coupling section above, if you add an inverter to a storage system, or if the storage system is sharing the inverter defined in the PV system, SolarNexus will use the published efficiency of that inverter by default when calculating conversion losses in the battery simulation. If necessary, you can choose to override that efficiency with a custom value.

If you don't explicitly define the inverter in the storage or PV system, SolarNexus will use a default assumed efficiency value for the inverter when calculating conversion losses. You can set that value to customize the assumed efficiency.

Likewise, if using a DC coupled setup, you can review and configure the assumed efficiency of the charge controller. Leave it at 100 if the system has no charge controller.

Battery Performance Details

While the annual throughput in the Battery Bank section gives you an indication of the overall battery performance, you can click the Battery Performance Details button to see additional information about of the modeled performance.

First Year Performance

This section shows the projected metrics in the first year of operation:

• Total Charge: Total amount of energy stored from PV or the grid. This is the total incoming energy before any inverter / charge controller / battery losses.
• Avg. Round Trip Efficiency: End-to-end efficiency from PV to storage back to AC. (Throughput = Total Charge * Round Trip Efficiency.)
  • In an AC coupled setup, this reflects the PV DC-to-AC conversion efficiency times the AC-to-DC storage conversion efficiency times the internal battery efficiency times the storage DC-to-AC conversion efficiency.
  • In a DC coupled setup, this reflects the PV-to-storage DC-to-DC efficiency times the internal battery efficiency times the storage DC-to-AC conversion efficiency.(The annual throughput is equivalent to the total annual charge minus input losses and output losses.
• Number of Cycles: Number of times the battery completed a charge/discharge cycle. For a typical residential configuration with daily cycling, this will usually be close to 365. However, even with expected daily cycling, it's possible for this number to exceed 365. The battery doesn't have to fully charge or discharge in order to count as a cycle. SolarNexus counts a new cycle whenever the battery goes from charging to discharging to charging again. Depending on irregularities in modeled hourly energy usage and PV output, it's possible for the battery to discharge during an hour where load exceeds PV output, charge again in the next hour if PV exceeds load, and then discharge again in the following hour if load exceeds PV output again. This can result in more than one reported cycle in a given day.
• Avg. Depth of Discharge: Average energy the battery discharges on each cycle. This is the difference between the maximum and minimum state of charge during a cycle. For example, if the battery is discharged from 95% of capacity (95% state of charge) down to 10% of its capacity (10% state of charge), that's considered an 85% depth of discharge. The value can be calculated as the annual discharge (throughput) divided by number of cycles divided by battery capacity. Avg. depth of discharge is an indication of how well the battery is being utilized. If the avg. depth of discharge is 50%, it means on average only half of the battery capacity is being used. Reasons for this being less than 100% include:
  • The storage modeling configuration includes a limit on the minimum/maximum state of charge. If you set the minimum state of charge to 20% and the maximum state of charge to 100%, for example, then the avg. depth of discharge will never be higher than 80%.
  • Battery is oversized. If the battery has more capacity than is needed to store the average amount of excess PV, the battery won't get fully charged from PV during the day and will thus only be able to discharge only a portion of its capacity in the evening.

Lifetime Performance

This table shows the projected throughput and performance degradation over the course of the battery lifetime. The Cumulative Throughput column shows the sum of the yearly discharged energy (throughput) up to each year. It's expressed in megawatt hours to match with how battery vendors often reference lifetime throughput in their warranties. The Retained Capacity % column shows how the effective capacity of the battery is projected to degrade by the end of each year. For example, in the screenshot above, the retained capacity is 81.5% at the end of year 10. That means the battery is only capable of storing 81.5% of its original capacity. The reduction in Charge and Discharge quantities each year is a result of the reduction in retained capacity.

Note: The Cashflows CSV that you can download from the Cashflows tab on the Analysis screen also includes a row showing the estimated annual/lifetime storage discharge (throughput).

It's important to understand that the projected capacity degradation is based on the modeled operation of the battery, not on a static degradation table. The higher the average depth of discharge, and the more annual cycles, the faster the battery will degrade.

Degradation also depends on battery chemistry and other attributes, so degradation curves will vary somewhat from battery to battery. In general, Lithium Iron Phosphate (LFP) batteries like Enphase, Pika and Sonnen degrade somewhat more slowly than Nickel Manganese Cobalt Oxide (NMC) batteries like the Tesla Powerwall and LG Chem RESU10.

 

Interactions with Other Systems

PV Systems

Energy storage systems are generally proposed in conjunction with a PV System to increase self consumption of PV generated kWhs. The interaction of the two is defined by the configuration of the dispatch model applied to the energy storage system (see above).

Efficiency Measures

SolarNexus accounts for projected efficiency savings in the battery simulation. First we subtract the efficiency savings from the original load before passing it into the simulation, so the battery simulation is operating on post-efficiency measure load rather than customer's current load.

 

Analyzing Energy Impact

SolarNexus simulates the operation of a storage system over each hour of the year so we can model the effect on energy flows on an hourly, daily, monthly and annual basis. We present this data in several ways to help you understand and visualize the storage system's energy impact at different levels of detail.

Annual Self Consumption

As a high-level summary of the overall energy impact, SolarNexus displays the battery's annual self consumption percentage in the upper right of the Storage System module. You'll see this number recalculate in real-time as you make changes to the storage equipment or modeling configuration.  

The annual self consumption from storage is the proportion of the site's total annual (post-efficiency measure) energy consumption that is projected to be supplied directly (behind the meter) from the storage system. For example, if the site uses a total of 12,000 kWh in a year, and the storage system is projected to charge and discharge 2,000 kWh over the course of the year to meet load, that means 20% of the site's consumption is self consumption from storage.

The energy impact summary at the top of the Services screen further shows how the storage system increases the overall self consumption of the proposed solution.

In this example, 39.9% of the site's annual consumption is projected to be self consumed from the PV system. Even if, say, the PV system offsets 100% of usage, this is saying that only 39.9% of annual consumption comes directly from the PV system while it is generating power. The remaining 54.6% is exported as excess energy during the day and imported back from the grid at night. However, with the addition of storage, an additional 16.7% of annual consumption will be supplied directly on site, by retaining excess solar during the day and discharging it to offset grid usage in the evening. The storage system thus increases the overall self consumption to 56.6% while also exporting energy to the grid.

Monthly Self Consumption

You can drill in to view self consumption by month by opening the Monthly / Hourly menu in the Annual Self Consumption summary and selecting Monthly Self Consumption %.

This takes you to the Energy Analysis screen, showing a graph of self consumption % by month. Percentage of energy imported from the grid is shown in black, percentage of energy self consumed from PV is shown in green, and percentage of energy self consumed from storage is shown in blue. You can see that in this case, self consumption from PV is lower in the winter months than the summer months while self consumption from storage is more consistent month-to-month.

Monthly Energy Flows

While the Self Consumption tab on the Energy Analysis screen shows the relative mix of energy sources, the Energy Flow tab shows the absolute quantity of grid imports, exports and self consumed energy.

The stacked quantities above the zero line show the inflow of energy while the stacked quantities below the zero line show the outflow of energy. The orange line shows the site's total monthly consumption. Above the line, black is imported energy from the grid, green is self consumed energy from PV, blue is self consumed energy from storage. Below the line, light green is exported energy from excess PV and yellow is stored energy from excess PV.

In this example, SolarNexus is projecting that in January almost all excess PV generation will be captured by the proposed storage system (yellow), but that stored energy when discharged (blue) is only enough to offset a small portion of grid usage. In June, on the other hand, the storage system is only capturing a small portion of the excess PV, but when discharged, that stored energy is enough to offset more than half of what would otherwise be imported from the grid.

The key thing to observe is that the blue and yellow bars show how a portion of the excess PV each month that would otherwise get exported to the grid is instead stored locally and discharged to offset grid imports.

Here is how the energy flow looks for the same system without storage:

By mentally overlaying the the yellow and blue bars from the chart above over this chart, you can visualize the effect of storage as taking a chunk out of the PV export bars (daytime) and shifting them to offset a chunk of the grid import bars (evening).

Daily Energy Flows

You can drill in to see projected daily energy flows for any month by clicking on the bars for that month in the Monthly Energy Flow chart.

This chart shows projected energy flow for the month of October for a particular solution. Notice that there are no blue bars (storage discharge) for any weekend days. That's because the storage system was configured to use the Load Shifting - Time of Use Optimization dispatch strategy and the solution specified a post-project tariff that has no peak periods on the weekends. Because all weekend hours have off-peak rates, there is no economic benefit to load shifting on the weekends and the storage system lies dormant. Actually, you can see that the battery is recharged from excess PV on Saturday but not discharged again until the following Monday.

Note: energy consumption is constant from day-to-day in this example because the project used a modeled, geo-typical load profile which assumes that all weekdays in a month have the same "weekday" load and all weekends in a month have the same "weekend" load. See here for more details about load modeling in SolarNexus.

Hourly Energy Flows

You can continue drilling in to see projected hourly energy flows for any day by clicking the bars for that day in the Daily Energy Flow chart. Here's the chart for October 18 (to pick a day at random).

To help you see the effect of storage more clearly, here's the chart for the same day for the same system without storage:

The orange line represents the site's modeled energy consumption during each hour of the day. You can see that in the early morning, the site is fully powered by the grid (black bars). Then at 7am, PV (green) starts to kick in, powering a small part of the load. By 9am, PV is fully powering the load plus generating some excess power. In the "no storage" scenario above, the excess PV is all exported back to the grid (light green). That continues until around 5pm when PV ramps down and the site is again fully powered by the grid for the rest of the night.

The particular post-solar tariff used in this example has peak time-of-use rates from 4pm-9pm. This is indicated on the chart by the shaded gray background during that period. You can see that most of the excess PV production is exported during off-peak hours while four out of the five peak hours are projected to be fully powered by the grid. The aim of installing storage for this project is to reduce grid usage during those peak, costly hours, and more specifically to increase the value of the exported PV by using it to offset grid energy when rates are high rather than selling the excess PV back to the utility when rates are low.

Going back to the first chart above showing the "with storage" scenario, you can see that load shifting in action. At 9am when PV first starts generating more energy than the site needs, rather than exporting the excess energy (light green), the site uses it to charge the battery (yellow). The battery continues charging from excess PV through 1pm, at which point the battery is full and excess PV is then exported to the grid. Then at 4pm, when PV production becomes insufficient to fully meet load, rather than importing from the grid (black), the battery is discharged (blue) to make up the difference. The battery continues discharging to meet load through the peak evening hours until 9pm, when it is no longer financially beneficial to self consume from storage.

As with the monthly chart above, you can mentally overlay the "with storage" chart onto the "without storage" chart to visualize how the storage system is shifting energy, from yellow to blue, to offset grid usage and extract more value from PV. 

Effect of Dispatch Strategy

Because the storage system used for the charts above was configured to use the Time of Use Optimization dispatch strategy, SolarNexus restricted the discharge to the peak hours for the selected tariff (4pm-9pm). Changing the system's dispatch strategy to Maximize Self Consumption results in the following chart for the same day:

It looks similar, but notice that the battery is now projected to discharge through 9pm, which is outside of the peak period. Under the Maximize Self Consumption strategy, SolarNexus runs the storage simulation such that the battery always tries to fully discharge. Because the discharge window is unconstrained, the storage system is actually able to utilize more of its capacity. You can see that the battery charging extends further into the day than in the Time of Use Optimization scenario above, indicating that the battery started its charge cycle at a lower state of charge, presumably because the battery was able to fully discharge the previous evening rather than being constrained by the peak period.

In fact, the storage system used in this example had a projected average depth of discharge of 69.7% and 365 annual cycles when configured to use the Maximize Self Consumption strategy, compared to a 58.5% average depth of discharge and 249 annual cycles when configured to use the Time of Use Optimization strategy. As a result, the system had a projected annual throughput of 2,696 kWh and annual self consumption of 22.5% when using the Maximize Self Consumption strategy vs. a projected annual throughput of 1,543 kWh and annual consumption of 12.9% when using the Time of Use Optimization strategy. This shows that it's important to properly model storage for the customer's specific post-project tariff scenario in order to make an accurate battery sizing assessment.

Energy Flows by Time of Use

When designing a storage system for time-of-use optimization, the most relevant energy metric is the amount of self consumption, or grid offset, during the peak time of use. With peak periods occurring late in the afternoon into the evening, customers will tend to have little self-consumption from PV, which is of course the impetus for storage. The more a storage system can offset grid usage during the peak period, the higher the bill savings will be.

You can see the overall annual self consumption during the peak period by going to the Energy Flow or Self Consumption % tabs on the Energy Analysis Screen and selecting Show By: Time of Use above the chart.

This view shows the energy flows for each time of use: Off Peak, Partial Peak, On Peak. (Some tariffs only have Off Peak and On Peak.)

In this example, you can see that the proposed solution is doing a good job at offsetting most of the grid usage in the On Peak period. There is some self consumption from PV (green) in the peak period, a larger amount of self consumption from storage (blue) and only a small amount of usage from the grid (black). Because this system was configured to use the Time of Use Optimization dispatch strategy, there is no self consumption from storage in the Off Peak or Partial Peak periods. You can also see that all the charging (yellow) takes place during the Off Peak period.

If we were to use the Maximize Self Consumption dispatch strategy, you can see again that self consumption from storage is no longer limited to the peak period (as we also saw above on the daily chart):

(Note that there is no economic reason to use the Maximize Self Consumption strategy with a time-of-use tariff, and in fact it is harmful because you end up losing money on each cycle that doesn't shift load from a more expensive rate period due to efficiency losses, but we're just showing it here for illustrative purposes.)

Back to the Optimize Time of Use scenario, you can drill in to see the energy flows in each specific seasonal time of use period by selecting Show By: Time of Use Period above the chart.

Here you can see that the site has 100% self consumption in the Summer On-Peak period and somewhat less than 100% in the Winter Mid-Peak period (which is the most expensive winter rate). Though relatively speaking, there is more absolute energy consumed from storage in the Winter Mid-Peak period.

 

Financial Analysis

When you run an analysis on a solution with a storage system, you'll see a summary of the storage system in the System Summary section at the top of the Analysis screen.

Storage Incentives - Rebates and Customer's Annual Value of Backup

There are two primary types of financial incentives in acquiring energy storage systems:

1. Government / Utility Rebates (not very common)
2. Annual value of having energy backup in case of outages (common, and typically the biggest financial value of having energy storage). See Energy Storage - Value of Backup Energy.

Like all project incentives, storage project incentives are defined for a given solution in the Analysis Parameters. Review and confirm applicability of default incentives or select additional incentives before running the analysis.

An administrator for your SolarNexus account can configure what storage incentives to add to your projects by default. Go to Administration > Project Settings > Analysis Parameters, add storage incentives and be sure to select "Energy Storage" as the service type and they'll automatically get added to all solution analyses that include storage.

 

Battery Replacement Costs

The only storage-specific analysis parameter is the battery replacement cost in the O&M section: 

Battery life is determined by chemistry, usage, and maintenance. Any long-term investment analyses should include realistic O&M costs, which mean battery replacements.

If you want to include the projected cost of replacing the batteries over the course of the analysis period, click on the O&M section to enter a replacement cost.

The projected replacement cost you enter will be applied at the end of the battery's useful life as determined by the battery replacement policy configured in the storage modeling section on the Services screen. You can enter the projected replacement cost as a fixed amount or as an amount per kWh of capacity. After running the analysis, you'll see the replacement cost reflected in the appropriate year(s) of the Estimated O&M Expenses column of the cash flows table.

 

Cost & Benefit Analysis (Load Shifting)

When you analyze a solar plus storage solution in SolarNexus, the Cost & Benefit Summary on the Analysis screen reflects the combined costs and benefits of the entire solution.

In addition, SolarNexus gives you a couple of ways to understand the incremental value of adding storage to a PV proposal.

Utility Bill Savings

The Electric Utility Bill Savings section includes a line, called Avg Monthly Bill w/o Storage, that shows what the post-project utility bill would be with only PV and no storage. By comparing this to the post-project utility bill for the whole solution, you can see the estimated incremental bill savings from adding storage.

In this example, the estimated monthly utility bill with a PV-only solution is $166.42, while the estimated monthly bill with the full PV + Storage solution is $116.25. That means storage is saving the customer an additional $50/month, for around a 25% incremental savings on top of solar.

Note: The Cashflows CSV that you can download from the Cashflows tab also includes rows showing the estimated annual/lifetime bill savings with solar-only and with solar+storage.

Storage systems can generate bill savings in at least a couple of main ways:

• Load shifting - charging the battery from excess PV or the grid when rates are low and discharging to meet load when rates are high, thereby saving on consumption charges. The higher the differential, the more savings.
• Peak shaving - using storage to reduce peak demand in order to lower demand charges.

(As of December 2018, SolarNexus only supports modeling for load shifting applications.) 

Levelized Value of Solar plus Storage (load shifting applications)

A useful way of looking at the value of solar and storage for load shifting applications is on a levelized basis -- the value per kWh generated and the value per kWh stored/discharged. When you analyze a solution with PV and storage, you'll see a section at the bottom with a number of levelized value metrics. 

Levelized metrics for Year 1:

ACP - Solar	Avoided Cost of Power for Solar. The year 1 avoided cost (utility bill savings) from solar per kWh of year 1 solar production.
ACP - Storage	Avoided Cost of Power for Storage. The additional year 1 avoided cost (utility bill savings) from adding storage per kWh of year 1 battery throughput.
ACP - Solar+Storage	Avoided Cost of Power for Solar plus Storage. The year 1 avoided cost (utility bill savings) from solar plus storage per kWh of solar production.

Levelized metrics for system lifetime:

LACE - Solar	Levelized Avoided Cost of Energy for Solar. The discounted lifetime avoided cost (utility bill savings) from solar per kWh of discounted lifetime solar production.
LACE - Storage	Levelized Avoided Cost of Energy for Storage. The discounted lifetime avoided cost (utility bill savings) from adding a battery per kWh of discounted lifetime battery discharge.
LACE - Solar+Storage	Levelized Avoided Cost of Energy for Solar plus Storage. The discounted lifetime avoided cost (utility bill savings) from solar plus storage per kWh of discounted lifetime solar production.

Taking the example above:

ACP - Solar = year 1 solar bill savings ($2497) / year 1 PV production (10850 kWh) = $0.23/kWh
ACP - Storage = year 1 storage savings ($602) / year 1 storage throughput (3635 kWh) = $0.16/kWh
ACP - Solar+storage = year 1 total savings (3099) / year 1 PV production (10850 kWh) = $0.29/kWh

 

ACP - Storage reflects the average differential between the import price of energy at the time it's discharged and the export price at the time it's stored (assuming the battery is charged from PV).

Notice that ACP - Solar+Storage is NOT the same thing as ACP - Solar + ACP - Storage. They have different denominators. ACP - Solar is the value per kWh generated by the PV system. ACP - Storage is the value per kWh stored and discharged by the battery.

But you can think of the storage system as increasing the value of each kWh generated by the PV system. That increase in value is the difference between ACP - Solar and ACP - Solar+Storage. So in the example above, storage is estimated to increase the value of each kWh of PV by 6 cents.

 

System Sizing

You may need to use some trial and error to find the best combination of PV system size and storage size. What counts as "best", of course, depends on the metric you're trying to optimize. For example, your goal might be to find the combination with the highest IRR that zeros out the customer bill.

Generally, in a retail-rate net metering scenario, given a PV system with 100% load offset, you'll be able to downsize the PV system somewhat when adding storage while keeping the bill at $0 (or as close to $0 as you can get given the utility's minimums). In tariff scenarios with lower export rates, where a 100% offset system still doesn't zero out the bill, you might be able to keep the system at or above 100% offset and use storage to bring down the bill.

To conduct the trial and error, one approach is to define a solution with a typically sized PV system and a typically sized storage system. Then clone that solution a number of times, changing either the PV system size or the storage capacity in each new solution and comparing the analysis results on the metrics you want to optimize.

As you add storage, look for the point where you hit diminishing returns. That is, if you double the storage capacity in a solution but the throughput and self consumption from storage don't double, it means the additional storage cannot be fully utilized and the customer won't get full value out of it for the cost.

 

Modeling Considerations

Load Modeling

When SolarNexus models the hour-by-hour operation of the storage system, the resulting energy impact and bill savings estimates are sensitive to the customer's hourly load profile. If the modeled load profile is significantly different from the true load profile, the results can be skewed. For example, if the modeled load profile assumes a majority of energy consumption happens during the day while the sun is shining, but the actual energy consumption is shifted more into the evening, SolarNexus will underestimate how much excess PV is available for charging the battery and will underestimate the potential value of installing solar.

The best case is if you can obtain actual interval data for the customer and upload it using the GreenButton format.

Lacking that, you can specify an hourly load profile to use for modeling. By default, SolarNexus uses a "geo-typical" load profile for the project, developed based on averaging a number of actual load profiles for sites in the geographic area. The geo-typical profile is usually good enough if you don't have any additional information about the customer's usage patterns. However, if you have specific details about the customer's usage, such as whether they are home during the day, use air conditioning, etc., you can apply a custom load profile to improve the accuracy of the modeling. This can be particularly important for commercial projects where actual load profiles vary significantly depending on the type of business.

Read the Defining Custom Load Profiles article for more information.

 

Limitations (as of Dec. 2018)

• You cannot add both an energy storage system and an efficiency measure to a solution if you are USING A GREEN BUTTON FILE for defining usage.