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Modeling 101: Clear, Accurate, and Auditable Spreadsheets

Posted on February 6, 2017 by Josh Lutton and Shirley You

Spreadsheets are important tools for all manner of organizational analysis and decision making.  Considering their importance, it is critical they are clear, accurate, and auditable.  We’ve built hundreds of models and in the process we’ve developed a set of guidelines that help us ensure our models reach these goals.  Here are our top seven recommendations:

1. Focus on Organization

A fundamental question for any model is how to organize it.  Starting with a well-organized structure can save many headaches down the road.

First, ask yourself:

  • How can I break the model into logical sections?
  • How should I label sections?
  • Who is my audience for this model? Would this make sense to him or her?
  • Would the user understand if I moved certain sections to different sheets?

Once you have the basic outline, work your way through the calculations linearly.  We typically build models with logic that starts at the top of a sheet and works linearly downward.  Enforcing a structure like this ensures the modeler’s logic is sound and makes it easier for the user to see that A leads to B leads to C and so on.  Models with logic moving higgledy-piggledy over a worksheet or workbook are easy to foul up and hard to understand.

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YieldCo Cost of Capital

Posted on May 10, 2016 by Shirley You and Josh Lutton

Large renewable energy project developers often use a type of financing vehicle colloquially known as a “YieldCo” to finance portfolios of assets that are expected to have stable cash flows over relatively long periods, such as solar or wind farms.  In theory, investors should be willing to accept lower returns on investments in these “safe” assets than they would on investments in the developers themselves, thus reducing the cost of capital for such assets and increasing their value.

We thought it would be useful to see how this has worked out in practice.  In this post, we show how we determine the cost of capital for a yieldco using 8point3 Energy Partners, a yieldco formed by SunPower and First Solar to own and operate solar systems, as an example.  Then we show the results of using the same methodology across a number of public yieldcos with a variety of asset types.  On average, we find a cost of yieldco equity is 7.01% levered and 5.46% unlevered.

This relatively low cost of capital has implications for the value of projects held or purchased by yieldcos.  It should allow developers that have yieldcos to sell their projects at attractive prices, and allow their yieldcos to pay more than many other project investors for projects they purchase from independent developers.

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Energy Storage 301: Solar + Storage Economics

Posted on November 17, 2015 by Micah Sussman and Josh Lutton

In this post we examine the economics of solar + storage.  We examine the value of solar and storage for two commercial buildings in each of three markets: California, New York, and Hawaii.  We find solar and storage are strongly synergistic in all three markets.

The NPVs of solar + storage investments are greater than the sum of the NPVs of solar investments and storage investments alone because, among other reasons:

  • The combination allows for much larger demand charge reductions than either technology can achieve on its own
  • Pairing storage with solar allows the owner of the storage system to claim the federal Investment Tax Credit on the storage system, subject to certain constraints on how it is charged

(We looked at the returns to storage alone in an earlier post.)

We are grateful to Geli, a provider of intelligent energy storage software solutions, which provided the building load profiles, solar production estimates, and storage system operating profiles for the analysis. Thanks to this cooperation we were also able to validate the economic calculations in our model versus those in an independently developed model.
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Energy Storage 201: Commercial BTM Energy Storage

Posted on September 4, 2015 by Josh Lutton and Micah Sussman

This is the third in a series of posts on grid energy storage. Earlier, in Energy Storage 101 and 102, we attempted to elucidate the applications of energy storage for various customer types and discussed the technologies and value chain. In this post, we examine the economics of behind-the-meter (BTM) storage for commercial customers. We model the returns to a hypothetical commercial BTM storage customer in New York City, San Diego, Honolulu, and Des Moines. We show how it is possible to optimize returns by sizing the battery intelligently with a software model.

For economy, we use the term “commercial” here to represent any non-residential end user of electricity, including commercial enterprises, schools, non-profits, government entities, etc. Also, we assume the host is the owner of the storage system.

Applications of Commercial Energy Storage

As we mentioned in Energy Storage 101, commercial customers have several potential sources of value for energy storage (Figure 1):

Figure 1: Sources of Value from commercial Btm energy storage

Sources of value from commercial BTM nergy storageStorage can be used for peak shaving and/or backup power.  Many buildings already have segregated wiring for systems they want running in case of an outage (e.g. elevators or emergency lighting), but in most cases a battery designed for peak shaving will not have enough capacity to run an entire building.  Here, we focus here only on the economics of peak shaving only because modelling the value of back-up power relies heavily on the importance of continuous power to a specific building.

In some markets, storage can also generate grid services revenue. For example, a storage system owner could sell frequency response services to an ISO or “generation” capacity to a utility.

Finally, storage could create value in conjunction with solar if storage would allow a larger solar system than would otherwise be allowed or economic and solar is otherwise less expensive than the grid. A battery system installed together with solar would also be eligible for an investment tax credit (30% through 2016, 10% thereafter). For simplicity, we don’t consider solar + batteries in this analysis. We will come back to this in a future post.

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Energy Storage 102: Technology and Value Chain

Posted on August 26, 2015 by Josh Lutton and Micah Sussman

This is the second in a series of posts on grid energy storage. In Energy Storage 101, we discussed how various customer types can benefit from storage.In this post, we discuss key storage technologies and identify the economic value chain for battery storage. Next week, we will examine, in detail, the economics of commercial behind-the-meter storage in Energy Storage 201.

Energy Storage Technologies

A variety of energy storage technologies have been/may be used for each the applications we described in Energy Storage 101. However, there are some technologies that are simply better for some applications than others. Here we will briefly examine the some of the more popular technologies:

  • Pumped hydro
  • Lithium ion batteries
  • Lead acid batteries
  • Sodium sulfur batteries
  • Flow batteries
  • Others (flywheel, compressed air, other batteries, etc.)

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