solar project finance model xls

solar project finance model xls

Developing an Effective Solar Project Finance Model in Excel

1. Introduction to Solar Project Finance

These key metrics are estimated at the project planning stage and used to evaluate business operation scenarios, entitlement frameworks, and equity and debt financing options. The modeling results capture the building blocks of solar valuation and allow the investor to make informed investment decisions. The more advanced the project modeling, the more financial investment decision options can be explored.

In addition, the developer must look at the longer-term implications of the project and the associated investment decision, planting the seeds of the investment decision and creating the conceptual dimensions of the “solar installed capacity paradox”. Is “installed solar” the return of the “immovable object” logistics investment decision?

Solar project finance consists of the calculated anticipation of the cash investment and further modeling of the project to assess the functionality of the project. Projected cash flow performance metrics – such as the project payback period, the project internal rate of return, and the levelized cost of electricity – are used to gauge the basic economic feasibility of the project.

What exactly is solar project finance, and why model it? Why not just go out and build a solar farm?

2. Key Components of a Solar Project Finance Model

The sophistication of your solar project finance model should match the complexity of your solar project. For small 100-300KW solar projects, a few links in Excel that clearly describe the project cash flows would suffice. For large 20MW+ scale projects, a comprehensive project finance financial model that describes the project cash flows should also include a DSCR (debt service coverage ratio) model, a cash sweep model, IRR model, and sensitivity and scenario analysis with flexible analysis on key financial drivers is warranted. As a professional solar project finance consultant, I have created large scale operational 20MW+ project finance models that allow the client to conduct discounted cash flow analysis, achievable DSCR analysis, sensitivity analysis, scenario analysis, IRR analysis on key financial drivers including tax equity benefits, and stress test analysis. Optional results in sensitivity and scenario analysis usually include distributions of IRR, 20-year NPV, and annual DSCR. The model allows for opportunities to maximize P50 and P90 IRR in various market environments. Parameters include equity internal rate of return and expected holding period.

– Project cash flows model – Project finance model – Power pricing models – Regulatory incentives – Bonus depreciation (capital cost allowance) and the investment tax credit – Operating and maintenance cost models – Debt service coverage ratio models – Cash equity internal rate of return model – Sensitivity and scenario analysis – Stress tests

The key components of a solar project finance model in Excel include:

3. Building and Structuring the Excel Model

Real estate developers and financiers have been using solar photovoltaic (PV) project finance models to calculate investment returns and compare finance costs since the ITC/1603 was passed in January 2009. However, few financial engineers and finance academics have undergone the important effort to fully understand financial models for solar projects and/or the ecological performance of solar panels. The aim of this chapter will be to educate by discussing conceptual, methodological and technical aspects of financial models designed for solar projects in global markets with a focus on the US. The key objective is to present a discussion of the methodologies and procedures typically used in the itemized formulation of such models, while emphasizing practical advice as frequently as possible. The items will be accompanied by real-world examples of input and output files in Excel.

After extensive research and due diligence, the decision has been made to develop a solar project. What’s the next step? How should developers and financiers proceed? What are the key risks that developers and financiers need to be aware of, in order to optimally allocate the risks in the capital structure? What information do utility and other makers of power purchase agreements (PPAs) expect the developers to provide, so that the PPAs can be negotiated and formed? How can developers raise cheap debt financing in order to maximize the magnitude of their equity returns? These issues are addressed in the current chapter, which will discuss how to create financial models for solar power projects and their numerous risks, nuances and pitfalls.

4. Sensitivity Analysis and Risk Management in Solar Project Finance Models

A clean debt sponsored or leveraged model structure is defined by a maximum debt commitment at the initial flip, combined with an equity cushion that results in a predetermined distribution waterfall as opposed to profit splits. Investors or lending institutions feel more comfortable with a corporate approach that entails minimum guarantees and increasingly higher debt coverage ratios. Moreover, a profitable IRR can still be generated from the asset even after altering the original basis of the cash flows with debt. Additionally, most players in the market have already priced in the benefits associated with permanent tax deductions like depreciation into the price of their panels. In essence, lease deals and deals with unattractive tax motivations are often passed over in favor of clean debt sponsored tax pass-through structures.

In the previous several sections, we have discussed the key parameters that solar project developers might look at when analyzing whether a potential solar project site makes sense for development. We have then moved on to discuss how developers can take into account complex scenarios, such as accelerated or bonus depreciation and the taxation of state or federal grants, when doing the tax equity side of a solar project finance model. The preceding section helped to provide a better understanding of several possible outcomes based on the variability of the inputs – more specifically, the tail case analysis. The final set of tools and tests within a solar project finance model are simply those that specifically address the inherent sensitivity of the initial partnership flip. Due to this inherent risk, few deals with partnership structures make it to the second tier of financing. Furthermore, the real-world deals that we have examined monthly often do not hold together after these highly leveraged partnership deals are first closed.

5. Case Studies and Best Practices

When building solar project finance models, data input can be simple or complex depending on the desired level of accuracy and the type of technology chosen by the potential investor. This model will always require an ample volume of very diverse project data, also often obtained in different submodels, which is necessary for the final construction of an integrated model. Models are always attached to tools that are consistent with the degree of detail about future events that the project owner wants to have. To portray the model that will be developed, it will determine the best and worst practices in each of these cases, pointing out the precise aspects that must be addressed in the model to project future better events. In this part, there are eight recommendations to use the model. The recommended improvements are added to the working model. At the end of the chapter, it is important to highlight project finance models that are often used in the financing of photovoltaic projects by banks, investors, and financial institutions.

The third part discusses case studies and best practices when using the solar project finance model. These case studies are a result of queries and suggestions provided by various readers and users of the model. Note that the model does not include functions that allow for a simple tax equity flip. Some functions can be used as building blocks to code more complex structures. This guide represents an effective tool for project finance analysts. If you are looking for other sophisticated structured project finance models, this is not the model for you. Some users have already suggested updating some functions in different areas, which will be taken into consideration for improvement in the next version of the model.