Underwriting Battery Energy Storage Systems (BESS) as an asset class
The nuanced requirements and risk assessments that make BESS an attractive yet complex asset class for investors
3 minute read
Prashant Khorana
Director, Power & Renewables Consulting
Prashant Khorana
Director, Power & Renewables Consulting
Prashant is Director, Data Product Owner – Asset Valuations within Wood Mackenzie's research and data organisation.
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View Brianna Alix's full profileUnderwriting Battery Energy Storage Systems (BESS) as an asset class requires a significantly more granular understanding of power markets than wind and solar.
From our conversations with investors, a few characteristics are necessary to make BESS investible:
- Infrastructure investors (core and core + value add) require confidence around modelling risks on the downside. Private Equity investors are already comfortable with the risk-return profile of BESS assets (both tolled and un-tolled). However, infrastructure investors still need further comfort around price risks.
- Guaranteed revenue streams for at least 50-60% of the nameplate capacity are required for lenders to be comfortable with permanent data. Most investors want to raise as much tax equity and debt as possible for their portfolios to deliver the lowest possible cost of capital for their portfolios.
- Volatility needs to be better understood to appreciate the equity upside case. Investors need more clarity on ‘why volatility would be higher for longer and why ancillaries would not eventually go to zero’ due to forecast inaccuracy in the intra-day market.
- Although most investors understand the value of taking on merchant risk, the general perception of merchant and uncontracted facilities being labelled as high risk remains an issue.
- Getting comfortable around the concentration risk, that is, most of the revenue being tied to a few days of high-risk opportunities for uncontracted facilities, is required.
- Coverage by OEMs and EPCs around liquidation damage payouts is required in case of delays or performance issues in the first few years of BESS operation. Specifically, in Texas, this coverage is important as damages could be significant as a large portion of revenue is derived from a small window of time.
Using a combination of fundamental and stochastic modelling
We used a combination of fundamental and stochastic modelling for battery revenue estimation. Ingestion of fundamental forecast data produced by the WoodMac long term modelling team is a critical first step. Fundamentals data ingested includes, but is not limited to, forecasted and historical hourly Day-Ahead (DA) power price data, historical Real-Time (RT) power price data, historical ancillaries data, and project characteristics. All these characteristics are ingested into a fundamental commitment optimisation engine to simulate forecasts for DA and RT markets. Historical and forecasted data on ancillaries and zonal pricing is used as an expectation, but volatility is simulated based on historical data. More specifically, for ancillaries, we use historical ancillary pricing data at the hourly, sub-hourly level, 5-min, or 15-minute level, depending on service and market.
Historical ancillary data, program expansion, weather forecasts, and growth in share of renewable capacity are all used to generate a view of the ancillary pricing forecast.
Generating opinions on which types of flexible resources are called for and which service requires extrapolating historical developments with strategic foresight on how power markets will evolve is a non-trivial task. However, our subject matter experts at Wood Mackenzie weigh in on such assumptions, and our consulting team uses operational data to validate assumptions.
Considering an archetype BESS Asset in Arizona
As an illustration, we consider a 55MW facility with a battery sized at equal pairing (55MWh or longer based on duration). We illustrate the value of adding a battery at various durations (1,2,4 hours). The choice of the hubs was not driven by market size but by the ease of explainability for this case study.
In this study (Palo Verde), we consider price points adjacent to the core pricing point. Wheeling power to neighbouring zones could be an option in some cases where the opportunity set is big enough to justify the costs of bringing in power from adjacent markets.
BESS as an asset class requires a meaningfully different approach than a standalone wind or solar facility. Colloquially, investors refer to BESS as the ‘Swiss army knife’ of the power system. Knowing which tool to pull from the army knife and at which time makes the difference between a winning or losing strategy.
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