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How is a portfolio of wind farms greater than the sum of its parts?

A few months ago, a financial client told us over the phone that the “portfolio effect” was a hoax! His exact words may have been that he did not observe the so-called benefits of the portfolio effect on the wind projects his company had invested in. Investment in a collection or portfolio of wind farms, while not new, seems to be especially popular right now as investors seek to reduce risk.  Many in the industry seem to be buying or selling (or not selling) not just one wind project at a time, but a bundled set of projects. This strategy of bundling different assets together to reduce overall risk is familiar. For example, if you want your retirement plan to stay afloat throughout your career, you invest in a variety of stocks and bonds so that if some do poorly one year, others that are doing well will keep your overall portfolio positive (or better yet growing).

As with stocks, the “portfolio effect” comes in when if one wind farm (or a subset of wind farms) performs poorly one year, hopefully other projects in the portfolio will have excellent performance thereby balancing out the bottom line. One goal is to minimize variability, because the more variable performance can be, the more likely you are to get a very bad year. Similarly, some investments (wind farms or otherwise) may turn out to have low returns in the long term while others will be long-term winners. Investing in a number of different assets will reduce the impact of the low performers in the long run as well as on a year-to-year basis.

The principle of diversification is straight forward; however, just as not every portfolio of stocks is created equal, neither is every wind portfolio. There are a few different factors that can make wind portfolios better or worse at achieving the goal of reducing risk. Of course one of the most important factors in individual wind farm and portfolio total performance is windiness. You can consult a global wind map for a static image of the long-term average windiness of different locations. For effective portfolios, however, you need to know how annual patterns of wind speeds vary over time. In other words, in years when it is less windy than average in Place A, does it tend to be more windy than average in Place B? The degree to which annual windiness patterns are uncorrelated (or negatively correlated) will in large part determine the strength of the portfolio. Large-scale climate patterns such as El Niño can connect the weather patterns of seemingly distant locations, so while geography is important, it is not the whole story. For example, annual average wind speeds in western NY State are correlated with an R-squared of approximately 0.25 to southwest Kansas, but as much as 0.7 to eastern Washington State. Good quality long-term wind data must be consulted to get a reliable view on the degree of correlation of wind resources in different regions.

Other forms of diversification will also serve the portfolio owner well, such as diversity of turbine technologies, and even diversity of energy estimation methods. Since future energy production (like stock performance) cannot be known in advance, we use various methods to estimate it. If there is a systematic bias in the estimation methods (there is evidence to suggest that a systematic bias has plagued the wind industry in the past, but may be improving in recent years, as discussed in a DNV GL report available for download, then there is a somewhat higher degree of dependence in these projects’ projected performance, even if they have different wind regimes and turbine technologies. The higher degree of correlation, in turn, leads to a diminished portfolio benefit.

Back to the financial client who was skeptical about the portfolio benefit for wind farms – we never did get all the details so we can only make educated guesses regarding his experience. Perhaps the wind farms in his portfolio were not in truly independent wind regimes. Perhaps there was a bias in the original wind energy estimates – in this case the portfolio effect, while real, may not have been of sufficient magnitude to make up for shortfalls in projected production. Finally, what time scale was he examining? It is important to remember that wind production is inherently variable. It is likely impossible, and certainly impractical, to create a portfolio so broad and diverse as to erase all year-to-year variability. There will still be “good” years and “bad” years, but with a sufficiently diverse portfolio, the bad years won’t be so bad. It is important to review portfolio performance over a sufficiently long period of time, much like your retirement plan investment strategy.

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