Tag Archives: fossil fuels

Levelized costs are calculated correctly

The Utility Dive recently published an opinion article that claimed that the conventional method of calculating the levelized cost of energy (LCOE) is incorrect. The UD article was derived from an article published in 2019 in the Electricity Journal by the same author, James Loewen. The article claimed that conventional method gave biased results against more capital intensive generation resources such as renewables compared to fossil fueled ones. I wrote a comment to the Electricity Journal showing the errors in Loewen’s reasoning and further reinforcing the rationale for the conventional LCOE calculation. (You have until August 9 to download my article for free.)

I was the managing consultant that assisted the California Energy Commission (CEC) in preparing one of the studies (CEC 2015) referenced in Loewen. I also led the preparation of three earlier studies that updated cost estimates. (CEC 2003, CEC 2007, CEC 2010) In developing these models, the consultants and staff discussed extensively this issue and came to the conclusion that the LCOE must be calculated by discounting both future cashflows and future energy production. Only in this way can a true comparison of discounted energy values be made.

The error in Loewen’s article arises from a misconception that money is somehow different and unique from all other goods and services. Money serves three roles in the economy: as a medium of exchange, as a unit of account, and as a store of value. At its core, money is a commodity used predominantly as an intermediary in the barter economy and as a store of value until needed later. (We can see this particularly when currency was generally backed by a specific commodity–gold.) Discounting derives from the opportunity cost of holding, and not using, that value until a future date. So discounting applies to all resources and services, not just to money.

Blanchard and Fischer (1989) at pp. 70-71, describe how “utility” (which is NOT measured in money) is discounted in economic analysis. Utility is gained by consumption of goods and services. Blanchard and Fischer has an extensive discussion of the marginal rate of substitution between two periods. Again, note there is no discussion of money in this economic analysis–only the consumption of goods and services in two different time periods. That means that goods and services are being discounted directly. The LCOE must be calculated in the same manner to be consistent with economic theory.

We should be able to recover the net present value of project cost by multiplying the LCOE by the generation over the economic life of the project. We only get the correct answer if we use the conventional LCOE.  I walk through the calculation demonstrating this result in the article.

Calculating the risk reduction benefits of closing Germany’s nuclear plants

Max Aufhammer at the Energy Institute at Haas posted a discussion of this recent paper reviewing the benefits and costs of the closure of much of the German nuclear fleet after the Fukushima accident in 2011.

Quickly reading the paper, I don’t see how the risk of a nuclear accident is computed, but it looks like the value per MWH was taken from a different paper. So I did a quick back of the envelope calculation for the benefit of the avoided consequences of an accident. This paper estimates a risk of an accident once every 3,704 reactor-operating years (which is very close to a calculation I made a few years ago). (There are other estimates showing significant risk as well.) For 10 German reactors, this translates to 0.27% per year.

However, this is not a one-off risk, but rather a cumulative risk over time, as noted in the referenced study. This is akin to the seismic risk on the Hayward Fault that threatens the Delta levees, and is estimated at 62% over the next 30 years. For the the German plants, this cumulative probability over 30 years is 8.4%. Using the Fukushima damages noted in the paper, this represents $25 to $63 billion. Assuming an average annual output of 7,884 GWH, the benefit from risk reduction ranges from $11 to $27 per MWH.

The paper appears to make a further error in using only the short-run nuclear fuel costs of $10 per MWH as representing the avoided costs created by closing the plants. Additional avoided costs include avoided capital additions that accrue with refueling and plant labor and O&M costs. For Diablo Canyon, I calculated in PG&E’s 2019 ERRA proceeding that these costs were close to an additional $20 per MWH. I don’t know the values for the German plants, but clearly they should be significant.

Repost: A catalog of studies on whether renewables create grid instability | Greentech Media

GTM compiles the studies done over the last month in anticipation of the release of the study ordered by Energy Secretary Rick Perry to examine how increased renewable energy threatens grid reliability.

Source: The Rising Tide of Evidence Against Blaming Wind and Solar for Grid Instability | Greentech Media

Proposed TOU rate revisions are “fighting the last war” in California


California’s investor-owned utilities (IOUs) have asserted that the underlying costs molding time variant or time of use (TOU) rate structures should be largely, or even exclusively, derived based on conventional fossil generation costs. The IOUs rely on “net load” to determine TOU prices, calculated by subtracting all load met by renewables, nuclear and hydropower generation—the majority of the utilities’ generation fleets.

In theory, net load is the portion of the load served by fossil-fueled generation that has the highest short-run operating costs, and therefore is “marginal.” The infamous “duck curve” shown above depicts the net load (not the metered load.) Yet, the marginal energy generation for most load is no longer served by natural gas; it is now met by renewable energy contracts. The utilities’ net load approach ignores the bulk of their true marginal costs to serve added load, which arise from procuring renewables.[1] The IOUs’ resource procurement has been dominated by adding solar, wind, biofuels, and other renewables since at least 2006 to meet the state’s renewable portfolio standard (RPS), first at 20 percent, then 33 percent, and soon 50 percent.

The tunnel-vision focus on net, rather than the entire, load is especially problematic in the context of State policy to phase-down fossil fuel generation. Eventually, natural gas production will even more significantly diminish, and could disappear from the grid entirely, leaving no price-setting metric under this paradigm. Insistence on the net load approach in the face of this transformation is akin to evaluating the economics of ridesharing based on the exclusive cost of taxis, without consideration of Uber® and Lyft®.

Once fossil-fuel resources are used minimally – an explicit state goal reflected in SB 350 – and potentially no longer on the margin, it is unclear what price benchmark the utilities will propose to set time-variant rates.  Continuing the trend toward fewer fossil-fuel resources is already reflected in pending legislation in Sacramento that proposes a clean-peak standard – AB 1405[2] – and a 100 percent Renewable Portfolio Standard—SB 584.[3] Relying solely on the cost of generation resources that State policy plans to phaseout to define TOU periods is inconsistent with good, long-term, ratemaking principles.  Instead, marginal energy generation costs should be calculated, at least in part, from a set of recent RPS-eligible PPAs, weighted by time of delivery.

Likewise, the marginal energy costs derived using the net load method, which drive the proposed shifts in TOU periods, reflect less than one-third of total average utility rates. The IOUs do not explain why cost differences within a modest component of overall rates should steer determination of TOU periods.

Further, it is not clear why the California Public Utilities Commission (CPUC) should rely on a speculative forecast about load shapes in 2024—seven years from now—to set today’s TOU periods. As the CPUC is well aware, the electricity system is changing rapidly along many dimensions. Infusion of utility-scale renewables, which is driving the IOUs’ rate analyses, is but one factor. Increasing amounts of storage and electric vehicles, shifting work patterns, and other social and economic factors will substantially influence load profiles over the next decade. In 2006, few energy experts foresaw stagnant, or even falling, electricity demand; there is even greater uncertainty today.

[1]This perspective excludes contributions made by utility-scale renewables that meet most of the remaining load, and by customer-side resources.

[2] See http://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201720180AB1405

[3] See https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=201720180SB584