Tag Archives: electricity rates

Comparing cost-effectiveness of undergrounding vs. microgrids to mitigate wildfire risk

Pacific Gas & Electric has proposed to underground 10,000 miles of distribution lines to reduce wildfire risk, at an estimated cost of $1.5 to $2 million per mile. Meanwhile PG&E has installed fast-trip circuit breakers in certain regions to mitigate fire risks from line shorts and breaks, but it has resulted in a vast increase in customer outages. CPUC President Batjer wrote in an October 25 letter to PG&E, “[s]ince PG&E initiated the Fast Trip setting practice on 11,500 miles of lines in High Fire Threat Districts in late July, it has caused over 500 unplanned power outages impacting over 560,000 customers.” She then ordered a series of compliance reports and steps. The question is whether undergrounding is the most cost-effective solution that can be implemented in a timely manner.

A viable alternative is microgrids, installed at either individual customers or community scale. The microgrids could be operated to island customers or communities during high risk periods or to provide backup when circuit breakers cut power. Customers could continue to be served outside of either those periods of risk or weather-caused outages.

Because microgrids would be installed solely for the purpose of displacing undergrounding, the relative costs should be compared without considering any other services such as energy delivered outside of periods of fire risk or outages or increased green power.

I previously analyzed this question, but this updated assessment uses new data and presents a threshold at which either undergrounding or microgrids is preferred depending on the range of relative costs.

We start with the estimates of undergrounding costs. Along with PG&E’s stated estimate, PG&E’s 2020 General Rate Case includes a settlement agreement with a cost of $4.8 million per mile. That leads to an estimate of $15 to $48 million. Adding in maintenance costs of about $400 million annually, this revenue requirement translates to a rate increase of 3.2 to 9.3 cents per kilowatt-hour.

For microgrid costs, the National Renewable Energy Laboratory published estimated ranges for both (1) commercial or community scale projects of 1 megawatt with 2.4 megawatt-hours of storage and (2) residential scale of 7 kilowatts with 20 kilowatt-hours of storage. For larger projects, NREL shows ranges of $2.07 to $2.13 million; we include an upper end estimate double of NREL’s top range. For residential; the range is $36,000 to $38,000.

Using this information, we can make comparisons based on the density of customers or energy use per mile of targeted distribution lines. In other words, we can determine if its more cost-effective to underground distribution lines or install microgrids based on how many customers or how much load is being served on a line.

As a benchmark, PG&E’s average system density per mile of distribution line is 50.6 customers and 166 kW (or 0.166 MW).

The table below shows the relative cost effectiveness for undergrounding compared to community/commercial microgrids. If the load density falls below the value shown, microgrids are more cost effective. Note that the average density across the PG&E service area is 0.166 MW which is below any of the thresholds. That indicates that such microgrids should be cost-effective in most rural areas.

The next table shows the relative cost effectiveness for individual residential microgrids, and again if the customer density falls below the threshold shown, then microgrids save more costs. The average density for service area is 51 customers per line-mile which reflects the concentration of population in the Bay Area. At the highest undergrounding costs, microgrids are almost universally favored. In rural areas where density falls below 30 customers per line-mile, microgrids are less costly at the lower undergrounding costs.

PG&E has installed two community-scale microgrids in remote locations so far, and reportedly considering 20 such projects. However, PG&E fell behind on those projects, prompting the CPUC to reopen its procurement process in its Emergency Reliability rulemaking. In addition, PG&E has relied heavily on natural gas generation for these.

PG&E simply may not have the capacity to construct either microgrids or install undergrounded lines in a timely manner solely through its organization. PG&E already is struggling to meet its targets for converting privately-owned mobilehome park utility systems to utility ownership. A likely better choice is to rely on local governments working in partnership with PG&E to identify the most vulnerable lines to construct and manage these microgrids. The residential microgrids would be operated remotely. The community microgrids could be run under several different models including either PG&E or municipal ownership.

The scale economy myth of electric utilities

Vibrant Clean Energy released a study showing that inclusion of large amounts of distributed energy resources (DERs) can lower the costs of achieving 100% renewable energy. Commentors here have criticized the study for several reasons, some with reference to the supposed economies of scale of the grid.

While economies of scale might hold for individual customers in the short run, the data I’ve been evaluating for the PG&E and SCE general rate cases aren’t necessarily consistent with that notion. I’ve already discussed here the analysis I conducted in both the CAISO and PJM systems that show marginal transmission costs that are twice the current transmission rates. The rapid rise in those rates over the last decade are consistent with this finding. If economies of scale did hold for the transmission network, those rates should be stable or falling.

On the distribution side, the added investment reported in those two utilities’ FERC Form 1 are not consistent with the marginal costs used in the GRC filings. For example the added investment reported in Form 1 for final service lines (transmission, services, meters or TSM) appears to be almost 10 times larger than what is implied by the marginal costs and new customers in the GRC filings. And again the average cost of distribution is rising while energy and peak loads have been flat across the CAISO area since 2006. The utilities have repeatedly asked for $2 billion each GRC for “growth” in distribution, but given the fact that load has been flat (and even declining in 2019 and 2020), that means there’s likely a significant amount of stranded distribution infrastructure. If that incremental investment is for replacement (which is not consistent with either their depreciation schedules or their assertions about the true life of their facilties and the replacement costs within their marginal cost estimates), then they are grossly underestimating the future replacement cost for facilities which means they are underestimating the true marginal costs.

I can see a future replacement liability right outside my window. The electric poles were installed by PG&E 60+ years ago and the poles are likely reaching the end of their lives. I can see the next step moving to undergrounding the lines at a cost of $15,000 to $25,000 per house based on the ongoing mobilehome conversion program and the typical Rule 20 undergrounding project. Deferring that cost is a valid DER value. We will have to replace many services over the next several decades. And that doesn’t address the higher voltage parts of the system.

We have a counterexample of a supposed monopoly in the cable/internet system. I have at least two competing options where I live. The cell phone network also turned out not to be a natural monopoly. In an area where the PG&E and Merced ID service territories overlap, there are parallel distribution systems. The claim of a “natural monopoly” more likely is a legal fiction that protects the incumbent utility and is simpler for local officials to manage when awarding franchises.

If the claim of natural monopolies in electricity were true, then the distribution rate components for SCE and PG&E should be much lower than for smaller munis such as Palo Alto or Alameda. But that’s not the case. The cost advantages for SMUD and Roseville are larger than can be simply explained by differences in cost of capital. The Division/Office of Ratepayer Advocates commissioned a study by Christensen Associates for PG&E’s 1999 GRC that showed that the optimal utility size was about 500,000 customers. (PG&E’s witness who was a professor at UC Berkeley inadvertently confirmed the results and Commissioner Richard Bilas, a Ph.D. economist, noted this in his proposed decision which was never adopted because it was short circuited by restructuring.) Given that finding, that means that the true marginal cost of a customer and associated infrastructure is higher than the average cost. The likely counterbalancing cause is an organizational diseconomy of scale that overwhelms the technological benefits of size.

Finally, generation no longer shows the economies of scale that dominated the industry. The modularity of combined cycle plants and the efficiency improvement of CTs started the industry down the rode toward the efficiency of “smallness.” Solar plants are similarly modular. The reason why additional solar generation appears so low cost is because much of that is from adding another set of panels to an existing plant while avoiding additional transmission interconnection costs (which is the lion’s share of the costs that create what economies of scale do exist.)

The VCE analysis looks a holistic long term analysis. It relies on long run marginal costs, not the short run MCs that will never converge on the LRMC due to the attributes of the electricity system as it is regulated. The study should be evaluated in that context.

Part 2: A response to “Is Rooftop Solar Just Like Energy Efficiency?”

Severin Borenstein at the Energy Institute at Haas has written another blog post asserting that solar rooftop rates are inefficient and must changed radically. (I previously responded to an earlier post.) When looking at the efficiency of NEM rates, we need to look carefully at several elements of electricity market and the overall efficiency of utility ratemaking. We can see that we can come to a very different conclusion.

I filed testimony in the NEM 3.0 rulemaking last month where I calculated the incremental cost of transmission investment for new generation and the reduction in the CAISO peak load that looks to be attributable to solar rooftop.

  • Using FERC Form 1 and CEC powerplant data, I calculated that the incremental cost of transmission is $37/MWH. (And this is conservative due to a couple of assumptions I made.) Interestingly, I had done a similar calculation for AEP in the PJM interconnect and also came up with $37/MWH. This seems to be a robust value in the right neighborhood.
  • Load growth in California took a distinct change in trend in 2006 just as solar rooftop installations gained momentum. I found a 0.93 correlation between this change in trend and the amount of rooftop capacity installed. Using a simple trend, I calculated that the CAISO load decreased 6,000 MW with installation of 9,000 MW of rooftop solar. Looking at the 2005 CEC IEPR forecast, the peak reduction could be as large as 11,000 MW. CAISO also estimated in 2018 that rooftop solar displaced in $2.6 billion in transmission investment.

When we look at the utilities’ cost to acquire renewables and add in the cost of transmission, we see that the claim that grid-scale solar is so much cheaper than residential rooftop isn’t valid. The “green” market price benchmark used to set the PCIA shows that the average new RPS contract price in 2016 was still $92/MWH in 2016 and $74/MWH in 2017. These prices generally were for 30 year contracts, so the appropriate metric for comparing a NEM investment is against the vintage of RPS contracts signed in the year the rooftop project was installed. For 2016, adding in the transmission cost of $37/MWH, the comparable value is $129/MWH and in 2017, $111/MWH. In 2016, the average retail rates were $149/MWH for SCE, $183/MWH for PG&E and $205/MWH for SDG&E. (Note that PG&E’s rate had jumped $20/MWH in 2 years, while SCE’s had fallen $20/MWH.) In a “rough justice” way, the value of the displaced energy via rooftop solar was comparable to the retail rates which reflect the value of power to a customer, at least for NEM 1.0 and 2.0 customers. Rooftop solar was not “multiples” of grid scale solar.

These customers also took on investment risk. I calculated the payback period for a couple of customers around 2016 and found that a positive payback was dependent on utility rates rising at least 3% a year. This was not a foregone conclusion at the time because retail rates had actually be falling up to 2013 and new RPS contract prices were falling as well. No one was proposing to guarantee that these customers recover their investments if they made a mistake. That they are now instead benefiting is unwarranted hubris that ignores the flip side of the importance of investment risk–that investors who make a good efficient decision should reap the benefits. (We can discuss whether the magnitude of those benefits are fully warranted, but that’s a different one about distribution of income and wealth, not efficiency.)

Claiming that grid costs are fixed immutable amount simply isn’t a valid claim. SCE has been trying unsuccessfully to enact a “grid charge” with this claim since at least 2006. The intervening parties have successfully shown that grid costs in fact are responsive to reductions in demand. In addition, moving to a grid charge that creates a “ratchet effect” in revenue requirements where once a utility puts infrastructure in place, it faces no risk for poor investment decisions. On the other hand the utility can place its costs into ratebase and raise rates, which then raises the ratchet level on the fixed charge. One of the most important elements of a market economy that leads to efficient investment is that investors face the risk of not earning a return on an investment. That forces them to make prudent decisions. A “ratcheted” grid charge removes this risk even further for utilities. If we’re claiming that we are creating an “efficient” pricing policy, then we need to consider all sides of the equation.

The point that 50% of rooftop solar generation is used to offset internal use is important–while it may not be exactly like energy efficiency, it does have the most critical element of energy efficiency. That there are additional requirements to implement this is of second order importance, Otherwise we would think of demand response that uses dispatch controls as similarly distinct from EE. Those programs also require additional equipment and different rates. But in fact we sum those energy savings with LED bulbs and refrigerators.

An important element of the remaining 50% that is exported is that almost all of it is absorbed by neighboring houses and businesses on the same local circuit. Little of the power goes past the transformer at the top of the circuit. The primary voltage and transmission systems are largely unused. The excess capacity that remains on the system is now available for other customers to use. Whether investors should be able to recover their investment at the same annual rate in the face of excess capacity is an important question–in a competitive industry, the effective recovery rate would slow.

Finally, public purpose program (PPP) and wildfire mitigation costs are special cases that can be simply rolled up with other utility costs.

  • The majority of PPP charges are a form of a tax intended for income redistribution. That function is admirable, but it shows the standard problem of relying on a form of a sales tax to finance such programs. A sales tax discourages purchases which then reduces the revenues available for income transfers, which then forces an increase in the sales tax. It’s time to stop financing the CARE and FERA programs from utility rates.
  • Wildfire costs are created by a very specific subclass of customers who live in certain rural and wildlands-urban interface (WUI) areas. Those customers already received largely subsidized line extensions to install service and now we are unwilling to charge them the full cost of protecting their buildings. Once the state made the decision to socialize those costs instead, the costs became the responsibility of everyone, not just electricity customers. That means that these costs should be financed through taxes, not rates.

Again, if we are trying to make efficient policy, we need to look at the whole. It is is inefficient to finance these public costs through rates and it is incorrect to assert that there is an inefficient subsidy created if a set of customers are avoiding paying these rate components.

Part 1: A response to “Rooftop Solar Inequity”

Severin Borenstein at the Energy Institure at Haas has plunged into the politics of devising policies for rooftop solar systems. I respond to two of his blog posts in two parts here, with Part 1 today. I’ll start by posting a link to my earlier blog post that addresses many of the assertions here in detail. And I respond to to several other additional issues here.

First, the claims of rooftop solar subsidies has two fallacious premises. First, it double counts the stranded cost charge from poor portfolio procurement and management I reference above and discussed at greater length in my blog post. Take out that cost and the “subsidy” falls substantially. The second is that solar hasn’t displaced load growth. In reality utility loads and peak demand have been flat since 2006 and even declining over the last three years. Even the peak last August was 3,000 MW below the record in 2017 which in turn was only a few hundred MW above the 2006 peak. Rooftop solar has been a significant contributor to this decline. Displaced load means displaced distribution investment and gas fired generation (even though the IOUs have justified several billion in added investment by forecasted “growth” that didn’t materialized.) I have documented those phantom load growth forecasts in testimony at the CPUC since 2009. The cost of service studies supposedly showing these subsidies assume a static world in which nothing has changed with the introduction of rooftop solar. Of course nothing could be further from the truth.

Second TURN and Cal Advocates have all be pushing against decentralization of the grid for decades back to restructuring. Decentralization means that the forums at the CPUC become less important and their influence declines. They have all fought against CCAs for the same reason. They’ve been fighting solar rooftops almost since its inception as well. Yet they have failed to push for the incentives enacted in AB57 for the IOUs to manage their portfolios or to control the exorbitant contract terms and overabundance of early renewable contracts signed by the IOUs that is the primary reason for the exorbitant growth in rates.

Finally, there are many self citations to studies and others with the claim that the authors have no financial interest. E3 has significant financial interests in studies paid for by utilities, including the California IOUs. While they do many good studies, they also have produced studies with certain key shadings of assumptions that support IOUs’ positions. As for studies from the CPUC, commissioners frequently direct the expected outcome of these. The results from the Customer Choice Green Book in 2018 is a case in point. The CPUC knows where it’s political interests are and acts to satisfy those interests. (I have personally witnessed this first hand while being in the room.) Unfortunately many of the academic studies I see on these cost allocation issues don’t accurately reflect the various financial and regulatory arrangements and have misleading or incorrect findings. This happens simply because academics aren’t involved in the “dirty” process of ratemaking and can’t know these things from a distance. (The best academic studies are those done by those who worked in the bowels of those agencies and then went to academics.)

We are at a point where we can start seeing the additional benefits of decentralized energy resources. The most important may be the resilience to be gained by integrating DERs with EVs to ride out local distribution outages (which are 15 times more likely to occur than generation and transmission outages) once the utilities agree to enable this technology that already exists. Another may be the erosion of the political power wielded by large centralized corporate interests. (There was a recent paper showing how increasing market concentration has led to large wealth transfers to corporate shareholders since 1980.) And this debate has highlighted the elephant in the room–how utility shareholders have escaped cost responsibility for decades which has led to our expensive, wasteful system. We need to be asking this fundamental question–where is the shareholders’ skin in this game? “Obligation to serve” isn’t a blank check.

Transmission: the hidden cost of generation

The cost of transmission for new generation has become a more salient issue. The CAISO found that distributed generation (DG) had displaced $2.6 billion in transmission investment by 2018. The value of displacing transmission requirements can be determined from the utilities’ filings with FERC and the accounting for new power plant capacity. Using similar methodologies for calculating this cost in California and Kentucky, the incremental cost in both independent system operators (ISO) is $37 per megawatt-hour or 3.7 cents per kilowatt-hour in both areas. This added cost about doubles the cost of utility-scale renewables compared to distributed generation.

When solar rooftop displaces utility generation, particularly during peak load periods, it also displaces the associated transmission that interconnects the plant and transmits that power to the local grid. And because power plants compete with each other for space on the transmission grid, the reduction in bulk power generation opens up that grid to send power from other plants to other customers.

The incremental cost of new transmission is determined by the installation of new generation capacity as transmission delivers power to substations before it is then distributed to customers. This incremental cost represents the long-term value of displaced transmission. This amount should be used to calculate the net benefits for net energy metered (NEM) customers who avoid the need for additional transmission investment by providing local resources rather than remote bulk generation when setting rates for rooftop solar in the NEM tariff.

  • In California, transmission investment additions were collected from the FERC Form 1 filings for 2017 to 2020 for PG&E, SCE and SDG&E. The Wholesale Base Total Revenue Requirements submitted to FERC were collected for the three utilities for the same period. The average fixed charge rate for the Wholesale Base Total Revenue Requirements was 12.1% over that year. That fixed charge rate is applied to the average of the transmission additions to determine the average incremental revenue requirements for new transmission for the period. The plant capacity installed in California for 2017 to 2020 is calculated from the California Energy Commission’s “Annual Generation – Plant Unit”. (This metric is conservative because (1) it includes the entire state while CAISO serves only 80% of the state’s load and the three utilities serve a subset of that, and (2) the list of “new” plants includes a number of repowered natural gas plants at sites with already existing transmission. A more refined analysis would find an even higher incremental transmission cost.)

Based on this analysis, the appropriate marginal transmission cost is $171.17 per kilowatt-year. Applying the average CAISO load factor of 52%, the marginal cost equals $37.54 per megawatt-hour.

  • In Kentucky, Kentucky Power is owned by American Electric Power (AEP) which operates in the PJM ISO. PJM has a market in financial transmission rights (FTR) that values relieving the congestion on the grid in the short term. AEP files network service rates each year with PJM and FERC. The rate more than doubled over 2018 to 2021 at average annual increase of 26%.

Based on the addition of 22,907 megawatts of generation capacity in PJM over that period, the incremental cost of transmission was $196 per kilowatt-year or nearly four times the current AEP transmission rate. This equates to about $37 per megawatt-hour (or 3.7 cents per kilowatt-hour).

A new agricultural electricity use forecast method holds promise for water use management

Agricultural electricity demand is highly sensitive to water availability. Under “normal” conditions, the State Water Project (SWP) and Central Valley Project (CVP), as well as other surface water supplies, are key sources of irrigation water for many California farmers. Under dry conditions, these water sources can be sharply curtailed, even eliminated, at the same time irrigation requirements are heightened. Farmers then must rely more heavily on groundwater, which requires greater energy to pump than surface water, since groundwater must be lifted from deeper depths.

Over extended droughts, like between 2012 to 2016, groundwater levels decline, and must be pumped from ever deeper depths, requiring even more energy to meet crops’ water needs. As a result, even as land is fallowed in response to water scarcity, significantly more energy is required to water remaining crops and livestock. Much less pumping is necessary in years with ample surface water supply, as rivers rise, soils become saturated, and aquifers recharge, raising groundwater levels.

The surface-groundwater dynamic results in significant variations in year-to-year agricultural electricity sales. Yet, PG&E has assigned the agricultural customer class a revenue responsibility based on the assumption that “normal” water conditions will prevail every year, without accounting for how inevitable variations from these circumstances will affect rates and revenues for agricultural and other customers.

This assumption results in an imbalance in revenue collection from the agricultural class that does not correct itself even over long time periods, harming agricultural customers most in drought years, when they can least afford it. Analysis presented presented by M.Cubed on behalf of the Agricultural Energy Consumers Association (AECA) in the 2017 PG&E General Rate Case (GRC) demonstrated that overcollections can be expected to exceed $170 million over two years of typical drought conditions, with the expected overcollection $34 million in a two year period. This collection imbalance also increases rate instability for other customer classes.

Figure-1 compares the difference between forecasted loads for agriculture and system-wide used to set rates in the annual ERRA Forecast proceedings (and in GRC Phase 2 every three years) and the actual recorded sales for 1995 to 2019. Notably, the single largest forecasting error for system-wide load was a sales overestimate of 4.5% in 2000 and a shortfall in 2019 of 3.7%, while agricultural mis-forecasts range from an under-forecast of 39.2% in the midst of an extended drought in 2013 to an over-forecast of 18.2% in one of the wettest years on record in 1998. Load volatility in the agricultural sector is extreme in comparison to other customer classes.

Figure-2 shows the cumulative error caused by inadequate treatment of agricultural load volatility over the last 25 years. An unbiased forecasting approach would reflect a cumulative error of zero over time. The error in PG&E’s system-wide forecast has largely balanced out, even though the utility’s load pattern has shifted from significant growth over the first 10 years to stagnation and even decline. PG&E apparently has been able to adapt its forecasting methods for other classes relatively well over time.

The accumulated error for agricultural sales forecasting tells a different story. Over a quarter century the cumulative error reached 182%, nearly twice the annual sales for the Agricultural class. This cumulative error has consequences for the relative share of revenue collected from agricultural customers compared to other customers, with growers significantly overpaying during the period.

Agricultural load forecasting can be revised to better address how variations in water supply availability drive agricultural load. Most importantly, the final forecast should be constructed from a weighted average of forecasted loads under normal, wet and dry conditions. The forecast of agricultural accounts also must be revamped to include these elements. In addition, the load forecast should include the influence of rates and a publicly available data source on agricultural income such as that provided by the USDA’s Economic Research Service.

The Forecast Model Can Use An Additional Drought Indicator and Forecasted Agricultural Rates to Improve Its Forecast Accuracy

The more direct relationship to determine agricultural class energy needs is between the allocation of surface water via state and federal water projects and the need to pump groundwater when adequate surface water is not available from the SWP and federal CVP. The SWP and CVP are critical to California agriculture because little precipitation falls during the state’s Mediterranean-climate summer and snow-melt runoff must be stored and delivered via aqueducts and canals. Surface water availability, therefore, is the primary determinant of agricultural energy use, while precipitation and related factors, such as drought, are secondary causes in that they are only partially responsible for surface water availability. Other factors such as state and federal fishery protections substantially restrict water availability and project pumping operations greatly limiting surface water deliveries to San Joaquin Valley farms.

We found that the Palmer Drought Stress Index (PDSI) is highly correlated with contract allocations for deliveries through the SWP and CVP, reaching 0.78 for both of them, as shown in Figure AECA-3. (Note that the correlation between the current and lagged PDSI is only 0.34, which indicates that both variables can be included in the regression model.) Of even greater interest and relevance to PG&E’s forecasting approach, the correlation with the previous year’s PDSI and project water deliveries is almost as strong, 0.56 for the SWP and 0.53 for the CVP. This relationship can be seen also in Figure-3, as the PDSI line appears to lead changes in the project water deliveries. This strong relationship with this lagged indicator is not surprising, as both the California Department of Water Resources and U.S. Bureau of Reclamation account for remaining storage and streamflow that is a function of soil moisture and aquifers in the Sierras.

Further, comparing the inverse of water delivery allocations, (i.e., the undelivered contract shares), to the annual agricultural sales, we can see how agricultural load has risen since 1995 as the contract allocations delivered have fallen (i.e., the undelivered amount has risen) as shown in Figure-4. The decline in the contract allocations is only partially related to the amount of precipitation and runoff available. In 2017, which was among the wettest years on record, SWP Contractors only received 85% of their allocations, while the SWP provided 100% every year from 1996 to 1999. The CVP has reached a 100% allocation only once since 2006, while it regularly delivered above 90% prior to 2000. Changes in contract allocations dictated by regulatory actions are clearly a strong driver in the growth of agricultural pumping loads but an ongoing drought appears to be key here. The combination of the forecasted PDSI and the lagged PDSI of the just concluded water year can be used to capture this relationship.

Finally, a “normal” water year rarely occurs, occurring in only 20% of the last 40 years. Over time, the best representation of both surface water availability and the electrical load dependent on it is a weighted average across the probabilities of different water year conditions.

Proposed Revised Agricultural Forecast

We prepared a new agricultural load forecast for 2021 implementing the changes recommended herein. In addition, the forecasted average agricultural rate was added, which was revealed to be statistically valid. The account forecast was developed using most of the same variables as for the sales forecast to reflect similarities in drivers of both sales and accounts.

Figure-5 compares the performance of AECA’s proposed model to PG&E’s model filed in its 2021 General Rate Case. The backcasted values from the AECA model have a correlation coefficient of 0.973 with recorded values,[1] while PG&E’s sales forecast methodology only has a correlation of 0.742.[2] Unlike PG&E’s model almost all of the parameter estimates are statistically valid at the 99% confidence interval, with only summer and fall rainfall being insignificant.[3]

AECA’s accounts forecast model reflects similar performance, with a correlation of 0.976. The backcast and recorded data are compared in Figure-6. For water managers, this chart shows how new groundwater wells are driven by a combination of factors such as water conditions and electricity prices.




Can Net Metering Reform Fix the Rooftop Solar Cost Shift?: A Response

A response to Severin Borenstein’s post at UC Energy Institute where he posits a large subsidy flowing to NEM customers and proposes an income-based fixed charge as the remedy. Borenstein made the same proposal at a later CPUC hearing.

The CPUC is now considering reforming the current net energy metering (NEM) tariffs in the NEM 3.0 proceeding. And the State Legislature is considering imposing a change by fiat in AB 1139.

First, to frame this discussion, economists are universally guilty of status quo bias in which we (since I’m one) too often assume that changing from the current physical and institutional arrangement is a “cost” in an implicit assumption that the current situation was somehow arrived at via a relatively benign economic process. (The debate over reparations for slavery revolve around this issue.) The same is true for those who claim that NEM customers are imposing exorbitant costs on other customers.

There are several issues to be considered in this analysis.

1) In looking at the history of the NEM rate, the emergence of a misalignment between retail rates that compensate solar customers and the true marginal costs of providing service (which are much more than the hourly wholesales price–more on that later) is a recent event. When NEM 1.0 was established residential rates were on the order of 15 c/kWh and renewable power contracts were being signed at 12 to 15 c/kWh. In addition, the transmission costs were adding 2 to 4 c/kWh. This was the case through 2015; NEM 1.0 expired in 2016. NEM 2.0 customers were put on TOU rates with evening peak loads, so their daytime output is being priced at off peak rates midday and they are paying higher on peak rates for usage. This despite the fact that the difference in “marginal costs” between peak and off wholesale costs are generally on the order of a penny per kWh. (PG&E NEM customers also pay a $10/month fixed charge that is close to the service connection cost.) Calculating the net financial flows is more complicated and deserve that complex look than what can be captured in a simple back of the envelope calculation.

2) If we’re going to dig into subsidies, the first place to start is with utility and power plant shareholders. If we use the current set of “market price benchmarks” (which are problematic as I’ll discuss), out of PG&E’s $5.2 billion annual generation costs, over $2 billion or 40% are “stranded costs” that are subsidies to shareholders for bad investments. In an efficient marketplace those shareholders would have to recover those costs through competitively set prices, as Jim Lazar of the Regulatory Assistance Project has pointed out. One might counter those long term contracts were signed on behalf of these customers who now must pay for them. Of course, overlooking whether those contracts were really properly evaluated, that’s also true for customers who have taken energy efficiency measures and Elon Musk as he moves to Texas–we aren’t discussing whether they also deserve a surcharge to cover these costs. But beyond this, on an equity basis, NEM 1.0 customers at least made investments based on an expectation, that the CPUC did not dissuade them of this belief (we have documentation of how at least one county government was mislead by PG&E on this issue in 2016). If IOUs are entitled to financial protection (and the CPUC has failed to enact the portfolio management incentive specified in AB57 in 2002) then so are those NEM customers. If on the other hand we can reopen cost recovery of those poor portfolio management decisions that have led to the incentive for retail customers to try to exit, THEN we can revisit those NEM investments. But until then, those NEM customers are no more subsidized than the shareholders.

3) What is the true “marginal cost”? First we have the problem of temporal consistency between generation vs. transmission and distribution grid (T&D) costs. Economists love looking at generation because there’s a hourly (or subhourly) “short run” price that coincides nicely with economic theory and calculus. On the other hand, those darn T&D costs are lumpy and discontinuous. The “hourly” cost for T&D is basically zero and the annual cost is not a whole lot better. The current methods debated in the General Rate Cases (GRC) relies on aggregating piecemeal investments without looking at changing costs as a whole. Probably the most appropriate metric for T&D is to calculate the incremental change in total costs by the number of new customers. Given how fast utility rates have been rising over the last decade I’m pretty sure that the “marginal cost” per customer is higher than the average cost–in fact by definition marginal costs must be higher. (And with static and falling loads, I’m not even sure how we calculated the marginal costs per kwh. We can derive the marginal cost this way FERC Form 1 data.) So how do we meld one marginal cost that might be on a 5-minute basis with one that is on a multi-year timeframe? This isn’t an easy answer and “rough justice” can cut either way on what’s the truly appropriate approximation.

4) Even if the generation cost is measured sub hourly, the current wholesale markets are poor reflections of those costs. Significant market distortions prevent fully reflecting those costs. Unit commitment costs are often subsidized through out of market payments; reliability regulation forces investment that pushes capacity costs out of the hourly market, added incremental resources–whether for added load such as electrification or to meet regulatory requirements–are largely zero-operating cost renewables of which none rely on hourly market revenues for financial solvency; in California generators face little or no bankruptcy risk which allows them to underprice their bids; on the flip side, capacity price adders such as ERCOT’s ORDC overprices the value of reliability to customers as a backdoor way to allow generators to recover investments through the hourly market. So what is the true marginal cost of generation? Pulling down CAISO prices doesn’t look like a good primary source of data.

We’re left with the question of what is the appropriate benchmark for measuring a “subsidy”? Should we also include the other subsidies that created the problem in the first place?

AB1139 would undermine California’s efforts on climate change

Assembly Bill 1139 is offered as a supposed solution to unaffordable electricity rates for Californians. Unfortunately, the bill would undermine the state’s efforts to reduce greenhouse gas emissions by crippling several key initiatives that rely on wider deployment of rooftop solar and other distributed energy resources.

  • It will make complying with the Title 24 building code requiring solar panel on new houses prohibitively expensive. The new code pushes new houses to net zero electricity usage. AB 1139 would create a conflict with existing state laws and regulations.
  • The state’s initiative to increase housing and improve affordability will be dealt a blow if new homeowners have to pay for panels that won’t save them money.
  • It will make transportation electrification and the Governor’s executive order aiming for 100% new EVs by 2035 much more expensive because it will make it much less economic to use EVs for grid charging and will reduce the amount of direct solar panel charging.
  • Rooftop solar was installed as a long-term resource based on a contractual commitment by the utilities to maintain pricing terms for at least the life of the panels. Undermining that investment will undermine the incentive for consumers to participate in any state-directed conservation program to reduce energy or water use.

If the State Legislature wants to reduce ratepayer costs by revising contractual agreements, the more direct solution is to direct renegotiation of RPS PPAs. For PG&E, these contracts represent more than $1 billion a year in excess costs, which dwarfs any of the actual, if any, subsidies to NEM customers. The fact is that solar rooftops displaced the very expensive renewables that the IOUs signed, and probably led to a cancellation of auctions around 2015 that would have just further encumbered us.

The bill would force net energy metered (NEM) customers to pay twice for their power, once for the solar panels and again for the poor portfolio management decisions by the utilities. The utilities claim that $3 billion is being transferred from customers without solar to NEM customers. In SDG&E’s service territory, the claim is that the subsidy costs other ratepayers $230 per year, which translates to $1,438 per year for each NEM customer. But based on an average usage of 500 kWh per month, that implies each NEM customer is receiving a subsidy of $0.24/kWh compared to an average rate of $0.27 per kWh. In simple terms, SDG&E is claiming that rooftop solar saves almost nothing in avoided energy purchases and system investment. This contrasts with the presumption that energy efficiency improvements save utilities in avoided energy purchases and system investments. The math only works if one agrees with the utilities’ premise that they are entitled to sell power to serve an entire customer’s demand–in other words, solar rooftops shouldn’t exist.

Finally, this initiative would squash a key motivator that has driven enthusiasm in the public for growing environmental awareness. The message from the state would be that we can only rely on corporate America to solve our climate problems and that we can no longer take individual responsibility. That may be the biggest threat to achieving our climate management goals.

ERCOT has the peak period scarcity price too high

The freeze and resulting rolling outages in Texas in February highlighted the unique structure of the power market there. Customers and businesses were left with huge bills that have little to do with actual generation expenses. This is a consequence of the attempt by Texas to fit into an arcane interpretation of an economic principle where generators should be able to recover their investments from sales in just a few hours of the year. Problem is that basic of accounting for those cashflows does not match the true value of the power in those hours.

The Electric Reliability Council of Texas (ERCOT) runs an unusual wholesale electricity market that supposedly relies solely on hourly energy prices to provide the incentives for incenting new generation investment. However, ERCOT is using the same type of administratively-set subsidies to create enough potential revenue to cover investment costs. Further, a closer examination reveals that this price adder is set too high relative to actual consumer value for peak load power. All of this leads to a conclusion relying solely on short-run hourly prices as a proxy for the market value that accrues to new entrants is a misplaced metric.

The total ERCOT market first relies on side payments to cover commitment costs (which creates barriers to entry but that’s a separate issue) and second, it transfers consumer value through to the Operating Reserve Demand Curve (ORDC) that uses a fixed value of lost load (VOLL) in an arbitrary manner to create “opportunity costs” (more on that definition at a later time) so the market can have sufficient scarcity rents. This second price adder is at the core of ERCOT’s incentive system–energy prices alone are insufficient to support new generation investment. Yet ERCOT has ignored basic economics and set this value too high based on both available alternatives to consumers and basic regional budget constraints.

I started with an estimate of the number of hours where prices need the ORDC to be at full VOLL of $9000/MWH to recover the annual revenue requirements of combustion turbine (CT) investment based on the parameters we collected for the California Energy Commission. It turns out to be about 20 to 30 hours per year. Even if the cost in Texas is 30% less, this is still more 15 hours annually, every single year or on average. (That has not been happening in Texas to date.) Note for other independent system operators (ISO) such as the California ISO (CAISO), the price cap is $1,000 to $2,000/MWH.

I then calculated the cost of a customer instead using a home generator to meet load during those hours assuming a life of 10 to 20 years on the generator. That cost should set a cap on the VOLL to residential customers as the opportunity cost for them. The average unit is about $200/kW and an expensive one is about $500/kW. That cost ranges from $3 to $5 per kWh or $3,000 to $5,000/MWH. (If storage becomes more prevalent, this cost will drop significantly.) And that’s for customers who care about periodic outages–most just ride out a distribution system outage of a few hours with no backup. (Of course if I experienced 20 hours a year of outage, I would get a generator too.) This calculation ignores the added value of using the generator for other distribution system outages created by events like a hurricane hitting every few years, as happens in Texas. That drives down this cost even further, making the $9,000/MWH ORDC adder appear even more distorted.

The second calculation I did was to look at the cost of an extended outage. I used the outages during Hurricane Harvey in 2017 as a useful benchmark event. Based on ERCOT and U.S. Energy Information Reports reports, it looks like 1.67 million customers were without power for 4.5 days. Using the Texas gross state product (GSP) of $1.9 trillion as reported by the St. Louis Federal Reserve Bank, I calculated the economic value lost over 4.5 days, assuming a 100% loss, at $1.5 billion. If we assume that the electricity outage is 100% responsible for that loss, the lost economic value per MWH is just under $5,000/MWH. This represents the budget constraint on willingness to pay to avoid an outage. In other words, the Texas economy can’t afford to pay $9,000/MWH.

The recent set of rolling blackouts in Texas provides another opportunity to update this budget constraint calculation in a different circumstance. This can be done by determining the reduction in electricity sales and the decrease in state gross product in the period.

Using two independent methods, I come up with an upper bound of $5,000/MWH, and likely much less. One commentator pointed out that ERCOT would not be able achieve a sufficient planning reserve level at this price, but that statement is based on the premises that short-run hourly prices reflect full market values and will deliver the “optimal” resource mix. Neither is true.

This type of hourly pricing overemphasizes peak load reliability value and undervalues other attributes such as sustainability and resilience. These prices do not reflect the full incremental cost of adding new resources that deliver additional benefits during non-peak periods such as green energy, nor the true opportunity cost that is exercised when a generator is interconnected rather than during later operations. Texas has overbuilt its fossil-fueled generation thanks to this paradigm. It needs an external market based on long-run incremental costs to achieve the necessary environmental goals.

What is driving California’s high electricity prices?

This report by Next10 and the University of California Energy Institute was prepared for the CPUC’s en banc hearing February 24. The report compares average electricity rates against other states, and against an estimate of “marginal costs”. (The latter estimate is too low but appears to rely mostly on the E3 Avoided Cost Calculator.) It shows those rates to be multiples of the marginal costs. (PG&E’s General Rate Case workpapers calculates that its rates are about double the marginal costs estimated in that proceeding.) The study attempts to list the reasons why the authors think these rates are too high, but it misses the real drivers on these rate increases. It also uses an incorrect method for calculating the market value of acquisitions and deferred investments, using the current market value instead of the value at the time that the decisions were made.

We can explore the reasons why PG&E’s rates are so high, much of which is applicable to the other two utilities as well. Starting with generation costs, PG&E’s portfolio mismanagement is not explained away with a simple assertion that the utility bought when prices were higher. In fact, PG&E failed in several ways.

First, PG&E knew about the risk of customer exit as early as 2010 as revealed during the PCIA rulemaking hearings in 2018. PG&E continued to procure as though it would be serving its entire service area instead of planning for the rise of CCAs. Further PG&E also was told as early as 2010 (in my GRC testimony) that it was consistently forecasting too high, but it didn’t bother to correct thee error. Instead, service area load is basically at the save level that it was a decade ago.

Second, PG&E could have procured in stages rather than in two large rounds of request for offers (RFOs) which it finished by 2013. By 2011 PG&E should have realized that solar costs were dropping quickly (if they had read the CEC Cost of Generation Report that I managed) and that it should have rolled out the RFOs in a manner to take advantage of that improvement. Further, they could have signed PPAs for the minimum period under state law of 10 years rather than the industry standard 30 years. PG&E was managing its portfolio in the standard practice manner which was foolish in the face of what was occurring.

Third, PG&E failed to offer part of its portfolio for sale to CCAs as they departed until 2018. Instead, PG&E could have unloaded its expensive portfolio in stages starting in 2010. The ease of the recent RPS sales illustrates that PG&E’s claims about creditworthiness and other problems had no foundation.

I calculated the what the cost of PG&E’s mismanagement has been here. While SCE and SDG&E have not faced the same degree of exit by CCAs, the same basic problems exist in their portfolios.

Another factor for PG&E is the fact that ratepayers have paid twice for Diablo Canyon. I explain here how PG&E fully recovered its initial investment costs by 1998, but as part of restructuring got to roll most of its costs back into rates. Fortunately these units retire by 2025 and rates will go down substantially as a result.

In distribution costs, both PG&E and SCE requested over $2 billion for “new growth” in each of its GRCs since 2009, despite my testimony showing that growth was not going to materialize, and did not materialize. If the growth was arising from the addition of new developments, the developers and new customers should have been paying for those additions through the line extension rules that assign that cost responsibility. The utilities’ distribution planning process is opaque. When asked for the workpapers underlying the planning process, both PG&E and SCE responded that the entirety were contained in the Word tables in each of their testimonies. The growth projections had not been reconciled with the system load forecasts until this latest GRC, so the totals of the individual planning units exceeded the projected total system growth (which was too high as well when compared to both other internal growth projections and realized growth). The result is a gross overinvestment in distribution infrastructure with substantial overcapacity in many places.

For transmission, the true incremental cost has not been fully reported which means that other cost-effective solutions, including smaller and closer renewables, have been ignored. Transmission rates have more than doubled over the last decade as a result.

The Next10 report does not appear to reflect the full value of public purpose program spending on energy efficiency, in large part because it uses a short-run estimate of marginal costs. The report similarly underestimates the value of behind-the-meter solar rooftops as well. The correct method for both is to use the market value of deferred resources–generation, transmission and distribution–when those resources were added. So for example, a solar rooftop installed in 2013 was displacing utility scale renewables that cost more than $100 per megawatt-hour. These should not be compared to the current market value of less than $60 per megawatt-hour because that investment was not made on a speculative basis–it was a contract based on embedded utility costs.