Risks of Going Solar

On February 22, 2016, Catherine Wolfram posted the blog Risks of Going Solar on the Energy Institute at Haas blog, part of the University of California Berkeley.  I posted the following, which I am adding to my blog.

Of the various regulatory Risks of Going Solar, Catherine Wolfram identifies two biggies, reducing the size of the net metering interval and shifting the rate design to include a smaller energy charge and a greater fixed charge.  But the risk of these two can be much larger than Dr. Wolfram suggests.  Reducing the size of the net metering interval exposes rooftop solar customers to the possibility of negative prices, while cost re-classification could result in (greater) demand charges instead of greater monthly customer charges.

In “Renewable Electric Power—Too Much of a Good Thing: Looking At ERCOT,” Dialogue, United States Association for Energy Economics, 2009 August,[1] I point out that a surplus of wind in West Texas forced the wholesale price for electricity below zero for about 25% of the pricing periods during that April, at least in West Texas.

Transmission constraints generally kept these negative prices from spreading to the rest of Texas.  Negative prices did spread to other parts of the state for just less than 1% of the rating periods.  As Dr. Wolfram well pointed out, these pricing periods are sometimes as short as 15 minutes (as they were in West Texas at the time), though are often one hour.

Many ISO do not seem to allow prices to go negative.  In West Texas, the combination of transmission constraints and the various credits[2] given to wind led to negative prices.  I believe that similar combinations elsewhere will force ISOs to allow negative prices in their dispatch programs.

I have long seen the need for utilities outside the footprint of an ISO to implement real time “value of solar” prices that are similarly negative.  Hawaii seems to be ripe for such negative solar prices.  Utilities outside the footprint of an ISO can implement “value of solar” prices using a Walrasian auction, as is discussed in many of my articles.

I actually disagree with the concept of a separate price for “value of solar.”  If we are to use prices to influence generation, there shouldn’t be a separate price for solar versus other spot generation imbalances.  A different price for unscheduled versus scheduled generation, yes, but not a separate price for just solar.

There will often be many prices during any pricing interval.  For instance, a single 15 minute period may be part of a 24×7 contracted delivery of power with one price and part of a 16×5 contracted deliveries with another price.  A third price might be applicable to variances.  Variances would include both solar that is dumped into the system and hiccups in the 24×7 or 16×5 deliveries, whether the hiccup is positive or negative.

Utility rate making often includes the concept of cost classification, where costs are identified as energy related, customer related, and demand related.  In the context of Risks of Going Solar, customer related and demand related are combined into the concept of a fixed charge.

The discussed increase in the monthly charge is only one way to reduce the energy charge.  The other way, and I believe a better way, to decrease the energy charge is to increase the demand charge, or to implement a demand charge when there is not a demand charge in place.

Customer charges impose greater burdens on small, often lower income, residential customers, while demand charges tend to protect these smaller customers, as is discussed in

  • “Curing the Death Spiral,” with Lori Cifuentes (Tampa Electric Company), Public Utilities Fortnightly, 2014 August;[3]
  • “Demand a Better Utility Charge During Era of Renewables: Getting Renewable Incentives Correct With Residential Demand Charges,” Dialogue, United States Association for Energy Economics, 2015 January;[4] and,
  • “Fairly Pricing Net Intervals While Keeping The Utility Financially Healthy,” 48th Annual Frontiers of Power Conference, cosponsored by The Engineering Energy Laboratory and The School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, Oklahoma, 2015 October 26-27.[5]

Thus, as we see a continued growth in solar, I see a growing need for finer pricing intervals and a growing need for demand charges.  Fortunately, the huge growth in interval meters allow these better rate designs.  We just need to political will to implement something other than a monthly charge for energy.

[1] http://livelyutility.com/documents/USAEE-ERCOT%20Aug%2009.pdf

[2] such as production tax credits and renewable energy credits

[3] https://www.fortnightly.com/fortnightly/2014/08/curing-death-spiral?authkey=54d8da5efd3f76661023d122f3e538b4b3db8c8d5bf97a65bc58a3dd55bb8672

[4] http://dialog.usaee.org/index.php/volume-23-number-1-2015/271-lively

[5] A copy is available on my website, www.LivelyUtility.com.

Grid Security in India

On 2011 February 26, S.K. Soonee, CEO at India’s Power System Operation Corporation Limited posted on LinkedIn’s Power System Operator’s Group a link to a paper written by the staff of India’s Central Electricity Regulatory Commission.   “Grid Security – Need For Tightening of Frequency Band & Other Measure” can be accessed at      http://www.cercind.gov.in/2011/Whats-New/AGENDA_NOTE_FOR_15TH_CAC_MEETINGHI.pdf  Through LinkedIn I provided the following comments.

 I am dismayed that the simple elegance of the UI pricing vector, as shown in the two diagrams for 2002-2004 and 2007-2009, will be replaced by the convoluted vectors on 2011 May 3. It seems that there is a potential for mischief with having the multitude of simultaneous prices, with an undue accumulation of money by the transmission grid as some UI out of the grid is priced at very high prices at the same instant that other UI into the grid is being priced at a lower price. This is an unwarranted arbitrage for the transmission system.

The HVDC links between S and NEW could provide a warranted arbitrage situation where the grid with lower frequency delivers to the grid with the lower frequency. The different frequencies would result in different prices, with the price differences providing some financial support for the HVDC links.

I was surprised that there was no mention made in regard to Figures 1 and 2 as to when UI pricing started, and how that UI onset resulted in a narrowing of the spread between daily high frequency and daily low frequency. I believe these figures could be well supplemented by a presentation of histograms of the monthly frequency excursions, and how those histograms have changed over time. A numeric approach would include monthly average frequency and monthly standard deviation from 50 Hertz, a statistic for which you have a special name that I forget.

Parts of the Agenda Note discuss the serious impact of very short periods of frequency excursions. These short periods of concern are much shorter than the 15 minute periods used for determining UI. The various parts of the Agenda Note could be harmonized by reducing the size of the settlement period for UI from 15 minutes to 5 minutes or 1 minute.

There is a discussion of limits on the amount of UI power that a participant can transact. I question the need for such limits. As a participant increases the UI power being transacted, the price will move in an unfavorable direction, providing an additional financial incentive for the participant to reduce UI power transactions. For example, a SEB that is short of power and is buying UI faces higher prices as the UI transaction amount increases. These higher prices provide a multiplicative incentive for the SEB to reduce its shortage and its purchase of UI.

Many systems plan for the biggest credible single contingency, which the report treats as the single largest unit. The report shows that entire plants have gone out at a same time, suggesting that the biggest credible single contingency is a plant not a generating unit.

As an aside, in the listing of the generating capacity by size of generating unit, my experience in the US suggests that the list understates the number of generators. There would be many times the identified number of plants if the list included captive generators such as backup generators, which may be as small as a few KW. Again, based on my experience in the US, the total capacity of those unidentified generators will rival the total capacity of the identified generators.

I wonder why the under frequency relays in the East are set lower than the relays in the other regions.

I don’t understand the terminology that “Nepal has several asynchronous ties with the Indian grid (AC radial links).” My interpretation is that Nepal has a disjoint system with each section tied synchronously to different locations of India, making the sections synchronous to each other through their links to India.

Load Profiles and Unscheduled Flows of Electricity

In response to my earlier comments about a Fox News article equating decoupling with socialism, I received a question about time of use rate making and how my comments regarding unscheduled flows of electricity picked on small utilities. My response follows.

Most utilities group customers by their consumption patterns. You are grouped with McMansions and with hovels. Not because you have the same consumption, but the same pattern. Let’s say that a McMansion uses 10 times the energy that you use each month. Then, if you look at the consumption for the period defined as “on peak”, the McMansion will use about 10 times the amount of electricity that you use “on peak”. Similarly during any other well defined period. TOU pricing will not differentiate your average price from his average price, or at least not much.

Not much unless you or the utility invest in devices that control your consumption patterns. Thirty five years ago I worked for American Electric Power (AEP) in its New York City office. I helped investigate ceramic storage, a concept then in use in England. Turn on electricity to these “hot rocks” at night and then during the day just blow a fan across them to get heat into the room. Conversely, there is ice storage. Connect your A/C unit to a tank that looks like a water heater. At night dump refrigerant through the Ice Bear (a commercial brand I have heard of) and create ice. During the day, put the refrigerant through the Ice Bear instead of running your compressor. This creates huge swings in the multiplier between you and McMansion. During the night the multiplier might be down to 5 or less. During the day, the multiplier might be up to 20. The result is that you pay a lower average rate using TOU if you manage your load.

Dynamic pricing means to me a moment by moment change in the price of electricity. During the hottest day of the year, the price might soar by a factor of 100. Avoid 7 hours at that high rate and you have reduced your average price by 1% (730 hours on average in the month) or more, at least if I have done the math correctly. Many utilities have equipment that they attach to your AC compressor to allow them to turn it off during such periods. The standard pricing approach is to pay you $5/month. They save money by avoiding some of the energy at the 100 times multiple.

Pricing is considered by many to be a form of rationing. Economists say that pricing is the best way to ration a commodity. It gets people to give up lower valued uses when there is a scarcity. I like to think of it as a way to soak those who can afford it so I can put in my controllers that allow me to store energy thermally. In some jargons, my thermal storage can be considered to be a form of supply side, though most just look at it as demand side.

As to whether the small utility gets the free ride or the large utility, it depends on the circumstance. My employer AEP, one of the largest in the country, may have been getting a free ride by building fewer very large generators. That lowered their average cost but they got reliability by interconnecting with other utilities that had many, though smaller, generators. Even the transmission example is not clear cut either way, especially when the high voltage line fails and the low voltage line experiences huge electrical line losses.

Socializing the Grid

A friend sent me a message overnight that asked me, since my friend says I have an understanding of utility issues, to identify the misstatements in a 2009 January 15 article “Browner: Redder than Obama Knows” by Steven Milloy. http://www.foxnews.com/story/0,2933,480025,00.html   My response is below.  Now, as I am posting this to my blog, I realize that the article is over two years old.  When I began writing my response, I had focused on the January 15 and thought that I was only 11 days behind the time instead of two years.  Oh, well.  The interest in the article is current even if the article isn’t.

Before I talk about the Fox article, “Browner: Redder than Obama Knows”, let me talk a little about the socializing of the electric system, an issue I have been trying to correct for over twenty years.

Electric systems improve reliability by increasing the number of generators connected to the grid.  More generators with enough capacity and we are more likely to have enough electricity for everyone.  Electric generators have great economies of scale.  Larger units mean less steel and concrete per KW or KWH.  Perhaps more importantly, fewer power plant employees.  Manning an operating room 24×7 for a 2,000 MW plant takes not many more people than for a 300 MW plant.

So, eighty years ago electric systems were in a quandary.  To maintain high reliability, electric systems needed more units.  To keep costs low and improve profit margins relative to a fixed price, electric systems needed larger units.  So the trade off was between more, therefore smaller, units versus larger, therefore fewer, units.  The solution was to interconnect with one’s competitors which increased the number of units connected to the grid and allowed utilities to build larger, less costly, units.  In the summer of 1969 and from 1971 to 1976 I worked for American Electric Power (AEP).  In perhaps ten years times, AEP went from building 280 MW generators, to 800 MW, to 1300 MW, being able to achieve those economies of scale by having more interconnections with its neighbors than almost any other utility in the US.

Those interconnections created a form of socialism.  The utilities did not figure out how to charge each other for the increased reliability provided by the interconnection.  Reliability came to be considered to be a public good, not to be charged for.  Reliability regions created rules for their interconnected utilities, such as having a 20% reserve margin for each utility or having spinning reserves equal to the size of the largest unit.  If we assume only the 20% reserves, then a very small utility could build one large unit to enjoy the economies of scale and rely on the large number of interconnected units for reliability.  If an industrial facility builds and operates a cogeneration plant (whose per KWH fuel costs because of the steam usage is half of the per KWH cost of a conventional plant), then the industrial facility will not want to have a spinning reserve requirement that reduces the generation by on the cheapest unit on the system.

Over twenty years ago I wrote “Tie Riding Freeloaders–The True Impediment to Transmission Access,” Public Utilities Fortnightly, 1989 December 21 arguing for a de-socialization of the electric system, both of the generation component discussed above and of the transmission component.  I say that we need a system to pay for unscheduled flows of electricity on very small time increments.  That way the small utility with the single large unit would pay the current value of electricity whenever the unit went down.  If the unit always failed during the summer peak, then the prices would be very high.  If the utility did sloppy maintenance and the unit was out more than the average for the rest of the grid, then the utility would be making frequent payments.  The reliability regions were not able to devise a reserve rule to penalize the sloppy maintenance practices or the bad timing issues.  I say that pricing the unscheduled flows achieves the appropriate grid discipline, or at least better grid discipline.  India put into place such a pricing mechanism and improved its grid discipline.

The physical interconnection created a form of socialism of the generating system.  Real time pricing of the imbalances would remove some of that socialism.

For the transmission system, socialism comes in the form of loop flow.  Engineers often use the short hand of saying electricity flows through the path of least resistance.  But, when there are several paths of relatively low resistance, the electricity divides among those paths such that the marginal line losses on each path are the same.  Thus, two parallel identical lines will split the load equally between them.  Attach something to one of the lines and the load will split in some slightly different way, but not all going to the one line with the least resistance despite the short hand.

Higher voltage lines have lower resistance than do lower voltage lines.  Higher voltage lines are more expensive per mile of wire but less expensive per KW-mile, with much lower line losses.  Consider this another example of economies of scale.

Consider a small utility that has a low voltage transmission line connecting its customers over a long corridor.  Consider a large utility serving roughly the same corridor that builds a high voltage transmission line parallel to the other line.  If the lines are connected to each other at each end, total line losses are reduced when some of the power from the small utility travels on the wires of the large utility.  If there is a scheduled transaction for the flow, the small utility will pay a wheeling fee to the large utility.  Generally there is no scheduled transaction and the small utility gets a free ride, a form of socialism.  Some describe the claim by the large utility for a wheeling fee to be “vampire wheeling.”  My article says that the network needs to price this unscheduled flow by differentiating the price geographically in addition to the temporal differentiation discussed above.

In regard to the Fox article, the aiding and abetting has taken the form of support for carbon taxes that would impact utilities differently.  A utility with a large nuclear fleet would see its competitors costs go up.  That would competitively advantage the nuclear fleet owner and in restructured markets, such as those operated by ISOs, the price of energy from the nuclear fleet would go up by the carbon tax without the cost of the nuclear fleet going up.

In regard to decoupling, some utilities will weatherize my home, with little or no charge to me.  That will lower the amount of electricity that I consume for HVAC.  The utility will treat the cost it incurred to weatherize my home as a legitimate rate case expense.  This raises the price that everyone, including me, pays.  If the utility has 100 customers, then I end up paying in higher rates less than 1% of the cost that the utility incurred to pay for weatherizing my home.  With a thousand customers, I pay less than 0.1%.  But I will pay for weatherize other peoples’ homes.  Except, that my new, green and economy minded, wife and I already spent a fortune on new double paned windows and other weatherizing features.  So my costs will not get socialized but I would pay the cost incurred by the utility for weatherizing others.

The Fox article presents three ways for decoupling, different ways for the utility commission to treat the weatherization costs as a legitimate rate case expense.  Or the government could use stimulus money for the same purpose, a different form of socialization.

My comments above don’t actually identify and explain misstatements, just explain some of the statements.

Getting the Smart Grid to Make Sense

For the smart grid to make economic sense, we need a way to pay for it by reducing the cost of generation, as well as the cost of wires, not just increase the cost of wires by the investment in the smart grid. There has to be some cost offsets. To accomplish those cost offsets, we need to change the load profile of the customers behind the meter, the cash register of the electric system. To change that load profile means we must give the customers economic incentives, which means changing the prices that are being charged to the customer. Yes, that means higher prices when things are going bad, but also lower prices at other times, including some times when things are going so well that they are going bad.

How can there be too much of a good thing such that “things are going so well that they are going bad?” I wrote of that in “Renewable Electric Power—Too Much of a Good Thing: Looking At ERCOT,” Dialogue, United States Association for Energy Economics, 2009 August. Prices for electric generation in the “wind patch” of West Texas were negative for about 25% of the month of April 2009. Things got so good, with so much wind, that things got bad, with prices that seem so unusual. And it need not just be the “wind patch” of West Texas where there is too much power. If my neighbor puts in a 1 MW wind mill in my residential neighborhood, that will overload the wires and cause too much of a good thing, as I wrote in “Microgrids And Financial Affairs,” Industrial Fuels and Power, January 2008.

The same concept applies to charging electric vehicles, as I wrote in “Dynamic Pricing: Using Smart Meters to Solve Electric Vehicles Related Distribution Overloads,” Metering International, Issue 3, 2010. This article was my response to a pro-EV group which wrote

In a study conducted by EPRI, plugging in just one plug-in hybrid electric vehicle (PHEV) to charge at 220 V overloaded 36 of 53 transformers examined during peak hours and five of 53 transformers during off-peak hours. It is, therefore, important to identify where GEVs are parked and charged so that utilities can make the upgrades necessary to maintain reliable service. (Electrification Roadmap, November 2009, p. 102, emphasis added)

Uniform Electricity Rates–Thailand discussion

In response to a discussion of the quest for uniform rates in Thailand, I asked:

How important are each of the causes of non-uniform tariffs? Generation including contracts? Transmission including line losses to remote areas? Density of customers along distribution lines? Knowing the answers to these questions can lead you to ways to create uniform tariffs.

In the US, the density of customers along distribution lines led the federal government in the 1930s to offer subsidized loans at very low interest rates to utilities that served rural areas. Most of these loans went to cooperatives. I understand that these loans were available to investor owned utilities, though with such severe restrictions that most investor owned utilities did not avail themselves of these government loans.

The rate design can impact the degree of non-uniformity. An area with low average consumption will need higher rates if the cost recovery is primarily in an energy charge, Bahts/KWH. A higher customer charge, Bahts/month for each customer for basic service, tends toward uniformity for such low use areas.

I later responded to further parts of the discussion with:

My question about the sources of non-uniformity of tariffs mentioned generation because some distributors of electricity have access to cheaper forms of generation, such as hydro plants, older fully depreciated plants, and a willingness to participate in load management.

In the US Northwest, the federal government built hydro facilities nominally dedicated to customers of government owned utilities and cooperatives. Customers of investor owned utilities were not allowed access to the output of these facilities. As fuel costs rose, the disparities because greater and Congress enacted an equalization plan where Bonneville provide some cheap energy to the investor owned utilities so that their residential customers could benefit. I don’t remember that exact details, but that provided some uniformity.

In some parts of the US, most of the generation is owned by investor owned utilities who sell electricity to government owned utilities and cooperatives on a cost based tariff. The tariff generally has a demand charge and an energy charge. The demand charge is based on the monthly maximum demand imposed by the buyer on the seller. Some of the buying utilities have implemented load management programs that clip their peak demand by interrupting consumer load for a few hours a month. The peak shaving efforts reduces the average cost of the buying utilities below the cost based rates of the selling utilities, leading to some non-uniformity in rates.