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Capacity Factor

In a recent article in the Energy Law Journal, the authors state,

By as early as 2016, installed distributed solar PV capacity in the United States could reach thirty gigawatts (GW).  If that forecast is on track, distributed solar generation will have increased from less than one GW in 2010 to the equivalent of nearly one-third of the nuclear generating capacity in the United States in less than a decade.1

Is the comparison to “one-third of the nuclear generating capacity” meaningful?  Could the amount of solar PV (photovoltaic) generation output expected to be available as early as within two years be equivalent to one-third of today’s nuclear generation output?  The short answer to both questions is “no” and the reason is that nuclear and solar generating facilities have substantially different Capacity Factors.

What is Capacity Factor?

Capacity Factor is the ratio of the actual output of an electricity generating unit over a time period to the unit’s maximum possible output over the same time period.  This ratio expresses the extent to which a unit is, or is not, operating at full output.  A high Capacity Factor, say 80% or 90%, indicates that a generating unit is operating close to “full out,” whereas a low Capacity Factor, say 20% or 30%, indicates that a generating unit is operating well below its maximum capability.

More specifically, Capacity Factor is defined as follows:

For example, a 500 megawatt (MW) unit that generates 2,187,500 megawatt-hours (MWh) of energy during the course of a year has a Capacity Factor of 50%, calculated as follows:

Capacity Factor = 2,187,500 MWh / (500 MW x 8,760 hours/year)

Capacity Factor = 50%

Why don’t generating units operate at 100% Capacity Factor?

There are many reasons.  All operating equipment must be backed off periodically for maintenance.  Mechanical failures and accidents lead to unscheduled outages.  The individual economics of each unit lead to them being called upon more or less under grid operators’ economic dispatch models.  Wind and solar units are physically constrained by how frequently the wind blows and the sun shines.

US Nuclear Generating Fleet

The current US nuclear generation fleet consists of 100 operating units with combined capacity of 99,125 MW which, during 2013, produced 789,016,510 MWh of electricity.  The overall Capacity Factor of the nuclear generating fleet is therefore:

Capacity Factor = 789,016,510 MWh / (99,125 MW x 8,760 hours/year)

Capacity Factor = 90.9%

Analysis

The Energy Information Administration (EIA) reports that during 2013, the average Capacity Factor of solar PV in the US was 19.4%.

Over the same time period, 99,125 MW of nuclear capacity, with its 90.9% Capacity Factor, generated 789,016,510 MWh of electricity:

Going back to the opening quote, one-third of the nuclear generating capacity in the United States” is 33,042 MW, which was responsible for 263,005,503 MWh of electricity:

Given Solar PV’s much lower Capacity Factor, 33,042 MW of solar PV capacity would generate only 56,152,330 MWh of electricity, or 206,853,173 MWh (78%) less than the output of the same amount of nuclear capacity:

In order to generate an equivalent amount of electricity as 33,042 MW of nuclear capacity, substantially more solar PV capacity would be required:

In other words, in addition to the 33,042 MW of solar PV capacity projected to be online by as early as 2016, another 121,718 MW of solar PV would be required in order to generate the same amount of electricity as 1/3 the output of the nuclear generation fleet:

Is the amount of solar generation expected to come online in a decade equivalent to one-third of today’s nuclear generation capacity?  No, and the reason is that nuclear and solar generating facilities have substantially different Capacity Factors, 90.9% versus 19.4%, respectively.

This is a challenge solar PV faces.   The nuclear industry increased its capacity factor from 50% during the 1950s to what it is today through operational improvements.  The capacity factors of coal and natural gas units vary based on their individual economics and their dispatch merit.  Solar PV is bounded by the physical limits of when the sun shines.

The purpose of this article is to take a recent quote and use it as an opportunity to explain Capacity Factor.  Solar PV, like other sources of electricity generation (nuclear, wind, coal, natural gas, geothermal, biomass, etc.) comes with a set of tradeoffs.  Each source has its own strengths and weaknesses.  The article is meant simply to look at Capacity Factor.  Other tradeoffs will be the subject of future articles.

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484-8096, or email us at jmcdonnell@avalonenergy.us.

Notes: 

1Elisabeth Graffy and Steven Kihm, Does Disruptive Competition Mean a Death Spiral for Electric Utilities?, Energy Law Journal, Volume 35, No, 1, 2014.

Data from the US Energy Information Administration.

Evelyn Teel contributed to this article.

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Copyright 2014 by Avalon Energy® Services LLC

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Real Electricity Prices (Energy Prices Always Go Up, Part 5)

This article is part of an occasional series that examines the common perception that energy prices always go up.  We have examined both electricity prices (read here and here) and natural gas prices (read here and here).

An article published recently by CNSNews.com states that, according to the Bureau of Labor Statistics (BLS), “The price of electricity hit a record for the month of October” and that “Americans now pay 42 percent more for electricity than they did a decade ago.”  Sounds scary.

Is it?  Let’s see.

Here, in graphical form, are the October US City Average electricity prices, in dollars per kilowatt-hour (kWh), as found on the BLS website.

During the period of time from 2003 to 2013, October electricity prices rose from $0.093/kWh to $0.132/kWh, a 41.9% increase.

It is important to note that the data above are in “nominal” dollars and do not account for the effects of inflation.  Over the time period examined, the purchasing power of a dollar has declined, so the electricity prices presented above are not being compared on a consistent basis.  In order to make the data consistent, we can normalize it by adjusting for inflation by converting the data to “real” 2013 dollars.  Another BLS dataset can help with this.

The BLS tracks changes in the purchasing power of a dollar through its Consumer Price Index (CPI).  The CPI can be used to convert dollar values from past years into inflation-adjusted dollar values for the current year.  For example, the 2003 electricity prices can be converted to 2013 dollars as follows:

Electricity Price 2013 = Electricity Price 2003 x (CPI Base Year / CPI Current Year)

Electricity Price 2013 = $0.093/kWh x (232.9/184.0)

Electricity Price 2013 = $0.118/kWh

The graph below shows the nominal electricity prices presented above along with the same data converted to real 2013 dollars:

The 42% increase on a nominal basis equates to only a 12% increase in real dollars.  Not quite so scary.

Looking further back in time, how have electricity prices behaved in nominal and real terms?

The graph below shows October electricity prices from the same BLS dataset for the period of time 1979 to 2013.

Over this period, October electricity prices have increased from $0.053/kWh to $0.132/kWh, a 149.1% increase.

The graph below shows the same data converted to real 2013 dollars:

In real 2013 dollars, October electricity prices have DECLINED from $0.170/kWh to $0.132/kWh.  This is a 22.4% decline in real dollars.

Do electricity prices always go up?  In real terms, no.

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484-8096, or email us at jmcdonnell@avalonenergy.us.

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Day-Ahead and Real-Time Pricing in NYISO

We recently looked at the Day-Ahead and Real-Time electricity markets in PJM.  The New York Independent System Operator (NYISO) also operates a two settlement process with Day-Ahead (DA) and Real-Time (RT) markets, which are the subjects of this article.

First some background.

The NYISO, like only two other ISOs (CalISO and ERCOT), serves only one state.  New York State has a population of 19.6 million people, 8.3 million of whom  live in New York City.  NYISO recorded its maximum summer peak load of 33,939 megawatts during 2006 and its maximum winter peak load of 25,541 megawatts during 2004/2005.  NYISO is very dependent on natural gas as a fuel source and minimally dependent on coal.  The make-up of generation in NYISO is as follows:

The NY Control Area is broken up into 11 Load Zones, labeled A through K.  Across the state, electric power generally flows from west to east and from north to south.

New York Independent System Operator – Control Area Load Zones

Roughly a third of the load in NYISO is located in Zone J (New York City).  The next highest load areas are Zone K (Long Island) and Zone C (Central, which includes Syracuse and Ithaca).  The remaining eight zones account for less than 50% of the total load in NYISO.  See the tables below:

With so much load concentrated in Zones J (NYC) and K (Long Island), and with most of the electricity generation located outside of these zones, energy supply in these two zones is often constrained,   leading to higher pricing.  We will see this later.

The Day-Ahead market is a forward market in which hourly Locational Based Marginal Prices (LBMP) are calculated for the next operating day based on generation offers, demand bids, and scheduled bilateral transactions.  The Real-Time market is a spot market in which current LBMPs are calculated at five-minute intervals based on actual grid operating conditions.  The Real-Time market is also referred to as a “balancing market.”

The following analysis is based on NYISO hourly pricing data over the two year period ending June 30, 2013—a total of 17,544 hours.

The table below summarizes, by zone, hourly pricing in the NYISO Day-Ahead market.

Zones J (NYC) and K (Long Island) have higher average pricing and significantly higher variance in pricing than other zones, as highlighted by their maximum and minimum values.

The table below summarizes hourly pricing data for the Real-Time market.

Average pricing in the Real-Time market is about the same as in the Day-Ahead market.  However, the variability in prices in the Real-Time market is much greater across the board.  This stands out graphically as shown below.

The following graphs plot all 17,544 hourly Day-Ahead prices for both Zone A (West) and Zone K (Long Island).  The vertical scales are kept constant for comparison purposes.  The red lines on each graph are trend lines.        

And, the two graphs below plot all 17,544 Real-Time prices for both zones.

Another way to look at this volatility is to examine the standard deviation of prices.  The results are presented on the graph below.  Comparing Zone K to Zone A, Day-Ahead prices were 3.4 times more variable in Zone K and Real-Time prices were 2.4 more variable in Zone K.    

Separate from the level of volatility, especially in Zones J and K, average prices in all of the zones have fallen considerably in recent years.  Average prices in Zone J and Zone K are less than half what they were in 2008.     

Conclusions:

Real-Time prices are more volatile than Day-Ahead prices.

Zone J (NYC) and Zone K (Long Island) prices are more volatile than those of the other nine zones in the NY Control Area.

Notes:

– The New York Independent System Operator (NYISO) is a not-for-profit corporation that began operations in 1999.  The NYISO operates New York’s bulk electricity grid, administers the state’s wholesale electricity markets, and provides comprehensive reliability planning for the state’s bulk electricity system.

– Underlying data and the control area map are from the New York Independent System Operator.

– Evelyn Teel contributed to this article.

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484- 8096, or email us at jmcdonnell@avalonenergy.us.

Please feel free to share this article.  If you do, please email or post the web link.  Unauthorized copying, retransmission, or republication is prohibited.

Copyright 2013 by Avalon Energy® Services LLC

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Real Energy Cost Savings

Below are the results from a sampling of reverse auctions conducted for Avalon Energy Services’ customers, including customers of varying size, over the past few months.  The first graph shows the customer’s annual energy costs before competitive bidding (blue line) and after contracts were executed on accepted bids (red line).  Pre-auction annual energy costs ranged from $0.7 million to $9.6 million, while post-auction costs ranged from $0.5 million to $5.6 million.

This translates into savings from about $0.2 million to about $4.0 million per year, as shown on the graph below:

Annual savings on a percentage basis are presented in this third graph and range from 27% to more than 40%.

Of course, past performance is not necessarily an indicator of future results, but in our experience, a well-executed and carefully managed reverse auction will achieve the most advantageous results for a customer.  The key is to use a skilled energy consultant who can effectively analyze your needs, customize a solution, and successfully use competition among suppliers to bring about the optimal energy procurement outcome.

Evelyn Teel contributed to this article.

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484- 8096, or email us at jmcdonnell@avalonenergy.us.

Please feel free to share this blog.  If you do, please email or post the web link.  Unauthorized copying, retransmission, or republication is prohibited.

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Day-Ahead and Real-Time Pricing During a Heat Wave

PJM operates two markets for energy, the Day-Ahead (DA) Market and the Real-Time (RT) Market.

PJM’s Day-Ahead Market is a forward market in which hourly LMPs (locational marginal prices) are calculated for the next operating day based on generation offers, demand bids, and scheduled bilateral transactions.

PJM’s Real-Time Market is a spot market in which current LMPs are calculated at five-minute intervals based on actual grid operating conditions.

How do the two markets relate?  Let’s use July 19, 2013 as an example.

During the day before (July 18), load serving entities (electric distribution companies and retail energy providers) submit to PJM their electricity usage forecasts for their load during July 19.  These forecasts, provided in one hour increments, together represent the aggregate PJM demand forecast for the delivery day, July 19.

Also, during the day before (July 18), electricity generators submit to PJM offers to supply energy during the delivery day, July 19.  These offers, also provided in one hour increments, together represent the total pool of supply PJM has available to match supply to demand.  Offers are zone specific.

Through its “least cost” dispatch model, PJM then sorts through the generators’ offers, accepting, for each one hour period for the delivery day, the least expensive offers first and then incrementally more expensive offers until it has enough supply to meet the forecasted demand.

As a great simplification, offers for the hour ending (HE) 1400 in the ComEd Zone may have looked something like this:

Below is a sample of actual accepted offers by selected zone for the July 19 hour ending 1400:

The graph below shows the Locational Marginal Prices (or the highest accepted offers) for each of the 24 hours of July 19 by selected zone.  Note that the vertical scale spans $0 to $240.

Then, reality happens.  Despite the best efforts on the part of retail energy providers to project usage, actual demand levels vary.  The weather is cooler or warmer than expected, commercial and industrial facility activity levels differ from what was projected, transmission lines become congested, substations fail.

Forecasted and actual (instantaneous) demand for July 19 is shown below:

Demand for electricity within PJM peaked at 156,944 megawatts at hour 1420 (2:20 pm).

During the delivery day, when actual demand is greater or less than what was procured in the Day-Ahead Market, energy is purchased or sold in the Real-Time Market to instantaneously match supply and demand.  Prices in the Real-Time Market during the hour ending 1400 were as presented below.  Note that in some zones the Real-Time price is higher than the zonal Day-Ahead price while at the same time, in other zones, the Real-Time price is below the Day-Ahead price.

Prices in the Real-Time Market over the full 24 hours of the delivery day of July 19 for select zones are presented below.  The vertical scale now spans $0 to $500.

Because prices are set every five minutes, prices in the Real-Time Market are more volatile than in the Day-Ahead Market, where they are set on an hourly basis.

In the Mid-Atlantic, July 19 was the fifth day of a heat wave.

Below is a contour map of Locational Marginal Prices as of 1605 (4:05 PM).

Below are both Day-Ahead and Real-Time prices during July 19, presented on one graph.

During this day, Real-Time prices were often higher than Day-Ahead prices.  This is not always the case.  Below is a graph of Real-Time and Day-Ahead prices during July 17, 2013.

Notes:

– “PJM” refers to the PJM Interconnection, which is a Regional Transmission Organization and operates the electric transmission system serving all or parts of Pennsylvania, New Jersey, Maryland, Delaware, the District of Columbia, Illinois, Indiana, Kentucky, Michigan, North Carolina, Ohio, Tennessee, Virginia, and West Virginia.

– Surface Heat Index map from Plymouth State Weather Center.

– Other data, maps and graphs from PJM.

– Evelyn Teel contributed to this article. 

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484- 8096, or email us at jmcdonnell@avalonenergy.us.

Please feel free to share this story.  If you do, please email or post the web link.  Unauthorized copying, retransmission, or republication is prohibited.

Copyright 2013 by Avalon Energy® Services LLC

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Energy Prices Always Go Up (Part 4)

As discussed several times previously on this blog, there is a common perception that energy prices always go up.  We have examined both natural gas prices (read here and  here) and electricity prices (read here).

In this post, we look again at electricity prices—specifically, how they behaved in PJM last year.

PJM zonal day-ahead load weighted average Locational Marginal Prices (LMPs) averaged $50.92 per megawatt-hour (MWh) during 2010 and $45.19 during 2011, an 11.3% decline.  During 2012, this weighted average price dropped to $34.55 per MWh, a further 33.6% decline.  This is a stunning decrease and was driven primarily by the decline in natural gas prices.  Electricity and natural gas prices are strongly correlated in PJM as natural gas-fired generating units are generally the marginal units called upon in PJM’s least cost dispatch model.

LMPs vary significantly by zone, as shown on the graph below.

The change in average LMPs between 2011 and 2012 varied by zone but, in all cases, was lower during 2012.  The decline ranged from 19.4% in the Commonwealth Edison zone to 35% in the Atlantic City Electric zone.  A sampling of zonal price changes is presented in the table below.

The overall decline can also be seen in the further contraction of prices into the lower end of the frequency distribution shown below.

From January 2007 to December 2012, Day Ahead LMPs in PJM averaged $46.57 per MWh.  This corresponds to the period during which PJM has in place its capacity market model, referred to as its Reliability Pricing model (RPM).  Current LMPs are well below this average, as shown in the graph below.

The LMPs plotted above are in nominal dollars and do not take into account inflation.  The effect of inflation can be illustrated by increasing the right side of the red line relative to the left side.  In other words, in real dollars, the decline in electricity prices in PJM is more dramatic than shown.

Do energy prices always go up?  The answer remains “no” as it relates to electricity and natural gas prices.

The Avalon Advantage – Visit our website at www.avalonenergy.us

Copyright 2012 by Avalon Energy® Services LLC

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Avalon Energy Services Completes New Energy Supply Contracts on behalf of Donohoe Real Estate Services

BETHESDA, Md., May 14, 2013 – Avalon Energy Services, the Mid-Atlantic’s leading energy consulting firm, announced today that they successfully completed an electricity procurement for 19 commercial real estate properties managed by Donohoe Real Estate Services. The properties are located in Maryland and the District of Columbia.  Under the new contracts, the properties will save more than $1.5 million per year on electricity supply costs.

“We are pleased to assist the premier firm of Donohoe Real Estate Services in obtaining such great savings,” said Jim McDonnell, Chief Operating Officer of Avalon Energy.

Tim Gallagher, President of Donohoe Real Estate Services, noted “At Donohoe, we have a more than century long tradition of creating value for our tenants and our property owners.  Working with Avalon Energy has allowed us to further build upon this tradition.”

Avalon Energy Services, LLC (Avalon Energy) provides a range of energy consulting services to commercial, industrial, institutional, and government customers.  Services include consulting related to energy procurement, energy audits, demand side management, and the implementation of distributed generation and combined heat and power (CHP) applications.  Avalon Energy’s website is www.avalonenergy.us.

Founded in 1884, The Donohoe Companies is the oldest full-service real estate organization in the Washington, DC region and also one of the largest — ranked in the top 50 private companies in the metropolitan area.

Donohoe has invested billions of dollars in Washington’s premier office, hotel, retail, industrial, and residential projects.  In addition, Donohoe provides a full range of building management, brokerage, and maintenance services to major institutions, corporations, and associations.

Today, guided by a fourth generation of the founding family, Donohoe remains committed to the basic values of excellence, integrity, and customer satisfaction. The philosophy and tradition that has brought Donohoe over a century of success continues to be the foundation of their business approach — hard work, fair play, and the willingness to take reasonable risks with prudent provision for the future.   For more information, please visit Donohoe’s website at www.donohoe.com.

Contact:

Jim McDonnell                                                Kevin Furnary

Chief Operating Officer                                 Senior Consultant

Avalon Energy Services, LLC                    Avalon Energy Services, LLC

888-484-8096, ext 202                               703-868-5677

jmcdonnell@avalonenergy.us                   kfurnary@avalonenergy.us

The Avalon Advantage – Visit our website at www.avalonenergy.us

Copyright 2012 by Avalon Energy® Services LLC

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What Does a Superstorm Look Like?

In previous blog posts, we have examined how weather and other events affect electricity prices.

What Does a Derecho Look Like?

What Does a Warm Day Look Like?

What Does an Earthquake Look Like?

We continue this series by looking at how Superstorm Sandy impacted electricity prices in the PJM service area.

After marching northward off the shore of the Atlantic coast, almost 1,000 mile wide Hurricane Sandy became Superstorm Sandy.  She made a sharp left turn and headed due west.  The eye of the storm, along with its tidal surge and 90 mile per hour winds, then made landfall in southern New Jersey around 6:30 PM on Monday, October 29, 2012.

The storm’s destructive winds caused extensive damage to property along its path.  This damage led to large and rapid reductions in electric load, first in New Jersey, the Delmarva Peninsula and New York, and soon thereafter, elsewhere in the Northeast.

As the storm approached land, the locational marginal prices (LMP) of electricity in the Mid Atlantic were about $40 to $50 per megawatt-hour.   After landfall, in the areas where the hurricane hit hardest in PJM – New Jersey and the Delmarva Peninsula – LMPs dropped dramatically and turned negative.  The image below is of a contour map of LMP prices in PJM at 9:10 PM on Monday, October 29.

The phenomenon of negative LMPs occurs from time to time, but is infrequent.  Negative LMPs rarely drop so far, across such a wide area, and for such an extended period of time as occurred here.  Negative LMPs even backed up into eastern and northern Pennsylvania.  The areas that were less affected by the storm, such as mainland Maryland and Virginia, maintained more normal LMP levels.

The graph below shows select PJM LMPs over the course of the entire day (midnight to midnight, Monday, October 29), before and after landfall of Superstorm Sandy.

Electricity prices remained fairly steady overall within PJM over the course of the day, with a peak occurring around 10 AM.  After the eye of the storm hit land, LMPs in the PSEG Zone (the largest electric utility in New Jersey) first spiked upwards and then turned negative for more than three hours.  At one point, LMPs in the PSEG Zone approached negative $400 per megawatt-hour (see pink line above).

System wide, load within PJM declined as the storm approached, landed and barreled into New Jersey, Delaware, Pennsylvania and New York.  This progression can be seen by the steepness of the change in instantaneous demand starting around 6 PM on the blue curve below.

Closer to the eye of the storm, in the Atlantic City Electric Zone (AE Zone), load began to fall off starting around 10 AM, continued to drop throughout the afternoon, showed some short lived recovery around 8 PM, and then fell precipitously thereafter.

Further north and west in New Jersey, in the Public Service Electric and Gas Zone (PS Zone), load similarly exhibited a slow fall off after noon and then a rapid decline starting around 6 PM.

In the Philadelphia Electric area, (PE Zone) load peaked at about 10 AM, slowly declined at first, and then also dropped off sharply starting around 6 PM.

The graph below shows the impact of Superstorm Sandy on the movement of power into and out of the PJM grid.  During most of the day, PJM was importing about 2,200 MW and continued to do so until about 10:30 PM when, the need for power greatly reduced, imports from adjacent grids fell dramatically.

The following day, Tuesday, October 30, LMPs were volatile and mostly positive as shown on the graph below.  This volatility was caused by the episodic restoration of generation, transmission lines, and sub-stations and distribution lines.

The overall decline in load PJM-wide and its subsequent slow recovery can be seen on the graph below.

This graph shows the AE Zone slowly recovering.

Load in the PS Zone also recovered slowly but in an even more sporadic manner.

Load recovery in the PE Zone followed a similar pattern.

Conclusion

The high winds, rain and tidal surge associated with Superstorm Sandy caused devastation to a large area of the Northeast.  Negative LMPs are generally short lived, transitory phenomena.  The magnitude of the initial damage caused by Superstorm Sandy can be seen by the highly negative LMPs that occurred over such a wide area, and for such an extended period of time.   This was a result of rapid decline of load and the inability of supply to be ramped down quickly to match the reduced level of load.

Notes:

– “PJM” refers to the PJM Interconnection, which is a Regional Transmission Organization and operates the electric transmission system serving all or parts of Pennsylvania, New Jersey, Maryland, Delaware, the District of Columbia, Illinois, Indiana, Kentucky, Michigan, North Carolina, Ohio, Tennessee, Virginia, and West Virginia.

– Satelite image from www.weather.com.

– Other data and maps from PJM.

– David White and Evelyn McDonnell contributed to this article.

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484- 8096, or email us at jmcdonnell@avalonenergy.us.

Copyright 2012 by Avalon Energy® Services LLC

 

 

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Best Friends? – Natural Gas and Electricity Prices – An Update

By David White

In a post from January 2012, the declining correlation between the price of natural gas and the price of electricity was explored (click here).  At that time, the correlation between the two was declining as a result of the greater recovery in electricity prices relative to those of natural gas.  The graphs from that post are presented below.

The graph on the left shows monthly average electricity and natural gas prices spanning January 1, 2001 through November 2011.  The graph on the right shows the correlation between the two.  This correlation peaked at 97.2% during May 2010, then declined to 45.4% during November 2011.

Since this post, both electricity prices and natural gas prices have generally moved upwards.  While they both have recovered, the difference between them has increased.  In other words,   Electricity prices have increased more than natural gas prices.  Plotted below is the continuation of electricity and natural gas prices through September 2012, displaying this recent rise in prices.

Despite the increased gap between electricity and natural gas prices, the correlation between them has increased significantly since the last posting.  This correlation is plotted below.

On the graph, the blue line represents the data presented in the January 2012 post, and the red line is the newly acquired data.  Since the last posting, the correlation between the prices peaked at 79.9% in April 2012 and, as of September 2012, is 71.9%.  This is a significant increase from the correlation value of 45.4% that was observed in November 2011.  Through last November, the correlation had an 11-year historical average of roughly 71% and is represented by the orange line on the graph.  While the correlation of electricity and natural gas prices has fluctuated significantly over the years and this pattern is sure to continue in the future, at the moment the correlation between electricity and natural gas prices is regressing to the historical mean.

The Avalon Advantage – Visit our website at www.avalonenergy.us, call us at 888-484- 8096, or email us at whitedm02@gmail.com or jmcdonnell@avalonenergy.us.

Copyright 2012 by Avalon Energy® Services LLC

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What Does a Derecho Look Like?

Late Friday, June 29, 2012 a destructive set of thunderstorms swept through the Mid-Atlantic region.  With winds of up to 80 mph, the storms produced extensive damage and left several million utility customers without electricity.  The National Weather Service (NWS) refers to this kind of fast-moving, long-lived, large, and violent thunderstorm complex as a “derecho.”

On the NWS map below, blue marks indicate reports of damaging wind.  Black squares indicate winds over 75 mph.

The graph below shows PJM system wide load during the day of Friday, June 29, 2012, with demand peaking at 147,183 MW at 16:20 (blue line).  Late in the evening, you can see the drop off in demand resulting from the storm, with the most rapid decline starting around 22:00.

The map below shows LMPs at 23:45 on Friday, 6-29-12, shortly after the storms had passed over Washington, DC and Baltimore but had not yet reached their full intensity on the Delmarva Peninsula and in southern New Jersey.  LMP prices in the legend are in dollars per megawatt-hour.


On Saturday, 6-30-12, demand in PJM reached only 120,024 MW at 17:30 (see blue line below), a reduction of more than 27,159 MW, or more than 18% lower than peak demand the day before.

The graph below shows demand within the Pepco Zone during Friday, 6-29-12.  Demand in the Pepco Zone reached a peak of 6,592 MW at 16:30 and then slowly dropped to about 5,500 MW by 22:30.  Then the storm hit.  As the storm made its way over Pepco’s service territory, demand plummeted by 3,000 MW, or 45%, in less than one hour as much of the distribution system was damaged and service rendered inoperable.

The following day, Saturday, 6-30-12, demand in the Pepco Zone continued to decline until 07:00, when it reached a low of approximately 2,300 MW.  Later the same day, demand peaked at only 3,939 MW, a reduction of 2,653 MW or 40% lower than the prior day’s peak.  Note the different vertical scale on the graph below.

The story was similar in the Baltimore area.  Demand in the BGE Zone peaked at 6,852 MW during Friday, 6-29-12.  The storm hit the area around 22:30, after which demand plummeted over the course of about an hour from about 6,000 MW to about 3,400 MW.

The following day, demand in the BGE Zone peaked at only 4,291 MW.

The table below summarizes peak demand before and after the storm.  On Friday, 6-29-12, prior to the storm, peak demand in PJM was 147,183 MW.  The following day peak demand was 120,024 MW, a more than 18% decline.  However, it is important to note that there are factors other than the storm related outages that influenced the decline in peak demand, most notably the day of the week.  6-30-12 (the day after the storm) was a Saturday, and on weekends commercial load is generally lower.  In fact, the “day ahead” peak demand forecast for 6-30-12 (made before the storm hit) was 135,065 MW.  This is a more realistic reference from which to measure how much load in PJM was still offline 18 hours after the storm.  By this reference, load was off by 15,040 MW, or a substantial 11%.  The level of load reduction in the Pepco and BGE zones was much more significant.

The graph below shows locational marginal prices ($/MWh) over the course of the day of Friday, 6-29-12.  Prices peaked at $280/MWh during the late afternoon and remained volatile during much of the evening.  When the storm hit the major East Coast load centers at about 22:30, LMPs briefly sank to $0, recovered, and then diverged significantly as midnight approached.  LMPs in the Pepco Zone went negative as there was more supply than the now greatly diminished load.  Negative LMPs in a congested zone, such as the Pepco Zone, is a highly unusual phenomenon and is an indicator of how rapid and extensive the damage was during the storm.

The graph below shows a close up of this significant divergence:

Before June 29, few of us were familiar with the term “derecho.”  Now we know what one looks like.

Notes:

– “PJM” refers to the PJM Interconnection, which is a Regional Transmission Organization and operates the electric transmission system serving all or parts of Pennsylvania, New Jersey, Maryland, Delaware, the District of Columbia, Illinois, Indiana, Kentucky, Michigan, North Carolina, Ohio, Tennessee, Virginia, and West Virginia.

– Data and maps from PJM.

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