Tag Archives: oil

Petroleum Administration for Defense Districts (PADDs): Past and Present

If you’re an energy-statistics nerd (which you probably are if you’ve found your way to this blog), you’ve no doubt seen various regional data expressed by PADD, or Petroleum Administration for Defense District. Referring to barrels of oil sent from one PADD to another or which PADD uses certain fuel types for home heating  allows for a useful shorthand for regions of the United States and their energy related statistics. Many people who come across the PADD system might already understand PADDs to be a bygone classification system from the country’s fuel rationing days, but most people’s understanding of the PADD system stops here and the history of PADDs are not explored any further.

 

That’s where this article comes in! This piece will serve to explain what the PADDs are, where they originated, how they evolved over the years, and how they are relevant today.



What are PADDs?

Petroleum Administration for Defense Districts, or PADDs, are quite simply the breaking down of the United States into different districts.
PADD 1 is referred to as the East Coast region and, because of its size, is further divided into three subdistricts:
  • PADD 1A, or New England, comprises Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont;
  • PADD 1B, or Central Atlantic, comprises Delaware, the District of Columbia, Maryland, New Jersey, New York, and Pennsylvania; and
  • PADD 1C, or Lower Atlantic, comprises Florida, Georgia, North Carolina, South Carolina, Virginia, and West Virginia.

PADD 2 is referred to as the Midwest region and comprises Illinois, Indiana, Iowa, Kansas, Kentucky, Michigan, Minnesota, Missouri, Nebraska, North Dakota, South Dakota, Ohio, Oklahoma, Tennessee, and Wisconsin.

PADD 3 is referred to as the Gulf Coast region and comprises Alabama, Arkansas, Louisiana, Mississippi, New Mexico, and Texas.

PADD4 is referred to as the Rocky Mountain region and comprises Colorado, Idaho, Montana, Utah, and Wyoming.

PADD5 is referred to as the West Coast region and comprises Alaska, Arizona, California, Hawaii, Nevada, Oregon, and Washington.

New PADDs

There are also two additional PADDs after the original five PADDs that rarely get mentioned, likely because they are much newer and the volume of oil products going in and/or out of them are minimal compared with the rest. Despite a mention of them in the Energy Information Administration‘s (EIA) write up of the PADD system,  PADDs 6 and 7 (meant to cover U.S. territories around the world) do not have data on them included on the prominent, publicly-facing EIA data sets. However, some digging shows that PADD 6 was added in 2015 in order to properly report needed information to the International Energy Agency and comprises the U.S. Virgin Islands and Puerto Rico, while PADD 7 includes GuamAmerican Samoa, and the Northern Mariana Islands Territory. You will commonly find sources citing just five total PADDs, but don’t let that throw you off. Simply impress those you meet at energy cocktail parties by memorizing what territories are in PADDs 6 and 7.

Origin of PADDs

The federal government first established the regions that would become the five PADDs during World War II. Specifically, the Petroleum Administration for War was established as an independent agency by Executive Order 9276 in 1942 in order to organize and ration the various oil and petroleum products to ensure the military had all the fuel it needed. Part of that organization process was the establishment of these five districts as a tool for that goal. The Petroleum Administration for War ended in 1946 after the war efforts were over, but these five original districts were quickly reestablished by the successor Petroleum Administration for Defense that was created by Congress in 1950 in response to the Korean War. This Administration provided these districts with the name Petroleum Administration for Defense Districts.


Source

Changes over time

As stated, the original function of the PADDs was to ensure proper distribution of oil supplies during World War II. In fact, the Department of Defense made use of the PADD system to redirect oil resources to specific PADDs  in response to Nazi attacks on U.S. tankers. These oil distribution efforts were the largest and most intricate such efforts yet, leading to the realization that interstate pipelines would soon become necessary to connect oil refineries with distant U.S. markets. But once World War II ended, the government determined there was no more need for the Petroleum Administration for War, and gone with the Administration were the districts.

After the Petroleum Administration for Defense revived the five districts, they were then under the management of the Department of Interior’s Oil and Gas Division, with the continued function to ensure the oil needs of the military, government, industry, and civilians of the United States were met. As with the Petroleum Administration for War, the Petroleum Administration for Defense was short-lived and was abolished just four years later by the Secretary of the Interior’s Order 2755 in April of 1954. Even though the government agency was eliminated, the names and organization of the various PADDs continued to be used ever since.

One significant change over the history of PADDs that is important to note is that there are no present day ‘official’ government keepers. While the PADDs served an official function and thus had official definitions set out by government agencies during World War II and the Korean War, that is no longer the case today– but that does not mean they are no longer significant. Within the Department of Energy (DOE), EIA uses the PADDs extensively in its aggregation and dissemination of data (discussed in more detail next). Further, government agencies have defined PADDs for use within specific regulations. For example, the Environmental Protection Agency (EPA) codified PADDs in the Code of Federal Regulations (CFR) when regulating motor vehicle diesel fuel sulfur use (though it explicitly dictates that the definition is only applicable as codified for that specific regulation) and specified total benchmarks and reductions that were to be met PADD-wide, as well as in reporting requirements regarding fuel additives so that they get published by PADD.

Use of PADDs today

With the government being out of the business rationing oil and petroleum since the end of the Korean War, the PADDs have found new purpose. The same PADDs have survived to allow analysis of data and patterns of crude oil and petroleum product movements within (and outside) the United States. Using these PADDs, government and industry players are able to ensure they are using the same regional collection of states and shorthand language to analyze and spot trends within regions instead of being confined to looking at the nation as a whole or analyzing on a more state-by-state basis.

Further, the PADDs are separated in a way that makes analysis straightforward. For example, following the crude supply in PADDs 2 and 3 are the most important to crude prices because they contain the largest number of refineries. Heating oil demand is mostly concentrated in PADD 1, making that the region to look at when investigating heating oil prices. Additionally, using the language of PADDs enable quick insights into data such as EIA noting the impact of Hurricane Harvey on flow of propane from PADD 2 to PADD 3 or detailing how PADD 1C needed to supplement its gasoline inventories with foreign imports when there was an accident that shutdown the pipeline that typically supplies the area with gasoline from PADD 2.

Examples of trends, statistics, and PADD characteristics

There are plenty of other examples of the usefulness of dealing with oil-related data within PADDs. A common example is to delineate from where different PADDs receive their oil. For example, with the knowledge that almost half of U.S. refining capacity is on the Gulf Coast (i.e., PADD 3) while less than 10% of refining capacity is on the East Coast (PADD 1) (though PADD 1 contains about one third of the U.S. population), an obvious conclusion is that there must be a lot of intra-PADD oil shipments everyday. In fact, about half of the oil consumed everyday by PADD 1 is supplied from PADD 3 over pipeline, rail, truck, and barge.

Going further, much of the commonly distributed data from EIA (click here to learn about the vast data available from EIA and how to navigate it all) utilizes PADDs. For example, EIA allows you to look at the following:

and much more.

So hopefully the next time you read a table from EIA that deals with oil movement specific to PADD 3 or read a news article citing the disruption of a pipeline that serves PADD 1, this article will come to mind and you’ll be better served to speak to it– and remember to try and win some bets with your knowledge of the seldom-mentioned PADDs 6 and 7!
Sources and additional reading:
About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

Best from “Today in Energy” in 2017

Among the wide array of regular articles the Energy Information Administration (EIA) releases, as detailed in this post on navigating EIA’s data sets , one of the most varied and interesting is the Today in Energy (TIE) series of articles released every weekday. According to EIA, TIE articles “provide topical, timely, short articles with energy news and information you can understand and use.”   

What makes TIE particularly compelling to read each day is that the topics it covers range across the spectrum of energy-related topics. Where most of the other reports released by the EIA are restricted to a specific fuel type or survey of consumers, TIE articles bring all of these topics from across EIA into relevant, digestible, and fascinating briefs to give a broad spectrum of information to its readers.



Further, TIE articles feature both stories that are relevant and important to current events (e.g., Hurricane Irma may cause problems for East Coast energy infrastructure) and stories that provide useful background information that can be referenced for years to come (e.g., Crude oil distillation and the definition of refinery). Not only that, but keeping up with TIE articles is a great way to keep up with other EIA publications as well, such as when articles such as the Annual Energy Outlook, International Energy Outlook, or Short-Term Energy Outlook are posted, TIE often includes an overview of some of the relevant conclusions of those articles and a link to read the full version.

To prove how valuable TIE articles can be for all these reasons, I’ve picked a sampling of 13 of my favorite TIE articles thus far in 2017 that are particularly interesting and demonstrate the cross-cutting topics offered by TIE. The ones I’ve chosen are based on the topics I find the most engaging, as well as the graphics that are the most clever and elegant.

1. EIA’s AEO2017 projects the United States to be a net energy exporter in most cases

January 5, 2017

Released the same morning as the Annual Energy Outlook 2017 (AEO2017), this article demonstrates the tendency of TIE to alert the readers of the latest EIA publications, while also providing a good overview to new readers as to what AEO2017 is and what the main takeaways from the report were.

2. Canada is the United States’ largest partner for energy trade

March 1, 2017

Utilizing the latest data from the U.S. census bureau, this article details the energy imports/exports between the United States and Canada broken out by U.S. region and fuel type and demonstrates TIE articles on the topic of trade. Most interesting is the graph showing the difference in electricity trade over the years from each of four U.S. regions.

Source: Energy Information Administration

3. U.S. energy-related CO2 emissions fell 1.7% in 2016

April 10, 2017

This TIE article from April breaks down carbon dioxide (CO2) emissions data, from the Monthly Energy Review, from 2005 to 2016 by both emitting fuel and industry, while also introducing carbon intensity as a metric and shows the progress made in reducing energy-related carbon intensity over the previous decade. As climate change heats up as an issue in domestic politics, industry, and foreign affairs, this type of window into U.S. CO2 emission data can prove invaluable.

4. Most U.S. nuclear power plants were built between 1970 and 1990

April 27, 2017

I chose this article because it provides a fascinating chart that shows the initial operating year of utility-scale generation capacity across the United States, broken out by fuel type, to demonstrate the relative age of each source of electricity generation and, in particular, the relative old age of the U.S. nuclear generating capacity, while also showing the explosion of non-hydroelectric renewable generation since the turn of the century.

Source: Energy Information Administration

5. American households use a variety of lightbulbs as CFL and LED consumption increases

May 8, 2017

An example of a TIE article getting into the use of energy inside of U.S. homes, this piece takes information from the 2015 Residential Energy Consumption Survey (RECS) to show how residential lighting choices have been trending in the face of increased regulation and availability of energy-efficient lighting technologies, highlighting the differences depending on renter vs. owner occupied, household income, and whether or not an energy audit has been performed.

6. More than half of small-scale photovoltaic generation comes from residential rooftops

June 1, 2017

Utilizing data from the Electric Power Monthly, this article breaks out the use of small-scale solar power systems based on the geographic location and type of building, highlighting the rapid rise these systems have experienced in the residential sector, as a great example of renewable energy in the residential sector.

7. Dishwashers are among the least-used appliances in American homes

June 19, 2017

Again taking data from RECS, this TIE article provides insights on the frequency that certain appliances are in American homes, how often they go unused in those homes, pervasiveness of ENERGY STAR compliant appliances, and other data regarding residential energy use of appliances. This article also includes a plug for the 2017 EIA Energy Conference that was to be held a week after its publication, again showing how good of a job reading TIE articles daily can do of making sure you know the latest happenings at EIA.

8. Earthquake trends in Oklahoma and other states likely related to wastewater injection

June 22, 2017

A reason I find this TIE article particularly interesting is that it goes beyond just the energy data collected by EIA and synchs with outside data from the Earthquake Catalog to show additional effects of energy production in the environment. This kind of interplay of data sources demonstrates how powerful EIA data collection can be when analyzed in proper context.

9. Monthly renewable electricity generation surpasses nuclear for the first time since 1984

July 6, 2017

I highlight this TIE article for two reasons. First, the graphic below showing the monthly generation of nuclear compared with the cumulative generation of renewable energies—and the highlighting of 2016-17 particular—is really illuminating. This graph is a great demonstration of the power of data visualizations to convey the data and the message of that data. Second, the reason behind that graphic—that monthly renewable generation surpassed nuclear generation for the first time in over three decades—is a remarkable achievement of the renewable energy sector, showing the trending direction of the U.S. fuel mix going forward.

Source: Energy Information Administration

10. California wholesale electricity prices are higher at the beginning and end of the day

July 24, 2017

This TIE article was identified because of how interesting the topic of wholesale electricity prices varying throughout the day can be. As net metering and residential production of electricity increases across the United States, this will be a topic those in the energy fields will want to keep a keen eye on.

11. Among states, Texas consumes the most energy, Vermont the least

August 2, 2017

Grabbing data from the State Energy Data System, this TIE article presents a graphic displaying the most and least overall energy use as well as the most and least energy use per capita among the 50 states and the District of Columbia. Using color to demonstrate the relative consumption and consumption per capita creates a pair of really elegant visuals.

Source: Energy Information Administration

 

12. Solar eclipse on August 21 will affect photovoltaic generators across the country

August 7, 2017

As everyone was scrambling to find their last minute eclipse glasses, this TIE article detailed where, and how much, the total solar eclipse of August 2017 was to diminish solar photovoltaic capacity and an assessment of how local utilities will be able to handle their peak loads during this time (a nice follow up TIE article on this also looked at how California dealt with these issues on the day of the eclipse, increasing electricity imports and natural gas generation).

Source: Energy Information Administration

13. U.S. average retail gasoline prices increase in wake of Hurricane Harvey

September 6, 2017

Another example of TIE addressing energy-related current events, this article not only provides the information and analysis of the effect that Hurricane Harvey had on retail gasoline prices, but it also provides the context of why the effect was being felt, how it compared to previous hurricanes, and what could be expected moving forward.

 

 

If you’ve been sufficiently convinced that Today in Energy articles would be an engaging read to start the day, you can sign up for an email subscription by following this link.

 

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

DOE in Focus: Strategic Petroleum Reserve

The Strategic Petroleum Reserve (SPR), owned by the U.S. federal government and operated by the Office of Fossil Energy within the Department of Energy (DOE), is collectively the largest reserve supply of crude oil in the world. These massive reserves of oil are divided between four storage sites along the Gulf of Mexico.
As the name implies, the SPR exists to provide a strategic fail-safe for the United States, ensuring that oil is reliably available in times of emergency, protecting against foreign threats to cut off trade, minimizing potential impacts of price fluctuations, and more. Understanding the SPR, both its history and its present form, are crucial to recognizing the role it may play in the future and understand the implications of its discussion by politicians.



Origin of the SPR

Initial calls for a stockpiling of emergency crude oil began as early as the 1940s, when Secretary of the Interior Harold Ickes advocated for such reserves. The idea continued to be brought up and kicked around through the decades– by the Minerals Policy Commission in 1952, by President Dwight Eisenhower in 1956, and by the Cabinet Task Force on Oil Import Control in 1970– but it wasn’t until the Arab oil embargo of 1973-74 that the concept of a strategic stockpiling of oil really gained traction.

For a detailed history on the embargo itself, I would recommend reading The Prize: The Epic Quest for Oil, Money, and Power by Daniel Yergin (who also wrote The Quest: Energy, Security, and the Remaking of the Modern World). But in short, the embargo was due to the United States’ support for Israel in the 1987 Arab-Israeli War. In response, the Organization of Arab Petroleum Exporting Countries (OAPEC) (not to be confused with OPEC– the Organization of Petroleum Exporting Countries) imposed an oil embargo on the United States, while also decreasing their overall production. U.S. production on its own was not enough to meet the country’s needs, and even in the rare instances when oil originating from the Arab nations made its way to the United States, it came at a price premium three times higher than before the embargo.

While an existing stockpile of oil would not have prevented the United States from paying the market price for oil, the availability of such reserves would be enough to help mitigate the magnitude of the market price jump. Not only that, but having reserves of oil available would buy the government time to continue diplomatic efforts to resolve the dispute before the oil shortage caused more devastating impacts on the national economy. Lastly, having a national reserve of oil would reduce the allure of any oil-exporting nations from using the control of their oil exports as a political tool in the first place, as it would not hold the immediate and impactful sway.
With these goals in mind and to prevent the repetition of the economic impacts felt in the U.S. by the oil embargo, President Gerald Ford signed into law the Energy Policy and Conservation Act (EPCA) in 1975. Among the law’s effects was to declare that the United States would build an oil reserve of up to one billion barrels, owned and operated by the federal government. On July 21, 1977, the first shipment of 412,000 barrels of oil from Saudi Arabia arrived and the SPR was officially open.

Operation of the SPR

Storage

The SPR comprises underground storage facilities at four different locations on the U.S. Gulf of Mexico, with each facility in a hollowed out salt dome. The locations in Texas and Louisiana were chosen because of the existence of the salt domes that have proven to be inexpensive and secure storage options and because the Gulf Coast is the most significant U.S. hub for oil refineries, pipelines, and shipments ports. Additionally, the SPR controls the Northeast Heating Oil Reserve (NEHHOR), which stores up to 2 million barrels of heating oil to ensure the northeast is insulated from emergency interruptions in heating oil during the winter months.
The SPR reserves have a storage capacity of over 713 million barrels, with the active amount of oil stored being enough to cover over 100 days of imports since early 2013.

Drawdowns

As the DOE is an executive agency, the decisions regarding when emergency withdrawals from the SPR are needed are made by the President, as specified in EPCA. According to this authorization, the President is only permitted to direct sales from the SPR if he or she “has found drawdown and sale are required by a severe energy supply interruption or by obligations of the United States under the international energy program” or if an emergency has significantly reduced the worldwide oil supply available and increased the market price of oil in such a way that it would cause “major adverse impact on the national economy.”
In addition to this authorization for full drawdowns, Congress enacted additional authority in 1990 to allow the President to direct a limited drawdowns to resolve internal U.S. disruptions without the need to declare a “severe energy supply interruption” or comply with international energy programs. These limited drawdowns are limited to a maximum of 30 million barrels.  Both full drawdowns and limited drawdowns are limited to the President’s authority.

Other SPR Movements

Outside of these authorities of the President over the SPR, the Energy Secretary also has the authority to direct a test sale of oil from the SPR of up to 5 million barrels. The purpose of these test sales is simply to evaluate the drawdown system of physically removing and transporting the oil from storage, as well as the sales procedure. By law, DOE is required to buy back oil from these test sales within a year.
SPR oil can also be sold through a process known as exchanges, where a company will borrow oil from the SPR to address emergency supply disruptions. The terms of the exchange will include the date by when the company is required to resupply the SPR with the amount of oil it borrowed plus an additional amount of oil as “interest.”
Lastly, Congress can enact laws to authorize additional sales of oil from the SPR. These non-emergency sales are typically to respond to smaller supply disruptions and/or to raise funds for specific reasons, such as the Bipartisan Budget Act authorization to sell a portion of SPR’s oil to pay for modernization of the SPR system and a general fund of the Department of Treasury.

Sales process

Regardless of the authority or reason for it, the oil sold from the SPR is done by competitive sale. The DOE issues a Notice of Sale in the Federal Register, detailing the volume, characteristics, and location of the oil for sale, as well as the procedural information for bidding on that oil. After the official authorization for a sale, it typically takes about two weeks to begin the movement of the oil– which can be moved at up to 4.4 million barrels per day.

Emergency drawdowns in SPR History

Since the embargo of the 1970s, there have been a handful of significant spikes in oil prices and interruptions to the U.S. and world supply caused by international conflict. However, having established U.S. reserves as large as they are has provided a domestic and foreign policy tool during that time.
There have only been three emergency drawdowns in SPR’s history. The first came in 1991, when President George H.W. Bush released 17.3 million barrels of SPR oil for sale to restore stability in world oil markets in response to the Persian Gulf War. In 2005, President George W. Bush called for the second emergency drawdown of SPR supplies, releasing 20.8 million barrels in response to the damage that Hurricane Katrina did to oil production and transportation infrastructure in the Gulf Coast. Most recently President Barack Obama authorized the largest sale by a President yet, releasing 30 million barrels in response to Middle East turbulence and subsequent disruption to the worldwide and U.S. oil supply.

Debate surrounding the SPR

Despite the agreement about the immense negative economic impacts from the oil embargo that prompted the formation of the SPR in the first place, the decisions surrounding the SPR are not without their faire share of critics and controversies.
One notable cause for debate surrounds the meaning of the language in the original authorization, specifically what exactly constitutes a “sever energy supply disruption.” This phrase was initially intended to authorize the SPR to release stocks of oil to resolve discernible, physical shortages of crude oil. However there have been debates about whether to expand that definition– such as the 2011 American Clean Energy and Security Act (which ultimately did not become law) to allow for the SPR to build reserves of additional refined oil products (outside of the already reserved crude oil and heating oil) and use them to mitigate drastic changes in the prices of those products independently of crude oil prices.
Other critics have pointed out that the private stock of inventory in the United States, excluding the SPR, far exceeds the SPR holdings. Some of these people then argue that it would be better to use these private stocks than any government stocks, as the free market would respond in the optimal way to prompt the release of these private stocks. The SPR, on the other hand, is rarely used and is more often positioned as a political tool and thus the role of keeping oil reserved is not one for the federal government, according to these credits
Another critique of the SPR, according to some, is that the government has demonstrated itself as incapable of using the stocks as they should. These critics point to times where oil prices climbed above $100 per barrel, causing significant economic disruption, without the government responding appropriately by releasing SPR oil to mitigate the price jumps. Instead, according to the argument, the markets (and specifically the oil futures market, which was created well after the inception of the SPR) do a better job.
Even as recently as September 2017, in the aftermath of the devastation in the Gulf Coast by Hurricanes Harvey and Irma, President Donald Trump and his Energy Secretary Rick Perry disagreed on the importance of keeping the SPR. While President Trump’s 2018 budget proposal called for selling off half of the oil in the SPR to pay off part of the federal deficit, Secretary Perry said the hurricanes were an example and reminder of why the United States needs the SPR. Worth noting is that the Trump administration did make the decision to send 500,000 barrels from the SPR to a Louisiana refinery in order to shield the economy from higher gas prices.

Future of the SPR

In August 2016, DOE reported to Congress on the state and the long-term strategy of the SPR. The main conclusions of this report included the following:
  • To ensure the stability of the SPR going forward, the infrastructure of the system needs further investment and upkeep;
  • Adding marine terminals is critical to the future ability of the SPR to add barrels to the market in an emergency;
  • The SPR continues to benefit the economy moving forward, and further reductions in the SPR beyond those already authorized would hinder those abilities;
  • If the SPR were to expand in inventory, new storage capacity would need to be developed;
  • Expansion beyond the current four-site configuration of the SPR would violate operational requirements; and
  • Certain improvements to the management and operations of the SPR could be made with limited amendments to EPCA.
However, the debate surrounding the SPR, the U.S. oil markets, and the worldwide energy landscapes are in a constant state of flux, so knowing what will come next for the SPR requires constant attention.

Keeping up with the SPR

If you’re interested in seeing the level of the reserves or watching the movement of oil into and out of the SPR, that information is publicly available to you. The Energy Information Administration’s website will let you look at the historical monthly/annual numbers for SPR stock. Additionally, the SPR website gives updates on the current inventory, broken out by sweet vs. sour crude.

The sale of oil from the SPR is uncommon enough that it will always be a newsworthy event. To be sure you keep up to date on any sales, you can sign up for email updates from the Office of Fossil Energy.  Subscribe to their email list here, making sure to select that you want information on “Petroleum Reserves.”

Sources and additional reading

History of SPR Releases– Office of Fossil Energy

History of the Strategic Petroleum Reserve

New legislation affects U.S. Strategic Petroleum Reserve– Today in Energy

Long-Term Strategic Review of the U.S. Strategic Petroleum Reserve– Report to Congress

Northeast Home Heating Oil Reserve (NEHHOR)

Statutory Authority for an SPR Drawdown

Strategic Petroleum Reserve- Office of Fossil Energy

Strategic Petroleum Reserve sales expected to start this month– Today in Energy

The Strategic Petroleum Reserve: History, Perspective, and Issues– Congressional Research Service

 

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

Correlating Energy Data Sets: The Right Way and the Wrong Way

Determining the correlation between multiple sets of data—a measure of whether data sets fluctuate with one another—is one of the most useful tools of statistical analysis. Correlating data sets can be the endgame itself, or it can be what cracks open the door on a full statistical investigation to determine the how and why of the correlation. No matter the reason, knowing what data correlation is, how to correlate data sets, what a confirmed correlation might mean are all necessary ideas to have in your tool belt.

 What is data correlation?

Generally speaking, correlation examines and quantifies the relationship between two variables, or sets of data. In statistics, data correlation is typically measured by the Pearson correlation coefficient (PCC), which ranges from -1 to +1. Whether the PCC is positive or negative indicates whether the relationship is a positive correlation (i.e., as one variable increases, the other variable generally increases as well) or a negative correlation (i.e., as one variable increases, the other variable generally decreases). The absolute value of the PCC indicates the strength of the relationship, where the closer it is to 1 the more strongly related the two variables are, while a PCC of 0 indicates no relationship whatsoever.

Source

 

How do you calculate data correlations?

The PCC of two variables can be easily calculated with a built-in function of Microsoft Excel (if you want to know how to calculate the PCC according to hand—first, kudos to you, scholar; second, see either this resource or this one for more detailed instructions on the calculation itself).



To start, list out your two variables in two columns of an excel sheet. For this example, we’ll pull the West Texas Intermediate (WTI) oil prices and the U.S. regular grade gasoline prices during a four-month period in the Fall of 2016 from the website for the Energy Information Administration (EIA) (for guidance on pulling data from EIA, see this previous blog post).

Link to Gasoline Price Data; Link to WTI Spot Price data

Note that the weekly prices here reflect the average price calculated for the week ending in the date listed. Also the Cushing, OK WTI spot price reflects the price of raw crude oil in Cushing, OK, a major trading hub for crude oil that is used as the price settlement point for WTI oil on the New York Mercantile Exchange (NYMEX).

Now to find the PCC, use the excel function CORREL. This function takes the form of the following:

=CORREL(ARRAY1, ARRAY2)

where ARRAY1 and ARRAY2 are the two data sets you are seeking to correlate.

Using this excel function, we get a PCC of 0.545. Remember that a positive PCC indicates that the two arrays tend to increase with each other,and that the closer the PCC is to 1 then the more closely related they are. This result of 0.545 would seem to indicate a fairly decent correlation between the price of WTI oil and the price of regular gasoline over these several months. Not only does a positive correlation between the prices of these two products make intuitive sense (because the price of crude oil is the largest factor in the retail price of gasoline), but we can confirm with a data visualization as well.

:

Note that the first graph is showing the change in the two prices over time, with the date on the x-axis and the prices on the two y-axes. Visualizing the data this way, we can see that the prices are climbing and falling somewhat step-in-step. The second graph shows the relationship in a different way, with the price of oil on a given week on the x-axis and the price of gas on the same week on the y-axis. Visualizing it this way, and including a trendline for that data, you again see that as one variable rises, generally so too does the other variable. However, clearly it isn’t a direct one-to-one relationship—hence why the calculated PCC is 0.5455 and not closer to 1.

As a second example, let’s now find the correlation between gas prices during this same time period with the quantity of finished motor gasoline supplied to the market—as basic economic principles give us a sense that there should be a relationship between quantity sold and price. Below we again pull the relevant data sets from EIA and use the CORREL function

Link to Gasoline Price Data; Link to Gasoline Supplied Data

Note that the weekly prices here reflect the average price calculated for the week ending in the date listed.

For these two variables, we get a PCC of -0.173. Now that the PCC is negative, this implies a negative correlation—i.e., as the gasoline price increases, the amount of gasoline sold decreases. This conclusion again makes a degree of intuitive economic sense, as when the price of something increases ,the expected consumer response would be to purchase less of it. However, with PCC so far from -1 we don’t necessarily see this as a very strong correlation. We can look at the data visualization for these data sets as well:

Looking at the first graph, we can again see visually what the PCC was indicating in general. As the gasoline price reaches local peaks, the amount of product supplied tends to reach local valleys, and vice versa. The second graph indicates that with a negative trend line, though again it’s overall just a slight, general trend and not very rigid—as indicated by the PCC being closer to 0 than it is to -1.

There’s a data correlation—what now?

So the key to answering what happens next is to know why you were looking for a data correlation in the first place. Let’s say I was examining the correlation between gas prices and oil prices because I wanted to identify the factors that best predicted gas prices going forward. For each of the two variables tested with gas prices over the four month period in 2016, the expected generally correlation was confirmed with the data, though the PCC wasn’t strong enough to definitively declare victory at having found a correlation. What would I do in this scenario?

More data

The first course of action would be to gather more information. I’ve only looked at 16 weeks of data, but it has been enough to give me a correlative hypothesis (increased gas prices correlate with increased WTI oil price and decreased gasoline supplied). You might take this hypothesis and expand your analysis to include more historical data and see if the same correlation holds or if it moves in a different direction. Further, you might reason out that there are more subtle interactions of between the data that should be explored. Perhaps looking at the price of gas and the price of oil during the same week is too simplistic, and rather you should be looking at the price of oil compared with the price of gas the following week, two weeks, or even month to account for the time needed to refine crude oil into gasoline? Or if your goal is to really find the most influential correlating factors, then it would go without saying to test many more variables to figure out the ones with the closest correlation. For gas prices, you might consider also looking at general economic data, import/export data, production and refining production data, drilling data, and much more.

Test further

Once you have exhausted the data you are looking at and determine what correlates well based on that data, it is important to make sure to test it as well to make sure any conclusions you make are based on sound correlation. As with any type of hypothesis, a correlation is essentially meaningless unless it gets tested.

A couple methods for testing the correlation are available. First, as mentioned previously, expand your data set and put the correlation to the test on a wider set of data—either by looking further in the past to see if the correlation persists, or by using the correlation as a predictive model for future data and seeing if the relationship holds when the new data becomes available.

If you have not already done so, creating a visual representation of data, as done for the two sets of variables above, is a great way to gain understanding of your correlation (and has numerous other advantages for taking in data). As you conduct your data detective work, be sure to always check yourself by creating graphs and other visualizations to confirm suspicions and/or catch some new insights. Whenever possible, as well, work with the data yourself instead of referencing the visualizations of others. In the worlds of data and statistics, it is notoriously easy to ‘make’ the data appear to say whatever you want to say to a lesser informed audience (stay tuned for a future post on this topic).

Another important ‘test’ of sorts is one we already implicitly did when selecting our examples in the previous section—reason out why a correlation might exist. For the prices of crude oil and finished motor gasoline, the reason behind a correlation is somewhat self-evident. But if you’re looking at variables that are less obviously linked, this is where you can do research or consult with experts to determine if there exists any logical rationale to explain the correlation. Otherwise you could be grasping at straws, despite the apparent correlation—discussed in more detail next.

Recognize limitations

Being aware of the limitations of correlating data is the best defense against falling victim to the shortcomings of the technique. This idea is best illustrated in another example.

Let’s say I was continuing the above effort to find factors that I could use in the future to predict gas prices. As discussed, the spot price of WTI oil, with a PCC of 0.545, is determined to be great candidate for correlation with a reasonable PCC, data visualizations that illuminate the relationship, and a very logical and rational reason for the two variables to be correlated. So if oil demand at a PCC of 0.545 is counted—then I should be excited when I stumble upon a mystery variable with a PCC of 0.592!

Link to Gasoline Price Data; Source of Mystery Variable (Spoiler Alert!)

Note—Mystery Variable had no available data for the week of November 7, 2016

With a PCC of 0.592, I could feel great that I have another factor to add to my model. Looking at the data visualizations below does nothing to dispel that notion, either.

The issue is, however, not realizing that if you wade through large enough sets of data you are virtually guaranteed to find coincidental correlations. In this example, I was able to find just such a coincidental correlative data set by looking through the only other vast set of data I spend as much (or sometimes, shamefully, more) time with than energy-related data—fantasy football! Yes, the mystery variable that appeared to correlate decently well with U.S. gas prices from September to December of 2016 was actually the standard fantasy points scored by Washington player, Chris Thompson (missing data for the week of November 7 was due to his bye week).

The man that correlates with gas prices

After revealing the actual source of my mystery variable, you would obviously have me pump my brakes on any correlation. There is no possible explanation for why these two variables would be correlated (unless perhaps you would like to make the argument that when the price of gas goes up, Chris Thompson drives less and walks to and from practice—thus improving his cardiovascular endurance and improving his performance that subsequent week; I unfortunately could find no information on his in-season transportation habits).

The fallacy of connecting my mystery variable to gas prices would almost certainly have been exposed were you to test the correlation through expanding the data set and logical reasoning, as previously discussed. Unfortunately, other factors will not always be so obvious to rule out—which is why having as large of data sets as possible is key. Even then, however, you are bound to stumble upon these coincidental correlations (for some thoroughly entertaining and statistically vigorous examples, check out the Spurious Correlations blog) when casting a wide enough net. That fact is just one of the quirky statistical truths with very large sets of data (if interested on this topic specifically, I’d highly recommend reading either or both of these two fabulous books: The Drunkard’s Walk: How Randomness Rules Our Lives & The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day)

Beyond that, even if the correlation might seem sound, keep in one of the firs things taught in introductory statistics, and also one of the first things forgotten, that correlation is not causation (credit to Thomas Sowell). So while our fantasy football to gas prices comparison is a false correlation, even a true correlation does not automatically let you leap to the conclusion that one variable must be causing the other– a topic that this section of the blog will assuredly revisit in a future post. For now, though, I’ll leave it to America’s favorite statistician to summarize:

“Most of you will have heard the maxim “correlation does not imply causation.” Just because two variables have a statistical relationship with each other does not mean that one is responsible for the other. For instance, ice cream sales and forest fires are correlated because both occur more often in the summer heat. But there is no causation; you don’t light a patch of the Montana brush on fire when you buy a pint of Haagan-Dazs.”
― Nate Silver, The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

The Quest: Energy, Security, and the Remaking of the Modern World

To start out this review honestly, I finished reading The Quest: Energy, Security, and the Remaking of the Modern World by Daniel Yergin over a year ago so this is not a particularly ‘fresh’ review from me. However, I found that it was the perfect book with which to begin my book review series because it is considered by many in the energy industry to be the seminal book tracking the historical and geopolitical forces that shaped today’s landscape of energy markets and systems (and I was able to reference the notes I made to myself when reading through it for the first time).

This is book is incredibly rich with information about EVERYTHING related to energy. Obviously at over 800 pages, it’s not a light or quick read– but the depth of information and amount you can learn from it, regardless of it you’re learning about the state of world energy affairs for the first time or you’re a seasoned veteran of the industry, makes taking the time to read it more than worthwhile.



The first section of The Quest starts with a deep dive into the world of oil– the history and politics that have shaped today’s oil landscape, from the fall of the Soviet Union to the formation of the various nations in the Middle East. I really enjoyed learning more about this political and geographic background, as without proper historical context it can be difficult to fully understand the posturing, trade deals, and tensions that are found in the daily headlines regarding oil-rich countries and their conflicts. I also greatly enjoyed the background information on how the current ‘electric age’ came to be, detailing the genius of Thomas Edison and Nikola Tesla, the early rivalry and battles between their nascent companies in setting up an electric system, and how the legacy of those decisions in the early 20th century still affect how we use energy over a hundred years later.

The book continues on to detail the future of oil, as well as a vast amount of background on the technologies that went into discovering, trading, and utilizing non-oil energy sources such as natural gas, coal, nuclear, and renewable energy. Yergin finishes the story by relating the wealth of background information and historical context of the international energy landscape to how it will come shape our world in the future– politically, economically, socially, and technologically– by way of climate change, public policy, the future of transportation, the security of the energy grid, and continuing competition between nations for resources.

Rating:

  • Content—5/5: This book is nothing if not extremely informative. Yergin does a phenomenal job at shining a spotlight at the relation between state of the modern world and the allocation of various sources of energy and how the balances have shifted over time. If you are interested in learning a broad but in depth background on the state of worldwide energy affairs, you would be hard-pressed to find another book with this much information and analysis crammed into it.
  • Readability3/5: Be forewarned, this is not a book to be picked up lightly unless you’re ready to commit to a thorough read. Obviously the intent was not for this to be a poolside, pop science read, but rather a thorough volume that extensively covers the topic. That is, of course, a good thing as Yergin wrote this book to be studied moreso than consumed. However, at over 800 pages it did at times feel like a homework assignment to pick up again and slough through another dense chapter—and because of this it ended up taking me pretty much all of last summer to read.
  • Authority—5/5: Yergin is a renowned energy researcher, market analyst, economist, and many other accolades that there aren’t room to list here. Not only does his name itself carry enough weight to make this book an authority on the topic, but the research and analysis that went into it is plainly evident. You are reading from one of the authorities in modern energy markets.
  • FINAL RATING—4.3/5: Again, this book is by no means a light read– and I had to take a break from it at times so I didn’t get overwhelmed on the topic (which is saying something, given that the future of energy is the social/political topic about which I’m most passionate). But if you can commit the time and really want to contextualize the past, present, and future of energy– do yourself a favor and pick up this book.

 

If you’re interested in following what else I’m reading, even outside of energy-related topics, feel free to follow me on Goodreads. Should this review compel you to pick up The Quest by Daniel Yergin, please consider buying on Amazon through this link.

 

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

Navigating the Vast EIA Data Sets

The Energy Information Administration (EIA) is an independent arm the Department of Energy (DOE) that is tasked with surveying, analyzing, and disseminating all forms of data regarding energy in the United States. Further, EIA is a politically isolated wing of the DOE– meaning it is there to provide independent and factual data and analysis, completely independent from the partisan decision makers in Washington or the political inclinations of those in charge of at the top of DOE. Because that is the case, you can be confident the data put out by EIA is not driven by any agenda or censored in favor of a desired conclusion.

Thus for anyone with even a passing interest in the national production and use of energy, EIA really is a treasure trove of valuable information. However, those who are unfamiliar with navigating the EIA resources can easily get overwhelmed by the vastness of the data at their fingertips. Additionally, even seasoned veterans of the federal energy landscape might find it difficult to find the exact piece of data for which they are digging within the various reports and data sets made publicly available on the EIA website. So regardless of your experience level, what follows is a brief guide to what type of information is available as well as some advice as to how to make the best use of your time surfing around EIA.gov.



Types of data available

One of the really fabulous things about the EIA data sets is that they cover every kind of energy you can imagine. The energy categories you can focus into include, but are not limited to, the following:

Within these energy categories, you can look at the trends of production, consumption, imports/exports, and carbon dioxide emissions going back years (oftentimes even decades) and also modeled as a forecast into the coming years. Most data sets will have tools to automatically manipulate the data to change between units (e.g., total barrels of oil vs. barrels of oil per day), or even manipulate data trends (e.g., go from weekly data to 4-week moving averages to 10-year seasonal averages). Depending on the type of data, these numbers are regularly updated weekly, monthly, and/or yearly. If there’s a topic of particular interest, there’s a good chance there’s a report with the data on it being released at regular intervals– some of the more prominent reports are highlighted below.

Regularly updated reports

EIA releases a regular stream of reports that serve to update the publicly available data at given intervals. Some of the more prominent reports are listed below, and they are typically used to update all of the energy categories previously mentioned:

  • The Monthly Energy Review (MER) is a fairly comprehensive report on energy statistics, both from the past month and historically back a number of decades. Published during the last week of every month, the MER includes data on national energy production, consumption, and trade across petroleum, natural gas, coal, electricity, nuclear, renewables– as well as energy prices, carbon dioxide emissions, and international petroleum.
  • The Short-Term Energy Outlook (STEO) is another monthly EIA report, this one released on the first Tuesday following the first Thursday of the month. The STEO includes data on much the same topics as the MER, with the inclusion of some international energy data, and it also includes monthly and yearly projections for the rest of the current year and all of  the next year based on EIA’s predictive models. The inclusions of these forecasts makes for particularly useful data sets for anyone who might be trying to stay a step ahead of the energy markets. Also of particular interest for statistically-minded people out there is a regular comparison of numbers between the current STEO forecast and the previous month’s forecast. These comparisons show which way the model shows data to be trending, with the more significant ones called out in the report and noted with reasoning behind the changes.
  • The Annual Energy Outlook (AEO), like the STEO, provides modeled projections of energy markets– though the AEO focuses just on U.S. energy markets, models these annual forecasts long-term through the year 2050, and is released every January. The other aspect of the AEO that makes it particularly interesting is that its modeled forecasts, in addition to a reference case forecast, include different assumptions on economic, political, and technological conditions and calculate how those various assumptions might affect the outlook. For example, the 2017 AEO includes projections based on high economic growth vs. low economic growth, high oil price vs. low oil price, high investment in oil and gas resources and technology vs. low investment, and a projection that assumes a complete roll-back of the Clean Power Plan.
  • The International Energy Outlook (IEO) provides forecast energy market data consistent with the AEO, but regarding the international energy market through 2040.
    • With forecasts in both the STEO and the AEO, an understanding of exactly what is meant by the forecasts is imperative. The forecasts and projections do not necessarily reflect what a human prognosticator within EIA thinks could, should, or will happen– rather it demonstrates what the predictive models calculate given the best possible and unbiased inputs available. This difference is a subtle one, but if you ever find yourself questioning “does the person behind this report really think this is going to happen?”, recognize that some nuance exists and the reason you are skeptical might have not yet been able to be statistically included in the model.
  • The State Energy Data System (SEDS) is published once annually and breaks down national energy use, price, spending, and production by sector and by individual states. Within each of these categories, you can also break down the data by energy type (e.g., coal vs. natural gas) and by primary energy use vs. electric power generation. Having this granularity is useful to further dig into if certain energy trends are regional, restricted to certain climates, or are in response to specific state policies.

While they are not necessarily releasing new and specific data on a regular basis, two other EIA articles of note are worth pointing out because of the interesting stories and analyses they tell:

  • Today in Energy (TIE) comes out every weekday and gives a quick and readable article with energy news, analyses, and updates designed to educate the audience on the relevant energy issues. TIE frequently features graphs and charts that elegantly demonstrate the data in an easy to understand but also vastly elucidating way. One of the real advantages to reading TIE each day, though, is they often include tidbits from all the previously mentioned regularly updated reports, as well as other major releases or EIA conferences, enabling you to keep up with the newest information from EIA (click here for a post on the best TIE articles of 2017 to get you started).
  • This Week in Petroleum (TWIP) is an article that comes out every Wednesday that is very similar to the TIE articles, but focuses on the world of petroleum specifically and provides crucial insights on topics such as drilling, oil company investments, retail prices, inventories, transportation of crude and refined petroleum products, and more.

If any of these regular reports are of interest to you, you can sign up to get email alerts anytime these (or a number of other) reports are released by EIA by visiting this page. If you don’t know which reports you’d want but you want to keep an eye on what EIA is putting out, you can also simply subscribe to the “This Week at EIA” list that will once a week send you an email to notify you of ALL the new EIA productions from that week.

Finding specific data

While keeping up with all the regular reports from EIA is immensely useful, what brings many people to the EIA website is the search for a specific piece of data. You might want to see a history of average gasoline prices in a certain region of the country, find the projection of how much solar capacity is expected to be added in the next few years, track how much petroleum product is being refined in the Gulf Coast, or countless other facts and figures. Below you’ll find a few strategies you can employ to track down the information you seek.

Navigating the menus

EIA.gov has a useful menu interface through which you can usually navigate to your desired dataset easily.

Source: Homepage of EIA.gov
  • The “Sources & Uses” drop down will be where you can navigate to data sets about specific fuel sources and energy use;
  • The “Topics” drop down highlights the analysis on data by EIA as well as economic and environmental data; and
  • The “Geography” drop down is where you can navigate data by state or look at international data.
Source: Homepage of EIA.gov

Navigating from these menus is fairly self-explanatory, but let’s walk through the example of finding the recent history of gasoline prices in the Gulf Coast region of the United States. Gasoline is a petroleum product, so we would click on “Petroleum & Other Liquids” under the “Sources & Uses” menu.

Once on the “Petroleum & Other Liquids” page, the information we’re interested in would be under the data menu with the “Prices” link.

Source: Landing page for EIA.gov/petroleum

You’ll then see a listing of various regular releases of petroleum product price reports and data sets. Since we’re interested in Gulf Coast gasoline prices, we’ll click the third link for “Weekly retail gasoline and on-highway diesel prices.”

Source: EIA’s Petroleum and Other Liquids Prices

Clicking on this report will bring up the below interactive table. The default view will be to show U.S. prices averaged weekly. The time frame can be adjusted to monthly or annual prices (we’ll keep it at weekly). The location of the prices can be changed to allow viewing of data by region of the country or by select states and cities (we’ll change it to the Gulf Coast). The interactive table then displays the most recent week’s data as well as the previous five weeks (note: for ‘gas prices’ as is most often reported in the media and related to people filling up the gas tanks in their cars, we’re interested in the row titled ‘Regular’).

Source: EIA’s Weekly Retail Gasoline and Diesel Prices

If you’re interested in going further back in time then shown in the interactive table, the ‘View History’ links can be clicked to bring up an interactive table and graph going as far back as EIA has data (1992, in this case), shown below. Alternatively, if you want to have the raw data to manipulate yourself in Microsoft Excel, then click the ‘Download Series History’ link in the upper left (I’ll download and keep this data, perhaps handy for later in this post).

Source: EIA’s Weekly Gulf Coast Regular All Formulations Retail Gasoline Prices

Note in the above interactive chart there is the built-in abilities to view history by weekly/monthly/annual data, to download the source data, or the adjust the data to be a moving average or seasonal analysis.

If you find a page with the type of information you’ll want to reference regularly or check in on the data as they update, be sure to bookmark the URL for quick access!

STEO Custom Table Builder

Another useful tool is the STEO Custom Table Builder, which can be found here. The Custom Table Builder allows you to find all of the data that is included in the monthly STEO report (e.g., U.S. and international prices, production, and consumption for petroleum products, natural gas, electricity, coal, and renewable energy; CO2 emission data based on source fuel and sector; imports and exports of energy commodities; U.S. climate and economic data broken down by region; and more). This data can be tracked back to 1997 or projected forward two years on a monthly, quarterly, or annual basis. All you need to do is go to the Custom Table Builder, shown below, and select the options you wish to display.

Source: EIA’s Custom Table Builder

As an example, let’s use the STEO Custom Table Builder to determine the projected of how much solar power capacity in the near term. Solar would fall under the ‘U.S. Renewable Energy’ category, so click to expand that category, then expand the ‘Renewable Energy Capacity,’ and you’ll see the STEO has data for data for the capacity of large-scale solar for power generation, large-scale solar for other sectors, and small-scale solar for other sectors.

Source: EIA’s Custom Table Builder

Select all the data relevant to solar data, select the years you want (we’ll look at 2017 thus far through the end of 2018), and what frequency you want the data (we’ll look at monthly). Then hit submit, and the following will be the custom table built for you.

Source: EIA’s Custom Table Builder

Note: The forecast data is indicated in the Custom Table Builder with the numbers shown in italics. The above data was pulled before the September 2017 STEO was published, so the projections begin with the month of August 2017.

For this example, we’ll want to then download all the data to excel so the total solar capacity can be added up and analyzed. Click the ‘Download to Excel’ button at the upper right to get the raw data, and with a few minutes in Microsoft Excel you can get the below chart:

Source of Data: EIA.gov, pulled on September 10, 2017

This graph, made strictly from STEO Custom Table Builder data, shows the following:

  • As of July 2017, large-scale solar generation capacity was only 0.3 GW outside of the power sector and 23.7 GW, while small-scale solar generation capacity was 14.8 GW.
  • Together, solar power capacity in the United States added up to 39.1 GW as of July 2017.
  • By the end of 2018, total solar power capacity is projected to rise to 53.7 GW (an increase of 14.5 GW, or 37%), according to the EIA’s August 2017 STEO.

Search function

Using a search bar on some websites can be surprisingly frustrating, but luckily the EIA search function is very accurate and useful. So, I have found that, when in doubt, simply doing a search on EIA.gov is the best option.

Perhaps I want to track the amount of petroleum products in production on the Gulf Coast. This information is not in the STEO report, so the Custom Table Builder won’t be of use. And maybe I don’t immediately see how to navigate to this specific information on the menus. I would type into the search bar the data I’m seeking as specific as possible—‘weekly gulf coast refiner gasoline production’:

Source: Homepage of EIA.gov

Doing the above search yields the below results, of which the first one looks like just what we need.

Source: EIA.gov

Click on that first link, and ta-da! We’re taken to the weekly gasoline refinery report for the Gulf Coast (referred to as PADD 3). Again, you see the options here to look at the history back to 1994 both on a weekly and a 4-week average basis, use the chart tools to analyze moving averages or seasonal analyses, or download the data to utilize in your own way.

Source: Weekly Gulf Coast Refiner and Blender Net Production of Conventional Motor Gasoline

Contact experts

As a last resort, the EIA website offers resources to contact should you have questions or issues navigating the data. The people behind the EIA data are civil servants who are intelligent and very dedicated to their job and making sure you get the accurate and relevant information you need. So in a pinch, head to the Contact Us page and find the topic on which you need help from a subject matter expert.

If you want an alternative to going straight to the people at EIA, however, feel free to contact me as well and I’d be happy to try and help you track down information on EIA.gov as well. Use any of the contact methods mentioned in the Contact Page of this site, or leave a comment on this post.

Using the data

I have found that it is not at all an exaggeration to say that the world (of energy data, at least) is at your fingertips with EIA’s publicly available data. To demonstrate, I’ll walk through a quick example of what you can find.

If we take the previously gathered weekly data for Gulf Coast gasoline prices and gasoline production, we can plot them on the same graph:

Source of Data: EIA.gov, pulled on September 10, 2017

By taking advantage of the publicly data on EIA’s website, we can notice some trends on our own. In the above, there is a drastic increase in Gulf Coast gasoline prices, coincident with a large decrease in Gulf Coast refiner production of gasoline that bucks the month-long trend of production generally increasing. This is a curious change and would prompt investigation as to the reason why. Luckily, several of EIA’s Today in Energy articles already points out this trend and offers explanation—all related to the effects of Hurricane Harvey on the Gulf Coast petroleum systems (Article 1, Article 2, Article 3). Just goes to show that one of the best way to stay abreast of trends and information in the energy world is to follow EIA’s various reports and analyses.

 

Updated on September 28, 2017

 

 

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

President Obama’s Energy and Environmental Legacy

In the Fall 2016 issue of The Current, the quarterly online magazine from the Women’s Council on Energy and the Environment (WCEE), I wrote a retrospective on now-former President Obama’s energy and environmental legacy as compared with his campaign promises. The main conclusion of that article was that Obama was leaving office with mixed results when it came to delivering on his stated goals in the energy and environmental spheres, and that the long-term legacy of those achievements would rest on the action or inaction of his yet-to-be-determined successor. With about a year having passed since publication of that article, and almost eight months for President Trump to have set the course for his energy and environmental agenda, I thought it would be interested to see how some of the initial conclusions have held up and how the new administration has followed up on those specific issues.



A quick note that this article will be slightly more politically based than I intend to take typically in this outlet. The goal of this blog will be to provide more straightforward information and analysis based in data, rather than take a side on any specific partisan debate. I want to give you the information and tools, and you can interpret it however you choose. However because this deals with an article that was already published, I thought it might be worth checking into the facts again after a year.

The makeup of the national energy supply

Obama campaign promise: Clean coal and nuclear power will find a place to stay

Conclusion in initial article: Mixed results— Clean coal remains elusive; nuclear was showing promise under the Environmental Protection Agency’s (EPA’s) Clean Power Plan (CPP), which ended up getting stalled until courts could review

Update: Progress has been further stalled— Pushing of clean coal to revitalize the coal industry has long been a part of President Trump’s energy plan. However there has not been appreciable increases in the implementation of clean coal—and the construction of a first-of-its-kind clean coal power plant in Mississippi was indefinitely suspended after falling far behind schedule and beyond budget.

When it comes to the CPP, the Trump administration has moved forward on its campaign promise to roll it back. In March, EPA Administrator Scott Pruitt informed states that they are not obligated to meet the deadlines set by the CPP while was still stalled in the judicial system.

The overall result is that the push to increase the portion of the nation’s energy supply made up by clean coal and nuclear power has stalled. The energy-related carbon dioxide intensity of coal has remained steady for years, indicating the proportion of ‘clean coal’ to total coal has not made significant gains. Similarly the below graph shows that the total power generation from nuclear, as well as the percentage of overall American energy generation attributed to nuclear, has remained steady for the last decade.

Based on Short-Term Energy Outlook data from Energy Information Administration (EIA) as of September 6, 2017—annual data for 2017 and 2018 are projections.

Based on Short-Term Energy Outlook data from Energy Information Administration (EIA) as of September 6, 2017—annual data for 2017 and 2018 are projections.

Clean tech investment and job growth

Obama campaign promise: Invest $150 billion over 10 years to deploy clean technologies and create millions of new jobs

Conclusion in initial article: Partially successful— the investment was exceeded by 2014, but the number of jobs created in the space fell well short of millions

Update: Inconclusive—For the entirety of Obama’s second term and since the Trump administration has taken office, the U.S. economy has consistently added jobs every month. Unfortunately, the Bureau of Labor Statistics stopped providing data on “green jobs” in 2013. In absence of this monthly data, the best source to track jobs in the clean tech space is the Department of Energy’s (DOE’s) U.S. Energy and Employment Report, issued annually in January. As such, it is impossible to know if the new jobs added to the economy are in the clean technologies, though some industry and government leaders have expressed concern that the Trump decision to pull out of the Paris climate change agreement will negatively impact the prospects for clean tech growth and employment.

Renewable electricity

Obama campaign promise: Increase percentage of electricity generated from renewable sources to 10% by 2012 and 25% by 2025

Conclusion in initial article: Mostly successful— reached 12% by 2012 but plateaued at about 13% through 2015

Update: Progress being made—While the Trump Administration has not focused on policies to specifically encourage renewable energy policies, market forces continue to encourage the penetration of renewable electricity generation. Annual data showed renewable energy generation reaching 15% in 2016 with EIA forecasting that to increase to 17% in 2017 and 16% in 2018.

Based on Short-Term Energy Outlook data from Energy Information Administration (EIA) as of September 6, 2017—annual data for 2017 and 2018 are projections.

 

Industrial energy efficiency

Obama campaign promise: Promote energy efficiency with industrial manufacturers

Conclusion in initial article: Awaiting results— Obama issued an executive order in 2010 that would achieve $100 billion in energy savings, but the results were to be measured over the following 10 years

Update: Still waiting—Obviously a one year update won’t change the conclusion that these results were still be measured over 10 years, which have not yet passed, so we’ll still await the outcome of this one. While no actions have been taken by President Trump to undue the executive order fulfilling Obama’s campaign promise focusing on national energy efficiency, it is noteworthy that President Trump’s approach to national energy issues has instead been to roll back regulations seen as impeding the development of U.S. energy resources (focusing on oil, natural gas, coal, and nuclear energy).

Government support of oil companies

Obama campaign promise: Eliminate tax breaks to big oil companies

Conclusion in initial article: No progress— Obama’s attempt to eliminate oil tax breaks were rejected by Congress for all of Obama’s proposed budgets

Update: No expected progress– President Trump’s priorities are notably different than Obama’s were, so the status quo of the tax breaks for oil companies are wholly expected to persist, as doing otherwise would not be seen as progress by Trump. On the contrary, there has been speculation of Trump expanding government aid to prop up the coal industry as well. These actions would keep with a worldwide trend according to a recent report by the International Monetary Fund that concluded fossil fuel subsidies, at $5.5 trillion annually, account for 6.5% of the global GDP.

Carbon emissions

Obama campaign promise: Make significant progress to reduce the national carbon dioxide (CO2) emissions

Conclusion in initial article: Jury still out— CPP would reduce CO2 emissions from power plants for the first time, but the Supreme Court placed a hold on the implementation

Update: As noted earlier, one of Obama’s signature energy accomplishments in the CPP is on life support after the Trump administration signaled to states that they would not be held to the emission requirements. However, U.S. CO2 emissions might be another area where the market forces are already in play to affect the outcome regardless of executive action or inaction. The below two graphs from EIA show a forecast continued drop in CO2 emissions per capita and a drastic drop in total CO2 emissions from a peak in 2019 to a minimum in 2033 (before again increasing due to growing population levels). This drop in CO2 emissions in the absence of federal policy comes because of the continuously falling price of less carbon intensive fuels such as natural gas, nuclear, and renewable energy sources compared with coal and petroleum, in addition to individual states and companies pledging to reduce emissions regardless of whether or not the CPP becomes law.

EIA’s Annual Energy Outlook
EIA’s Annual Energy Outlook

Conclusion

Obama was elected after campaigning on addressing climate change and promising federal action to reduce impacts of the energy sector. Upon his imminent departure from office, giving him a grade on fulfilling his campaign promises proved difficult due to some of the long-term nature of potential results as well as the impact his successor could potentially have on furthering or rolling back parts of his agenda. With the benefit of another year to reflect upon, the conclusion of Obama’s legacy as being overall mixed seems even more entrenched due to the contrasting views held by President Trump. While the dominoes of some of his actions (such as federal investment in clean tech and industrial energy efficiency) are still falling, some of his more ambitious attempts (namely the Clean Power Plan and the Paris climate agreement) have been thwarted by the Trump administration.

If you’re interested in watching the energy makeup of the United States, the relative carbon emissions, or the overall total energy used across the nation, stay tuned for a primer I’m planning on the EIA’s vast public datasets to show you how you can find that raw data yourself.

 

 

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.