Total Solar Eclipse and Its Impact on Solar Power

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On August 21, 2017 a rare total solar eclipse will sweep across the United States, starting in western Oregon and passing southeast across the country to South Carolina. During this time, the sun will appear either partially or completely blocked by the moon, depending on your location. The “Great American Total Solar Eclipse” will be the first total solar eclipse to span across the United States since 1918. This event also marks the first time where the U.S. electric grid will be significantly impacted by a solar eclipse.

solar

Figure 1. The path of August’s total solar eclipse. Source.

The eclipse is expected to cause a major dip in solar production for a period of hours on this day, especially on the west coast. California, for example, is expecting to lose about 6,000 MW from the grid due to the lack of sunlight, which California ISO (CAISO) is planning to make up for via natural gas and hydro generation. The Washington Post article goes on to discuss how another challenge for CAISO is ensuring the substitute generators are able to ramp up and down quick enough to handle the changes in solar generation. For instance, as the moon begins to block the sun, solar energy collection is expected to decrease at a rate of 70 MW/minute. Similarly, ramp up rates of around 90 MW/minute are expected once the sunlight begins to come back.

This total solar eclipse will mark the first one to be visible on any part of the contiguous United States since 1979, long before solar power held any share of market generation. It will also be the first solar eclipse of any kind in the United States since May 2012, and solar has grown at record rates since then. Luckily, Europe witnessed a similar total solar eclipse in March 2015 to give us a better context of what to expect. Germany, who alone accounts for ~40% of European solar capacity, saw a drop of solar output from 21.7 GW to 6.2 GW during the eclipse. Reuters also reported that to make up the loss of generation, they looked to gas, coal, nuclear and hydroelectric pumped storage energy, and that overall, Europe experienced a reduction of 17 GW of solar power during the eclipse and did an excellent job of successfully weathering the event through proper planning ahead of time.

Back in the U.S., solar power accounted for 9% of California’s generation in 2016 and the state is home to nearly half of the nation’s total solar capacity.  On August 21, California is expected to lose 50 to 75% of its solar production during the five or so hours. We will then see for the first time how the United States electric grid as a whole will adapt to its first significant dip in solar energy caused by a natural phenomenon.

Filed under: Clean Power Plan, Hydro Power, Renewable Power, Solar PowerTagged with: , , ,

How Good is the EIA at Predicting Henry Hub?

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Natural gas power plants are a key component of bulk electrical systems in North America. In the U.S., natural gas power plants made up the largest portion of installed capacity, 42%, as of December 2016 and contributed more to generation than any other source. In Mexico, natural gas power plants supplied 54% of the required electricity in 2015 and are a key component of the capacity additions in development of the national electrical system. Natural gas is also likely to be the primary energy source in the U.S. due to increased regulation on coal units, uncertainty around the future of nuclear generation, and low natural gas prices.

Natural gas prices are a critical driver of electricity prices and a key input variable in electric power models. Due to the large amount of natural gas power plants in North America, and because fuel costs are the largest cost component of a thermal power plant, wholesale electricity prices are tightly coupled with natural gas prices. There is also an important feedback loop, in that natural gas demand, and price, is tightly coupled to the operation of natural gas power plants. Understanding the interplay between gas and power markets, and uncertainties in forecasts, is critical for forecasting either.

The U.S. Energy Information Administration (EIA) provides natural gas price short-term forecasts through the Short-Term Energy Outlook (STEO) and long-term forecasts through the Annual Energy Outlook (AEO). For the purposes of this article, we will focus on the STEO. The STEO is a monthly report with, among other items, a natural gas consumption and price forecast for 13 to 24 months in the future depending on the month published. The model predicts consumption and prices for three sectors (commercial, industrial, and residential) in the nine U.S. census districts. To do this, the model calculates natural gas consumption and supply levels to build an inventory. Prices are derived from a regression equation using the inventory and heating and cooling degree days, and analysts then make adjustments for final prices. Detailed information on each equation and method is provided by EIA Natural Gas Consumption and Prices document.

How good is the EIA at forecasting natural gas prices from a month to a year out?

To evaluate the STEO forecasts of natural gas prices, we downloaded each monthly STEO report from January 2012 to December 2016 to allow for at least a full year of analysis with historical prices. This period was selected because it is representative of the current trend of low natural gas prices (relative to historical). The mean absolute error (MAE) and mean absolute percent error (MAPE) were calculated for each forecasted value. Prices were then evaluated for the first forecast in each year and a subset of forecasts from consecutive months during a price spike. The mean absolute percent error was also evaluated for each report year and across all reports.

For the period analyzed (2012 to 2016, shown in orange below), the wholesale Henry Hub gas price averaged $3.30/mmbtu with a high price of $6.19/mmbtu in early 2014 due to the extreme Northeast weather (i.e., the polar vortex) and a low price of $1.78/mmbtu due to warm weather conditions and large amount of storage late in 2016. This period is representative of relatively low natural gas prices as compared to the previous five-year period with high prices exceeding $10/mmbtu driven by high oil prices and an average of $5.63/mmbtu despite the sharp decline due to the financial crisis in 2008-2009.

hh1

Figure 1. Historical Henry Hub natural gas prices. The yellow period denotes the study period used for this analysis. Source: EIA.

We started by looking at the longest-term forecasts (24 months) that are delivered in January of each year, and saw an inability to capture rapid fluctuations in prices in the study period:

hh2

Figure 2. Historical Henry Hub gas prices with 24 month forecasts from the January STEO of each year starting in 2012 and ending in 2015 using the base case data. Source: EIA STEO.

The January 2012 forecast missed the sharp reduction in prices from the winter to summer that were driven by high storage volumes. Less volatility occurred over the first part of the January 2013 forecast, however this forecast missed the large increase in prices to over $6/mmbtu which were driven by extreme weather conditions. The January 2014 forecast also missed the weather-driven high price for this period and then was high-biased in the later months of the forecast. The January 2015 forecast was high-biased the entire forecast period and missed the lower prices which were driven by a combination of mild weather and high storage volumes.
The STEO forecast is very sensitive to the initial conditions or starting month’s price. For example, plotting each month’s forecast during the increase from $3.74/mmbtu in November 2013 to $6.19/mmbtu in February of 2014 shows the impact of the rapid change in initial condition (last known price) on the first month forecasted value:

hh3

Figure 3. Historical Henry Hub gas prices with forecasted values from the months leading up to the rapid price spike in February 2014.

Presumably the long-term fundamental drivers of the STEO do not change as much as the initial conditions, and thus the longer-term forecast is much less sensitive to initial conditions.
Despite missing the fluctuation events, on average across the years analyzed the STEO is within 8% of the price in the first month of the forecast, 25% of the price out to eight months and 33% of the price out to 13 months:

hh4

Figure 4. Mean absolute percent error calculated for each forecasted month of STEO reports. Data are averaged over a report year, as well as over all of the report years. Maximum and minimum percent error is calculated over all STEO reports.

On average, the trend has increasing error with forecast length, however, this does not occur in the 13-month 2012 or 2013 STEOs. The expected error growth with time does appear in the 2014 and 2015 STEOs, reaching nearly 60% in the 2014 STEO. The maximum percent error in any given forecast grows rapidly from 26% in the first forecasted month to 75% in the fourth forecasted month, and reaches a high of over 100% 12 and 13 months out.
In absolute terms, the error ranges on average from $0.25/mmbtu in the first forecasted month to $0.88/mmbtu 13 months out. Maximum and minimum errors range from less than a penny up to $2.45/mmbtu.

hh5

Figure 5. Mean absolute error calculated for each forecasted month of STEO reports. Data are averaged over a report year, as well as over all of the report years. Maximum and minimum absolute error is calculated over all STEO reports.

Is the STEO forecast good enough? Unfortunately, as with many answers, it depends. More importantly, however, is understanding the limitations and uncertainties in their gas forecasts. If relying on EIA forecasts, you must realize the sensitivity to initial conditions and the typical error growth in the first months to year of the forecast. With this information, sensitivity studies can be formulated to capture possible fluctuations in gas prices. Taken together with other uncertainties such as demand, transmission outages, and plant outages, you can begin to form an ensemble of forecasts.

Filed under: Natural Gas, UncategorizedTagged with: , , ,

EPIS Releases New Version of AURORA

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Version 12.3 introduces significant enhancements

Las Vegas, Nevada – April 25, 2017 — EPIS (www.epis.com), the market leader in power market
simulation, forecasting and analysis, announced the release of version 12.3 of its AURORA
software at the Platts Global Power Markets™ Conference. The latest version boasts a number
of enhancements to storage logic, ancillary services, long-term logic, improved RPS modeling
and nodal capabilities.

AURORA 12.3 further solidifies its position as the most valuable power market forecasting
and analysis software on the market today. It is fast, easy to use, and transparent. Upgrades in
the new version include:

  • Enhanced Storage Logic—improved ability to model the intricacies of renewable and
    storage integration, electric vehicles, and other technologies.
  • Ancillary Services Enhancements—significant enhancements, including sub-hourly
    dispatch and use in nodal studies, and improved MW reporting for simultaneous
    contributions to multiple products
  • Improved RPS Modeling—offers new option to identify resources not eligible to set
    capacity prices– especially useful when modeling RPS policies where renewable
    resources must be built but cannot participate in capacity markets. Also, RPS constraints
    can now be input as a percentage of demand or MWh value, giving more flexibility to
    specifying RPS targets over time.
  • Long-Term (LT) Capacity Expansion Logic Enhancements—now have the option to
    change dispatch-hour sampling dynamically—accelerating studies, but still providing
    detail on final production run.
  • New LT Constraint Types—including capacity and energy max limits, which provide
    more flexibility for build decisions to targets in LT studies.
  • New LT Reporting Option—new build report output table making it helpful to quickly
    see which constraints were binding (min, max by technology/fuel/area).
  • Nodal SCUC—version 12.3 also includes an exciting new option to run a full security
    constrained unit commitment (SCUC). The mixed-integer program that performs the
    commitment decisions, now accounts for nodal constraints, including branch, corridor,
    and contingency constraints. The new SCUC ability is in addition to a new, proprietary
    solving method that significantly speeds nodal analysis.

AURORA v.12.3 is further enhanced by the proven and calibrated databases that either
come with the license or as an add-on, including: U.S.-Canada, Europe or Mexico. The calibrated
datasets simplify meaningful forecasting. All AURORA databases include a base-case 25-year
power price forecast and generator capacity expansion and retirement plan. The sources and
procedures used to update the data are thoroughly documented. Updates to the databases are
provided under the annual AURORA license.

For the past 20 years, AURORA has had a reputation for being best-in-class, with unmatched
support. Version 12.3 further establishes its position as the leader in power market forecasting
and analysis.

Filed under: EventsTagged with: , , , , , , ,

Data: Timing is Everything

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Staying ahead of the curve by staying on top of industry data

Keeping data current, and applicable to your modeling needs, is not a simple task. It is a known theme within the power industry to expect that as soon as you input data, there will be a need for another update. Much of this has to do with today’s markets being much more transparent than in previous years and more data being available than ever before. Deregulation has played a large role in this transformation; with its need for open markets and transparent pricing came the introduction of a slew of new market products.

Fifty years ago when deregulation began, what are now fundamental market drivers (e.g. sub-hourly, capacity auctions, demand response, energy efficiency, etc.) were unheard of at that time.  The rise of various market data available can be attributed in part to deregulation, or simply to the evolution of technology and the markets. Couple this with the increase in computing speed, server technology advancements, and society’s current “instant gratification” attitude, and you have an industry that demands the right data right now. The growth of available data inputs has led to the need for checks and balances and transparency to the underlying fundamentals. There are a lot more moving parts in today’s power industry which culminates to where we are today: professionals with an enormous amount of data to keep up with and incorporate into simulation models.

In an effort to help integrate posted data in a timely fashion, EPIS has summarized some of the major release dates for data across the U.S., that when considered as a whole, can help your annual planning. The data releases below are grouped by subject type and then further color coded by region. Depending on your modeling needs (large region, day-ahead, capacity expansion, nodal, etc.) you will care about different data releases. However, making sure the data is available when you need it is a significant part of the process that applies across all modeling endeavors.

 

data_spreadsheet

Figure 1: Some of the key market data releases and the time frame they are typically available

An Excel version of this information is also available for download from our website.  When you filter by region you can see a clearer picture of data availability and start to form regional timelines for your own updates based on the available data.

In today’s transparent power markets, staying current can be a difficult task. Knowing when the data is available is an important first step to planning your update schedules in order to most effectively forecast power markets.

Filed under: Data ManagementTagged with: , ,

Top 10 Pieces of Advice from AURORAxmp Support Experts

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Recently, Power Market Insights asked EPIS’s support team to share their top tips for making the most of AURORAxmp. EPIS is known for having best-in-class support and the experts on the team had some very useful advice to share.

Using Both AURORAxmp’s Help Feature and the Website’s Knowledge Base

  1. Take advantage of context-sensitive Help. One very useful feature, especially when first learning the model is the context-sensitive Help. You can always learn more about a specific form or column/table in the model by selecting it and pressing F1 on your keyboard. The Help document contains a wealth of information about all aspects of the model and how it works, making it a valuable reference for users from beginners to experts.
  2. Utilize the online Knowledge Base. Although Help is an excellent way to familiarize yourself with the nuts and bolts of AURORAxmp, the online Knowledge Base on the Support website contains a catalog of presentations on topics that can help you learn the model faster. You can find a compilation of presentations that were given at past conferences, like our annual Electric Market Forecasting Conference or our Spring Group Trainings, not only from EPIS employees but other AURORAxmp users as well. Many of the presentations give step-by-step examples on how to set up different inputs in the model. Using the Knowledge Base alongside the Help document is a great way for a user to thoroughly understand specific areas of AURORAxmp.

Working with AURORAxmp Inputs and Outputs

  1. Be judicious with output reporting. Output databases can grow quickly, which can also increase runtimes. Be sure to limit reporting to just the data you need by using the Report column, available in most input tables. By setting the Report Column to TRUE and de-selecting the All Items box in Run Setup > Reporting form for that output table, you can limit output to just the items you are most interested in. Couple this with the Custom Columns feature, where only the columns you need are reported and you’ll have a perfectly tailored output database.
  2. Take advantage of the dbCompare tool. You can compare either Input or Output databases and then save the results to Excel. In both cases, you can keep a permanent record of the differences, without having to review multiple change sets or manually compare outputs.
  3. Avoid errors due to Improper permissions. Check to make sure that your folder permissions are correct, which will save time in the long run. In some IT environments with enhanced user access security, it may be necessary for your IT team to give you additional rights to certain folders on the system. Contact our Support Team to find out which folders need read and write access.
  4. Test changes in small batches. Take a look at the Data Management article in the Help’s Knowledge Base. When planning to make large sets of changes, it is wise to test them in small batches.  Specifically, perform a short AURORAxmp run after each batch to ensure data was entered properly and is flowing through the model as intended. It is simple to set your period/hours to something very short and fast and direct output to a temporary database. This practice alone can save significant time and effort in tracing troublesome input data.

Managing, Saving, Authenticating

  1. Use Tab My Forms. Many people are unaware of the Tab My Forms option which can help organize multiple AURORAxmp windows on their screens. It can be found under Tools > Options > User Preferences. Along the same lines, if you right-click on a tab, you can select Close All But This to help clean-up your screen when you have too many tabs open.
  2. Create an archive of your project. If you think you need to replicate the results in the future, create an archive. They are great for packaging all the file components of your project into a single .zip file and can easily be transferred to colleagues or used to store a project that you may need to revisit in the future. Once an archive is opened, the project contains everything you need to replicate the output—the same database, change sets, and project settings.  Once unarchived, you simply have to hit Run to replicate the output. This can come in handy if you are asked to replicate output or verify input parameters and run settings.
  3. Know your SQL Server authentication options. AURORAxmp supports two methods to authenticate with your SQL Server: Windows Active Directory-based and SQL Server-based. Windows Active Directory is typically used when individual users are writing output that doesn’t need to be accessed or modified by other users in the organization. SQL Server authentication is best used when output files are going to be shared by multiple users. In this case, some organizations prefer to use a common, single, SQL Server username for multiple users to share.

Hardware

  1. Understand which computer hardware is best. Considering new hardware? AURORAxmp runs best on physical hardware with fast RAM, a fast CPU and speedy disks. Low latency RAM and a good memory controller seem to have the greatest impact on runtime, followed closely by a fast CPU. While AURORAxmp will take advantage of threading in a variety of places, for a single case fast, single-threaded CPUs with a high clock speed seem to perform best. The fastest AURORAxmp runtimes have been observed on overlocked physical hardware with low latency RAM.

Of course, the support experts at EPIS can help with any questions or issues you may have. Next time you talk to one of them, be sure to ask them about tips and tricks to maximizing the power of AURORAxmp.

What’s your favorite trick or tip? Share it in the comments section.

Filed under: SupportTagged with: , , , ,

Power Market Insights Finishes Strong in 2016

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2017 promises to be an even better year of delivering valuable market insight and expertise

The EPIS blog, Power Market Insights is nearly one year old and in that time has posted editorial with a great deal of practical information. The articles, authored by EPIS domain experts, were all carefully researched and delivered valuable intelligence to the industry.

For example, an article on large scale battery storage discussed technology issues and advances that affect the rapidly growing wind and solar market. The article quotes analyst predictions that battery storage costs will drop to $230/kWh by 2020, with an eventual drop to $150/kWh. It goes on to state that worldwide battery storage may grow to almost 14GW by 2023.

Power Market Insights delivered a perspective on the new electric market in Mexico, weeks after that country’s most recent industry reforms were launched. The article reported the fundamental shift in the market and outlined how these reforms would “modernize a constrained and aging system, improve reliability, increase development of renewable generation and drive new investment.” The author discussed the role of zonal resource planning analysis and the importance of data availability. Months later, EPIS announced its Mexico Database for use with AURORAxmp.

Data plays a large role in articles on European power market reporting changes and the EIA easing of data accessibility. Both articles rely on the expertise of EPIS’s Market Research team. The EIA data accessibility article discussed how improvements to the management and delivery of their datasets expand the list of tasks for which EIA data may be useful. For many power modelers, who were unaware of these changes, this information gives important insight that can make their jobs easier. Likewise, the discussion on European power market reporting changes informed readers on ways the available data, while improved, may differ among sources and offered an example of the importance of cross-checking sources.

Two articles lifted the hood to give readers a peek into the workings of algorithms and computing speed. The article on the algorithms at the core of power market modeling offered readers a foundational overview of the mathematical optimizations used in forecasting and analyzing power markets. The computing speed article explained Moore’s Law, discussed how maxed out processors are shifting focus to more cores and how software architecture will soon lose its “free ride.” All of this was put into the perspective of computing data like hourly dispatch and commitment decisions. Both articles enable readers to be able to intelligently discuss the computing parameters that affect their daily performance.

Industry issues were delved into with articles on the water-energy nexus, nuclear retirements, the California market hydropower comeback, uncertainty for ERCOT markets and several articles on the CPP. The writers lent their considerable expertise for these articles—for example, the author of the articles on the CPP had read the entire 304-page filing in the Federal Register before distilling it down for readers to quickly digest.

A number of articles discussed issued faced by modelers as they work to forecast and analyze the market. Pieces on integrated modeling of natural gas and power, working with data in power modeling, the fundamentals of energy efficiency and demand response and reserve margins offered real-world discussions designed to help AURORAxmp users and other industry professionals do their jobs better.

The blog’s 2017 editorial calendar is being finalized right now and will continue to create high-quality articles designed to be of interest to energy and power market professionals. Look for feature editorials next year written by leading analysts and experts in the industry at large. Put Power Market Insights into your must-read list.

Filed under: Power Market InsightsTagged with: ,

Contemplating the Water-Energy Nexus

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The concept of the water-energy nexus is a broad, over-arching term for the relationship between water and energy production systems, including both electricity generation and fuel extraction. Water plays an important role in all phases of fuel extraction and electricity generation. In turn, energy is required to extract, convey, and deliver water of appropriate quality for its diverse uses. In 2014, the U.S. Department of Energy (DOE) released their report on the water-energy nexus, citing the need for joint water-energy policies and better understanding of the interconnection and its susceptibility to climate change as a matter of national security.

water_flow

Figure 1: The complex dependence of water and energy systems. Source: US DOE

Power Generation and Water Consumption

As shown in the Sankey Diagram above, thermoelectric power generation is the single largest user of water, which is used mainly for cooling. Agriculture competes directly with the energy sector for water resources, putting the nation’s food security in competition with its energy sufficiency. The impact of changes in climate, shifting precipitation patterns, and greater frequency of extreme weather events has the potential to alter the availability of water resources. These effects, combined with population growth, could intensify existing competition for water resources and impact energy production and distribution. Furthermore, it is important to note that water and energy systems are also dependent on weather systems. Loosely speaking, warmer and drier weather conditions tend to increase demand for electricity while generally reducing the availability of water resource for hydropower and cooling purposes. Acknowledging the interactions between water and energy could help us understand how scarce conditions tend to occur together and cause compounding issues.

Citing the EIA Form 860 (EIA 2013a), the DOE report on water-energy nexus notes that over 90 percent of plants that are planned to retire require a water-intensive cooling process. Looking forward, only 45 percent of planned additions would not need cooling, meaning that the majority of new plants will still require water-intensive cooling. This complex interdependence of water and energy systems will have an impact on which energy technologies remain viable in the future. Obviously, changes in water resource availability would have the biggest influence on hydropower plants. The EIA states that, “In 2015, hydropower accounted for about 6% of total U.S. electricity generation and 46% of electricity generation from all renewables.” Beyond hydropower, the water-energy nexus may also affect the future of emerging technologies. The U.S. DOE report notes that while cost is the biggest hurdle today for Carbon Capture and Sequestration (CCS) technology, water usage may prove to be an equally large hurdle to overcome. Water consumption, measured in gallons per kWh of electricity generated, is estimated to double if CCS technology is adopted in its current form. The water-energy nexus is also expected to have an impact on oil and gas exploration. It is possible that technologies such as solar power that require low water usage may prove to be crucial in the near future.

The Importance of Strategic Planning

Situations like the recent drought in California will bring more and more scrutiny and prioritization of water usage. Proper strategic planning is going to be paramount in dealing with water shortages and competing priorities. A holistic modeling framework will be vital for such planning.

EPIS, LLC has been actively engaged in understanding the key challenges posed by the water-energy nexus. Recently, EPIS participated in the “Understanding the water-energy nexus: integrated water and power system modelling” workshop that was organized by the U.S. DOE and European Union’s Joint Research Centre (JRC). The workshop, which brought together academics, industry experts, regulators and model developers, focused on developing a framework for an integrated water-energy model that captures the critical factors in a tractable manner. AURORAxmp’s ability to explicitly model energy conversion capabilities was seen as a possible approach for easily representing the complexities of the water-energy nexus. While the event provided us with insights into various subtleties of this problem, one thing became clear: As water demand and prioritization becomes a larger issue, further research and development are needed.

Filed under: Water-Energy NexusTagged with: , , ,

Nuclear Retirements – The Unknown Future of Nuclear Power in the United States

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Nuclear Plants Nearing Retirement

The U.S. currently has over 2 GW of nuclear capacity scheduled to be retired within the next four years.  The three planned closures are the 678 MW Pilgrim Nuclear Power Station, the 610 MW Oyster Creek Generating Station, and the 852 MW James A. Fitzpatrick Power Station.  The operators of these plants determined that while they had received extensions to their initial licenses, remaining operational was not economically viable.

nuc1

Figure 1: U.S. Nuclear Capacity Source

As of August 2016, announced retirements looking even further into the future total above 7 GW with a few others being politically tenuous it further compounds the uncertainty within the nuclear fleet. Included in this 7 GW is the Fort Calhoun plant in Nebraska that was shut down by Omaha Public Power this year on October 24. However, this is just the tip of the iceberg when you consider the remaining plants and their need for future license extensions.

The Arduous Licensing Process

Nuclear plants are initially licensed for up to forty years by the U.S. Nuclear Regulatory Commission (NRC).  The operator may then apply for an additional twenty-year renewal; following that they can apply for a further extension of twenty more years.  All extensions are initiated by the operator and must be started sufficiently ahead of the expiration of their current license for the NRC to evaluate the safety and environmental impacts of an extension.  When operators apply more than five years prior to expiration, they can usually continue to operate while under this review.  If they don’t apply until within five years of the expiration, they may be forced to stop operating until they are approved.  The renewal process contains multiple cumbersome steps as shown in the diagram below.

nuc2

Figure 2: License Renewal Process Source

 

Current Operating Nuclear Plants

The U.S. has 100 operating nuclear power plants; 45, or nearly half, have already operated through their forty-year operating license and are on their initial twenty-year extension.  Two of these are approaching the need to apply for their second extension: Peach Bottom in Pennsylvania and Surry in Virginia.

nuc3

Figure 3: Active Nuclear Reactors  Source

To look at it another way, 81 plants have received their first renewal, an aging fleet in its own right.   But this means up to 30 GW of nuclear power has an unknown fate based on a not-yet-granted second license extension alone.  To date, no renewal applications have been permanently rejected but several plants have needed to make extensive improvements to gain approval.

nuc4

Figure 4: Licensed Nuclear Plants Source

According to a recent Moody’s report, today’s low gas environment is making it difficult for some smaller nuclear units to survive competitively in the power market.  The future of gas will likely play a key role in the future of nuclear viability, as even without costly improvements some nuclear generators are struggling to stay afloat.

Nuclear Plants Coming Online

Interestingly, there are still a number of newly constructed plants currently in the process of becoming licensed that will bring over 5,000 MW online by 2020; these include plants in Tennessee, North Carolina and Georgia.  Additionally, there are up to six more applications for a combined 10 new reactors currently under review by the NRC.  A few companies are also looking into new designs that are smaller in scale, under 500 MW as opposed to +1,000 MW, that are more modular in design.  This new technology would give them the flexibility to be placed on more urban sites as needed to accommodate grid needs.

The Future Role of Nuclear Power

While a few sites are in the process of retiring their reactors, nuclear power is likely to be a part of the energy solution going forward for some time.  The minutiae of the policies may change, but one thing is certain: nuclear power will play a significant role in meeting U.S. electricity needs while curbing carbon pollution.  The U.S. Department of Energy reports the level of nuclear power generation for the country has been at 20 percent, the question is what hurdles will nuclear owners and operators have to overcome to maintain that level?

Filed under: Clean Power Plan, Nuclear Power, Renewable Portfolio StandardsTagged with: , , , ,

EPIS Releases Mexico Database for Use with AURORAxmp

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Database will provide power market simulation, forecasting and analysis for Mexico and borders

Salt Lake City, Utah – October 26, 2016

http://www.globenewswire.com/news-release/2016/10/26/883166/0/en/EPIS-Releases-Mexico-Database-for-Use-with-AURORAxmp.html

EPIS, the market leader in power market simulation, forecasting and analysis, has released the Mexico Wholesale Market (Mercado Eléctrico Mayorista – MEM) database.  The database will be offered as an upgrade or add-in to its industry-leading AURORAxmp software.

Users of the AURORAxmp software, which is known for delivering unparalleled forecasting and analytical productivity, ease of use and support, will now have access to high quality MEM data, pulled from trusted sources. The AURORAxmp MEM database will be regularly updated to reflect the most recent PRODESEN assumptions from SENER and other key sources including: CENACE data, and analyst experience with CFE and other IPPs in Mexico.

“Recent and ongoing energy market reforms in Mexico, coupled with growth expectations, are creating significant investment opportunities in electric power generation and transmission infrastructure. The most recent PRODESEN (2016-2030) report estimates approximately $90B (USD) in generation investment opportunities and $25B (USD) in transmission and distribution investment opportunities,” said Ben Thompson, CEO of EPIS. “Our MEM database allows users of AURORAxmp to forecast and do market simulations, taking into account this important market.”

It is critical that data sources represent the current state of the National Electricity System and its expected evolution over the next 15 or 20 years. These sources need to be updated regularly, scrubbed to fill in gaps and reflect operational realties, and are tested and calibrated in models so it is trustworthy and commercially reliable. The MEM database offers this needed level of quality.

The AURORAxmp MEM database is formatted, tested, and immediately ready to use for high-quality valuations, market analysis (including energy and capacity), as well as congestion and risk analysis of Mexican power markets. It offers cross-border analysis with boundary zones, including Belize, Guatemala, ERCOT (TX), WECC (AZ) and WECC (CAISO).

The AURORAxmp MEM Database includes primary Mexican power grids, including:

  • Sistema Interconectado Nacional (SIN)
  • Baja California (BCA)
  • Baja California Sur (BCS)

The systems are fully represented by 53 zones that align with PRODESEN and include “proxies” for transmission with boundary zones like Belize, Guatemala, ERCOT (TX), WECC (AZ) and WECC (CAISO).

Our product contains the best available data, refined to represent the current system’s operational realities and market including:

  • Gas constraints
  • Hydro conditions
  • Policy initiatives, including clean energy goals
  • Well-documented sources

Highlights include:

  • Generation: Approximately 800 operational generators, with another 150 in advanced development (construction or LT auction winners), including supporting hourly wind and solar profiles for each zone
  • Fuel prices, including Mexico natural gas hubs Mexico diesel prices (driven to an extent by U.S. imports), Houston Ship Channel, Henry Hub, South Texas, Waha, SoCal Border and distillate/residual fuel oil (FO2/FO6), coal and diesel from U.S. EIA, adjusted for Mexican transport costs
  • Transmission: inter-zonal transfer limits (links) and underlying physical lines, with resistance values, from which loss assumptions can be derived

As with any AURORAxmp database, users can expect the highest level of software integration, model control and easy data exchange. Users can easily import and overlay their own assumptions and other data sources for more powerful, customized insights.

About EPIS

EPIS, LLC (www.epis.com) is the developer of AURORAxmp, the leading-edge software for forecasting wholesale power market prices. The company also provides ready-to-use data for North America and Europe, and unrivaled customer support to its growing body of customers worldwide. A variety of organizations-including utilities (large and small), independent power producers (IPPs), developers, traders, energy consultants, regulatory agencies and universities-use AURORAxmp to model power system dispatch and the formation of both nodal and zonal wholesale power prices, and to perform a wide range of associated analytics over the short- and long-term. AURORAxmp is a comprehensive solution to power market modeling needs. Offices are located in Salt Lake City, UT, Tigard, OR and Sandpoint, ID.

Filed under: Data Management, Mexico Power MarketTagged with: , , ,

EIA Eases Data Accessibility for Power Modelers

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The U.S. Energy Information Administration (EIA) has long been a key source for electrical market data. In the past, much of the EIA’s data have been useful for long-term planning, but have suffered from long lag times and cumbersome manual downloads. Some data have not been published until months or even years after the time period they describe. For example, a generator which began operating in May of 2012 might not have appeared in the EIA’s primary resource list (the EIA-860) until October or November of 2013. Historically, these issues have limited the usefulness of EIA data for many modeling purposes.

However, over the last 2 years, the EIA has made several improvements to the management and delivery of their datasets which some longtime modelers may not be aware of. These enhancements include the EIA-860M, the new Excel Add-in, and the U.S. Electric System Operating Data application. Together, these enhancements greatly expand the list of tasks for which EIA data may be useful.

Form 860M

The EIA-860 is a comprehensive list of grid-connected generators in the U.S. with capacity greater than 1 MW. No data set is perfect, but the EIA-860 has characteristics which are attractive to anyone concerned with data quality. EIA-860 data are collected directly from plant owners who are legally required to respond, it is expressed in consistent terms nationwide, and it is vetted by EIA staff prior to release. While thorough and generally accurate, this process is slow and has only been conducted once each year, leading to lag times of 10-22 months.

In July of 2015, the EIA quietly started publishing data from a new monthly survey, the EIA-860M. This survey is sent to plant owners which reported capacity coming online or retiring in the near future as reported in the most recent EIA-860. The EIA-860M keeps track of these expected changes, and gives plant owners a chance to update the EIA on their progress mid-year. Much of this information has previously been available through the Electric Power Monthly reports, but the EIA-860M combines these data with similar information from the full EIA-860 to create a comprehensive list of active generators. Here are a few things to keep in mind when working with the EIA-860M:

  • It includes a smaller set of unit characteristics than the full EIA-860
  • It has a lag of 2-3 month, so responses for May are posted late-July
  • Like the EIA-860, the Retired list for the EIA-860M is not comprehensive. Only entities with operating plants are required to file with the EIA. So, if a company shuts down its last plant, it no longer responds to the EIA-860 or EIA-860M surveys, and its retired plants will not show up in the Retired list
  • Unlike the EIA-860, the EIA-860M is not vetted prior to release. In order to maintain a timely publishing schedule, the EIA-860M is posted “as-is” and is subject to update without notification

Despite these limitations, the EIA-860M is a relatively thorough and current census of existing and planned generating capacity in the US. It is a welcome addition to the EIA’s current offerings.

Electric System Operating Data

The EIA has taken their first step into the world of intra-day reporting with the new U.S. Electric System Operating Data viewer. While the tool is still in Open Beta, and comes with a fair number of known issues, it promises to be an excellent source for very near-term information about the bulk electrical grid of the U.S.

nyis1

Figure 1: EIA Operating Data – Status Map

Since July of 2015, the EIA has been collecting hourly data from all 66 Balancing Authorities operating in the U.S., including:

  • Day-ahead demand forecasts
  • Actual demand
  • Net generation
  • Interchange with surrounding Balancing Authorities

When everything is working smoothly, the EIA posts these data with a lag of only 80 minutes! These same data are available for download in table form and include API codes for pulling them directly into an Excel workbook using the add-in described below. The EIA also includes a series of pre-made charts and reports on daily supply-demand balance, discrepancies between forecast and actual demand, and much more.

Even for long-term planners, the new datasets collected by the EIA will likely be useful. Never before has the EIA published such granular demand and interchange data. The interchange data in particular has historically been very difficult to find from a publicly available source. Also, Balancing Authorities are much more useful footprints for modeling purposes than states, which is how the EIA partitions much of their information currently. Although it is still in its infancy, the Electric System Operating Data tool promises to open many avenues of analysis which were previously infeasible.

Excel Add-in

Released in February of 2015, the EIA Excel Add-in is useful for importing frequently updated data series into an existing process. While the EIA Interactive Table Viewer is handy for browsing and pulling individual data series, the data almost always need some sort of manipulation or conversion before being input into production cost models such as AURORAxmp. Whether you are converting between nominal and real dollars, changing units, extrapolating growth rates, or combining EIA data with other sources, a series of computations are usually required between raw data and useful inputs. The new Excel add-in allows a user to construct an Excel workbook with all the necessary conversions which can be updated to the latest EIA data with a single click.

ribbon

Figure 2: EIA Excel Add-in Ribbon

Economic data series from the St. Louis Federal Reserve are also available through the same add-in, allowing the user to pull in indicators such as inflation or exchange rates alongside energy-specific data from the EIA. Not only does this save time, it ensures that the correct data series is queried each time the data are updated.

The EIA has always been a key data source for energy analysts, and they are rapidly evolving to become even better. Staying up to date with their latest offerings can reveal relatively easy solutions for some of the toughest data management and upkeep issues encountered by power system modelers.

Filed under: Data ManagementTagged with: , , , , ,