Living in the Past?

Living in the past is not healthy. Is your database up-to-date? EPIS just launched the latest update to the North American Database, version 2016_v4, marking the fourth North American data update this year! Recent changes in the power industry present challenges to database management which will be discussed in this post.

In general, the transformation in power generation sources in the U.S. coupled with evolving electricity demand and grid management represents a paradigm shift in the power sector. In order to accurately model power prices in the midst of such change, one must have a model built on fundamentals and a database that is up-to-date, has reasonable assumptions, is transparent and is flexible. A recent post described the technical side of working with databases in power modeling. This entry outlines important changes in the East Interconnect, the impacts those changes have on data assumptions and configuration and the steps we are taking to provide excellent databases to our clients.

Recent shifts in power generation sources challenge database assumptions and management. New plant construction and generation in the U.S. are heavily weighted towards renewables, mostly wind and solar and as a result, record generation from renewables has been reported across the East Interconnect. Specifically, on April 6, 2016, the Southwest Power Pool (SPP) set the record for wind penetration:

Record Wind Penetration Levels 2015

Figure 1. Record wind penetration levels in Eastern ISOs compared with average penetration in 2015. SPP holds the record which was reported on April 6, 2016. Record sources: NYISO, SPP, MISO, ISO-NE, PJM. 2015 Averages compiled from ISO reports, for example: NYISO, SPP, MISO, ISO-NE, PJM. *Average 2015 generation used to calculate penetration.

Similarly, the New York City area reached a milestone of over 100 MW in installed solar distributed resources. Accompanying the increase in renewables are increases in natural gas generation and reductions in coal generation. In ISO-NE, natural gas production has increased 34 percent and coal has decreased 14 percent since 2000, as highlighted in their 2016 Regional Electricity Outlook. These rapid changes in power generation sources require frequent and rigorous database updates.

Continued electric grid management changes in the East Interconnect also requires flexibility in databases. One recent change in grid management was the Integrated System joining the Southwest Power Pool, resulting in Western Area Power Administration’s Heartland Consumers Power District, Basin Electric Power Cooperative and Upper Great Plains Region joining the RTO. The full operational control changed on October 1, 2015, thus expanding SPPs footprint to 14 states, increasing load by approximately 10 percent and tripling hydro capacity. Grid management change is not new, with the integration of MISO South in 2013 as an example. Changes such as these require flexibility in data configuration that allow for easy restructuring of areas, systems and transmission connections.

Variability in parameters, such as fuel prices and demand, introduce further difficulty in modeling power markets. The so called “Polar Vortex” weather phenomena shocked North Eastern power markets in the winter of 2013/2014 with cold temperatures and high natural gas prices resulting in average January 2014 energy prices exceeding $180/MWh in ISO-NE. It seemed like the polar opposite situation occurred this last winter. December 2015 was the mildest since 1960, and together with low natural gas prices, the average wholesale power price hit a 13-year low at $21/MW. The trend continued into Q1 of 2016:

Monthly average power price in ISO-NE Q1 2014 and 2016

Figure 2. Monthly average power price in ISO-NE in Q1 2014 and 2016. Variability between years is a result of high natural gas prices and cold weather in 2014 versus low natural gas prices and mild weather in 2016.

Whether extreme events, evolving demand or volatile markets, capturing uncertainty in power modeling databases is challenging. In AURORAxmp, users can go one step further by performing risk simulations; specifying parameters such as fuel prices and demand to vary across a range of simulations. This is a very powerful approach to understanding the implications of uncertainty within the input data.

The aforementioned changes in generation, grid management and demand, offer exciting new challenges to test power market models and data assumptions. To test our platform, EPIS performs a historical analysis as a part of each database release. Inputs of historical demand and fuel prices are used to ensure basic drivers are captured and model output is evaluated not only in terms of capacity, but monthly generation, fuel usage and power prices. The result of this process is a default database that is accurate, current, contains reasonable assumptions, is transparent and is flexible to ensure you have the proper starting point for analysis and a springboard for success.

With the release of North_American_DB_2016_v4, EPIS continues to provide clients with superb data for rigorous power modelling. The 2016_v4 update focuses on the East Interconnect and includes updates to demand, fuels, resources, DSM and other miscellaneous items. Clients can login to our support site now to download the database and full release notes. Other interested parties can contact us for more information.

Filed under: Data Management, Power Market InsightsTagged with: , , , , , ,

The New Electric Market in Mexico

The Role of Zonal Resource Planning Analyses

On January 26, 2016 a once-in-a-lifetime event occurred that may have been overlooked by the casual observer: Mexico launched the first phase of its reformed, now competitive, electric market. The day-ahead market began for the Baja Mexico interconnection and is the first component of a comprehensive change to the nation’s electric system.

Over the last few years, sweeping market reforms and designs were drafted, approved by the government, and are now beginning to be implemented in a fundamental shift for electricity in Mexico. The expectation is that incorporating a market structure will modernize a constrained and aging system, improve reliability, increase development of renewable generation and drive new investment.

A market shift like this underscores the critical need to produce meaningful and accurate analyses for long-term resource planning, in addition to participating in the day-ahead nodal market.

The importance of data availability to market participants cannot be overstated. As a result of the market reforms in Mexico, the sole utility, Comisión Federal de Electricidad (CFE), is being split into multiple entities and government organizations are being restructured to address the change from a state-run system to a competitive marketplace. Yet, the detailed data required for trading activities, such as those begun in January, and to support the proposed nodal market is difficult to obtain. Sources for much of this data are still being determined and still not available in some cases.

However, for typical generator development and economics, investment, and lifecycle forecasting – studies that require 30-40 year planning horizons – data is available. Resource planning analytics have become imperative to the development of new generation and transmission, informing investment in the energy sector, producing integrated resource plans for utilities, as well as numerous different studies for other stakeholders. Planning tools like AURORAxmp play a key role in these analyses, but so does the need for accurate market data.

Dispatch simulation models used for these studies typically define market topographies at the zonal (or control area) level. Mexico is currently divided into nine of these zones, or, “control regions”.

New Electric Market Control Regions in Mexico

Each of these zones contains generator information, load/demand information, and aggregated transmission capacities to/from adjoining zones. This data can be used by the dispatch simulation to forecast prices, value, risk, etc. for the study period. In the case of resource planning, it can produce detailed capacity expansion analyses to understand:
-Understand the value and operation of existing units.
-Determine whether to retire uneconomic or obsolete generators.
-Consider the value and performance of new generation that may have been added by the simulation.

Analysts can specify additional information such as new generation technologies (e.g. renewable generator options), capital costs, return components and other financial information to produce results that will inform build/buy decisions.

AURORAxmp has been used in a variety of studies in Mexico since 2002. Consultants and IPPs have utilized the software to produce meaningful results used in long-term resource planning decisions, and the zonal topography has provided the advantage of demonstrating value in the current market.

Developing a solid fundamental outlook that allows the assessment of potential long-term risks and opportunities is imperative for decision making and sound financial planning whether you are assessing the development a new power plant or acquiring an existing asset in Mexico. The wholesale power market in Mexico is expected to from a day-ahead and real-time nodal market to include traded pricing hubs with a futures market. A zonal model using AURORAxmp can provide an invaluable tool for long-term price forecasting, scenario analysis and asset valuation for the new Mexican reality.
– Marcelo Saenz, Pace Global, A Siemens Business

Although the proposed market will eventually operate at the nodal level, long-term studies at the zonal level remove the effects of temporary events at the nodal level, thus providing a more stable result for financial decisions.

AURORAxmp has the robust abilities to simulate both zonal and nodal markets. However, its leading capabilities in performing long-term resource planning analysis will continue to be especially important for markets, like Mexico, that will go through enormous changes and growth over the next few years.

Filed under: Power Market Insights, UncategorizedTagged with: , , , , ,