Some questions and answers about MacDonald, Clack et al, 2016, “Future cost-competitive electricity systems and their impact on U.S. CO2 emissions.” Return to press release.
- What were the most important findings of this study?
- Why are NOAA researchers leading a renewable energy study?
- What is the National Energy With Weather Simulator?
- How does NEWS work?
- How does the model optimize costs?
- How do these results compare with commitments made in Paris or in the Clean Power Plan?
- How does the model identify potential renewable generation sites?
- Who would build and pay for this optimized electrical power system?
- What would this do to my electrical bill?
- Would all these wind turbines affect the weather?
- If climate change affects the weather, including where wind blows, would the model results change?
- How much of U.S. greenhouse gas emissions are represented by the electricity sector?
- Why are 1990 and 2005 used as benchmarks for greenhouse gas emissions?
- How is the National Electricity with Weather System (NEWS) model different from other models?
Short bios of co-lead authors
Running numerous generation and transmission scenarios through the National Energy with Weather System (NEWS) Simulator (NEWS) model produced a number of important findings.
- The United States could slash greenhouse gas emissions from electric power production by up to 78 percent below 1990 levels within 15 years with current technology while meeting increased demand and without raising consumer costs.
- The model estimates future electricity costs in that renewable-rich future at 8.5 to 10.2 cents per kilowatt hour, less than average national cost today.
- To deliver electricity at the lowest cost possible, the model “chose” to build a high-voltage direct current (HVDC) network that serves to connect electrical power generation and consumption across the contiguous 48 states. The model factored the cost of grid construction into the cost of electricity.
- A national-scale renewable generation system and a national HVDC grid would overcome the “intermittency problem” of solar and wind power. If Wyoming’s winds calmed, Nevada could send in solar power.
- Low-cost and low-emissions electricity are not mutually exclusive.
Wind and solar energy generation potential are inherently dependent on weather patterns. As the nation’s premier weather research agency, NOAA is uniquely positioned to provide scientific data vital to the development of these nationally significant energy resources.
The National Energy with Weather System (NEWS) Simulator is a tool developed by researchers at NOAA’s Earth System Research Laboratories (ESRL) and the Cooperative Institute for Research in Environmental Sciences (CIRES) to simulate the U.S. electrical power sector. Specifically, they are investigating what happens within the system as large amounts of variable generation (wind and solar PV) are integrated as power sources. The aim is to produce a model that can be used by decision-makers on a variety of scales to evaluate the costs and benefits of a broad range of generation and transmission technologies.
The NEWS simulator designs new electrical generation and delivery systems based on renewable power generation estimates from high-resolution weather data, potential future renewable and conventional power sources, electric load requirements for 256 regions and alternative future transmission infrastructures. The simulator selects the type of energy and the locations for generation that best meet the specific needs of system requirements.
In designing new systems, NEWS factors the cost of building new transmission lines and new power generators (turbines and solar panels) into the estimated cost to consumer. NEWS can be programmed to design systems that produce the least amount of carbon dioxide, or waste the smallest percentage of the electric load, or build the least amount of new generation, or even create the smallest amount of new transmission. However, all of these outputs are based on the renewable energy generation potential generated by analysis of NOAA weather data.
The model minimizes the total amortized cost of the electricity system. It takes into account generation, transmission, electric losses, curtailment and other cost related factors. The model then fulfils the operations of an electricity system while keeping costs to a minimum. Once the model can no longer find a solution that is cheaper than all the rest, it stops and produces the result. As it is linear programming, the result is always the global minimum, meaning there is never a lower cost, using the same input values.
The paper did not directly compare model results with the United Nations Climate Change Conference in Paris last year or with the Clean Power Plan. In Paris, 195 nations including the United States agreed to take action to reduce carbon emissions to keep global temperature rises below 2 degrees Celsius this century; the United States pledged to cut greenhouse emissions from all sectors up to 28 percent below 2005 levels by 2025. The Environmental Protection Agency’s Clean Power Plan aims by 2030 to cut carbon pollution from power plants 32 percent below 2005 levels.
The model evaluates renewable potential from a NOAA weather dataset with wind and resource data for 152,000 sites across the continental United States every hour for a year. The model is restricted from building out generation or transmission on restricted sites, such as national forests; residential, commercial and industrial properties; and terrain too steep to safely support wind and solar development. These sites are fed into the model and it selects sites that fulfill the operation of the grid while reducing the cost of the system [Supplemental section 1.2, figure 3, link may not work for some, given paywall.]
The model does not answer this question. Rather, it’s a tool that can be used to evaluate many potential future electrical generation and delivery systems by many parties in the industry—from power companies and transmission line operators to regulators and users—to plan for a more efficient, cost-effective future.
In all “solutions,” the model produces power at 8.5 to 10.2 cents per kilowatt hour, less than current national average residential costs of 12.3 cents/kWh (from the Energy Information Administration).
The model is cost-optimized, so it seeks the lowest-cost way to provide electrical power. The model estimates future costs based on industry projections, but because it is impossible to anticipate all factors that might influence future cost, the model uses several different cost scenarios.
Current studies show the density of wind generation facilities anticipated by the model is less than would be required to influence the weather. One recent publication, for example: http://www.pnas.org/content/112/36/11169.full.pdf
The team can adjust model inputs to reflect climate-related changes or anticipated changes in wind patterns, temperature patterns, and other weather-related variables. (Energy demand, transmission and pricing scenarios can also be evaluated.) The model is a tool that can be used to ask questions about an infinite set of possible future electrical power systems.
Electrical generation accounts for about 40 percent of U.S. CO2 emissions.
In 1990, the United Nations Intergovernmental Panel on Climate Change released its first scientific assessment, and this year became the benchmark for many climate science research and assessment products. The year 2005 is the point of comparison in the Environmental Protection Agency’s Clean Power Plan, which, by 2030, aims to cut carbon pollution from the power sector 32 percent below 2005 levels.
In recent years, similar tools have been developed that deal with electrical power system optimization.
NEWS differs from these models in its use of weather data with high temporal and spatial resolution, over continental-scale geography and extended time periods. The model evaluates renewable energy generation potential by analyzing NOAA weather data from 152,000 grid points in the continental United States and beyond (roughly every 10 miles) and every hour of the day from 2006 through 2008. The model uses a new linear programming approach to optimize (minimize) the cost of generation and transmission systems, including: dispatch, transmission and capacity expansion, reserve pooling and more. [see supplemental, link may not work for some, given paywall]. NEWS is currently undergoing further development to expand its capabilities.
Authors of “Future cost-competitive electricity systems and their impact on U.S. CO2 emissions” are Sandy MacDonald (NOAA); Christopher Clack (CIRES and NOAA) [co-lead-authors], Anneliese Alexander (CIRES and NOAA), Adam Dunbar (NOAA) James Wilczak (NOAA) and Yuanfu Xie (NOAA).
Alexander MacDonald is a research meteorologist who retired from NOAA in January following more than a decade as director of NOAA’s Earth System Research Laboratories and years in other leadership positions. During his 42-year-long career in the agency, he led teams that made significant improvements to U.S. weather forecasting and the understanding of our atmosphere, including innovations in high-performance computing and the development of new weather prediction models. MacDonald, who is outgoing president of the American Meteorological Service, earned a Meritorious Presidential Rank Award for many contributions including his invention of “Science On a Sphere®”, an educational and visualization tool now in more than 100 science centers and other institutions around the globe. He also earned a Distinguished Presidential Rank Award for his service and leadership of the global modeling efforts at the Earth System Research Laboratories.
Christopher Clack is a research scientist for the Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder working with NOAA’s Earth System Research Laboratories. Clack received his first class BSc (Hons) in mathematics and statistics for the University of Manchester in the UK in 2006. He then went on to research applied mathematics and plasma physics at the University of Sheffield in the UK in 2009. During his PhD, Clack completed an area of study centered on nonlinear resonance theory within the framework of magnetohydrodynamics (MHD) that remained unsolved for 20 years. The theories derived have helped our understanding of the Sun as well as possibilities for fusion reactors, such as ITER. In 2010, Clack moved to the United States with his wife to pursue a career in mathematics to investigate the emergence of sunspots on the surface of the Sun. During this time, he became increasingly interested in global warming and its impacts. Therefore, he sought a position to work on modeling the grid to try and determine some answers. He started work at CIRES for NOAA in 2011, and several years later the NEWS simulator was created. He now leads the development of the NEWS simulator and all its associated components.