ABSTRACT

As the renewable energy industry continues to grow so does the requirement for atmospheric modeling and analysis tools to understand the variability associated with integrating wind and solar power on the U.S. grid. Renewable energy generation is variable presenting challenges for electrical grid operation and requires a variety of measures to adequately firm power. One strategy for minimizing the variability of renewable energy production is site diversity. Assuming that a network of renewable energy systems feed a common electrical grid, site diversity ensures that when one generation system on the network has a reduction in generation others make up the difference.

The United States Department of Energy has an objective to grow renewable energy generation and integration from 1% to 20% by 2030. Two-key challenges exist including: 1) Enabling system-level approaches to overall generation capacity expansion and integration (including policy changes to realize this), and 2) Addressing the variability issues of renewable generation. The current approach to renewable generation expansion has been to deploy wind and solar sites in the windiest/sunniest locations without regard to the variability of generation problem. Because weather is highly correlated, even over relatively short distances, regular variability in generation can be expected if renewable sites are concentrated in small geographical areas. This variability makes it more challenging to integrate onto the electric grid complicating the firming requirements.

This seminar will discuss the development and applications of an assessment and planning tool which leverages the atmospheric modeling of high resolution wind databases as well as remote sensed cloud databases to address the variability of wind and solar power production. The tool is known as MORE Power (Maximizing and Optimizing Renewable Energy). MORE Power uniquely quantifies the optimal placement of wind and/or solar sites to maximize high quality power. In addition it shows the real value of transmission expansion as an enabler to aggregate diverse variable resources, and it identifies the benefits of larger balancing areas as a key enabler for greater grid stability and therefore a reduced need to keep transmission capacity in reserve.

A modified version of the Weather Research and Forecasting (WRF) mesoscale model is used to generate a high-resolution wind database over the Continental United States for the period 1995-2009. Wind and density data at 100 meters above ground level are extracted at 1 hour intervals and 12 kilometer resolution from WRF. A satellite derived cloud climatology using GOES is developed for the same period at 15 minute intervals and at 4 kilometer horizontal resolution. Examples of MORE Power applications will be shown.