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Analyzing and Optimizing Supply and Demand of Intermittent Renewable Electricity through Transmission Load Flow Modeling

Project Summary

This is a project to use a transmission load flow model combined with an atmospheric model to examine the ability of California to deliver a smooth supply of different future (c. 2020) penetrations of renewable energy (solar, wind, geothermal, hydroelectric, and wave energy), some of which is intermittent. One result of the study will be a determination of whether future changes in California renewable electricity supply can be used reliably to provide minute-by-minute, day-by-day, and season-by-season electricity demand in California, particularly with different penetrations of electric and plug-in-hybrid vehicles. If not, recommendations of where and by how much to modify the capacity of the California transmission grid will be provided. In addition, ideal locations of new renewable wind and solar resources will be provided.

Research Plan

For this project, we will predict winds, waves, and solar radiation throughout California with a high-resolution-in-time-and-space atmospheric climate-weather prediction-air quality model. Such predictions will be applied to specific wind, wave, photovoltaic, and solar thermal, etc., technologies to calculate available power. Power data will be fed into a transmission load flow model that simulates high voltage power systems on a time scale from minutes to days. Seasonal power flow data for California will be used to determine current levels of power in California. The transmission model will be used to determine the extent to which the current transmission and distribution grid can deliver the necessary power from new renewable energy generators and, if not, what new transmission is needed to optimize power delivery. Estimated additional geothermal, wind, solar, and wave power sources will be accounted for by incorporating new generating buses in regions with each renewable resource and by increasing generation at existing sites. From the simulations, we will determine the feasibility of reducing generation from specific natural gas and coal (very few) plants throughout the state while minimizing additions to the transmission infrastructure. Additional analysis will be directed toward, for example, determining the effects of vehicle-to-grid control methods in reducing intermittency (e.g., smart meters for providing electricity to vehicles when excess power is available). Finally, we will assess the effect of interconnecting geographically-disperse wind farms on reducing intermittency.

Significance of Research

This project will provide information about whether a large penetration of different types of geographically-disperse renewables, combined through the power grid, can provide stable and load-following electricity. It will also provide information about ideal locations of wind, solar, and wave-power plants for maximizing load-balancing ability, minimizing intermittency, and minimizing transmission requirements. By examining the ability of large-scale renewables to meet electric power demand, the study can reduce a barrier to their expansion, namely the concern that they are intermittent and not reliable. Such a barrier reduction can increase the penetration of renewables, ultimately resulting in significant reductions in fossil fuel use and climate-relevant emissions.

Project Abstract: Analyzing and Optimizing Supply and Demand of Intermittent Renewable Electricity Through Transmission Load Flow Modeling (0.1MB PDF)
Mark Z. Jacobson, Mike Dvorak, Elaine Hart, Gerard Ketefian, Graeme Hoste

Final Report: Final Survey Report (.462 MB PDF)
Mark Z. Jacobson