<p> The resource mix for the U.S. electrical power grid is undergoing rapid change with increased levels of solar photovoltaic (PV) and wind turbine electricity generating capacity. There are potential negative impacts to grid resilience resulting from hurricane damage to wind and solar power stations connected to the power transmission grid. Renewable power sources are exposed to the environment more so than traditional thermal power sources. To our knowledge, damage to power generating stations is not included in studies on hurricane damage to the electrical power grid in the literature. The lack of a hurricane wind damage prediction model for power stations will cause underestimation of predicted hurricane wind damage to the electrical grid with high percentages of total power generation capacity provided by solar photovoltaic and wind turbine power stations. </p><p> Modeling hurricane wind damage to the transmission grid and power stations can predict damage to electrical grid components including power stations, the resultant loss in power generation capacity, and restoration costs for the grid. This Praxis developed models for hurricane exposure, fragility curve-based damage to electrical transmission grid components and power generating stations, and restoration cost to predict resiliency factors including power generation capacity lost and the restoration cost for electrical transmission grid and power generation system damages. Synthetic grid data were used to model the Energy Reliability Council of Texas (ERCOT) electrical grid. A case study was developed based on Hurricane Harvey. This work is extended to evaluate the changes to resiliency as the percentage of renewable sources is increased from 2017 levels to levels corresponding to the National Renewable Energy Lab (NREL) Futures Study 2050 Texas scenarios for 50% and 80% renewable energy. </p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10844532 |
| Date | 18 August 2018 |
| Creators | Watson, Eileen B. |
| Publisher | The George Washington University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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