Wednesday, 26 January 2011
Handout (1.5 MB)
As the renewable energy industry continues to grow so does the requirement for atmospheric modeling and analysis tools to maximize both wind and solar power. Renewable energy generation is variable however; presenting challenges for electrical grid operation and requires a variety of measures to adequately firm power. These measures include the production of non-renewable generation during times when renewables are not available. One strategy for minimizing the variability of renewable energy production is through site diversity. Assuming that a network of renewable energy systems feed a common electrical grid, site diversity ensures that when one system on the network has a reduction in generation others on the same grid make up the difference. The Renewable Energy Network Optimization Tool (ReNOT) has been developed to perform trade studies for the wind and solar generation industry. The tool uses long period high fidelity time series of wind and cloud data to optimize the placement of wind and solar farms given a user's constraints. For example, it may be desirable from an economic and financial perspective to locate generation farms in close proximity to existing electrical grid infrastructure. Therefore, ReNOT's multi-facted scoring system can include a penalty function which trades power generation versus cost to build off the infrastructure. With nearly 35 Gigawatts (GW) of wind generation in existence today across the United States and greatly expanded generation expected over the coming decade it would be of great value to the renewable energy community to see how climate change impacts might impact the optimal locations of future generation. For example, in this illustrative study we are evaluating marginal increase in wind power generation quantity and consistency across the Continental United States (CONUS) given that the State of Texas today has approximately 9.4 GW of installed "name-plate" capacity. This study is performed using our 15 year (1995-2009) downscale simulation of hub-height winds over CONUS at 12 km and 1 hour resolution, respectively. In addition, we are developing a climate change projection of hub-height winds for the period 2060-2074 so that an impact study can be performed whereby a comparison of how the best generation locations change from the present (1995-2009) to the future. The questions are, given the current production today over Texas, where might generation capacity be sited over the remainder of CONUS to even out the actual electrical production? And, do the regions of the best marginal increase in generation change as climate changes? A similar study was performed for the space to ground free space optical communication community using the Lasercom Network Optimization Tool (LNOT). Clouds severely attenuate an optical link thereby degrading availability. LNOT is used to determine the optimal locations of sites to maximize cloud freeness. The impact of additional availability when adding an extra site to an existing five-site lasercom network is shown in Figure 1. The five site network has a cloud freeness 99.17% of the time. Bright colors represent areas where additional availability is possible ( up to 0.5%) . In general these regions are located hundreds of kilometers from the existing five site network (dark blue dots), showing the value of decorrelation and geographical diversity. Analogous results from the ReNOT study will be presented at the conference.
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