Although wind and solar energy are regarded as potential contributors to future US energy production, there is wide disagreement concerning the level of energy that could be reasonably produced from these sources. The variability of wind and solar energy as the weather varies is one important question, as is the availability of the large suitable land areas that such energy production requires. We present the results of a study that uses weather and land data to determine the costs, reliability and resource requirements of a national system that would convert the preponderance of US energy production to wind and solar by 2030. Data used in the study included estimates of wind and solar energy available over the US 48 states from January 1, 2006 to December 31, 2008. Wind data at turbine heights were estimated from the Rapid Update Cycle Model on a 13 km resolution grid over the US conterminous 48 states. Similarly, direct and diffuse solar radiation estimates were obtained for the RUC and from GOES satellite imagery. Land data, including land slope, biological description, and human structure density were used to determine areas that would allow power production. National demand for electricity was projected to 2030, with assumptions of 1.1% growth per year and a 43% conversion of the US auto fleet to electric. A linear programming minimization is used to determine the optimal network in terms of cost and availability. The minimization used gas power peaking plants to provide power when the national wind and solar system fell short of the national electric load. The results of the study will include maps showing the optimal configuration for a national system. We will present cost and reliability estimates that would help determine the feasibility of large scale deployment of wind and solar energy systems.