National Energy with Weather System (NEWS) Simulator Results

Abstract

The importance of weather-driven renewable energies for the United States energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. In 2009, we began a large-scale investigation into the characteristics of weather-driven renewables. The project utilized the best available weather data assimilation model to compute high spatial and temporal resolution power datasets for the renewable resources of wind and solar PV. The coincident time series of electrical load and weather data on a 13-km grid is used to investigate optimal designs of electric power systems over the contiguous US. In the past two years, the team have expanded the sophisticated mathematical optimization tool that is based upon linear programming (1) with an economic objective. We performed a simplified test where the US electric system consisted of wind, solar PV, nuclear, hydroelectric and natural gas only with the addition of HVDC bulk transmission. The test shows that if the US meets its goals in price reduction of variable generation the US would only have dramatic reductions of carbon dioxide emissions that is cost effective with a national-scale interconnected system. The smaller the system the higher the carbon emissions and steeper the cost.