National Energy with Weather System Simultator (NEWS) Sets Bounds on Cost Effective Wind and Solar PV Deployment in the USA without the Use of Storage.

Thursday, 18 December 2014
Christopher Clack1, Alexander E MacDonald2, Anneliese Alexander1, Adam D Dunbar2, Yuanfu Xie2 and James M Wilczak3, (1)University of Colorado, Boulder, CO, United States, (2)NOAA Boulder, Earth Systems Research Laboratory, Boulder, CO, United States, (3)NOAA, Boulder, CO, United States
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 weather model used is the Rapid Update Cycle for the years of 2006-2008. The team also collated a detailed electrical load dataset for the contiguous USA from the Federal Energy Regulatory Commission for the same three-year period. The coincident time series of electrical load and weather data allows the possibility of temporally correlated computations for optimal design over large geographic areas.

The past two years have seen the development of a cost optimization mathematic model that designs electric power systems. The model plans the system and dispatches it on an hourly timescale. The system is designed to be reliable, reduce carbon, reduce variability of renewable resources and move the electricity about the whole domain. The system built would create the infrastructure needed to reduce carbon emissions to 0 by 2050. The advantages of the system is reduced water demain, dual incomes for farmers, jobs for construction of the infrastructure, and price stability for energy.

One important simplified test that was run included existing US carbon free power sources, natural gas power when needed, and a High Voltage Direct Current power transmission network. This study shows that the costs and carbon emissions from an optimally designed national system decrease with geographic size. It shows that with achievable estimates of wind and solar generation costs, that the US could decrease its carbon emissions by up to 80% by the early 2030s, without an increase in electric costs. The key requirement would be a 48 state network of HVDC transmission, creating a national market for electricity not possible in the current AC grid. The study also showed how the price of natural gas fuel influenced the optimal system designed.