Predicting performance of a renewable energy-powered microgrid throughout the United States using typical meteorological year 3 data

Natural disasters are increasing in frequency and cost throughout the United States. Long term power outages frequently result from natural disasters, which leads to higher reliance on inefficient and cost ineffective gasoline or diesel powered generators to meet energy needs. The development of deployable renewable energy-powered microgrids as mobile power sources would allow energy demands to be met in portable and effective way, while reducing diesel fuel consumption. Characterizing system performance of renewable energy-powered microgrids prior to deployment would allow a future system to be appropriately sized to meet all required electrical loads at a given intermittent diesel generator operational frequency. Appropriate sizing of renewable energy powered microgrids and backup diesel generators would decrease system operation and transportation costs as well as define the appropriate amount of fuel to be kept on hand. This paper focuses on developing figures that represent the quantity of external AC or DC load a microgrid could supply as a function of intermittent diesel generator operational frequency. Typical meteorological year 3 (TMY3) data from 217 Class I locations throughout the United States were inserted into an operational frequency prediction model to characterize the quantity of external AC and DC load the system could supply at intermittent diesel generator operational frequencies of 1%, 5%, 10%, 25%, and 50%. Ordinary block Kriging analysis was performed to interpolate AC and DC load power between TMY3 Class I locations for each diesel generator operating frequency. Figures representing projected AC and DC external load were then developed for each diesel generator operating frequency.