Abstract:
The need for energy-efficient and reliable electric power in remote arctic communities of Alaska is a driving force for research in this work. Increasing oil prices, high transportation costs for fuels, and new environmental standards have forced many utilities to explore hybrid energy systems in an attempt to reduce the cost of electricity (COE). This research involves the development of a stand-alone hybrid power system model using MATLABRTM SimulinkRTM for synthesizing the power system data and performing the economic and environmental analysis of remote arctic power systems. The hybrid model consists of diesel electric generators (DEGs), a battery bank, a photovoltaic (PV) array, and wind turbine generators (WTGs). The economic part of the model is used to study the sensitivity analysis of fuel cost and the investment rate on the COE, the life cycle cost (LCC) of the system, and the payback time of the system. The environmental part of the model calculates the level of various pollutants including carbon dioxide (CO2), nitrogen oxides (NOx), and the particulate matter (PM10). The environmental analyses part of the model also calculates the avoided cost of various pollutants. The developed model was used to study the economics and environmental impacts of a stand-alone DEG system installed at the University of Alaska Fairbanks Energy Center, the wind-diesel-battery hybrid power system installed at Wales Village, Alaska, and the PV-diesel-battery hybrid power system installed at Lime Village, Alaska. The model was also used to predict the performance of a designed PV-wind-diesel-battery system for Kongiganak Village. The results obtained from the SimulinkRTM model were in close agreement with those predicted by the Hybrid Optimization Model for Electric Renewables (HOMER) software developed at National Renewable Energy Laboratory (NREL).
