A multi period community energy system optimization model for Arctic and Northern communities considering both thermal and electric loads

Abstract Remote communities across the Arctic continue to rely heavily on fossil fuels for energy sources, which is environmentally damaging and decreases energy security in these regions. Energy system planning models can help communities transition to renewable energy and displace the need for imported diesel. Many studies have developed generation expansion planning (GEP) models to make staged investment decisions. However, few models integrate both electricity and thermal energy needs. In this work, space heating via surface geothermal water is integrated directly into a mixed integer linear programming GEP optimization model, validated on a case study in Pilgrim Hot Springs, Alaska. It was found that a renewably-powered system consisting of wind, solar, and battery storage units was economically superior to a system with diesel, saving over $3457 per year in annualized costs. An analysis of generator capacity lumpiness revealed that a purely renewables system with a hypothetical 20 kW wind turbine (WT) could meet the energy needs of the community for an annualized cost of $13 525, a 24% decrease when compared to a system using a commercially available 100 kW WT. The recommended system met the expressed preferences of the case study community in achieving diesel independence.