Statistical representation of demand for GIS-based load profile allocation in distribution networks

Realistic load profiles are critical to quantify the benefits and challenges associated with the adoption of new technologies. The allocation of these profiles to loads in a distribution network model considering the corresponding monthly energy consumption, class of customer (residential or industrial/commercial), and location (from Geographic Information Systems, GIS) is an important task that must be accomplished to better assess the corresponding effects. This GIS-based allocation, nonetheless, has not been discussed in the existing literature. This work presents a methodology that adopts results from a statistical characterization of electricity demand to create stochastic load profiles that are then allocated to customers represented by loads in a GIS distribution network model considering their monthly energy consumption, class, and geographical location. The demand is characterized via a thorough statistical analysis of data gathered during a nation-wide power quality monitoring program. More importantly, the load profile creation for GIS-based allocation is implemented as a free and open-source tool that is currently being used in different studies. The effectiveness of the methodology and performance of the tool are demonstrated using information of over 1,000 residential and 400 industrial/commercial customers in Costa Rica, and a real, large-scale distribution network with more than 13,000 customers.