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The emergence of distributed energy resources has led to new challenges inthe operation and planning of power networks. Of particular significance is theintroduction of a new layer of complexity that manifests in the form of newuncertainties that could severely limit the resiliency and reliability of amodern power system. For example, the increasing adoption of unconventionalloads such as plug-in electric vehicles can result in uncertain consumer demandpatterns, which are often characterized by random undesirable peaks in energyconsumption. In the first half of 2021, the electric vehicle sales increased bynearly 160%, thus accounting for roughly 26% of new sales in the globalautomotive market. This paper investigates the applicability of generalizedmixture models for the statistical representation of aggregated load in systemsenhanced with high capacity distributed energy resources such as plug-inelectric vehicles.

On Statistical Modeling of Load in Systems with High Capacity Distributed Energy Resources