PNNL

Abstract

This paper demonstrates the creation of time-varying, end-use electric load models with electric meter data for use by advanced, model-based volt-VAR optimization (VVO) control schemes. VVO has been shown to reduce energy consumption and peak demand in the electric distribution system. Modern VVO systems use power flow models to make control decisions. In order to make optimal decisions, these models must contain accurate load models. To improve these load models, this work uses active power, reactive power, and voltage magnitude measurements from advanced metering infrastructure (AMI) in a simulated distribution feeder to create electric load models for each customer meter. Three different modeling approaches are discussed, and their effectiveness is measured by comparing the optimality of VVO solutions with a base case. The results show that the models derived from AMI data can accurately represent some end-use load behavior like total energy costs, but lose accuracy when considering more dynamic system behavior like voltage violations over small time intervals. This work helps to advance state-of-the-art, model-based VVO by providing a data-driven modeling technique which acknowledges that optimal distribution system control requires a treatment of the system which is dependent on time, voltage, and system conditions.