Dispatch capacity forecasting of distributed energy resources for load peak shaving

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Date

2022-04

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University of New Brunswick

Abstract

The progress of the electric power grid to a decentralized and ‘smart’ system has enabled the participation of distributed energy resources (DERs) to provide peak load shaving and ancillary services. This thesis focuses on a probabilistic dispatch capacity forecast of aggregated DERs, with models that allow the simulation of individual loads and the estimation of their potential load shifting capacity during peak hours, while tracking customer comfort. As part of the forecasting method, this work proposes a scheme for aggregated DER control that consists of a modified direct load control strategy and a modified advanced demand response control schedule. The simulation results show the potential of the proposed approach to increase the dispatchable capacity during peak hours in aggregations of the DERs considered, while maintaining customer comfort.

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