Abstract
Abstract
Future energy systems will be dominated by variable renewable power generation and interconnected sectors, leading to rapidly growing complexity. Flexible elements are required to balance the variability of renewable power sources, including backup generators and storage devices, but also flexible consumers. Demand response (DR) aims to adapt the demand to the variable generation, in particular by shifting the load in time. In this article, we provide a detailed statistic analysis of the collective operation of many DR units. We establish and simulate a model for load shifting in response to real-time electricity pricing using local storage systems. We show that DR drives load shifting as desired but also induces strong collective effects that may threaten system stability. The load of individual households synchronizes, leading to extreme demand peaks. We provide a detailed statistical analysis of the grid load and quantify both the likelihood and extent of extreme demand peaks.
Funder
Helmholtz-Gemeinschaft
Bundesministerium für Bildung und Forschung
Deutsche Forschungsgemeinschaft
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems
Cited by
4 articles.
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