Efficient Algorithm for Scalable Event-based Demand Response Management in Microgrids
Areg Karapetyan, Majid Khonji, Chi-Kin Chau, Khaled Elbassioni, H., H. Zeineldin

TL;DR
This paper introduces a fast, scalable approximation algorithm for event-based demand response in microgrids, enabling quick load management during contingencies while ensuring system stability and near-optimal utility.
Contribution
It presents a simple greedy algorithm with theoretical performance guarantees for demand response, validated through extensive simulations on large customer datasets and real-world system data.
Findings
Algorithm operates in milliseconds for thousands of customers
Achieves near-optimal load curtailment with provable bounds
Effectively maintains voltage and network constraints during islanded mode
Abstract
Demand response management has become one of the key enabling technologies for smart grids. Motivated by the increasing demand response incentives offered by service operators, more customers are subscribing to various demand response programs. However, with growing customer participation, the problem of determining the optimal loads to be curtailed in a microgrid during contingencies within a feasible time frame becomes computationally hard. This paper proposes an efficient approximation algorithm for event-based demand response management in microgrids. In event-based management, it is important to curtail loads as fast as possible to maintain the stability of a microgrid during the islanded mode in a scalable manner. A simple greedy approach is presented that can rapidly determine a close-to-optimal load curtailment scheme to maximize the aggregate customer utility in milliseconds…
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