A Distributed Energy Management Approach for Smart Campus Demand Response

Abstract

In a smart campus, the potential to reduce energy consumption in buildings is high. In this sense, campus utility operators increasingly need an energy management system capable of interacting with buildings' demand response (DR), which can be automated and cloud-based with the help of information and communication technologies (ICTs). Even so, cloud-based DR implementation still faces some challenges, including computation load, communication delay, and privacy concerns. To address these issues, we developed a cloud-based DR model, which is implemented as a cloud-edge combined computing platform. A competitive equilibrium state of load shedding among the campus buildings is designed to balance the trade-off between occupant discomfort and energy usage. In this article, we adopt the clustering-based distributed alternating direction method of multipliers (ADMM) to decompose the campus load reduction assignment problem into a series of DR subproblems, each of which could be solved by each building with the edge layer computing devices. Two different campus study cases demonstrate the feasibility and performance of the proposed distributed DR algorithm.