Real-Time Power Balancing via Decentralized Coordinated Home Energy Scheduling

TL;DR

This paper introduces a decentralized coordinated home energy management system that enables neighborhood-wide real-time power balancing through collaborative scheduling, using stochastic optimization and message exchange.

Contribution

It presents a novel decentralized CoHEM architecture with stochastic modeling and approximation techniques for real-time power balancing in residential areas.

Findings

Effective real-time power balancing demonstrated in simulations

Decentralized algorithm allows local scheduling with minimal communication

Improved demand-supply matching reduces rebound effects

Abstract

It is anticipated that an uncoordinated operation of individual home energy management (HEM) systems in a neighborhood would have a rebound effect on the aggregate demand profile. To address this issue, this paper proposes a coordinated home energy management (CoHEM) architecture in which distributed HEM units collaborate with each other in order to keep the demand and supply balanced in their neighborhood. Assuming the energy requests by customers are random in time, we formulate the proposed CoHEM design as a multi-stage stochastic optimization problem. We propose novel models to describe the deferrable appliance load (e.g., Plug-in (Hybrid) Electric Vehicles (PHEV)), and apply approximation and decomposition techniques to handle the considered design problem in a decentralized fashion. The developed decentralized CoHEM algorithm allow the customers to locally compute their scheduling solutions using domestic user information and with message exchange between their neighbors only. Extensive simulation results demonstrate that the proposed CoHEM architecture can effectively improve real-time power balancing. Extensions to joint power procurement and real-time CoHEM scheduling are also presented.