A Robust Building Energy Management Algorithm Validated in a Smart House Environment

Abstract

A building energy management (BEM) system is a core hardware/software platform that enables demand response applications for building operators in the smart grid environment. This paper presents the BEM algorithm that is designed to be robust against communication failures and data errors. It has been implemented in the smart building located at Yildiz Technical University in Istanbul, Turkey, and results are reported herein. Appliance usage profiles and customer preferences used in the BEM demonstration were derived from a survey of Turkish customers. Both summer and winter usage profiles were used to validate the efficacy of the proposed algorithm in a real-world smart building environment. The paper also discusses lessons learned from field implementation.

Enabling Residential Demand Response Applications with a ZigBee-Based Load Controller System

“…But, in the proposed control scheme in this paper, the 1-min interval allows sufficient time to attempt retransmission of data. Therefore, a selective repeat (SR) automatic repeat request (ARQ) scheme [8] is employed to ensure that a successful communication is made within the 1-min interval. This also keeps the control algorithms less computation intensive for deployment in low-cost controllers.…”

“…In the worst case scenario, where successive re-transmission attempts fail and an updated data cannot be obtained by the HEM in a given minute, the last obtained correct data is used for decision making. As can be seen from the load profiles of the residential loads to be controlled by the proposed load controller system [8], the assumption that power consumption remains almost same for a load in the same state for successive minutes is valid for the concerning loads. Also, as the state change is only issued by the HEM itself, the reuse of past data in case of missing data does not cause any incorrect decision making.…”

“…It can help mitigate power system stress conditions and improve the utilization of generation, transmission and distribution resources. As a result, there have been a lot of interest in developing effective HEM/BEM algorithms [2][3][4][5][6][7][8], as well as hardware infrastructures/ components for complete HEM/BEM solutions [9][10][11][12][13][14][15][16][17]. For communication and control of household loads, most HEM solutions rely either on an existing network of wireless sensors [9] or new design of smart outlets/smart plugs/smart sensors in a system that may use ZigBee [10], power line communication (PLC) [11], ZigBee and PLC [12], infrared (IR) [13], BACnet [14], or cloud-based technologies [15].…”

A double-layer smart charging strategy of electric vehicles taking routing and charge scheduling into account

“…There are several studies considering this integration area in home energy management system framework. Such studies can be found in [28][29][30][31].…”

GPU-Accelerated Foreground Segmentation and Labeling for Real-Time Video Surveillance

“…The monitoring module aims to sense the environmental information, including temperature, humidity, foreground objects, and other datasets. These sensing datasets are converted into several condition variables for evaluating an environment situation, which are then transmitted to smart meters via a low-cost and wireless sensor network based on ZigBee communication protocol [2]. Based on the received condition variables, the ubiquitous Precise background subtraction is an important step for accurate foreground segmentation.…”