Intelligent cloud home energy management system using household appliance priority based scheduling based on prediction of renewable energy capability

Byun, Jinsung; Hong, Insung; Park, Sehyun

doi:10.1109/tce.2012.6414985

Cited by 104 publications

(52 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…From the perspective of structure, agent based smart MG [15][16][17][18][19] has three control levels. On the bottom level is the micro source, inverter interface and corresponding control system based local agents; on the middle level is the communication system based SCADA agent; on the top level is the agents based smart system, as shown in Figure 1.…”

Section: Multi Agent Based Smart Mgmentioning

confidence: 99%

“…The agents are intelligent and capable of responding to external events, having clear control objectives. SCADA agent, DG agents, Load agents, Intelligent House agents [19] and Energy Management System (EMS) agent [20,21] communicate and interact with each other autonomously and form a small-scale smart MG system. The networked structure greatly improves the reliability of communication.…”

Section: Multi Agent Based Smart Mgmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Variable Droop Curve Control Strategies in Smart Microgrid

et al. 2017

View full text Add to dashboard Cite

Abstract:In micro grid (MG), active/reactive power sharing for all dis-patchable units is an important issue. To meet fluctuating loads' active and reactive power demands, the units generally adopt primary P-f and Q-U droop control methods. However, at different state of charge (SOC) values, the capability of Lead Acid Battery Bank (LABB) based units to take loads varies in a large range; active power should not be shared according to the units P capacities in a constant ratio. Besides, influenced by the output and line impedance between units, reactive power is not able to be shared in proportion to the units Q capacities. Another problem, after MG power balance requirement is satisfied, frequency and voltage are deviating from their rated values thus power quality is reduced. This paper presents a new smart MG which is based on the multi agent system. To solve the problems mentioned above, P-f and Q-U droop curves are adjusted dynamically and autonomously in local agents. To improve the power quality, secondary restoration function is realized in a decentralized way, the computation tasks are assigned to local, the computation capability and communication reliability requirements for central PC are low, and operation reliability is high. Simulation results back the proposed methods.

show abstract

Section: Multi Agent Based Smart Mgmentioning

confidence: 99%

Section: Multi Agent Based Smart Mgmentioning

confidence: 99%

Distributed Variable Droop Curve Control Strategies in Smart Microgrid

et al. 2017

View full text Add to dashboard Cite

show abstract

“…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].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

View full text Add to dashboard Cite

Home energy management (HEM) systems are getting increasingly popular in both academic and commercial communities. Most HEM solutions rely on either smart appliances or plugging traditional appliances into smart outlet/smart plugs which can communicate with the central HEM server. Conventional non-communicating powerintensive loads that are directly hard-wired to the supply panel of the house in the U.S., e.g., water heaters and clothes dryers, therefore are difficult to be made part of an HEM system. This paper describes the design and implementation of a microcontroller and ZigBee based load controller system that allows these loads to be controlled by an HEM system. The proposed system consists of four load controllers (LCs) that monitor and control four power-intensive household loads, and one communication controller (CC) that acts as a communication medium between LCs and a central HEM unit. The CC and all the LCs are packaged into one load controller box that can be placed beside the main circuit panel of the house and the wirings to the power-intensive loads are routed through the LCs. Within the box, the LCs and the CC communicate via hard-wired serial peripheral interface. The CC then communicates with the HEM system via ZigBee. The proposed system is expected to offer a cost-effective method

show abstract

“…A fully automated DR program [3] is one that can provide load management to meet electric utility needs without direct customer intervention. With an increasing interest in DR programs for residential customers in recent years, various automated DR approaches have been developed [4][5][6][7][8][9][10][11][12][13][14][15][17][18][19][20][21][22][23]25].…”

Section: Introductionmentioning

confidence: 99%

“…Different methodologies have been applied. For example, authors in [14] implemented a dynamic priority based scheduling scheme; authors in [15] employ a convex programming based solution, whereas authors in [17,25] employed dynamic programming based approaches. Authors in [18] proposed implementation for a green home with built-in PV and motorized blinders.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

View full text Add to dashboard Cite

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.

show abstract

Intelligent cloud home energy management system using household appliance priority based scheduling based on prediction of renewable energy capability

Cited by 104 publications

References 19 publications

Distributed Variable Droop Curve Control Strategies in Smart Microgrid

Distributed Variable Droop Curve Control Strategies in Smart Microgrid

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

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

Contact Info

Product

Resources

About