Smart home energy management system including renewable energy based on ZigBee and PLC

Han, Jinsoo; Choi, Chang‐Hwan; Park, Wan-Ki; Lee, Il-Woo; Kim, Sang-Ha

doi:10.1109/tce.2014.6851994

Cited by 332 publications

(63 citation statements)

References 10 publications

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“…However, these costs can be reduced through the cooperative operation of the customer side. A cooperative operation system is possible with HEMSsmart grid technology [45][46][47][48]. The reactive power incentive concept provides an amount of profit to the customer to contribute to the sustainable power system of DisCo.…”

Section: Reactive Power Incentive Methodsmentioning

confidence: 99%

Optimal Operation Method for Distribution Systems Considering Distributed Generators Imparted with Reactive Power Incentive

et al. 2018

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Featured Application: The incentive method with flexible contribution functions can be applied to demand response by the reactive power market and distribution company, which has the possibility to reduce the additional installation of distribution control equipment and battery capacity. It also leads to the reduction of total electricity purchase cost of consumers, and the power system can achieve high mixing of renewable energy in the grid with the reactive power incentive demand response and the IoT development. Furthermore, reliability assessment of cooperative control with the participation rate will give an important contribution to the robust design of the system. Abstract: In order to solve urgent energy and environmental problems, it is essential to carry out high installation of distributed generation using renewable energy sources (RESs) and environmentally-friendly storage technologies. However, a high penetration of RESs usually leads to a conventional power system unreliability, instability and low power quality. Therefore, this paper proposes a reactive power control method based on the demand response (DR) program to achieve a safe, reliable and stable power system. This program does not enforce a change in the active power usage of the customer, but provides a reactive power incentive to customers who participate in the cooperative control of the distribution company (DisCo). Customers can achieve a reduction in their total energy purchase by gaining a reactive power incentive, whilst the DisCo can achieve a reduction of its total procurement of equipment and distribution losses. An optimal control schedule is calculated using the particle swarm optimization (PSO) method, and also in order to avoid over-control, a modified scheduling method that is a dual scheduling method has been adopted in this paper. The effectiveness of the proposed method was verified by numerical simulation. Then, simulation results have been analyzed by case studies.

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Section: Reactive Power Incentive Methodsmentioning

confidence: 99%

Optimal Operation Method for Distribution Systems Considering Distributed Generators Imparted with Reactive Power Incentive

et al. 2018

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“…In Han et al, 12 the authors proposed a smart home energy management system using the ZigBee-based energy measurement to monitor the energy consumption of home appliances and lights. The central light control collects the energy consumption and analyzes them to optimize home energy.…”

Section: Related Workmentioning

confidence: 99%

A secure electric energy management in smart home

Mbarek

Meddeb

Jaballah

et al. 2017

Int J Communication

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Summary We formulate and study an intelligent and secure house electricity system on the basis of the Internet of Things. The security of sensitive data collected and transmitted by sensor nodes installed in home appliances and household electrical devices is critical, since the transmitted data can be easily manipulated by different types of attacks. The confidentiality and integrity of household electrical devices information must be assured to insure appropriate and timely response. Providing a secure aggregation mechanism is thus very essential to protect the integrity and the privacy of data aggregation. In this paper, we propose a secure data aggregation scheme that exploits compressed sensing (CS) to reduce the communication overhead of collected electrical power measurement. Then, the data will be encrypted by each sensor node after the compressing phase, and a cryptography hash algorithm is used to ensure data integrity. Finally, we apply an aggregation function for data priorities and then send the data for diagnosis. Then, we will present simulation results for the evaluation of the proposed electric energy management system.

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“…The open problem, in the contemporary transition period, is to adopt those new home automation technologies into already built and furnished houses, minimizing the annoyance during the installation phase. For this reason, the power management is a crucial factor, and despite the vastness of smart homes literature [19][20][21][22][23][24][25], it is still challenging to state that the batteries life issue has been solved.…”

Section: Introductionmentioning

confidence: 99%

Wireless Sensor Networks for Smart Homes: A Fuzzy-Based Solution for an Energy-Effective Duty Cycle

Pau

Salerno

2019

Electronics

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This paper introduces a fuzzy-based method that, according to the ratio of Throughput to Workload and the battery level, manages the sleeping time of devices in Wireless Sensor Networks (WSNs) for smart homes. The purpose of this work is a system that can be executed on off-the-shelf hardware and offers enhanced performance confronted with other approaches. The challenge here is to achieve a practical method that reaches the target while bypassing complex and computationally expensive solutions, which would diminish the possible applicability of the method in real scenarios. The retrieved results prove that the proposed approach outperforms other solutions, significantly prolonging the life of battery-powered wireless devices with also satisfactory values of the ratio Throughput to Workload. Besides, a proof-of-concept implementation on off-the-shelf devices confirms that the proposed method does not expect powerful hardware and can be surely implemented on a low-cost device.

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Smart home energy management system including renewable energy based on ZigBee and PLC

Cited by 332 publications

References 10 publications

Optimal Operation Method for Distribution Systems Considering Distributed Generators Imparted with Reactive Power Incentive

Optimal Operation Method for Distribution Systems Considering Distributed Generators Imparted with Reactive Power Incentive

A secure electric energy management in smart home

Wireless Sensor Networks for Smart Homes: A Fuzzy-Based Solution for an Energy-Effective Duty Cycle

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