Power consumption scheduling for residential buildings

Mangiatordi, Federica; Pallotti, Emiliano; Vecchio, Paolo del; Leccese, Fabio

doi:10.1109/eeeic.2012.6221508

Cited by 36 publications

(18 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The work of Mangiatordi et al investigates the use of the paradigm of swarm intelligence to scheduling the operation of household appliances in order to smooth the variation and reduce the peak‐to‐average ratio of total electricity demand at home. The proposed load‐scheduling model for smart home energy management aims at reducing the gap between the daily average electrical power and the peak load demand.…”

Section: Related Workmentioning

confidence: 99%

“…However, such sensors are limited in terms of scalability and are also difficult to install and maintain. As an alternative, recent works present solutions to control and monitor buildings using wireless sensor and actuator networks (WSANs). Such WSANs are composed of low‐cost devices with limited energy and computing power, equipped with sensing capabilities and wireless links and also encompassing actuator devices, responsible for performing tasks that may actively affect the physical environment .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A control and decision system for smart buildings using wireless sensor and actuator networks

Farias

Soares

Pìrmez

et al. 2014

Trans. Emerging Tel. Tech.

View full text Add to dashboard Cite

A research field that makes use of information and communication technologies to provide solutions to contemporaneous environmental challenges such as greenhouse gas emissions and global warming is the 'smart building' field. The use of wireless sensor and actuator networks (WSANs) emerges as an alternative for the use of information and communication technologies in the smart buildings. However, most of smart building applications make use of centralised architectures with sensing nodes transmitting messages to a base station wherein, effectively, the control and decision processes happen. In this context, we present CONDE, a decentralised CONtrol and DEcision-making system for smart building applications using WSANs. CONDE main contributions are as follows: (i) the decentralisation of the control and decision-making processes among WSAN nodes, saving energy of both the WSAN and the building; (ii) the integration of applications through sharing the sensed data and chaining decisions between applications within the WSAN, also saving energy of both the WSAN and the building; and (iii) the provision of a consensual multilevel decision that takes into account the cooperation among nodes to have a broader view of the monitored building. Performed experiments have shown CONDE gains in terms of the following: (i) response time; (ii) system efficiency; and (iii) energy savings from the network and the building.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A control and decision system for smart buildings using wireless sensor and actuator networks

Farias

Soares

Pìrmez

et al. 2014

Trans. Emerging Tel. Tech.

View full text Add to dashboard Cite

show abstract

“…As described above, lighting energy accounts for the greatest portion in the waste of energy. Hence, it is likely that the proper control of lighting energy would bring the biggest energy-saving effects 13 . For the efficient control of luminaires, a variety of information is needed.…”

Section: Potential Of Lighting Energy Savingsmentioning

confidence: 99%

Lighting Scheduling for Energy Saving in Smart House Based on Life Log Data

Yang

Lee

2014

Procedia Environmental Sciences

View full text Add to dashboard Cite

Efficient energy consumption in homes is one of key elements of sustainable healthy residential living. This thesis deals with decision-making method and procedure for home energy use scheduling designed to boost energy efficiency. Home energy use scheduling is a complex task that combines various data for decision-making. To carry out the task, this study used the idea of utilizing 'life log data,' which is recording and storing daily routines. Life log data is recorded and stored in a metrics developed through a literature study and it contains 5W1H data (Who, When, Where, What, Why, How). Through the 5W1H data, lifestyle of residents can be analysed to determine the right services for them. The processes are as follows; House environments, Service determined, Similarity analysis, Data filtering, Smart service. As the life log data is developed by human's experience, this system makes it possible for one to one personalized service. And it can be possible personal energy savings at home. One of the key merits in relation to the utilization of the life-log data is that it can provide a customized one-on-one service reflecting the behavioural patterns and the lifestyles of a resident.

show abstract

“…For instance, in [38], the PSO is introduced for wind turbine converters, in [39,40] for photovoltaic systems, in [41] for neural networks training, in [42] for DC/DC converter, in [43][44][45] for energy management, in [46] for Unmanned Aerial Vehicle (UAV) management and control, in [47] for clustering, and so on. The results shown in all these works confirm that an optimization through the PSO can lead to valuable advantages regarding the performance of approaches based on a fuzzy controller.…”

Section: Introductionmentioning

confidence: 99%

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

2017

View full text Add to dashboard Cite

Abstract:Energy efficiency is a fundamental requirement for a wireless protocol to be suitable for use within the Internet of Things. New technologies are emerging aiming at an energy-efficient communication. Among them, Bluetooth Low Energy is an appealing solution. Recently, the specifications of Bluetooth 5 have been presented with the purpose to offer significant enhancements compared to the earlier versions of the protocol. Bluetooth 5 comes with new communication modes that differ in range, speed, and energy consumption. This paper proposes a fuzzy-based solution to cope with the selection of the communication mode, among those introduced with Bluetooth 5, that allows the best energy efficiency. This communication mode, used by mobile devices, is dynamically regulated by varying the transmission power, returned as the output of a Fuzzy Logic Controller (FLC). A Particle Swarm Optimization (PSO) algorithm is presented to achieve the optimal parameters of the proposed FLC, i.e., optimizing the triangular membership functions, by varying their range, to reach the best results concerning the battery life of mobile devices. The proposed FLC is based on triangular membership functions because they represent a good trade-off between computation cost and efficiency. The paper presents a detailed description of the FLC design, a logical analysis of the PSO algorithm for the derivation of best performance conditions values, and experimental assessments, obtained through testbed scenarios.

show abstract

Power consumption scheduling for residential buildings

Cited by 36 publications

References 8 publications

A control and decision system for smart buildings using wireless sensor and actuator networks

A control and decision system for smart buildings using wireless sensor and actuator networks

Lighting Scheduling for Energy Saving in Smart House Based on Life Log Data

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

Contact Info

Product

Resources

About