Home energy management based on Bayesian network considering resident convenience

Shoji, Tomoaki; Hirohashi, Wataru; Fujimoto, Yu; Hayashi, Yasuhiro

doi:10.1109/pmaps.2014.6960597

Cited by 16 publications

(12 citation statements)

References 4 publications

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Section: N L Vijaykumarmentioning

confidence: 99%

“…One method adapts the Bayesian Network (BN) to control power appliances that are designed for comfort [15].…”

Section: Related Literaturementioning

confidence: 99%

“…3, September 2017 Other solutions of this kind are used to control and optimize power consumption. One method adapts the Bayesian Network (BN) to control power appliances that are designed for comfort [15].This network makes a probabilistic relationship between the states of the equipment and the residential environment.Journal of Microwaves, Optoelectronics and Electromagnetic Applications, Vol. 16, No.…”

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confidence: 99%

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SmartCoM: Smart Consumption Management Architecture for Providing a User-Friendly Smart Home based on Metering and Computational Intelligence

Oliveira

Alfaia

Souto

et al. 2017

J. Microw. Optoelectron. Electromagn. Appl.

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Abstract-With advances in information technology for health and wellness, Smart Home-based solution providers using Internet of Things (IoT) technologies, have increased in importance and become accepted as an alternative means of saving energy when based on Home Energy Management Systems (HEMS). This paper defines a modern architecture (SmartCoM), which is implemented to monitor and manage residential dwellings by using IoT technologies. This involves setting out the parameters that can make interoperability possible between measurement and management , and the layers of data communication, which are the features necessary for the hardware required for monitoring and measurement. In addition, an interface is defined by a middleware layer to integrate the management of external installations and the visualization of data by means of a cloud service. The SmartCoM end-to-end architecture is defined in detail from the standpoint of the consumer and optimization strategies are employed for both the end customer and the utility. The main advantages of using SmartCoM were confirmed by the numerical results obtained from the proposed architecture. This paper ends by showing the current position of SmartCoM as well as suggesting further stages for this line of research.Index Terms-device software platforms, Internet of Things, middleware, Smart Home. I. INTRODUCTIONIn recent years, the panorama of the power systems has been subject to change following the introduction of new business models, for example, electric power distribution. These new models enable consumers to be actively involved on the basis of Smart Grid experiences. This participation makes the scenario more complex with respect to services since it raises serious challenges -for example, when integrating, software and hardware features. This is because the power systems and power companies operate in heterogeneous environments which is an essential strategic factor in ensuring a certain degree of safety (an inherent feature of the electricity sector). As well as this, there is also a need to include services that can outperform those of the traditional electricity networks. Belém, Pará, Brazil, rodrigo.alfaia@itec.ufpa.br, anderson.souto@itec.ufpa.br, marcelino@ufpa.br, rfrances@ufpa.br N. L. VijaykumarNational Institute for Space Research (INPE), São José dos Campos, São Paulo, Brazil, ZIP: 12227-010, Email: vijay.nl@inpe.br Journal of Microwaves, Optoelectronics and Electromagnetic Applications, Vol. 16, No. 3, September 2017 In general, Smart Grid can be regarded as a network that can manage electrical devices in several domains, and provide efficiency, reliability, safety and quality of services. It has a set of seven interconnected domains [2]. The first four (large-scale generation, transmission, distribution and end consumers or customers) are responsible for generation, transmission and distribution. These domains must ensure bi-directional communication between the customers and Advanced Metering Infrastructure (AMI) to provide a "full...

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Section: N L Vijaykumarmentioning

confidence: 99%

“…One method adapts the Bayesian Network (BN) to control power appliances that are designed for comfort [15].…”

Section: Related Literaturementioning

confidence: 99%

mentioning

confidence: 99%

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SmartCoM: Smart Consumption Management Architecture for Providing a User-Friendly Smart Home based on Metering and Computational Intelligence

Oliveira

Alfaia

Souto

et al. 2017

J. Microw. Optoelectron. Electromagn. Appl.

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“…In recent years, a special interest is given to the technologies designed to support natural resource consumption behavioural change such as efficient household water use (e.g. [16] [17]). Thanks to the advancement of digital sensors, researchers and companies are developing smart metering systems that can collect real life water consumption data and present to users in different visualised formats.…”

Section: Introductionmentioning

confidence: 99%

A Social-Centred Gamification Approach to Improve Household Water Use Efficiency

Wang

Capiluppi

2015

2015 7th International Conference on Games and Virtual Worlds for Serious Applications (VS-Games)

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Abstract-The research community is showing a growing interest in gamification and there are works showing the usefulness of gamification in different problem domains. Recently, a special interest has been given to the gamification design on systems addressing natural resource consumption issues such as to encourage efficient household water consumption. Despite the potential benefits, the gamification design method for such system is not conclusive. In this paper, we proposed a social-centred gamification approach to improve household water use efficiency. The approach firstly identified the water use related social network activities based upon existing popular social network activities. The approach then gamified each identified activity in terms of traditional instruments for improving water use efficiency and gamification rewards. The approach also used a set of indicators to explicitly detect and monitor both online social network activities and offline water use activities. With this approach the gamification effectiveness can be better traced and evaluated.

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“…We perform numerical simulations to demonstrate the effectiveness of our proposed framework corresponding to DR signal. This paper is an expanded version of papers presented at PMAPS2014 [8] and ICEE2014. [9] This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

Personalized Energy Management Systems for Home Appliances Based on Bayesian Networks

Shoji

Hirohashi

Fujimoto

et al. 2015

Journal of International Council on Electrical Engineering

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In Japan, the electricity consumption of household domestic appliances is increasing. The introduction of the demand response (DR) framework will promote electricity consumption reductions in the household sector by limiting electricity usage and by regulating the price of electricity. Because the appropriate operation patterns differ for each user under the DR programme, a home energy management system (HEMS) will play an important role by considering the priority of various home appliances and by appropriately modifying appliance operations to minimize the impact on a user's lifestyle. In this study, HEMS based on the Bayesian network is proposed; the system will learn the behaviour of a user and prioritize the operation of home appliances under restrictions on electricity consumption.

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Home energy management based on Bayesian network considering resident convenience

Cited by 16 publications

References 4 publications

SmartCoM: Smart Consumption Management Architecture for Providing a User-Friendly Smart Home based on Metering and Computational Intelligence

SmartCoM: Smart Consumption Management Architecture for Providing a User-Friendly Smart Home based on Metering and Computational Intelligence

A Social-Centred Gamification Approach to Improve Household Water Use Efficiency

Personalized Energy Management Systems for Home Appliances Based on Bayesian Networks

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