Socially Intelligent Interfaces for Increased Energy Awareness in the Home

Karlgren, Jussi; Fahlén, Lennart E.; Wallberg, Anders; Hansson, Pär; Ståhl, Olov; Söderberg, Jonas; Åkesson, Karl-Petter

doi:10.1007/978-3-540-78731-0_17

Cited by 14 publications

(9 citation statements)

References 8 publications

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“…Figure 1 illustrates the short-term power management of appliances, where energy consumption peak is avoided [50]. Shift of energy usage load for avoiding peak times for reducing the need for high production capacities has been identified as one of the keys for energy efficiency [51].…”

Section: Load Managementmentioning

confidence: 99%

Towards an Agent Based Framework for Modelling Smart Self-Sustainable Systems

Tomičić¹,

Schatten²

2015

: Interdiscip. Descr. Complex Syst.

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Self-sustainability is a property of a system; a system is considered to be self-sustainable if it can sustain itself without external support in an observed period of time. If this property is mapped to a human settlement in context of resources (water, energy, food, etc.), it would describe a human settlement which is independent of external resources (like the national electrical grid or a central water distribution system), where such external resources are either not available, or not desirable.This article contributes to presenting the state-of-the-art overview of self-sustainability-related research. While self-sustainability as in the above described form was not a direct subject of research, there are several fields which are either related to, or could be of significant value to the self-sustainability research in this context. The extensive literature overview also showed no frameworks for modeling self-sustainable systems in the context of human settlements. Herein a motivation for using agent-based modeling and simulation techniques will be given.

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Section: Load Managementmentioning

confidence: 99%

Towards an Agent Based Framework for Modelling Smart Self-Sustainable Systems

Tomičić¹,

Schatten²

2015

: Interdiscip. Descr. Complex Syst.

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“…Another strand of research focuses on providing intelligent interfaces to increase awareness of energy usage and hence influence the householder's behaviour [10,11].…”

Section: Current Related Workmentioning

confidence: 99%

An Intelligent Energy Management System for Educational Buildings

Al-Daraiseh

Shah

El-Qawasmeh

2013

International Journal of Distributed Sensor Networks

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This paper proposes an intelligent model for real-time control of the hygrothermal behaviour in low energy buildings. Through the management of information related to internal and external conditions combined with the design and context data, the built network lead to assess the correct strategy for an adequate hygrothermal behaviour (choosing between active and passive systems for control of indoor air-quality). The expected benefits are a healthy environment, the stable performances of materials, the containment of maintenance costs, the reduction of the use of passive systems in order to cut CO2 emissions.

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“…Power management generally enables a computer to enter reduced power states such as standby or sleep mode. So far, the best known power management guidelines are those set by the U.S. Environmental Protection Agency (EPA) Energy Star program [4]. Desktop computers that meet EPA Energy Star guidelines power down to no more than 15 percent of maximum power usage while in sleep mode.…”

Section: Related Workmentioning

confidence: 99%

Location-Based Intelligent Power Generation and Management Algorithms for Physically Challenging Rural Areas

Olusegun¹,

Tan²

2013

LNSE

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Climatic change is one of the driving forcesbehind a new wave of energy management systems beingpracticed in different parts of the world today. Powergeneration and Management in disconnected rural villages ischallenging. The situation is even more challenging whenlandscape structures in such environment are irregular. Thispaper describes the implementation of two algorithms used inpower generation and management of rural energy supplies:Location-based Solar Energy Potential Prediction Algorithm(LOSEPPA) and Intelligent Fuzzy-controlled PowerGeneration and Management Algorithm (IFPGMA).LOSEPPA takes as input, the geographic latitude of thelocation to compute the solar irradiance factor. IFPGMAintelligently manages the utilization of the generated solarenergy. Geographic latitude plays an important role in theavailability of sufficient solar radiation as well as the state ofthe atmosphere. Therefore, the value of solar irradiance factorserves as a guide to the state of the atmosphere in terms ofdegree of cloud cover, temperature, humidity and landscapestructure; which determines the feasibility of the solar energyimplementation. With the solar irradiance factor, solar panelcan be mounted along specific angle of inclination to the sun.The implemented design is based on solar PV modulesarranged in array, integrated with rechargeable batteries andconverter models to drive solar energy generation for poweringnetworking equipments. The proposed system was simulatedusing Homer energy software, C++ and MATLAB-Simulink.Result show that the more irregular the landscape is, thelower the solar irradiance factor. Solar irradiance factor valueof 400 and above predicts well enough sunshine for solar PVimplementation. Set point values for batterycharging/discharging and the charge controller, maintainscircuit voltage supplies at 130V maximum and 2KWh/day at$0.735/KWh with an initial investment cost of $3,090 for thesolar implementation

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Socially Intelligent Interfaces for Increased Energy Awareness in the Home

Cited by 14 publications

References 8 publications

Towards an Agent Based Framework for Modelling Smart Self-Sustainable Systems

Towards an Agent Based Framework for Modelling Smart Self-Sustainable Systems

An Intelligent Energy Management System for Educational Buildings

Location-Based Intelligent Power Generation and Management Algorithms for Physically Challenging Rural Areas

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