Energy Awareness Displays: Designing a Prototype for Personalised Energy Consumption Feedback at the Workplace

2012 ◽  
Author(s):  
Dirk Borner ◽  
Marco Kalz ◽  
Marcus Specht
Keyword(s):  
Energy Consumption ◽  
Energy Awareness ◽  
Awareness Displays

scholarly journals A Survey of Communications and Networking Technologies for Energy Management in Buildings and Home Automation

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Aravind Kailas ◽  
Valentina Cecchi ◽  
Arindam Mukherjee
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Energy Management ◽  
Smart Grids ◽  
Energy Demand ◽  
Demand Curve ◽  
Future Research ◽  
Energy Awareness ◽  
Home Energy Management ◽  
Networking Technologies

With the exploding power consumption in private households and increasing environmental and regulatory restraints, the need to improve the overall efficiency of electrical networks has never been greater. That being said, the most efficient way to minimize the power consumption is by voluntary mitigation of home electric energy consumption, based on energy-awareness and automatic or manual reduction of standby power of idling home appliances. Deploying bi-directional smart meters and home energy management (HEM) agents that provision real-time usage monitoring and remote control, will enable HEM in “smart households.” Furthermore, the traditionally inelastic demand curve has began to change, and these emerging HEM technologies enable consumers (industrial to residential) to respond to the energy market behavior to reduce their consumption at peak prices, to supply reserves on a as-needed basis, and to reduce demand on the electric grid. Because the development of smart grid-related activities has resulted in an increased interest in demand response (DR) and demand side management (DSM) programs, this paper presents some popular DR and DSM initiatives that include planning, implementation and evaluation techniques for reducing energy consumption and peak electricity demand. The paper then focuses on reviewing and distinguishing the various state-of-the-art HEM control and networking technologies, and outlines directions for promoting the shift towards a society with low energy demand and low greenhouse gas emissions. The paper also surveys the existing software and hardware tools, platforms, and test beds for evaluating the performance of the information and communications technologies that are at the core of future smart grids. It is envisioned that this paper will inspire future research and design efforts in developing standardized and user-friendly smart energy monitoring systems that are suitable for wide scale deployment in homes.

scholarly journals A Proactive Energy-Awareness Based Traffic Routing in Tree Topology Wireless Sensor Networks Precluding Energy Holes Formation

2020 ◽  
Author(s):  
Mayada S. A. Mustafa ◽  
Borhanuddin M. Ali ◽  
Fadlee F. A. Rasid ◽  
Shaiful J. B. Hashim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Tree Topology ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Hole Formation ◽  
Energy Hole ◽  
Traffic Routing ◽  
Entire Network ◽  
Sink Hole

A single tree topology is a commonly employed topology for wireless sensor networks (WSN) to connect sensors to one or more remote gateways. However, its many-to-one traffic routing pattern imposes heavy burden on downstream nodes, as the same routes are repeatedly used for packet transfer, from one or more upstream branches. The challenge is how to choose the most optimal routing paths that minimizes energy consumption across the entire network. This paper proposes a proactive energy awareness-based many-to-one traffic routing scheme to alleviate the above said problem referred to as Energy Balance-Based Energy Hole Alleviation in tree topology (EBEHA-T). This protocol combines updated status of variations in energy consumption pattern around sink-hole zones and distribution of joint nodes among the trees. With this approach, EBEHA-T proactively prevents sink-hole formation instead of just a reactive response after they have occurred. Performance evaluation of EBEHA-T against benchmark method RaSMaLai shows increased energy saving across the entire network and a marked improvement in energy consumption balance in energy-hole zones. This precludes energy hole formation and the consequent network partitioning, leading to improved network lifetime beyond that of the RasMaLai. OMNET++ network simulation software has been used for the evaluation.

Energy Awareness Displays

2012 ◽  
pp. 471-476
Author(s):  
Dirk Börner ◽  
Jeroen Storm ◽  
Marco Kalz ◽  
Marcus Specht
Keyword(s):  
Energy Awareness ◽  
Awareness Displays

scholarly journals Toward green computing in wireless sensor networks: prediction-oriented distributed clustering for non-uniform node distribution

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Ajay Sikandar ◽  
Rajeev Agrawal ◽  
Manoj Kumar Tyagi ◽  
A. L. Narasimha Rao ◽  
Mukesh Prasad ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Wireless Communication ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Next Generation ◽  
Distributed Clustering ◽  
Set Up ◽  
Distributed Networking

Abstract Recently, researchers and practitioners in wireless sensor networks (WSNs) are focusing on energy-oriented communication and computing considering next-generation smaller and tiny wireless devices. The tiny sensor-enabled devices will be used for the purpose of sensing, computing, and wireless communication. The hundreds/thousands of WSNs sensors are used to monitor specific activities and report events via wireless communication. The tiny sensor-enabled devices are powered by smaller batteries to work independently in distributed environments resulting in limited maximum lifetime of the network constituted by these devices. Considering the non-uniform distribution of sensor-enabled devices in the next-generation mobility centric WSNs environments, energy consumption is imbalanced among the different sensors in the overall network environments. Toward this end, in this paper, a cluster-oriented routing protocol termed as prediction-oriented distributed clustering (PODC) mechanism is proposed for WSNs focusing on non-uniform sensor distribution in the network. A network model is presented, while categorizing PODC mechanism in two activities including setting cluster of nodes and the activity in the steady state. Further cluster set up activity is described while categorizing in four subcategories. The proposed protocol is compared with individual sensor energy awareness and distributed networking mode of clustering (EADC) and scheduled sensor activity-based individual sensor energy awareness and distributed networking mode of clustering (SA-ADC). The metrics including the overall lifetime of the network and nodes individual energy consumption in realistic next-generation WSNs environments are considered in the experimental evaluation. The results attest the reduced energy consumption centric benefits of the proposed framework PODC as compared to the literature. Therefore, the framework will be more applicable for the smart product development in the next-generation WSNs environments.

scholarly journals Virtual Machine Placement Algorithm for Both Energy-Awareness and SLA Violation Reduction in Cloud Data Centers

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Zhou Zhou ◽  
Zhigang Hu ◽  
Keqin Li
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Data Centers ◽  
High Energy ◽  
Energy Awareness ◽  
Cloud Data ◽  
Light Load ◽  
Sla Violation ◽  
Cloud Data Centers ◽  
Placement Algorithm

The problem of high energy consumption is becoming more and more serious due to the construction of large-scale cloud data centers. In order to reduce the energy consumption and SLA violation, a new virtual machine (VM) placement algorithm named ATEA (adaptive three-threshold energy-aware algorithm), which takes good use of the historical data from resource usage by VMs, is presented. In ATEA, according to the load handled, data center hosts are divided into four classes: hosts with little load, hosts with light load, hosts with moderate load, and hosts with heavy load. ATEA migrates VMs on heavily loaded or little-loaded hosts to lightly loaded hosts, while the VMs on lightly loaded and moderately loaded hosts remain unchanged. Then, on the basis of ATEA, two kinds of adaptive three-threshold algorithm and three kinds of VMs selection policies are proposed. Finally, we verify the effectiveness of the proposed algorithms by CloudSim toolkit utilizing real-world workload. The experimental results show that the proposed algorithms efficiently reduce energy consumption and SLA violation.

scholarly journals Adding Psychological Factor in the Model of Electricity Consumption in Office Building

2018 ◽  
Vol 8 (6) ◽  
pp. 4486 ◽  
Author(s):  
Meredita Susanty
Keyword(s):  
Energy Consumption ◽  
Electricity Consumption ◽  
Energy Awareness ◽  
Group Level ◽  
Energy Usage ◽  
Agent Based ◽  
Organizational Settings ◽  
Significant Difference ◽  
Comparative Feedback ◽  
The Impact

Researches indicate that energy behaviour is the key to energy conservation and suggest that comparative feedback on energy usage can generate savings in residential and organizational settings. In implementing comparative feedback in workplace, there are two different ways to disaggregate collective energy consumption and apportion it to building users; individual or group level. This research uses agent-based modelling and simulation to examine the impact of applying different approaches of energy data apportionment to change staff behaviour toward energy consumption reduction. A simulation model of energy consumption in workplace as a base model is a re-implementation and simplification from former research. Several psychological factors and decision-making mechanism are then being added as an extension. The model divides staffs into four energy awareness stereotypes based on motivation level. Sensitivity analysis suggests that motivation is an important factor in changing user‟s behaviour and the experiment results indicates greater potential for energy saving when energy usage is apportioned to group level. The significant difference of energy consumption level makes user with low and medium motivation should become the target of energy reduction campaign.

A multiobjective hybrid imperialist competitive algorithm for multirobot cooperative assembly line balancing problems with energy awareness

2018 ◽  
Vol 233 (9) ◽  
pp. 2991-3003 ◽  
Author(s):  
Bing-hai Zhou ◽  
Xue-yun Kang
Keyword(s):  
Energy Consumption ◽  
Assembly Line ◽  
Imperialist Competitive Algorithm ◽  
Hill Climbing ◽  
Robotic Assembly ◽  
Energy Awareness ◽  
Assembly Lines ◽  
Total Cost ◽  
Competitive Algorithm ◽  
Cooperative Assembly

The environmental and economic pressures caused by energy consumption arouse energy-saving consciousness of the manufacturing industry. In recent years, robots have been extensively used in assembly systems as called robotic assembly lines where the energy consumption is a major expense, particularly in the workstation with the multirobot cooperative assembly of multirobot. To deal with this problem, the paper presents a novel mathematical model with three objectives of minimizing the cycle time, the sum of energy consumption, and the total cost of robots of assembly lines. Due to the nondeterministic polynomial time nature of the considered problem, a multiobjective hybrid imperialist competitive algorithm with nondominated sorting strategy is developed, which uses a representation technique of three-level coding, i.e. the station level, the task level, and the robot level and proposes an original concept of workstation decision assignment matrix to identify the performed tasks by the same type of robots in a workstation. Furthermore, a late-acceptance hill-climbing algorithm is combined into the algorithm to improve the performance of the proposed algorithm. Finally, testing cases are designed to measure the performance of the proposed method by comparing with two other high-performing multiobjective methods. The computational and statistical results show that the proposed multiobjective hybrid imperialist competitive algorithm is conducive to improve the line efficiency, to reduce the sum of energy consumption, and to cut the total cost of robots in an assembly line effectively.

Identifying and Categorizing Opportunities for Design for Sustainable User Behavior

2014 ◽  
Author(s):  
Chathura Withanage ◽  
Rahul Ashok ◽  
Katja Hölttä-Otto ◽  
Kevin Otto
Keyword(s):  
Energy Consumption ◽  
Failure Modes ◽  
User Behavior ◽  
Energy Awareness ◽  
Daily Routine ◽  
World Population ◽  
Actual Behavior ◽  
Household Energy ◽  
Routine Manner ◽  
Sustainable Behavior

The constantly growing world population and depleting natural resources make promoting sustainable behavior of paramount importance. Household energy is a significant percent of global energy consumption. While there has been significant work in improving energy awareness, there remains opportunity in designing systems that help direct users toward more sustainable behavior. This is particularly true since user behavior, as influenced by attitudes, beliefs and preferences, is a main driver of the household energy consumption. In this paper, a method is presented to identify and categorize design for sustainable behavior opportunities as failure modes on unnecessary overconsumption. We do this by comparing actual behavior against the minimum necessary to complete the task. Any deviation from the energy minimum is a failure mode opportunity. We clarify when opportunities are suitable for design for sustainable behavior, and when opportunities require stronger intervention of product or process redesign. To do this, user behavior was analyzed in a living laboratory format. Subjects were asked to perform a simple daily cooking activity in two phases; first in their routine manner and subsequently by trying to reduce energy consumption. In addition to recorded data on energy consumed, the users were interviewed on each user activity to understand which activities people were aware of means to reduce energy and in which they were not. The overall results show that all participants were able to reduce their energy consumption significantly when asked to do so, but these energy reducing behaviors were often ignored and not part of their daily routine. Based on this analysis, we identify opportunities where improving energy awareness is the issue, and other opportunities where more difficult sustainable design of the product or the process is needed since users are already aware but choose not to bother with reducing consumption.

scholarly journals A fuzzy rule-based system to predict energy consumption of genetic programming algorithms

2018 ◽  
Vol 15 (3) ◽  
pp. 635-654 ◽  
Author(s):  
Josefa Álvarez ◽  
Franciso Chávez ◽  
Pedro Castillo ◽  
Juan García ◽  
Francisco Rodriguez ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Evolutionary Algorithms ◽  
Genetic Programming ◽  
Fuzzy Rule ◽  
Energy Awareness ◽  
Environmentally Conscious ◽  
Rule Based ◽  
Rule Based System ◽  
Proposed Model ◽  
Programming Algorithms

In recent years, the energy-awareness has become one of the most interesting areas in our environmentally conscious society. Algorithm designers have been part of this, particularly when dealing with networked devices and, mainly, when handheld ones are involved. Although studies in this area has increased, not many of them have focused on Evolutionary Algorithms. To the best of our knowledge, few attempts have been performed before for modeling their energy consumption considering different execution devices. In this work, we propose a fuzzy rulebased system to predict energy comsumption of a kind of Evolutionary Algorithm, Genetic Prohramming, given the device in wich it will be executed, its main parameters, and a measurement of the difficulty of the problem addressed. Experimental results performed show that the proposed model can predict energy consumption with very low error values.

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