853 resultados para Energy consumption survey
Resumo:
This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.
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Objective. To assess the effectiveness of workplace interventions in improving physical activity. Data Source. EBSCO research database (and all subdatabases). Study Inclusion and Exclusion Criteria. Articles were published from 2000 to 2010 in English, had appropriate designs, and measured employees' physical activity, energy consumption, and/or body mass index (BMI) as primary outcomes. Articles that did not meet the inclusion criteria were excluded. Data Extraction. Data extracted included study design, study population, duration, intervention activities, outcomes, and results. Data Synthesis. Data were synthesized into one table. Results of each relevant outcome including p values were combined. Results. Twelve (60%) of 20 selected interventions reported an improvement in physical activity level, steps, or BMI, and there was one slowed step reduction in the intervention group. Among these, 10 were less than 6 months in duration; 9 used pedometers; 6 applied Internet-based approaches; and 5 included activities targeting social and environmental levels. Seven of 8 interventions with pre-posttest and quasi-experimental controlled design showed improvement on at least one outcome. However, 7 of 12 randomized controlled trials (RCTs) did not prove effective in any outcome. Conclusion. Interventions that had less rigorous research designs, used pedometers, applied Internet-based approaches, and included activities at social and environmental levels were more likely to report being effective than those without these characteristics.
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The ISSCT Engineering Workshop 2008 in Brazil was well attended with 62 participants including 39 overseas visitors from 15 countries. The workshop addressed the theme Design, manufacturing and maintenance of sugar mill equipment. From the technical sessions, the following conclusions were drawn: • Several speakers articulated a shared vision of the future of the Brazilian sugar industry. This shared vision gives considerable confidence that the vision can become a reality. • There is an increased focus on energy products. As a result, the reduction of factory energy consumption in order to maximise the energy available for products is also a focus. • New equipment and products are being developed with reduced power consumption, lower capital and maintenance costs, and better performance. • Methods presented for reducing maintenance costs included the use of a maintenance management system, condition monitoring and material selection. The workshop was held in conjunction with Piracicaba’s annual SIMTEC exhibition for the sugar and alcohol industries that provides a forum for technical presentations and discussion, and showcases products and services from manufacturers and service providers. In return for holding the workshop in conjunction with SIMTEC, SIMTEC provided sponsorship for the workshop, including paying travel and accommodation costs for two invited speakers, and organisation for the workshop. The ISSCT and SIMTEC technical programs were arranged so that their technical sessions did not clash, and the ISSCT program was extended a day to provide an opportunity for ISSCT participants to attend the SIMTEC exhibition. Informal feedback from workshop participants suggested that the arrangement between ISSCT and SIMTEC worked well. Site visits to two manufacturing facilities and two sugar mills were arranged as part of the workshop.
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In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.
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An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.
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Microalgae dewatering is a major obstruction to industrial-scale processing of microalgae for biofuel prodn. The dil. nature of harvested microalgal cultures creates a huge operational cost during dewatering, thereby, rendering algae-based fuels less economically attractive. Currently there is no superior method of dewatering microalgae. A technique that may result in a greater algal biomass may have drawbacks such as a high capital cost or high energy consumption. The choice of which harvesting technique to apply will depend on the species of microalgae and the final product desired. Algal properties such as a large cell size and the capability of the microalgae to autoflocculate can simplify the dewatering process. This article reviews and addresses the various technologies currently used for dewatering microalgal cultures along with a comparative study of the performances of the different technologies.
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Non-thermal plasma (NTP) is a promising candidate for controlling engine exhaust emissions. Plasma is known as the fourth state of matter, where both electrons and positive ions co-exist. Both gaseous and particle emissions of diesel exhaust undergo chemical changes when they are exposed to plasma. In this project diesel particulate matter (DPM) mitigation from the actual diesel exhaust by using NTP technology has been studied. The effect of plasma, not only on PM mass but also on PM size distribution, physico-chemical structure of PM and PM removal mechanisms, has been investigated. It was found that NTP technology can significantly reduce both PM mass and number. However, under some circumstances particles can be formed by nucleation. Energy required to create the plasma with the current technology is higher than the benchmark set by the commonly used by the automotive industry. Further research will enable the mechanism of particle creation and energy consumption to be optimised.
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Drying has been extensively used as a food preservation procedure. The longer life attained by drying is however accompanied by huge energy consumption and deterioration of quality. Moisture diffusivity is an important factor that is considered essential to understand for design, analysis, and optimization of drying processes for food and other materials. Without an accurate value of moisture diffusivity, drying kinetics, energy consumption, quality attributes such as shrinkage, texture, and microstructure cannot be predicted properly. However, moisture diffusivities differ due to variation of composition and microstructure of foodstuff and drying variables. For a particular food, it changes with many factors including moisture content, water holding capacity, process variables and physiochemical attributes of food. Published information on moisture diffusivities of banana is inadequate and sometimes inconsistent due to lack of precise repeatable analysis techniques. In this work, the effective moisture diffusivity of banana was determined by Thermogravimetric Analysis (TGA), which ensures precise measurements and reproduction of experiments. A TGA Q500 V20.13 Build 39 was deployed to obtain the drying curve of the food material. It was found that effective moisture diffusivity ranged from 6.63 x10-10 to 1.03 x10-9 and 1.34 x10-10 to 6.60 x10-10 for isothermal at 70 0C and non-isothermal process respectively.These values are consistent with the value of moisture diffusivity found in the literature.
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The dynamic, chaotic, intimate and social nature of family life presents many challenges when designing interactive systems in the household space. This paper presents findings from a whole-of-family approach to studying the use of an energy awareness and management system called “Ecosphere”. Using a novel methodology of inviting 12 families to create their own self-authored videos documenting their energy use, we report on the family dynamics and nuances of family life that shape and affect this use. Our findings suggest that the momentum of existing family dynamics in many cases obstructs behaviour change and renders some family members unaware of energy consumption despite the presence of an energy monitor display in the house. The implication for eco-feedback design is that it needs to recognise and respond to the kinds of family relations into which the system is embedded. In response, we suggest alternative ways of sharing energy-related information among families and incentivising engagement among teenagers.
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This paper presents a novel path planning method for minimizing the energy consumption of an autonomous underwater vehicle subjected to time varying ocean disturbances and forecast model uncertainty. The algorithm determines 4-Dimensional path candidates using Nonlinear Robust Model Predictive Control (NRMPC) and solutions optimised using A*-like algorithms. Vehicle performance limits are incorporated into the algorithm with disturbances represented as spatial and temporally varying ocean currents with a bounded uncertainty in their predictions. The proposed algorithm is demonstrated through simulations using a 4-Dimensional, spatially distributed time-series predictive ocean current model. Results show the combined NRMPC and A* approach is capable of generating energy-efficient paths which are resistant to both dynamic disturbances and ocean model uncertainty.
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This thesis presents the design process and the prototyping of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture. Achieved by the joint operation of multiple autonomous vehicles to improve energy consumption, reduce labour, and increase efficiency in the application of inputs for the management of crops. The Small Robotic Farm Vehicle (SRFV) is a lightweight and energy efficient robotic vehicle with a configurable, modular design. It is capable of undertaking a range of agricultural tasks, including fertilising and weed management through mechanical intervention and precision spraying, whilst being more than an order of magnitude lower in weight than existing broadacre agricultural equipment.
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Biophilic urbanism, or urban design that reflects humanity’s innate need for nature, stands to make significant contributions to a range of national, state and local government policies related to climate change mitigation and adaptation, by investigating ways in which nature can be integrated into, around and on top of buildings. Potential benefits of such design include reducing the heat island effect, reducing energy consumption for thermal control, enhancing urban biodiversity, improving well being and productivity, improving water cycle management, and assisting in the response to growing needs for densification and revitalisation of cities. This report will give an overview of the concept of biophilia and consider enablers and disablers to its application to urban planning and design. The paper will present findings from stakeholder engagement and a series of detailed case studies, related to a consideration of the economics of the use of biophilic elements (direct and indirect).
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Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This project investigates these factors and focuses on the performance of and interaction between: green design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. This paper suggests six areas of strategic research that are needed to understand how conditions can be created to support productivity in green buildings, and deliver significant energy consumption reductions.
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Biophilic urbanism, or urban design which refl ects human’s innate need for nature in and around and on top of our buildings, stands to make signifi cant contributions to a range of national, state and local government policies related to climate change mitigation and adaptation. Potential benefi ts include reducing the heat island effect, reducing energy consumption for thermal control, enhancing urban biodiversity, improving well being and productivity, improving water cycle management, and assisting in the response to growing needs for densifi cation and revitalisation of cities. This discussion paper will give an overview of the concept of biophilia and consider enablers and disablers to its application to urban planning and design. The paper will present findings from stakeholder engagement related to a consideration of the economics of the use of biophilic elements (direct and indirect). The paper outlines eight strategic areas being considered in the project, including how a ‘daily minimum dose’ of nature can be received through biophilic elements, and how planning and policy can underpin effective biophilic urbanism.
Resumo:
The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.