86 resultados para Electrical energy consumption
Resumo:
Growing demand for urban built spaces has resulted in unprecedented exponential rise in production and consumption of building materials in construction. Production of materials requires significant energy and contributes to pollution and green house gas (GHG) emissions. Efforts aimed at reducing energy consumption and pollution involved with the production of materials fundamentally requires their quantification. Embodied energy (EE) of building materials comprises the total energy expenditure involved in the material production including all upstream processes such as raw material extraction and transportation. The current paper deals with EE of a few common building materials consumed in bulk in Indian construction industry. These values have been assessed based on actual industrial survey data. Current studies on EE of building materials lack agreement primarily with regard to method of assessment and energy supply assumptions (whether expressed in terms of end use energy or primary energy). The current paper examines the suitability of two basic methods; process analysis and input-output method and identifies process analysis as appropriate for EE assessment in the Indian context. A comparison of EE values of building materials in terms of the two energy supply assumptions has also been carried out to investigate the associated discrepancy. The results revealed significant difference in EE of materials whose production involves significant electrical energy expenditure relative to thermal energy use. (C) 2014 Elsevier B.V. All rights reserved.
Resumo:
In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.
Quick, Decentralized, Energy-Efficient One-Shot Max Function Computation Using Timer-Based Selection
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In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-based, one-shot max function computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in a centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two contention stages. First, the nodes in each cluster contend with each other using the timer scheme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the highest sensor reading in their cluster to the fusion node. One new challenge is that the use of the timer scheme leads to collisions, which can make the algorithm fail. We optimize the algorithm to minimize the average time required to determine the maximum subject to a constraint on the probability that it fails to find the maximum. TMC significantly lowers average function computation time, average number of transmissions, and average energy consumption compared to approaches proposed in the literature.
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Minimizing energy consumption is of utmost importance in an energy starved system with relaxed performance requirements. This brief presents a digital energy sensing method that requires neither a constant voltage reference nor a time reference. An energy minimizing loop uses this to find the minimum energy point and sets the supply voltage between 0.2 and 0.5 V. Energy savings up to 1275% over existing minimum energy tracking techniques in the literature is achieved.
Resumo:
An integrated approach to energy planning, when applied to large hydroelectric projects, requires that the energy-opportunity cost of the land submerged under the reservoir be incorporated into the planning methodology. Biomass energy lost from the submerged land has to be compared to the electrical energy generated, for which we develop four alternative formulations of the net-energy function. The design problem is posed as an LP problem and is solved for two sites in India. Our results show that the proposed designs may not be viable in net-energy terms, whereas a marginal reduction in the generation capacity could lead to an optimal design that gives substantial savings in the submerged area. Allowing seasonal variations in the hydroelectric generation capacity also reduces the reservoir size. A mixed hydro-wood generation system is then examined and is found to be viable.
Resumo:
This paper attempts to evaluate the energy inputs needed to produce rural buildings. Based on a survey, a comparison is carried out of traditional and innovative technologies with reference to their energy consumption. Some basic data regarding energies in transportation are also presented. The implications of this analysis for development objectives is discussed.
Resumo:
Provision of modern energy services for cooking (with gaseous fuels)and lighting (with electricity) is an essential component of any policy aiming to address health, education or welfare issues; yet it gets little attention from policy-makers. Secure, adequate, low-cost energy of quality and convenience is core to the delivery of these services. The present study analyses the energy consumption pattern of Indian domestic sector and examines the urban-rural divide and income energy linkage. A comprehensive analysis is done to estimate the cost for providing modern energy services to everyone by 2030. A public-private partnership-driven business model, with entrepreneurship at the core, is developed with institutional, financing and pricing mechanisms for diffusion of energy services. This approach, termed as EMPOWERS (entrepreneurship model for provision of wholesome energy-related basic services), if adopted, can facilitate large-scale dissemination of energy-efficient and renewable technologies like small-scale biogas/biofuel plants, and distributed power generation technologies to provide clean, safe, reliable and sustainable energy to rural households and urban poor. It is expected to integrate the processes of market transformation and entrepreneurship development involving government, NGOs, financial institutions and community groups as stakeholders. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Traditionally, an instruction decoder is designed as a monolithic structure that inhibit the leakage energy optimization. In this paper, we consider a split instruction decoder that enable the leakage energy optimization. We also propose a compiler scheduling algorithm that exploits instruction slack to increase the simultaneous active and idle duration in instruction decoder. The proposed compiler-assisted scheme obtains a further 14.5% reduction of energy consumption of instruction decoder over a hardware-only scheme for a VLIW architecture. The benefits are 17.3% and 18.7% in the context of a 2-clustered and a 4-clustered VLIW architecture respectively.
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Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving clock speed, reducing energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long global wires which leads to delay in execution and significantly high energy consumption.In this paper, we propose a new instruction scheduling algorithm that exploits scheduling slacks of instructions and communication slacks of data values together to achieve better energy-performance trade-offs for clustered architectures with heterogeneous interconnect. Our instruction scheduling algorithm achieves 35% and 40% reduction in communication energy, whereas the overall energy-delay product improves by 4.5% and 6.5% respectively for 2 cluster and 4 cluster machines with marginal increase (1.6% and 1.1%) in execution time. Our test bed uses the Trimaran compiler infrastructure.
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A common and practical paradigm in cooperative communication systems is the use of a dynamically selected `best' relay to decode and forward information from a source to a destination. Such systems use two phases - a relay selection phase, in which the system uses transmission time and energy to select the best relay, and a data transmission phase, in which it uses the spatial diversity benefits of selection to transmit data. In this paper, we derive closed-form expressions for the overall throughput and energy consumption, and study the time and energy trade-off between the selection and data transmission phases. To this end, we analyze a baseline non-adaptive system and several adaptive systems that adapt the selection phase, relay transmission power, or transmission time. Our results show that while selection yields significant benefits, the selection phase's time and energy overhead can be significant. In fact, at the optimal point, the selection can be far from perfect, and depends on the number of relays and the mode of adaptation. The results also provide guidelines about the optimal system operating point for different modes of adaptation. The analysis also sheds new insights on the fast splitting-based algorithm considered in this paper for relay selection.
Resumo:
In the recent years. India has emerged as one of the fast growing economies of the world necessitating equally rapid increase in modern energy consumption. With an imminent global climate change threat, India will have difficulties in continuing with this rising energy use levels towards achieving high economic growth. It will have to follow an energy-efficient pathway in attaining this goal. In this context, an attempt is made to present India's achievements on the energy efficiency front by tracing the evolution of policies and their impacts. The results indicate that India has made substantial progress in improving energy efficiency which is evident from the reductions achieved in energy intensities of GDP to the tune of 88% during 1980-2007. Similar reductions have been observed both with respect to overall Indian economy and the major sectors of the economy. In terms of energy intensity of GDP, India occupies a relatively high position of nine among the top 30 energy consuming countries of the world. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Energy is a major constituent of a small-scale industry such as grain mills. Based on a sample survey of several mills spread over Karnataka, a state in India, a number of energy analyses were conducted primarily to establish relationships and secondarily to look at them in more detail. Initially specific energy consumption (SEC) was computed for all industries so as to compare their efficiencies of energy use. A wide disparity exists in SEC among various grain mills. In order to understand the disparities better, regression analyses were performed on the variables energy and production, SEC and production, and energy/SEC with percentage production capacity utilization. The studies show that smaller range industries have lower capacity utilization. This paper also examines the energy savings possible by shifting industries from the lower production ranges to the next higher range (thereby utilizing installed production capacity optimally). This leads to an overall energy capacity saving of 23.12% for the foodgrain sector and 18.67% for the paddy dehusking subgroup. If this is extrapolated to the whole state, we obtain a saving of 55 million kWh.
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Relentless CMOS scaling coupled with lower design tolerances is making ICs increasingly susceptible to wear-out related permanent faults and transient faults, necessitating on-chip fault tolerance in future chip microprocessors (CMPs). In this paper we introduce a new energy-efficient fault-tolerant CMP architecture known as Redundant Execution using Critical Value Forwarding (RECVF). RECVF is based on two observations: (i) forwarding critical instruction results from the leading to the trailing core enables the latter to execute faster, and (ii) this speedup can be exploited to reduce energy consumption by operating the trailing core at a lower voltage-frequency level. Our evaluation shows that RECVF consumes 37% less energy than conventional dual modular redundant (DMR) execution of a program. It consumes only 1.26 times the energy of a non-fault-tolerant baseline and has a performance overhead of just 1.2%.
Resumo:
The frequency and temperature dependence of the dielectric constant and the electrical conductivity of the transparent glasses in the composition 0.5Cs(2)O-0.5Li(2)O-3B(2)O(3) (CLBO) were investigated in the 100 Hz - 10 MHz frequency range. The dielectric constant for the as-quenched glass increased with increasing temperature, exhibiting anomalies in the vicinity of the glass transition and crystallization temperatures. The temperature coefficient of dielectric constant was estimated (35 +/- 2 ppm. K-1) using Havinga's formula. The dielectric loss at 313 K is 0.005 +/- 0.0005 at all the frequencies understudy. The activation energy associated with the electrical relaxation determined from the electric modulus spectra was found to be 1.73 +/- 0.05 eV, close to that of the activation energy obtained for DC conductivity (1.6 +/- 0.06 eV). The frequency dependent electrical conductivity was analyzed using Jonscher's power law. The combination of these dielectric characteristics suggests that these are good candidates for electrical energy storage device applications.
Resumo:
Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.