Energy Utilization Coefficient

• Energy Utilization Coefficient is a measure that quantifies the ratio of useful energy output to total energy input, critical for assessing system efficiency.
• It inspires refined metrics such as xPUE and utility-energy efficiency, which offer detailed insights in cloud infrastructures, data centers, and wireless sensor networks.
• Accurate evaluation of this coefficient enables optimized design and operational strategies across energy systems, improving sustainability and performance.

Searching arXiv for recent and relevant papers on “energy utilization coefficient” and closely related metrics across domains. to=arxiv_search.search 大发云json code='{"^^^^^^^^6query6 utilization coefficient\" OR ^^^^^^^^6all:\6 efficiency metric\" OR ^^^^^^^^6all:\6 usage effectiveness\" OR ^^^^^^^^6all:\6 efficiency\" OR ^^^^^^^^6all:\6 conversion efficiency\"","max_results":^^^^6all:\6query6^^^^,"sort_by":"relevance"}'【อ่านข้อความเต็มjson code='&&&^^^^6query6^^^^&&&)","title":"xPUE: Extending Power Usage Effectiveness Metrics for Cloud Infrastructures","authors":["Josué Anglès d\'Auriac","Georges Da Costa","Patricia Stolf"],"abstract":"The energy consumption analysis and optimization of data centers have been an increasingly popular topic over the past few years. It is widely recognized that several effective metrics exist to capture the efficiency of hardware and/or software hosted in these infrastructures. Unfortunately, choosing the corresponding metrics for specific infrastructure and assessing its efficiency over time is still considered an open problem. For this purpose, energy efficiency metrics, such as the Power Usage Effectiveness (PUE), assess the efficiency of the computing equipment of the infrastructure. However, this metric stops at the power supply of hosted servers and fails to offer a finer granularity to bring a deeper insight into the Power Usage Effectiveness of hardware and software running in cloud infrastructure.Therefore, we propose to leverage complementary PUE metrics, coined xPUE, to compute the energy efficiency of the computing continuum from hardware components, up to the running software layers. Our contribution aims to deliver realtime energy efficiency metrics from different perspectives for cloud infrastructure, hence helping cloud ecosystems-from cloud providers to their customers-to experiment and optimize the energy usage of cloud infrastructures at large.","categories":["cs.DC"],"published":"^^^^6 OR all:\6query6 OR all:\6 OR all:\6^^^^-^^^^6query6 OR all:\6^^^^-^^^^6all:\6query6^^^^"},{"arxiv_id":"(&&& Efficiency Oriented User Association with Power Control in Heterogeneous Networks","authors":["Nan Qi","Wenchi Cheng","Xiaojing Huang","Xiaohu Ge"],"abstract":"This letter investigates optimizing utility-energy efficiency (UEE), defined as the achieved network utility when consuming a unit of power, rather than a typical energy efficiency metric, in a heterogeneous network (HetNet). To tackle the nonconvexity of the problem due to integer constraints and coupled variables, we devise an alternating optimization algorithm. It applies Lagrangian dual analysis with auxiliary variables, which successfully transforms each subproblem to a convex one with efficient solutions. The proposed algorithm is consequently guaranteed to converge to a local optimum with noticeable performance gain via simulation verifications.","categories":["cs.IT","math.OC"],"published":"^^^^6 OR all:\6query6all:\6^^^^8-^^^^6query66^^^^- OR all:\6^^^^&&&)","title":"Universality of energy conversion efficiency for optimal tight-coupling heat engines and refrigerators","authors":["Ying Wang","Zhuo Cai","Jincan Chen"],"abstract":"A unified PRESERVED_PLACEHOLDER_^^^^6query6^^^^-criterion for heat devices (including heat engines and refrigerators) which is defined as the product of the energy conversion efficiency and the heat absorbed per unit time by the working substance [de Tom\'as et al ^^^^6 OR all:\6query6all:\6 OR all:\6^^^^ Phys. Rev. E 8^^^^6 OR all:\6^^^^ ^^^^6query6all:\6query6all:\6query6 OR all:\6^^^^R] is optimized for tight-coupling heat engines and refrigerators operating between two heat baths at temperatures PRESERVED_PLACEHOLDER_^^^^6all:\6^^^^ and PRESERVED_PLACEHOLDER_^^^^6 OR all:\6^^^^. By taking a new convention on the thermodynamic flux related to the heat transfer between two baths, we find that for a refrigerator tightly and symmetrically coupled with two heat baths, the coefficient of performance (i.e., the energy conversion efficiency of refrigerators) at maximum PRESERVED_PLACEHOLDER_^^^^6 OR all:\6^^^^ asymptotically approaches to PRESERVED_PLACEHOLDER_^^^^6 OR all:\6^^^^ when the relative temperature difference between two heat baths PRESERVED_PLACEHOLDER_^^^^6 OR all:\6^^^^ is sufficiently small. Correspondingly, the efficiency at maximum $\chi$ (equivalent to maximum power) for a heat engine tightly and symmetrically coupled with two heat baths is proved to be $\eta_C/2+\eta_C^2/8$ up to the second order term of $\eta_C\equiv (T_h-T_c)/T_h$, which reverts to the universal efficiency at maximum power for tight-coupling heat engines operating between two heat baths at small temperature difference in the presence of left-right symmetry [Esposito et al ^^^^6 OR all:\6query6query6^^^^9 Phys. Rev. Lett. ^^^^6all:\6query6 OR all:\6^^^^ ^^^^6all:\6 OR all:\6query66query6 OR all:\6^^^^].","categories":["cond-mat.stat-mech"],"published":"^^^^6 OR all:\6query6all:\6 OR all:\6^^^^-^^^^6all:\6 OR all:\6^^^^-^^^^6 OR all:\6all:\6^^^^"},{"arxiv_id":"(&&&^^^^6 OR all:\6^^^^&&&)","title":"Hybrid DEEC: Towards Efficient Energy Utilization in Wireless Sensor Networks","authors":["Nadeem Javaid","Shafaqat Ali Khan","Tahir D. Pahlevi","Adeel Iqbal","Amina Qasim","Zahid Khan"],"abstract":"The clustering algorithm are considered as a kind of key technique used to reduce energy consumption. It can help in increasing the stability period and network life time. Routing protocol for efficient energy utilization should be designed for heterogeneous Wireless Sensor Networks (WSNs). We purpose Hybrid-DEEC (H-DEEC), a chain and cluster based (hybrid) distributed scheme for efficient energy utilization in WSNs. In H-DEEC,elected Cluster Heads (CHs) communicate the Base Station (BS) through beta elected nodes, by using multi-hopping. We logically divide the network into two parts, on the basis of the residual energy of nodes. The normal nodes with high initial and residual energy will behighlyprobable to be CHs than the nodes with lesser energy. To overcome the deficiencies of H-DEEC, we propose Multi-Edged Hybrid-DEEC (MH-DEEC). In MH-DEEC the criteria of chain construction is modified. Finally, the comparison in simulation results with other heterogeneous protocols show that, MH-DEEC and H-DEEC achieves longer stability time and network life time due to efficient energy utilization.","categories":["cs.NI"],"published":"^^^^6 OR all:\6query6all:\6 OR all:\6^^^^-^^^^6query6 OR all:\6^^^^-^^^^6all:\6^^^^9"},{"arxiv_id":"(&&& OR all:\6^^^^&&&)","title":"Methane and oxygen from energy-efficient, low temperature in situ resource utilization enables missions to Mars","authors":["Alyssa Trigwell","Abigail A. Rousis","Kevin C. Hand","Katherine L. Fritsch"],"abstract":"NASA mandate is a human mission to Mars in the ^^^^6 OR all:\6query6 OR all:\6query6^^^^s and sustained exploration of Mars requires in-situ resource utilization (ISRU). Exploiting the Martian water cycle (alongside perchlorate salts that depress the freezing point of water to less than ^^^^6 OR all:\6all:\6 OR all:\6^^^^K) and the available 9^^^^6 OR all:\6^^^^ volume percent atmospheric CO^^^^6 OR all:\6^^^^, we detail an ultra-low temperature (^^^^6 OR all:\6 OR all:\6 OR all:\6^^^^K) CO^^^^6 OR all:\6^^^^-H^^^^6 OR all:\6^^^^O electrolyzer to produce methane fuel and life-supporting oxygen on Mars. Methane production is thermodynamically favored across a range of operational pressures and temperatures and our electrolyzer polarization model concurred with reported experimental performance. A hypothetical ^^^^6all:\6query6^^^^-cell, ^^^^6all:\6query6query6^^^^ square cm electrode-area-per-cell electrolyzer produced ^^^^6query6^^^^.^^^^6 OR all:\6all:\6^^^^g per W per day of CH^^^^6 OR all:\6^^^^ and ^^^^6 OR all:\6^^^^.^^^^6 OR all:\6 OR all:\6^^^^g per W per day of O^^^^6 OR all:\6^^^^ at ^^^^6 OR all:\6^^^^V per cell (operating voltage) versus ^^^^6query6^^^^.8g per W per day of O^^^^6 OR all:\6^^^^ produced by the Mars Oxygen in-situ Resource Utilization Experiment (MOXIE) from the Mars ^^^^6 OR all:\6query6 OR all:\6query6^^^^ mission (MOXIE produces no fuel). Material performance requirements are presented to show that this technology is an energy-efficient complement to the MOXIE high temperature approach.","categories":["astro-ph.EP","physics.chem-ph"],"published":"^^^^6 OR all:\6query6 OR all:\6 OR all:\6^^^^-^^^^6query6 OR all:\6^^^^-^^^^6 OR all:\6all:\6^^^^"},{"arxiv_id":"(&&&^^^^6 OR all:\6^^^^&&&)","title":"A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT","authors":["Saleem Bhatti","Muhammad M. E. A. Mahmoud","Hossam S. Hassanein"],"abstract":"Recent research has shown the potential of using available mobile fog devices (such as smartphones, drones, domestic and industrial robots) as relays to minimize communication outages between sensors and destination devices, where localized Internet-of-Things services (e.g., manufacturing process control, health and security monitoring) are delivered. However, these mobile relays deplete energy when they move and transmit to distant destinations. As such, power-control mechanisms and intelligent mobility of the relay devices are critical in improving communication performance and energy utilization. In this paper, we propose a Q-learning-based decentralized approach where each mobile fog relay agent (MFRA) is controlled by an autonomous agent which uses reinforcement learning to simultaneously improve communication performance and energy utilization. Each autonomous agent learns based on the feedback from the destination and its own energy levels whether to remain active and forward the message, or become passive for that transmission phase. We evaluate the approach by comparing with the centralized approach, and observe that with lesser number of MFRAs, our approach is able to ensure reliable delivery of data and reduce overall energy cost by ^^^^6 OR all:\66^^^^.76% -- 88.^^^^6query6 OR all:\6^^^^%.","categories":["cs.NI"],"published":"^^^^6 OR all:\6query6 OR all:\6all:\6^^^^-^^^^6query66^^^^- Energy Consumption based on Resource Utilization","authors":["Charles Miers","Alessandro F. de Oliveira","Edson Trindade","Marcos Pietri da Silva","Raphael M. de Oliveira","Jonathan M. Campos","Emerson R. de Mello"],"abstract":"Power management is an expensive and important issue for large computational infrastructures such as datacenters, large clusters, and computational grids. However, measuring energy consumption of scalable systems may be impractical due to both cost and complexity for deploying power metering devices on a large number of machines. In this paper, we propose the use of information about resource utilization (e.g. processor, memory, disk operations, and network traffic) as proxies for estimating power consumption. We employ machine learning techniques to estimate power consumption using such information which are provided by common operating systems. Experiments with linear regression, regression tree, and multilayer perceptron on data from different hardware resulted into a model with 99.9^^^^6 OR all:\6^^^^% of accuracy and 6.^^^^6 OR all:\6 OR all:\6^^^^ watts of error in the best case.","categories":["cs.DC","cs.LG"],"published":"^^^^6 OR all:\6query6all:\6^^^^7-^^^^6query6^^^^9- OR all:\6^^^^"},{"arxiv_id":"(Zhou et al., 2013)","title":"AxPUE: Application Level Metrics for Power Usage Effectiveness in Data Centers","authors":["Ying Song","Yunqi Zhang","Dawei Sun","Dongsheng Wang","Long Wang","Yongqiang He","Weimin Zheng"],"abstract":"The rapid growth of data volume brings big challenges to the data center computing, and energy efficiency is one of the most concerned problems. Researchers from various fields are now proposing solutions to green the data center operations. Power usage effectiveness metric plays an important role in the energy saving research. However, the exising usage effectiveness metrics focus on measuring the relationship between the total facility energy consumed and the IT equipment energy consumed, without reflecting the energy efficiency of applications. In this paper, we analyze the requirements of application-level metrics for power usage efficiency of the data centers, and propose two novel energy efficiency metrics to provide strong guidance and useful insight to data center design and optimization. We conduct comprehensive experiments in the practical data centers using BigDataBench, a big data benchmark suite, and the results demonstrate the rationality and efficiency of AxPUE in measuring the actual computation energy consumption in data centers.","categories":["cs.DC"],"published":"^^^^6 OR all:\6query6all:\6 OR all:\6^^^^-^^^^6all:\6query6^^^^- OR all:\6 OR all:\6^^^^"},{"arxiv_id":"(Zheng et al., 2022)","title":"Impact of Bidding and Dispatch Models over Energy Storage Utilization in Bulk Power Systems","authors":["Hanyu Zhou","Tongxin Zheng","Jin Tan","Xingpeng Li"],"abstract":"Energy storage is a key enabler towards a low-emission electricity system, but requires appropriate dispatch models to be economically coordinated with other generation resources in bulk power systems. This paper analyzes how different dispatch models and bidding strategies would affect the utilization of storage with various durations in deregulated power systems. We use a dynamic programming model to calculate the operation opportunity value of storage from price predictions, and use the opportunity value result as a base for designing market bids. We compare two market bidding and dispatch models in single-period economic dispatch: one without state of charge (SoC) constraints and one with SoC constraints. We test the two storage dispatch models, combined with different price predictions and storage durations, using historical real-time price data from New York Independent System Operator. We compare the utilization rate with respect to results from perfect price forecast cases. Our result shows that while price prediction accuracy is critical for short duration storage with a less than four hours capacity, storage with a duration longer than twelve hours can easily achieve a utilization rate higher than 8^^^^6query6^^^^% even with naive day-ahead price predictions. Modeling storage bids as dependent of SoC in single-period real-time dispatch will provide around ^^^^6 OR all:\6^^^^% of improvement in storage utilization over all duration cases and bidding strategies, and higher renewable share will likely improve storage utilization rate due to higher occurrence of negative prices.","categories":["eess.SY","econ.GN","math.OC"],"published":"^^^^6 OR all:\6query6 OR all:\6 OR all:\6^^^^-^^^^6query6all:\6^^^^- An Energy-Efficient Reinforcement Learning Strategy for optimizing QoS and User Connectivity in 6G Integrated Satellite-Terrestrial Networks","authors":["Md. Mohabbat Hossain","M. Shamim Kaiser","Arman Zaman","Mir Mehedi Hasan","S. M. Nahiduzzaman","Mohamed H. AbdelAzeem","A. B. M. Alim Al ইসলাম"],"abstract":"This paper introduces EcoQPower, an energy-efficient reinforcement learning framework aimed at optimizing user connectivity and quality of service (QoS) in 6G integrated satellite-terrestrial networks (ISTNs). By leveraging the Twin Delayed Deep Deterministic Policy Gradient (TD^^^^6 OR all:\6^^^^) algorithm, the framework dynamically adjusts transmit power and user association decisions, significantly reducing energy consumption while maintaining robust QoS. Simulations reveal that EcoQPower outperforms baseline methods, reducing total power consumption by 7^^^^6 OR all:\6^^^^.87% and energy efficiency metrics by up to 79.^^^^6 OR all:\6^^^^8% under varying user densities. The framework demonstrates strong adaptability to different user loads, making it a promising solution for next-generation sustainable communication networks.","categories":["cs.NI","eess.SP"],"published":"^^^^6 OR all:\6query6 OR all:\6 OR all:\6^^^^-^^^^6all:\6all:\6^^^^- OR all:\6query6^^^^"}]