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Estimation of Power Consumption in Screw Gas Compressor Installed on Natural Gas Power Plant
(2025-01-01)
Sommani, Piyanart
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Yoomak, Suntiti
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Ananwattanaporn, Santipont
The knowledge of the precise power consumption of screw gas compressors, which is the highest power requirement when compared with other equipment used in natural gas power plants, can be an indicator of energy efficiency in natural gas power plants and impact the construction cost of the project. This paper proposed a calculation method for the estimated power requirement of the screw gas compressor and verified the calculation model with data from two different natural gas power plants. The verification methodology has been done by comparing the result with the obtained power from the unit during 11 operation scenarios. The result has indicated that the proposed calculation model can achieve an error less than 5% on all of operation scenarios. Thus, the proposed estimation model can be used to simplify the calculation process for the power requirement of a screw gas compressor.
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System Performance Enhancement with Energy Efficiency Based Sleep Control for 5G Heterogeneous Cellular Networks
(2022-04-01)
Dataesatu, Arif
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Sanada, Kosuke
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Hatano, Hiroyuki
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Mori, Kazuo
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Boonsrimuang, Pisit
This paper presents an improved sleep control algorithm for small base stations (SBSs) in 5G New Radio (NR) heterogeneous cellular networks (HetNets). HetNets consist of various base station tiers, including macro base stations (MBSs) and small base stations (SBSs), and have been suggested as a promising solution to enhance wireless coverage and network capacity, employing many SBSs into the MBS coverage. However, power consumption increases significantly as a result of an increase in the number of the SBSs. To solve this problem, the SBS sleep control has been proposed to reduce power consumption for the SBSs and improves energy efficiency, whereas it deteriorates system throughput compared with no sleep control system, consequently degrading the quality of service (QoS) performance at user equipments (UEs). This paper proposes an enhanced algorithm for SBS sleep control based on energy efficiency as a decision criterion for SBS operating state. From the evaluation results through computer simulation, the proposed scheme can provide improved performance for both energy efficiency and system throughput simultaneously, that is it can improve energy efficiency while maintaining almost the same system throughput as the no sleep control system. Concretely, the proposed scheme has the 14.89% improvement in energy efficiency while providing almost the same system throughput of over 99%, compared with no sleep control system
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Impact of Driving Behavior on Power Consumption of Electric Bus: A Case Study on Rama IX Bridge
(2022-01-01)
Phyo, Lwin Yamon
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Depaiwa, Nattawoot
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Yamakita, Masaki
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Kerdsup, Burin
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Masomtob, Manop
Recently, the influence of the bus transportation system in Thailand has become the most critical impact on our surroundings. Government of Thailand has initiated the projects to replace internal combustion engine buses with net zero-emission. However, there are the problems of power consumption in battery electric buses, especially on climbing resistance which is a major impact on the power demand and recuperation. This paper aims to investigate the impact of driving behavior on power consumption of electric buses. Many scenarios have been created to study such behavior. Also, driving across Rama IX bridge which is the critical scenario on the performance of electric buses in Thailand has been evaluated.
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GPU Performance Tuning and Power Efficiency on the DGX A100 Cluster
(2022-01-01)
Udomchoksakul, Khanin
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Sangpetch, Orathai
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Sangpetch, Akkarit
The complexity of current Deep learning has been growing rapidly nowadays. Such advancement allows various organizations such as private sectors and government to leverage intelligent systems on their use cases. High Performance Computing (HPC) infrastructure nowadays has pivoted to GPU-oriented systems, enabling developers and researchers to train complex models with large datasets unlike conventional clusters equipped only with CPU cores. However, focus on power efficiency on the HPC system has not been prevalent especially on the new system such as DGX A100 that does not have datapoints on how GPUs consumed power. Even though such HPC cluster can be powerful, always allowing it to run at the maximum capacity results to financial cost to the HPC provider at the end. Therefore, for any organization providing the system, it is crucial for them to balance the cluster capabilities while maintaining overall power consumption which can potentially be costly in the long term. This paper reveals A100 GPU metrics that are relevant to Power usage and explains GPU profiling applied to Deep learning workload on the cluster, saving up to 32% of the power usage while compromising only 11.5% of training time compared to a default profile. Then, the paper investigates literature review that could be learned further adopted to the current system at CMKL university as the next milestone.
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Energy Efficiency Enhancement in 5G Heterogeneous Cellular Networks Using System Throughput Based Sleep Control Scheme
(2020-02-01)
Dataesatu, Arif
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Boonsrimuang, Pornpawit
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Mori, Kazuo
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Boonsrimuang, Pisit
Currently, Cellular architectures are designed with an efficient providing infrastructure is one of the critical challenges in 5G dense heterogeneous cellular networks (HetNets). By adding many small base stations (SBSs) in a macro base station (MBS) is one way to support the rapid growth of mobile data communication, high data rate services and to provide continuous coverage. The high number of network elements leads to a significant increase in power consumption. To solve the problem, the SBS on/off algorithm has been introduced to reduce power consumption but also reduced energy efficiency as we called the conventional schemes. This paper we proposed as the SBS switching to sleep state algorithm based on the system throughput (MBS cell throughput and SBS cell throughput) is used the decision criteria for SBS to be in the sleep state. The simulation results, The proposed scheme can reduce the total power consumption of the network and enhance energy efficiency more than the conventional schemes.
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Low energy optimization for MPEG-4 video encoder on ARM-based mobile phones
(2006-11-02)
Pakdeepaiboonpol, P.
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Kittitornkun, S.
Most compiler optimization techniques concern most about speed. In this paper, we present two high-level power/energy optimization methods for ARM-based battery-powered embedded multimedia systems, e.g. mobile phones, pocket PCs, personal multimedia systems, etc. The experiments using MPEG-4 simple profile level 0 (SP@LO) video encoder on ARM920T with two QCIF video sequences 15 fps, 24 kbps show that the proposed techniques can complement the existing speed-oriented ones to achieve lower energy/power consumption up to 5.7% relative to all ARM C++ optimization levels despite the 16-KB instruction and 16-KB data caches of ARM 920T core. © 2006 IEEE.
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Improved speed rate in current mode algorithmic ADC
(2005-12-01)
Tipsuwarnpron, V.
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Roengruen, P.
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Chuchotsakunleot, W.
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Maitreechit, S.
A low power current-mode analog to digital converter suitable for equipment are required low voltage, low power (ADC). It uses a quartzite level with current injection technique to increase the speed of current mirrors. And this method to reduce the required input signal for a given range and higher operating speeds. In this paper, the feasibility of current-mode algorithmic ADC is demonstrated and advantages of various 2 techniques for use in the converters are considered. Experimental results for 4-bits algorithmic ADC using a 0.8 μm CMOS technology are reported, including power consumption.
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Power optimization for mobile MPEG-4 video decoder
(2005-12-01)
Pakdeepaiboonpol, Pairoj
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Kittitornkun, Surin
Most compiler optimization techniques concern most about speed. In this paper, we present two high-level power/energy optimization methods for ARM-based battery-powered embedded multimedia systems, e.g. mobile phones, pocket PCs, personal multimedia systems, etc. The experiments using MPEG-4 simple profile level 0 (SP@LO) video decoder on ARM920T with two QCIF video sequences 15 fps, 24 kbps show that the proposed techniques can complement the existing speedoriented ones to achieve lower energy/power consumption up to 13% relative to all ARM C++ optimization levels despite the 16KB Instruction and 16-KB data caches of ARM 920T core. © 2005 IEEE.

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