• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1079-1080
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• 2006

This paper presents the methods to save energy by using load consumption pattern analysis. Base on the substation annual power usage data, the characteristic of the substation power consumption have investigated. With this investigation effective electrical billing condition and the control target load has been determined. Most of power usage comes from the motor car, so power system and load table of motor car were reviewed. And in the metropolitan area the peak power consumption occurs at summer or winter rush hours because of its typical characteristics. From this data control point of time are determined. Through the whole study the methode to control the power Peak consumption are proposed and prototype was designed.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.253-255
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• 2003

Electricity is the prime commodity in mobile device, e.g. smart phone, PDA, MP3 player and etc. This strict restriction on power consumption requirement of the mobile device puts unique demand in designing hardware and software components of the device. In this paper, we address the issue of minimizing the power consumption in retrieving the continuous media data from the disk drive for real-time playback purpose. Different from the legacy text based data, real-time multimedia playback requires that the storage supplies the data block continuous fashion. This may put immense burden on the power scarce environment since the disk Is required to be active for the entire playback duration. We develop elaborate algorithm which carefully analyzes the power consumption profile of the disk drive and which establishes the data retrieval schedule for the given playback. It computes the amount of data blocks to read, the length of active and standby period. According to our simulation result, the ARM algorithm exhibits superior performance in continuous media retrieval from the aspect of power consumption to legacy playback scheme.

• ETRI Journal
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• v.30 no.1
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• The Journal of the Korea Contents Association
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• v.6 no.8
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• pp.1-7
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• 2006

In this paper, proposed the method to increase the battery life of the Wibro terminal by reducing its power consumption. The amount of power consumption was analysed. And as the results, it is shown that the suggested method can be reduced the power consumption. The performance of the proposed system, which control the number of pilot of symbol, analysed by the simulation. It is shown that the power consumption of the terminal can be reduced by the reduction of the CINR for the percentage of pilot per symbol, as 0.48dBm for 10% and 0.95dBm for 20%, which can be accomplished by changing the current system of having the fixed number of pilot.

• The KIPS Transactions:PartA
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• v.18A no.3
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• pp.93-98
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• 2011

While the use of battery-powered embedded systems has been rapidly increasing, the current level of battery technology has not kept up with the drastic increase in power consumption by the system. In order to prolong system usage time, the battery size needs to be increased. The amounts of power consumption by embedded systems are determined by their hardware configuration and software for manipulating hardware resources. In spite of that, the hardware provides features for lowering power consumption, if those cannot be utilized efficiently by software including operating system, reduction in power consumption is not optimized. In this paper, we propose a BET(Break Even Time)-based scheduling method using task partition to reduce power consumption of multimedia applications in a mobile embedded system environment.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.84-93
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• 2017

This study was carried out to improve the electric power consumption of HVAC in the blow mold machine(BMM) and work environment. The experiment was conducted with the simulated HVAC system of 1/15 of the actual BMM. The temperature of main facility and two preheaters was fixed at 200 and $60^{\circ}C$ respectively in all test conditions. The measured points of temperature were chosen as critical locations considering the work environment. The tendency of temperature distributions decreases as the duct was closed to the main facility. The reduction rate of power consumption of HVAC increases up to 32.3% when both duct and cooling systems are operated. Also the efficiency of HVAC is improved about 9% through the modified design of duct system. It notes that the electric power consumption of HVAC can be reduced by the optimum design and operating condition of duct and cooling system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.91-96
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• 2019

There are so many low power MAC protocols for wireless sensor network. IEEE802.15.4 among them has disadvantage of a large power consumption for synchronization. To save power consumption it use the superframe operation alternating sleep mode and awake mode. But latency is longer result from superframe operation. Typical asynchronous B-MAC can have shorter latency according to check interval. But transmitter consumes more power because of long preamble. And receiver is suffering from overhearing. In this paper, we propose the adaptive check interval scheme of B-MAC for enhancing the power consumption and delay latency performance. Its power consumption is evaluated by comparing the proposed scheme with a typical IEEE802.15.4.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.215-225
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• 2020

Light detection and ranging (LiDAR) sensors detect the distance of the surrounding environment and objects. Conventional LiDAR sensors require a certain amount of a power because they detect objects by transmitting lasers at a regular interval depending on a constant resolution. The constant power consumption from operating multiple LiDAR sensors is detrimental to autonomous and electric vehicles using battery power. In this paper, we propose two algorithms that improve the inefficient power consumption during the constant operation of LiDAR sensors. LiDAR sensors with algorithms efficiently reduce the power consumption in two ways: (a) controlling the resolution to vary the laser transmission period (T_P) of a laser diode (LD) depending on the vehicle's speed and (b) reducing the static power consumption using a sleep mode depending on the surrounding environment. A proposed LiDAR sensor with a resolution control algorithm reduces the power consumption of the LD by 6.92% to 32.43% depending on the vehicle's speed, compared to the maximum number of laser transmissions (N_x·max). The sleep mode with a surrounding environment-sensing algorithm reduces the power consumption by 61.09%. The proposed LiDAR sensor has a risk factor for 4-cycles that does not detect objects in the sleep mode, but we consider it to be negligible because it immediately switches to an active mode when a change in surrounding conditions occurs. The proposed LiDAR sensor was tested on a commercial processor chip with the algorithm controlling the resolution according to the vehicle's speed and the surrounding environment.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.349-364
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• 2014

This study analyzed Granger causality between power consumption and production activity in manufacturing sector, by using error correction model. It found that there exists the connection between power consumption and production activity in manufacturing sector. By reflecting the industrial characteristics, it found not only the bilateral causality (power consumption ${\leftrightarrow}$ production activity) in power non-intensive industry, high value-added industry and low value-added industry, but also one-way causality (power consumption ${\rightarrow}$ production activity) in power-intensive industry. These results imply that power demand management policy focusing on efficiency improvement is necessary primarily to minimize negative impacts on production activity, and also stable power supply system is required to meet the increase of power demand.

• ETRI Journal
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• v.37 no.1
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• pp.157-164
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• 2015

As GPU power consumption in smartphones increases with more advanced graphic performance, it becomes essential to estimate GPU power consumption accurately. The conventional GPU power model assumes, simply, that a GPU consumes constant power when turned on; however, this is no longer true for recent smartphone GPUs. In this paper, we propose an accurate GPU power model for smartphones, considering newly adopted dynamic voltage and frequency scaling. For the proposed GPU power model, our evaluation results show that the error rate for system power estimation is as low as 2.9%, on average, and 4.6% in the worst case.