• Journal of Wind Energy
• /
• v.15 no.2
• /
• pp.10-22
• /
• 2024

This research is a comprehensive analysis of wind power prediction sensitivity using a Long Short-Term Memory (LSTM) deep learning neural network model, accounting for the inherent uncertainties in wind speed estimation. Utilizing a year's worth of operational data from an operational wind farm, the study forecasts the power output of both individual wind turbines and the farm collectively. Predictions were made daily at intervals of 10 minutes and 1 hour over a span of three months. The model's forecast accuracy was evaluated by comparing the root mean square error (RMSE), normalized RMSE (NRMSE), and correlation coefficients with actual power output data. Moreover, the research investigated how inaccuracies in wind speed inputs affect the power prediction sensitivity of the model. By simulating wind speed errors within a normal distribution range of 1% to 15%, the study analyzed their influence on the accuracy of power predictions. This investigation provided insights into the required wind speed prediction error rate to achieve an 8% power prediction error threshold, meeting the incentive standards for forecasting systems in renewable energy generation.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.11
• /
• pp.369-382
• /
• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Journal of Biomedical Engineering Research
• /
• v.22 no.3
• /
• pp.241-247
• /
• 2001

ABR(auditory brainstem response) is one of the audiometry which measures objective hearing threshold level by acquiring electric evoked potentials emanated from auditory nerve system responding to an auditory stimulation. However, the obtained potentials which are largely interfered by power line noise, have extremely low SNR, thus ensemble average algorithm is generally used. The purpose of this study was to investigate the effect of iteration number in ensemble average on the reduction of the power line noise. The power line noise was modeled to be a 60 Hz sinusoidal signal and the energy of the modeled signal was calculated when it was averaged. It was verified by simulation that the energy had the periodic zero points for each stimulation rate, and 60 Hz signal induced by the power line was applied to the developed ABR system to confirm that the period of zero energy point was the same with that of the simulation. By the properly selected iteration number, power line noise could be reduced and more reliable ABR could be acquired.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.12 no.4
• /
• pp.446-451
• /
• 2009

In this paper, we described the design and test results of a high output power amplifier MMIC developed by using 0.5um power pHEMT processes on a 6-inch GaAs wafer for the X-band T/R module application. In the MMIC design, we have used a simple on-chip gate active bias technology to compensate the threshold-voltage variation of pHEMT during the fabrication process and 16-to-1 power combining method to achieve the output power over 10watt. The fabricated chip has an output power over 12watts and maximum PAE of 32% over the frequency range of fo +/-750MHz.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.3-8
• /
• 2014

Recently, a spectrum sensing technique employing the maximum value of a received power spectrum as a test statistic has been presented in the literature for the purpose of detecting a wireless microphone signal in TV bands This detects the presence of a primary user by comparing the test statistic with some threshold, which depends on the background noise power level as well as a target false alarm rate. Therefore its performance may deteriorate when the noise power uncertainty occurs. As a means to mitigate this difficulty, we present a spectrum sensing strategy adopting the ratio of the maximum and the minimum value of the power spectrum as a test statistic and analyze its performance of spectrum sensing.

• Journal of electromagnetic engineering and science
• /
• v.11 no.2
• /
• pp.128-132
• /
• 2011

In interference tolerance based spectrum sharing systems, primary receivers (PRs) are protected by a predefined peak or average interference power constraint. To implement such systems, cognitive radio (CR) transmitters are required to adjust their transmit power so that the interference power received at the PR receivers is kept below the threshold value. Hence, a CR-transmitter requires knowledge of its channel and the primary receiver in order to allocate the transmit power. In practice, it is impossible or very difficult for a CR transmitter to have perfect knowledge of this channel state information (CSI). In this paper, we investigate the impact of imperfect knowledge of this CSI on the performances of both a primary and cognitive radio network. For fixed transmit power, average interference power (AIP) constraint can be maintained through knowledge of the channel distribution information. To maintain the peak interference power (PIP) constraint, on the other hand, the CR-transmitter requires the instantaneous CSI of its channel with the primary receiver. First, we show that, compared to the PIP constraint with perfect CSI, the AIP constraint is advantageous for primary users but not for CR users. Then, we consider a PIP constraint with imperfect CSI at the CR-transmitter. We show that inaccuracy in CSI reduces the interference at the PR-receivers that is caused by the CR-transmitter. Consequently the proposed schemes improve the capacity of the primary links. Contrarily, the capacities of the CR links significantly degrade due to the inaccuracy in CSI.

• Journal of Satellite, Information and Communications
• /
• v.6 no.2
• /
• pp.131-135
• /
• 2011

In this paper, we describe the design and implementation of wireless smart plug having AC power sensor and intelligent standby power control algorithm for energy sensor network. The adaptive standby power control algorithm has function to apply different threshold of standby power by using learning algorithm depending on electric equipments. As using the proposed algorithm, user convenience will be more better and power consumption can be more reduced. The implemented prototypes of wireless smart plug and wireless access point were tested to verify the required functions and performance. As a result, we confirmed practicality of wireless smart power sensor and satisfaction of given design specifications.

• Korean Journal of Metals and Materials
• /
• v.47 no.1
• /
• pp.38-43
• /
• 2009

To investigate the effect of RF power on the structural, optical and electrical properties of amorphous InGaZnO (a-IGZO), its thin films and TFTs were prepared by RF magnetron sputtering method with different RF power conditions of 40, 80 and 120 W at room temperature. In this study, as RF power during the deposition process increases, the RMS roughness of a-IGZO films increased from 0.26 nm to 1.09 nm, while the optical band-gap decreased from 3.28 eV to 3.04 eV. In the case of the electrical characteristics of a-IGZO TFTs, the saturation mobility increased from $7.3cm^2/Vs$ to $17.0cm^2/Vs$, but the threshold voltage decreased from 5.9 V to 3.9 V with increasing RF power. It is regarded that the increment of RF power increases the carrier concentration of the a-IGZO semiconductor layer due to the higher generation of oxygen vacancies.

• Convergence Security Journal
• /
• v.9 no.2
• /
• pp.71-78
• /
• 2009

It is very difficult to apply previous security protocols to WSNs(Wireless Sensor Networks) directly because WNSs have resource constrained characteristics such as a low computing ability, power, and a low communication band width. In order to overcome the problem, we proposes a secure group communication scheme applicable to WSNs. The proposed scheme is a combined form of the TEEN(Threshold sensitive Energy Efficient sensor Network protocol) clustering based hierarchical routing protocol and security mechanism, and we assume that WSNs are composed of sensor nodes, cluster headers, and base stations. We use both private key and public key cryptographic algorithms to achieve an enhanced security and an efficient key management. In addition, communications among sensor nodes, cluster headers, and base stations are accomplished by a hierarchical tree architecture to reduce power consumption. Therefore, the proposed scheme in this paper is well suited for WSNs since our design can provide not only a more enhanced security but also a lower power consumption in communications.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.42 no.2 s.332
• /
• pp.31-40
• /
• 2005

The Multi-Threshold CMOS (MTCMOS) technology provides a solution to the high performance and low power design requirements of mobile computing applications. In this paper, we (i) motivate the post-mask-tooling performance enhancement technique combined with the MTCMOS leakage current suppression technology, and (ii) develop a practical MTCMOS ASIC design methodology which fine-tunes and integrates best-in-class techniques and commercially available tools to fix the new design issues related to the MTCMOS technology. Towards validating the proposed techniques, a Personal Digital Assistant (PDA) processor has been implemented using the methodology, and a 0.18um Process. The fabricated PDA processor operates at 333MHz which has been improved about $23\%$ at no additional cost of redesign and masks, and consumes about 2uW of standby mode leakage power which could have been three orders of magnitude larger if the MTCMOS technology was not applied.