• Title/Summary/Keyword: powerline communication (PLC)

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Performance Comparison over Gaussian Channel of Binary Chirp DS-CDMA System for Powerline Communication (전력선 통신을 위한 Binary Chirp DS-CDMA System의 가우시안 채널 하에서 성능 비교)

  • Park, Sung-Wook;Park, Jong-Wook
    • 전자공학회논문지 IE
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    • v.43 no.2
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    • pp.70-74
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    • 2006
  • The performance of conventional direct sequence code division multiple access (DS-CDMA) systems is decreased under environments such as additive white Gaussian noise (AWGN), channel distortion and interference noise due to multiple access user. By means of this parameter, auto correlation value of pseudo noise spreading sequence is decreased at receiver. This techniques which are based on correlation of between signature waveform signal. In this paper, to improve correlation property, we proposed the binary chirp DS-CDMA techniques which combine the DS-CDMA and chirp modulation. The proposed system which is based on binary chirp symbol has a good correlation value. Thus, we called BC DS-CDMA. To evaluate the system's performance, we compare the performance of the proposed systems with DS-CDMA systems under AWGN channel and halogen noise which exists on the powerline. The simulation results show that the proposed method has better performance than conventional technique.

The Design and Implementation of AMI System Using Binary CDMA (Binary CDMA 기반의 AMI 시스템 설계 및 구현)

  • Joe, In-Whee;Jeong, Jong-Yuel
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.8C
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    • pp.663-669
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    • 2012
  • To solve the energy problem and finding new growth engines, interest for the smart grid is increasing and related technologies are making great efforts to secure in the world. AMI (Advanced Metering Infrastructure) Among them is the first to be constructed and getting attention as a key component of smart grid. A fusion of various technologies in technology development and demonstration is underway on Jeju Island Smart Grid Demonstration Complex in Korea, and focusing on broadband power line communication technology infrastructure is actively underway in Korea Electric Power Corporation. AMI system using power line communication technology without building a separate communication lines are available for power supply lines, but communication is impossible in occurs because admission to the power company or the ideal infrastructure for communication is not considered. In this paper, we analyze the requirements to build AMI system using Binary CDMA and powerline communications technology, and design the basic communication protocol based on Binary CDMA, implement network management and relay feature. By doing so, ways to apply Ad-hoc Binary CDMA indigenous technology to the AMI system were derived, and could build a system to make use of Wired (PLC) and wireless (Binary CDMA) simultaneously.

Intelligent Home Energy Management based on Powerline Communication (전력선통신을 이용한 지능형 홈에너지 관리시스템)

  • Ju, Seong-Ho;Choi, Moon-Seok;Choi, Jong-Hyup;Lim, Yong-Hoon;Kim, Tae-Kyung
    • Proceedings of the KIPE Conference
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    • 2008.06a
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    • pp.148-150
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    • 2008
  • 지구온난화와 화석연료의 고갈 등 에너지관련 문제들이 발생함에 따라 제한된 자원의 효율적인 소비가 중요한 연구주제로 다루어지고 있다. 특히 자원수입국인 우리나라의 경우는 국제 유가 급등과 같은 에너지파동에 상당히 민감하기 때문에 에너지 관리를 통한 정확한 수급정책 수립 및 효율적인 소비생활이 무엇보다 중요하다. 이를 위해 우선적으로 취할 수 있는 해결책 중의 하나가 댁내 가전기기의 불필요한 전력낭비를 최소화하는 것이다. 이번 연구에서는 전력선통신(PLC)기반 원격검침 인프라를 활용하여 1차적으로 가전기기의 대기전력을 지능적으로 관리함으로써 전력낭비를 최소화하고 2차적으로 전력소비모니터링 서비스를 제공함으로써 사용자가 능동적으로 전력소비를 줄일 수 있도록 하는 지능형 홈에너지 관리시스템을 개발하였으며, 실제 수용가를 대상으로 구축, 운영함으로써 향후 에너지를 효율적으로 관리할 수 있는 방안을 제시하고자 한다.

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Channel characteristics of multi-path power line using a contactless inductive coupling unit (비접촉식 유도성 결합기를 이용한 다중경로 전력선 채널 특성)

  • Kim, Hyun-Sik;Sohn, Kyung-Rak
    • Journal of Advanced Marine Engineering and Technology
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    • v.40 no.9
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    • pp.799-804
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    • 2016
  • Broadband powerline communication (BPLC) uses distribution lines as a medium for achieving effective bidirectional data communication along with electric current flow. As the material characteristics of power lines are not good at the communication channel, the development of power line communication (PLC) systems for internet, voice, and data services requires measurement-based models of the transfer characteristics of the network suitable for performance analysis by simulation. In this paper, an analytic model describing a complex transfer function is presented to obtain the attenuation and path parameters for a multipath power line model. The calculated results demonstrated frequency-selective fading in multipath channels and signal attenuation with frequency, and were in good agreement with the experimental results. Inductive coupling units are used as couplers for coupling the signal to the power line to avoid physical connections to the distribution line. The inductance of the ferrite core, which depends on the frequency, determines the cut-off frequency of the inductive coupler. Coupling loss can be minimized by increasing the number of windings around the coupler. Coupling efficiency was improved by more than 6 dB with three windings compared to the results obtained with one winding.

Power Consumption Prediction Scheme Based on Deep Learning for Powerline Communication Systems (전력선통신 시스템을 위한 딥 러닝 기반 전력량 예측 기법)

  • Lee, Dong Gu;Kim, Soo Hyun;Jung, Ho Chul;Sun, Young Ghyu;Sim, Issac;Hwang, Yu Min;Kim, Jin Young
    • Journal of IKEEE
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    • v.22 no.3
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    • pp.822-828
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    • 2018
  • Recently, energy issues such as massive blackout due to increase in power consumption have been emerged, and it is necessary to improve the accuracy of prediction of power consumption as a solution for these problems. In this study, we investigate the difference between the actual power consumption and the predicted power consumption through the deep learning- based power consumption forecasting experiment, and the possibility of adjusting the power reserve ratio. In this paper, the prediction of the power consumption based on the deep learning can be used as a basis to reduce the power reserve ratio so as not to excessively produce extra power. The deep learning method used in this paper uses a learning model of long-short-term-memory (LSTM) structure that processes time series data. In the computer simulation, the generated power consumption data was learned, and the power consumption was predicted based on the learned model. We calculate the error between the actual and predicted power consumption amount, resulting in an error rate of 21.37%. Considering the recent power reserve ratio of 45.9%, it is possible to reduce the reserve ratio by 20% when applying the power consumption prediction algorithm proposed in this study.