Modeling and Link Performance Analysis of Busbar Distribution Systems for Narrowband PLC


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HASIRCI Z., ÇAVDAR İ. H., ÖZTÜRK M.

RADIOENGINEERING, cilt.26, sa.2, ss.611-620, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Sayı: 2
  • Basım Tarihi: 2017
  • Doi Numarası: 10.13164/re.2017.0611
  • Dergi Adı: RADIOENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.611-620
  • Anahtar Kelimeler: Bit-error-rate, busbar, channel capacity, channel modeling, M2M, narrow band, parameter optimization, power line communication, smart grid, S-parameters, PROPAGATION CONSTANT, NOISE
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Busbar distribution system is used as a modular infrastructure to carry electrical energy in low voltage grid. Due to the widespread usage in industrial areas, the power line communication possibilities should be investigated in terms of smart grid concept. This paper addresses modeling of the busbar distribution system as a transmission line and gives some suggestions on the link performance for narrowband power line communication for the first time in literature. Firstly, S-parameters of different current level busbars were measured up to 500 kHz for all possible two-port signal paths. The utilization of the frequency-dependent RLCG(f) model was proposed to extract transmission line characteristics to eliminate the unwanted measurement effects. Particle swarm algorithm was used to optimize the model parameters with a good agreement between measured and simulated S-parameters. Additionally, link performance of busbar distribution system as a power line communication channel at 3 kHz-148.5 kHz band was examined for frequency shift keying and phase shift keying modulations under different network configurations such as varying busbar type, the line length between transmitter and receiver, branch number, and terminating load impedance. Obtained results were presented as bit-error-rate vs. signal-to-noise ratio graphs.