### Information Technology, Artificial Intelligence and Machine Learning in Smart Grid – Performance Comparison between Topology Identification Methodology and Neural Network Identification Methodology for the Branch Number Approximation of Overhead Low-Voltage Broadband over Power Lines Network Topologies

#### Abstract

Broadband over Power Lines (BPL) networks that are deployed across the smart grid can benefit from the usage of machine learning, as smarter grid diagnostics are collected and analyzed. In this paper, the neural network identification methodology of Overhead Low-Voltage (OV LV) BPL networks that aims at identifying the number of branches for a given OV LV BPL topology channel attenuation behavior is proposed, which is simply denoted as NNIM-BNI. In order to identify the branch number of an OV LV BPL topology through its channel attenuation behavior, NNIM-BNI exploits the Deterministic Hybrid Model (DHM), which has been extensively tested in OV LV BPL networks for their channel attenuation determination, and the OV LV BPL topology database of Topology Identification Methodology (TIM). The results of NNIM-BNI towards the branch number identification of OV LV BPL topologies are compared against the ones of a newly proposed TIM-based methodology, denoted as TIM-BNI.

**Citation:** Lazaropoulos, A. G. (2021). Information Technology, Artificial Intelligence and Machine Learning in Smart Grid-Performance Comparison between Topology Identification Methodology and Neural Network Identification Methodology for the Branch Number Approximation of Overhead Low-Voltage Broadband over Power Lines Network Topologies. Trends in Renewable Energy, 7, 87-113. DOI: 10.17737/tre.2021.7.1.00133

#### Keywords

#### Full Text:

FULL TEXT (PDF)#### References

F. Aalamifar and L. Lampe, â€œOptimized WiMAX profile configuration for smart grid communications,â€ IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 2723-2732, 2017.

A. G. Lazaropoulos, â€œWireless Sensor Network Design for Transmission Line Monitoring, Metering and Controlling Introducing Broadband over PowerLines-enhanced Network Model (BPLeNM),â€ ISRN Power Engineering, vol. 2014, Article ID 894628, 22 pages, 2014. doi:10.1155/2014/894628. [Online]. Available: http://www.hindawi.com/journals/isrn.power.engineering/2014/894628/

A. G. Lazaropoulos, â€œImprovement of Power Systems Stability by Applying Topology Identification Methodology (TIM) and Fault and Instability Identification Methodology (FIIM)â€“Study of the Overhead Medium-Voltage Broadband over Power Lines (OV MV BPL) Networks Case,â€ Trends in Renewable Energy, vol. 3, no. 2, pp. 102-128, Apr. 2017. [Online]. Available: http://futureenergysp.com/index.php/tre/article/view/34

A. G. Lazaropoulos, â€œMain Line Fault Localization Methodology in Smart Gridâ€“Part 1: Extended TM2 Method for the Overhead Medium-Voltage Broadband over Power Lines Networks Case,â€ Trends in Renewable Energy, vol. 3, no. 3, pp. 2-25, Dec. 2017. [Online]. Available: http://futureenergysp.com/index.php/tre/article/view/36

A. G. Lazaropoulos, â€œBusiness Analytics and IT in Smart Grid â€“ Part 1: The Impact of Measurement Differences on the iSHM Class Map Footprints of Overhead Low-Voltage Broadband over Power Lines Topologies,â€ Trends in Renewable Energy, vol. 6, no. 2, pp. 156-186, May 2020. [Online]. Available: http://futureenergysp.com/index.php/tre/article/view/117/pdf

M. H. Rehmani, M. Reisslein, A. Rachedi, M. Erol-Kantarci, and M. Radenkovic, â€œIntegrating renewable energy resources into the smart grid: recent developments in information and communication technologies,â€ IEEE Transactions on Industrial Informatics, vol. 14, no. 7, pp. 2814-2825, 2018.

F. R. Yu, P. Zhang, W. Xiao, and P. Choudhury, â€œCommunication systems for grid integration of renewable energy resources,â€ IEEE Network, vol. 25, no. 5, pp. 22â€“29, Sep. 2011.

B. Heile, â€œSmart grids for green communications [industry perspectives],â€ IEEE Wireless Commun., vol. 17, no. 3, pp. 4â€“6, Jun. 2010.

A. G. Lazaropoulos, â€œReview and Progress towards the Capacity Boost of Overhead and Underground Medium-Voltage and Low-Voltage Broadband over Power Lines Networks: Cooperative Communications through Two- and Three-Hop Repeater Systems,â€ ISRN Electronics, vol. 2013, Article ID 472190, pp. 1-19, 2013. [Online]. Available: http://www.hindawi.com/isrn/electronics/aip/472190/

A. S. de Beer, A. Sheri, H. C. Ferreira, and A. H. Vinck, â€œChannel frequency response for a low voltage indoor cable up to 1GHz,â€ In Power Line Communications and its Applications (ISPLC), 2018 IEEE International Symposium on, pp. 1-6, 2018.

A. G. Lazaropoulos and P. G. Cottis, â€œTransmission characteristics of overhead medium voltage power line communication channels,â€ IEEE Trans. Power Del., vol. 24, no. 3, pp. 1164-1173, Jul. 2009.

A. G. Lazaropoulos and P. G. Cottis, â€œCapacity of overhead medium voltage power line communication channels,â€ IEEE Trans. Power Del., vol. 25, no. 2, pp. 723-733, Apr. 2010.

A. G. Lazaropoulos and P. G. Cottis, â€œBroadband transmission via underground medium-voltage power lines-Part I: transmission characteristics,â€ IEEE Trans. Power Del., vol. 25, no. 4, pp. 2414-2424, Oct. 2010.

A. G. Lazaropoulos and P. G. Cottis, â€œBroadband transmission via underground medium-voltage power lines-Part II: capacity,â€ IEEE Trans. Power Del., vol. 25, no. 4, pp. 2425-2434, Oct. 2010.

E. Biglieri, â€œCoding and modulation for a horrible channel,â€ IEEE Commun. Mag., vol. 41, no. 5, pp. 92â€“98, May 2003.

M. Gebhardt, F. Weinmann, and K. Dostert, â€œPhysical and regulatory constraints for communication over the power supply grid,â€ IEEE Commun. Mag., vol. 41, no. 5, pp. 84-90, May 2003.

P. S. Henry, â€œInterference characteristics of broadband power line communication systems using aerial medium voltage wires,â€ IEEE Commun. Mag., vol. 43, no. 4, pp. 92-98, Apr. 2005.

S. Liu and L. J. Greenstein, â€œEmission characteristics and interference constraint of overhead medium-voltage broadband power line (BPL) systems,â€ in Proc. IEEE Global Telecommunications Conf., New Orleans, LA, USA, Nov./Dec. 2008, pp. 1-5.

M. GÃ¶tz, M. Rapp, and K. Dostert, â€œPower line channel characteristics and their effect on communication system design,â€ IEEE Commun. Mag., vol. 42, no. 4, pp. 78-86, Apr. 2004.

A. G. Lazaropoulos, â€œTowards Modal Integration of Overhead and Underground Low-Voltage and Medium-Voltage Power Line Communication Channels in the Smart Grid Landscape: Model Expansion, Broadband Signal Transmission Characteristics, and Statistical Performance Metrics (Invited Paper),â€ ISRN Signal Processing, vol. 2012, Article ID 121628, pp. 1-17, 2012. [Online]. Available: http://www.hindawi.com/isrn/sp/2012/121628/

D. G. Della and S. Rinaldi, â€œHybrid Communication Network for the Smart Grid: Validation of a Field Test Experience,â€ IEEE Trans. Power Del., vol. 30, no. 6, pp. 2492-2500, 2015.

F. Versolatto and A. M. Tonello, â€œAn MTL theory approach for the simulation of MIMO power-line communication channels,â€ IEEE Trans. Power Del., vol. 26, no. 3, pp. 1710-1717, Jul. 2011.

P. Amirshahi and M. Kavehrad, â€œHigh-frequency characteristics of overhead multiconductor power lines for broadband communications,â€ IEEE J. Sel. Areas Commun., vol. 24, no. 7, pp. 1292-1303, Jul. 2006.

L. Stadelmeier, D. Schneider, D. Schill, A. Schwager, and J. Speidel, â€œMIMO for inhome power line communications,â€ presented at the Int. Conf. on Source and Channel Coding, Ulm, Germany, Jan. 2008.

T. Sartenaer, â€œMultiuser communications over frequency selective wired channels and applications to the powerline access networkâ€ Ph.D. dissertation, Univ. Catholique Louvain, Louvain-la-Neuve, Belgium, Sep. 2004.

T. Calliacoudas and F. Issa, â€œâ€œMulticonductor transmission lines and cables solver,â€ An efficient simulation tool for plc channel networks development,â€ presented at the IEEE Int. Conf. Power Line Communications and Its Applications, Athens, Greece, Mar. 2002.

S. Galli and T. Banwell, â€œA deterministic frequency-domain model for the indoor power line transfer function,â€ IEEE J. Sel. Areas Commun., vol. 24, no. 7, pp. 1304-1316, Jul. 2006.

S. Galli and T. Banwell, â€œA novel approach to accurate modeling of the indoor power line channel-Part II: Transfer function and channel properties,â€ IEEE Trans. Power Del., vol. 20, no. 3, pp. 1869-1878, Jul. 2005.

A. PÃ©rez, A. M. SÃ¡nchez, J. R. ReguÃ©, M. Ribá½¹, R. AquiluÃ©, P. RodrÃ©guez-Cepeda, and F. J. Pajares, â€œCircuital and modal characterization of the power-line network in the PLC band,â€ IEEE Trans. Power Del., vol. 24, no. 3, pp. 1182-1189, Jul. 2009.

T. Sartenaer and P. Delogne, â€œDeterministic modelling of the (Shielded) outdoor powerline channel based on the multiconductor transmission line equations,â€ IEEE J. Sel. Areas Commun., vol. 24, no. 7, pp. 1277-1291, Jul. 2006.

T. Sartenaer and P. Delogne, â€œPowerline cables modelling for broadband communications,â€ in Proc. IEEE Int. Conf. Power Line Communications and Its Applications, MalmÃ¶, Sweden, Apr. 2001, pp. 331-337.

C. R. Paul, Analysis of Multiconductor Transmission Lines. New York: Wiley, 1994.

J. A. B. Faria, Multiconductor Transmission-Line Structures: Modal Analysis Techniques. New York: Wiley, 1994.

H. Meng, S. Chen, Y. L. Guan, C. L. Law, P. L. So, E. Gunawan, and T. T. Lie, â€œModeling of transfer characteristics for the broadband power line communication channel,â€ IEEE Trans. Power Del., vol. 19, no. 3, pp. 1057-1064, Jul. 2004.

A. Semlyen and B. Gustavsen, â€œPhase-domain transmission-line modeling with enforcement of symmetry via the propagated characteristic admittance matrix,â€ IEEE Trans. Power Del., vol. 27, no. 2, pp. 626-631, Apr. 2012.

A. G. Lazaropoulos, â€œStatistical Broadband over Power Lines Channel Modeling â€“ Part 1: The Theory of the Statistical Hybrid Model,â€ Progress in Electromagnetics Research C, vol. 92, pp. 1-16, 2019. [Online]. Available: http://www.jpier.org/PIERC/pierc92/01.19012902.pdf

A. G. Lazaropoulos, â€œMeasurement Differences, Faults and Instabilities in Intelligent Energy Systems â€“ Part 2: Fault and Instability Prediction in Overhead High-Voltage Broadband over Power Lines Networks by Applying Fault and Instability Identification Methodology (FIIM),â€ Trends in Renewable Energy, vol. 2, no. 3, pp. 113-142, Oct. 2016. [Online]. Available: http://futureenergysp.com/index.php/tre/article/view/27/33

A. G. Lazaropoulos, â€œMeasurement Differences, Faults and Instabilities in Intelligent Energy Systemsâ€“Part 1: Identification of Overhead High-Voltage Broadband over Power Lines Network Topologies by Applying Topology Identification Methodology (TIM),â€ Trends in Renewable Energy, vol. 2, no. 3, pp. 85-112, Oct. 2016. [Online]. Available: http://futureenergysp.com/index.php/tre/article/view/26/32

Y. Huo, G. Prasad, L. Lampe, and V. C. Leung, â€œAdvanced Smart Grid Monitoring: Intelligent Cable Diagnostics using Neural Networks,â€ in Proc. IEEE Int. Symp. Power Line Communications and its Applications, May 2020, pp. 1-6.

A. M. Tonello, N. A. Letizia, D. Righini, and F. Marcuzzi, â€œMachine learning tips and tricks for power line communications,â€ IEEE Access, vol. 7, pp. 82434-82452, 2019.

Y. Cui, X. Liu, J. Cao, and D. Xu, â€œNetwork Performance Optimization for Low-Voltage Power Line Communications,â€ MDPI Energies, vol. 11, no. 5, pp. 1266-1290, 2018.

M. Ibnkahla, â€œApplications of neural networks to digital communicationsâ€“a survey. Signal processing,â€ vol. 80, no. 7, pp. 1185-1215, 2020.

D. Okoh, Computer Neural Networks on MATLAB. CreateSpace Independent Publishing Platform, 2016.

K. P. Murphy, Machine Learning: A Probabilistic Perspective. Cambridge, MA, USA: MIT Press, 2012.

A. G. Lazaropoulos, â€œStatistical Channel Modeling of Overhead Low Voltage Broadband over Power Lines (OV LV BPL) Networks â€“ Part 1: The Theory of Class Map Footprints of Real OV LV BPL Topologies, Branch Line Faults and Hook-Style Energy Thefts,â€ Trends in Renewable Energy, vol. 6, no. 1, pp. 61-87, Mar. 2020. [Online]. Available: http://futureenergysp.com/index.php/tre/article/download/112/pdf

OPERA1, D44: Report presenting the architecture of plc system, the electricity network topologies, the operating modes and the equipment over which PLC access system will be installed, IST Integr. Project No 507667, Dec. 2005.

P. Amirshahi, â€œBroadband access and home networking through powerline networksâ€ Ph.D. dissertation, Pennsylvania State Univ., University Park, PA, May 2006.

M. Dâ€™Amore and M. S. Sarto, â€œA new formulation of lossy ground return parameters for transient analysis of multiconductor dissipative lines,â€ IEEE Trans. Power Del., vol. 12, no. 1, pp. 303-314, Jan. 1997.

M. Dâ€™Amore and M. S. Sarto, â€œSimulation models of a dissipative transmission line above a lossy ground for a wide-frequency range-Part I: Single conductor configuration,â€ IEEE Trans. Electromagn. Compat., vol. 38, no. 2, pp. 127-138, May 1996.

M. Dâ€™Amore and M. S. Sarto, â€œSimulation models of a dissipative transmission line above a lossy ground for a wide-frequency range-Part II: Multi-conductor configuration,â€ IEEE Trans. Electromagn. Compat., vol. 38, no. 2, pp. 139-149, May 1996.

A. G. Lazaropoulos, â€œBroadband Performance Metrics and Regression Approximations of the New Coupling Schemes for Distribution Broadband over Power Lines (BPL) Networks,â€ Trends in Renewable Energy, vol. 4, no. 1, pp. 43-73, Jan. 2018. [Online]. Available: http://futureenergysp.com/index.php/tre/article/view/59/pdf

A. G. Lazaropoulos, â€œNew Coupling Schemes for Distribution Broadband over Power Lines (BPL) Networks,â€ Progress in Electromagnetics Research B, vol. 71, pp. 39-54, 2016. [Online]. Available: http://www.jpier.org/PIERB/pierb71/02.16081503.pdf

I. C. Demetriou, â€œAn application of best ð¿1 piecewise monotonic data approximation to signal restoration,â€ IAENG International Journal of Applied Mathematics, vol. 53, no. 4, pp. 226-232, 2013.

I. C. Demetriou, â€œL1PMA: A Fortran 77 Package for Best L1 Piecewise Monotonic Data Smoothing,â€ Computer Physics Communications, vol. 151, no. 1, pp. 315-338, 2003.

Y. T. Ma, K. H. Liu, and Y. N. Guo, â€œArtificial neural network modeling approach to power-line communication multi-path channel,'' in Proc. Int. Conf. Neural Netw. Signal Process, Jun. 2008, pp. 229-232.

R. Hecht-Nielsen, â€œTheory of the backpropagation neural network,â€ Neural networks for perception. Academic Press, pp. 65-93, 1992.

D. Okoh, Neural Network Training Code (https://www.mathworks.com/matlabcentral/fileexchange/59362-neural-network-training-code), MATLAB Central File Exchange. Retrieved April 22, 2020.

F. Pan, W. Wang, A. K. Tung, and J. Yang, â€œFinding representative set from massive data,â€ In Fifth IEEE International Conference on Data Mining (ICDM'05), Nov. 2005.

S. V. R. Kannan and A. Veta, â€œOn clusterings: Good, bad and spectral,â€ Journal of the ACM (JACM), vol. 51, no. 3, pp. 497-515, 2000.

D. S. Hochbaum and A. Pathria, â€œAnalysis of the greedy approach in problems of maximum k-coverage,â€ Naval Research Quarterly, vol. 45, pp. 615-627, 1998.

DOI: http://dx.doi.org/10.17737/tre.2021.7.1.00133

### Refbacks

- There are currently no refbacks.

Copyright (c) 2021 Athanasios G. Lazaropoulos

This work is licensed under a Creative Commons Attribution 4.0 International License.

This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright @2014-2024 Trends in Renewable Energy (ISSN: 2376-2136, online ISSN: 2376-2144)