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The reactive power and voltage control management strategy based on virtual reactance cloud control

Wei Min Zhang Yan Xia Zhang
Archives of Electrical Engineering | 2020 | vol. 69 | No 4 | 921-936 | DOI: 10.24425/aee.2020.134639
Keywords cloud model graph theory virtual reactance voltage reactive power management
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Abstract

The paper aims at the higher reactive power management complexity caused by the access of distributed power, and the problem such as large data exchange capacity, low accuracy of reactive power distribution, a slow convergence rate, and so on, may appear when the controlled objects are large. This paper proposes a reactive power and voltage control management strategy based on virtual reactance cloud control. The coupling between active power and reactive power in the system is effectively eliminated through the virtual reactance. At the same time, huge amounts of data are treated to parallel processing by using the cloud computing model parallel distributed processing, realize the uncertainty transformation between qualitative concept and quantitative value. The power distribution matrix is formed according to graph theory, and the accurate allocation of reactive power is realized by applying the cloud control model. Finally, the validity and rationality of this method are verified by testing a practical node system through simulation.

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Authors and Affiliations

Wei Min Zhang
Yan Xia Zhang

Improving Segmentation of 3D Retina Layers Based on Graph Theory Approach for Low Quality OCT Images

Agnieszka Stankiewicz Tomasz Marciniak Adam Dąbrowski Marcin Stopa Piotr Rakowicz Elżbieta Marciniak
Metrology and Measurement Systems | 2016 | vol. 23 | No 2 | 269-280 | DOI: 10.1515/mms-2016-0016
Keywords optical coherence tomography (OCT) segmentation of retinal layers image segmentation graph theory
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Abstract

This paper presents signal processing aspects for automatic segmentation of retinal layers of the human eye. The paper draws attention to the problems that occur during the computer image processing of images obtained with the use of the Spectral Domain Optical Coherence Tomography (SD OCT). Accuracy of the retinal layer segmentation for a set of typical 3D scans with a rather low quality was shown. Some possible ways to improve quality of the final results are pointed out. The experimental studies were performed using the so-called B-scans obtained with the OCT Copernicus HR device.

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Authors and Affiliations

Agnieszka Stankiewicz
Tomasz Marciniak
Adam Dąbrowski
Marcin Stopa
Piotr Rakowicz
Elżbieta Marciniak

Multi-sourced power system restoration strategy based on modified Prim’s algorithm

Artur Łukaszewski Łukasz Nogal
Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 5 | e137942 | DOI: 10.24425/bpasts.2021.137942
Keywords self-healing grid micro-grid reconfiguration greedy algorithms graph theory simulations Prim’s algorithm
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Abstract

Self-healing grids are one of the most developing concepts applied in electrical engineering. Each restoration strategy requires advanced algorithms responsible for the creation of local power systems. Multi-agent automation solutions dedicated for smart grids are mostly based on Prim’s algorithm. Graph theory in that field also leaves many problems unsolved. This paper is focused on a variation of Prim’s algorithm utility for a multi-sourced power system topology. The logic described in the paper is a novel concept combined with a proposal of a multi-parametrized weight calculation formula representing transmission features of energy delivered to loads present in a considered grid. The weight is expressed as the combination of three elements: real power, reactive power, and real power losses. The proposal of a novel algorithm was verified in a simulation model of a power system. The new restoration logic was compared with the proposal of the strategy presented in other recently published articles. The novel concept of restoration strategy dedicated to multi-sourced power systems was verified positively by simulations. The proposed solution proved its usefulness and applicability.
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Bibliography

  1.  S.A. Arefifar, Y.A.-R.I. Mohamed, and T.H.M. EL-Fouly, “Comprehensive Operational Planning Framework for Self-Healing Control Actions in Smart Distribution Grids,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4192‒4200, 2013, doi: 10.1109/tpwrs.2013.2259852.
  2.  J. Quiros-Tortos and V. Terzija, “A Graph Theory Based New Approach for Power System Restoration,” in Proc. 2013 IEEE Grenoble PowerTech (POWERTECH), 2013, doi: 10.1109/ptc.2013.6652108.
  3.  T.D. Sudhakar and K.N. Srinivs, “Power System Reconfiguration Based on Prim’s Algorithm,” in Proc. 2011 1st International Conference on Electrical Energy Systems (ICEES), 2011, doi: 10.1109/ICEES.2011.5725295.
  4.  M.M. Ibrahim, H.A. Mostafa, M.M.A. Salama, R. El-Shatshat, and K.B. Shaban, “A Graph-theoretic Service Restoration Algorithm for Power Dystribution Systems,” in Proc. 2018 International Conference on Innovative Trends in Computer Engineering (ITCE), 2018, doi: 10.1109/itce.2018.8316647.
  5.  A. Golshani, W. Sun, and K. Sun, “Advanced power system partitioning method for fast and reliable restoration: toward a self-healing grid,” IET Gener. Transmiss. Distrib., vol. 12, no,1, pp.45‒52, 2018, doi: 10.1049/iet-gtd.2016.1797.
  6.  J. Quiros-Tortos, M. Panteli, P. Wall, and V. Tereija, “Sectionalising methodology for paraller system restoration based on graph theory,” IET Gener. Transmiss. Distrib., vol. 9, no. 11, pp. 1216‒1225, 2015, doi: 10.1049/iet-gtd.2014.0727.
  7.  M. Parol, P. Kapler, J. Marzecki, R. Parol, M. Połecki, and Ł. Rokitnicki, “Effective approach to distributed optimal operation control in rural low voltage microgrids,” Bull. Pol. Acad. Sci. Tech. Sci, vol. 68, no. 4, pp. 661‒678, 2020, doi: 10.24425/bpasts.2020.134178.
  8.  S. Sannigrahi, S.R. Ghatak, and P. Acharjee, “Multi-objective optimisation-based active distribution system planning with reconfiguration, intermittent RES and DSTATCOM,” IET Renew. Power Gener., vol. 13, no. 13, pp. 2418‒2429, 2019, doi: 10.1049/iet-rpg.2018.6060.
  9.  A. Bonfilio, M. Invernizzi, A. Labella, and R. Procopio, “Design and Implementation of a Variable Synthetic Inertia Controller for Wind Turbine Generators,” IEEE Trans. Power Syst., vol. 34, no. 1, pp. 754‒764, 2019, doi: 10.1109/tpwrs.2018.2865958.
  10.  F. Vazinram, R. Effatnejad, M. Hedayati, and P. Hajihosseini, “Decentralised self-healing model for gas and electricity distribution network,” IET Gener. Transmiss. Distrib., vol. 13, no.  19, pp. 4451‒4463, October 2019, doi: 10.1049/iet-gtd.2019.0416.
  11.  M. Eriksson, M. Armendariz, O. Vasilenko, A. Saleem, and L. Nordström, “Multi-Agent Based Distribution Automation Solution for Self-Healing Grids,” IEEE Trans. Ind. Electron., vol.  62, no. 4, pp. 2620‒2628, 2015, doi: 10.1109/tie.2014.2387098.
  12.  J. Li, Reconfiguration of power network based on graph-theoretic algorithms, Graduate Theses and Dissertations, Iowa State University, 2010, pp. 10‒35, doi: 10.31274/etd-180810-2753.
  13.  T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, “Section 23.2: The algorithms of Kruscal and Prim” in Introduction to Algorithms, 3rd ed., MIT Press, 2009, pp. 631‒638.
  14.  J. Ansari, A. Gholami, and A. Kazemi, “Multi-agent systems for reactive power control in smart grids,” Int. J. Electr. Power Energy Syst., vol. 83, pp. 411‒425, 2016, doi: 10.1016/j.ijepes.2016.04.010.
  15.  M. Borecki, M. Ciuba, Y. Kharchenko, and Y. Khanas, “Substation reliability evaluation in the context of the stability prediction of power grids,” Bull. Pol. Acad. Sci. Tech. Sci, vol. 68, no. 4, pp. 769‒776, 2020, doi: 10.24425/bpasts.2020.134170.
  16.  Q. Wang, S. Tao, X. Du, C. Zhong, and Y. Tang, “Coordinating Control Strategy for Multi Micro Energy Systems Within Distribution Grid Considering Dynamic Characteristics and Contradictory Interests,” IEEE Access, vol. 7, pp. 139548‒139559, 2019, doi: 10.1109/ access.2019.2943926.
  17.  Z. Wang and J. Wang, “Self-healing resilient distribution systems based on sectionalization into microgrids,” IEEE Trans. Power Syst., vol. 30, no. 6, pp. 3139‒3149, 2015, doi: 10.1109/tpwrs.2015.2389753.
  18.  W. Bąchorek and M. Benesz, “Analysis of sectionizing switch placement in medium voltage distribution networks in the aspect of improving the continuity of power supply,” Bull. Pol. Acad. Sci. Tech. Sci, vol. 68, no. 3, pp. 459‒466, 2020, doi: 10.24425/bpasts.2020.133377.
  19.  R.J. Wilson, Introduction to Graph Theory, London, Pearson Education Limited, 2010, pp. 8‒79.
  20.  J.A. Bondy and U.S.R. Murty, Graph theory with applications. London, Citeseer, 1976, pp. 10‒55.
  21.  B.S. Torres, L.R. Ferreira, and A.R. Aoki, “Distributed Intelligent System for Self-Healing in Smart Grids,” IEEE Trans. Power Del., vol. 33, no. 5, pp. 2394‒2403, 2018, doi: 10.1109/tpwrd.2018.2845695.
  22.  X. Yang, Y. Zhang, H. He, S. Ren, and G. Weng, “Real-Time Demand Side Management for a Microgrid Considering Uncertainties,” IEEE Trans. Smart Grid, vol. 10, no. 3, pp. 3401‒3414, 2019, doi: 10.1109/tsg.2018.2825388.
  23.  A. Younesi, H. Shayeghi, A. Safari, and P. Siano, “Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation,” Energy, vol. 207, 118220, 2020, doi: 10.1016/j.energy.2020.118220.
  24.  Y. Shen, Y. Chen, J. Zhang, Z. Sang, and Q. Zhou, “Self-Healing Evaluation of Smart Distribution Network Based on Uncertainty Theory,” IEEE Access, vol. 7, pp. 140022‒140029, 2019, doi: 10.1109/access.2019.2939537.
  25.  K. Anoh, S. Maharjan, A. Ikpehai, Y. Zhang, and B. Adebisi, “Energy Peer-to-Peer Trading in Virtual Microgrids in Smart Grids: A Game- Theoretic Approach,” IEEE Trans. Smart Grid, vol. 11, no. 2, pp. 1264‒1275, 2020, doi: 10.1109/tsg.2019.2934830.
  26.  A. Chris and V. Koivunen, “Coalitional Game-Based Cost Optimalization of Energy Portfolio in Smart Grid Communities,” IEEE Trans. Smart Grid, vol. 10, no. 2, pp. 1960‒1970, 2019, doi: 10.1109/TSG.2017.2784902.
  27.  M. Zadsar, M.R. Haghifam, and S.M.M. Larimi, “Approach for self-healing resilient operation of active distribution network with microgrid,” IET Gener. Transmiss. Distrib., vol. 11, no. 18, pp. 4633‒4643, 2017, doi: 10.1049/iet-gtd.2016.1783.
  28.  W. Jiang, C. Yang, Z. Liu, M. Liang, P. Li, and G. Zhou, “A Hierarchical Control Structure of Distributed Energy Storage System in DC Micro-Grid,” IEEE Access, vol. 7, pp. 128787‒128795, 2019, doi: 10.1109/access.2019.2939626.
  29.  K. Karimizadeh, S. Soleymani, and F. Faghihi, “Optimal placement of DG units for the enhancement of MG networks performance using coalition game theory,” IET Gener. Transmiss. Distrib., vol. 14, no. 5, pp. 853‒862, 2020, doi: 10.1049/iet-gtd.2019.0070.
  30.  J. Machowski, J. W. Bialek, and J. R. Bumby, Power System Dynamics: Stabilty and Control. Haboken, New Jersey, John Wiley & Sons, Ltd., 2008, pp. 89‒99.
  31.  P. Li, J. Ji, H. Ji, G. Song, Ch. Wang, and J. Wu, “Self-healing oriented supply restoration method based on the coordination of multiple SOPs in active distribution networks,” Energy, vol. 195, 116968, 2020, doi: 10.1016/j.energy.2020.116968.
  32.  S. Pochpor and H.M. Suryawanshi, “Design and Analysis of Triplen Controlled Resonant Converter for Renewable Sources to Interface DC Micro Grid,” IEEE Access, vol. 7, pp. 15330‒15339, 2019, doi: 10.1109/access.2019.2891165.
  33.  S. Heinen and M.J. O’Malley, “Complementarities of Supply and Demand Sides in Integrated Energy Systems,” IEEE Trans. Smart Grid, vol. 10, no. 1, pp. 1156‒1165, 2019, doi: 10.1109/tsg.2018.2871393.
  34.  F. Liberati, A. Di Giorgio, A. Giuseppi, A. Pietrabissa, E. Habib, and L. Martirano, “Joint Model Predictive Control of Electric and Heating Resources in a Smart Building,” IEEE Trans. Ind. Electron, vol. 55, no. 6, pp. 7015‒7027, 2019, doi: 10.1109/TIA.2019.2932954.
  35.  A. Mojallal, S. Lotfifard, and S.M. Azimi, “A Nonlinear Supplementary Controller for Transient Response Improvement of Distributed Generations in Micro-Grids,” IEEE Trans. Sustain. Energy, vol. 11, no. 1, pp. 489‒499, 2020, doi: 10.1109/tste.2019.2895961.
  36.  S. Gude and Ch-Ch Chu, “Single Phase Enhanced Phase-Locked Loops Based on Multiple Delayed Signal Cancellation Filters for Micro- Grid Applications,” IEEE Trans. Ind. Electron, vol. 55, no.  6, pp. 7122‒7133, 2019, doi: 10.1109/TIA.2019.2915563.
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Authors and Affiliations

Artur Łukaszewski
ORCID: ORCID
Łukasz Nogal
ORCID: ORCID

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