ANN based On-Load Tap Changer for Distribution Network with Distributed Generation

Halil Cimen, Emre Hasan Dursun, Mehmet Şefik Üney

Abstract


Number of distributed generation (DG) plants integrated to utility network increases due to rising of electricity consumption. DG plants have a big impact on voltage level of network in accordance with this increasing. Especially DG plants based on renewable resources may cause voltage rise and drop because of their intermittently energy generation. Generally, the voltage level is regulated by reactive power control technique and On-load tap changer (OLTC). Generally, HV/MV transformers use OLTC to regulate the voltage level under load. The conventional voltage control techniques depend on current of branch at the main substation end. If the rising of DG installation is taken into consideration, the conventional methods can be inadequate. Artificial intelligence techniques can be used to mitigate this problem. In this paper, an Artificial Neural Networks (ANN) model is designed for determination of OLTC best tap position. ANN model is trained by using different values of network voltage level, DG generation values and amount of load demand. Designed model is applied on electrical network of Selcuk University. The electrical network of Selcuk University is modeled by using PSCAD/EMTDC. 1MW Photovoltaic (PV) power plant is determined as DG plant.


Keywords


Distributed generation; voltage regulation; OLTC; ANN; artificial intelligence; photovoltaic power plant.

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References


P. P. Barker and R. W. D. Mello, "Determining the impact of distributed generation on power systems. I. Radial distribution systems," in 2000 Power Engineering Society Summer Meeting, 2000, vol. 3, pp. 1645-1656 vol. 3.

W. El-Khattam and M. Salama, "Distributed generation technologies, definitions and benefits," Electric power systems research, vol. 71, no. 2, pp. 119-128, 2004.

R. A. Shalwala, "PV Integration into Distribution Networks in Saudi Arabia," University of Leicester, 2012.

M. A. Azzouz, H. E. Farag, and E. F. El-Saadany, "Fuzzy-based control of on-load tap changers under high penetration of distributed generators," in 2013 3rd International Conference on Electric Power and Energy Conversion Systems, 2013, pp. 1-6.

I. Ali and S. Kucuksari, "Voltage regulation of unbalanced distribution network with distributed generators," in 2016 North American Power Symposium (NAPS), 2016, pp. 1-6.

N. H. Hashim, T. K. A. Rahman, M. F. A. Latip, and I. Musirin, "Application of ANN to determine the OLTC in minimizing the real power losses in a power system," in Proceedings. National Power Engineering Conference, 2003. PECon 2003., 2003, pp. 66-70.

S. K. Salman and Z. G. Wan, "Fuzzy Logic-Based AVC Relay for Voltage Control of Distribution Network with and without Distributed/Embedded Generation," in 2007 IEEE Lausanne Power Tech, 2007, pp. 2128-2132.

T. Ackermann, G. Andersson, and L. Söder, "Distributed generation: a definition," Electric power systems research, vol. 57, no. 3, pp. 195-204, 2001.

J. Ekanayake, N. Jenkins, K. Liyanage, J. Wu, and A. Yokoyama, Smart grid: technology and applications. John Wiley & Sons, 2012.

L. Fausett, Fundamentals of neural networks: architectures, algorithms, and applications. Prentice-Hall, Inc., 1994.




DOI: http://dx.doi.org/10.22385/jctecs.v15i0.237