Development of ANN Controlled UPFC Based Protection Model for Nigerian 330kv Power Lines
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This paper, proposed the use of artificial neural network (ANN) based UPFC for transmission network loss minimization. The overall effect of power losses on the system is a reduction in the quantity of power available to the consumers. Power loss leads to high cost of power generation, transmission and distribution. Unlike exiting up change and regulating transformer techniques for loss reduction, FACTS devices have fast switching capability and can be subjected to very free control algorithms for more optimal performance in loss reduction application in power systems. The neural network was modeled to output the firing angle to enable the FACTS device effectively control the adsorption and injection of reactive power for transmission loss reduction. The Nigerian 330KV power grid was used as a case study for the evaluation of the proposed power loss reduction system A digital model of the case study power system with the proposed neural network controlled UPFC integrated was created in the MATLAB/SIMULINK programming environment. Genetic algorithm was used for the optimal placement of the FACTS device in the MATLAB/SIMULINK model of the Nigerian 330KV transmission system. Simulation carried out involved alteration of power flow in order to cause different levels and distribution of losses in the network. With each variation, load flows was carried out to evaluate the distribution of losses and the active and reactive loss reduction achieved by the proposed system. The simulation and evaluation were carried out under two scenarios: (i) with the UPFC installed and (ii) without the UPFC installed. With each variation of the load at the bus, load flow is run to determine total system loss either with the UPFC installed or without the UPFC installed. Results obtained showed that the proposed system achieved an average active power loss reduction of 12.8416% and an average reactive power loss reduction of 21.82%.
Bamigbola, O., M. Ali, and M. Oke(2014), Mathematical modeling of electric power flow and the minimization of power losses on transmission lines. Applied Mathematics and Computation, p. 214-221.
Magadum, M.R.B. and M.T.M. Timsani(2016), Minimization of Power Loss in Distribution Networks by Different Techniques, pp. 13-45
Bayliss C.R(2001), Transmission and Distribution Electrical Engineering, London: Newness, 2nd ed , pp. 11-23.
Lukman D & Blackburn T.R (2004), Modified algorithm of load flow simulation for loss minimization in power systems, Proceedings of the Australian Universities Power Engineering Conference (AUPEC 94) pp.34,37
Engr. H. S. Labo(2010), Current status and future outlook of the transmission network, pp.12-22
M S Bhalla(2013),Transmission and Distribution Losses (Power)
M. Vilathgamuwa, X. Zhu, and S. S. Choi(2000), A robust control method to improve the performance of a unified power flow controller, Electrical Power System Research, vol. 55, pp. 103-111.
B. C. Pal(2002) , Robust damping of interarea oscillations with unified power flow controller, IEE Proceedings on Generation, Transmission, Distribution, vol. 149, no. 6, pp. 733-738.
H. M. A. Rahim, and S. A. Al-Baiyat(2004), A robust damping controller design for a unified power flow controller, in Proc. 39th IEEE Universities Power Engineering Conference, (UPEC), IEEE, Bristol, pp. 265-269.
A.H M.A. Rahim, J. M. Bakhashwain, and S. A. Al-Baiyat(2006), Robust damping controls for a unified power flow controller, International Journal of Emerging Electric Power Systems, vol. 6, no. 2, pp. 1-21.
S. A. Taher, S. Akbari, A. Abdolalipour, and R. Hematti(2010), Robust decentralized controller design for UPFC using μ-synthesis, Communications in Nonlinear Science and Numerical Simulation, vol. 15, pp. 2149-2161.
Numphetch, S., Uthen, L., Umaporn, K., Dusit, U. & Thanatchai, K. (2011), Loss Minimization Using Optimal Power Flow based on Swarm Intelligences , ECTI Transactions on Electrical, Electronic and Communication Engineering, 9 (1), pp 212-222.
T.S. Abdel-Salam, A.Y. Chikhani, R. Hackam(2015). A new technique for loss reduction using compensating capacitors applied to distribution systems with varying lad conditions. IEEE Transactions on Power Delivery, Vol.9, No. 2, pp. 819-827
N. Acharya, P. Mahat, N. Mithulananthan(2006), An analytical approach for DG allocation in distribution network., International Journal of Electric Power and Energy System, Vol.28, No. 10, pp.669-678
F. Sheidei, M. Shadkam, M. Zarei(2008). Optimal distributed generation allocation in sub-transmission systems employing ant colony to reduce losses, In: proceedings of 43 rd International universities Power Engineering conference UPEC; pp.44-67
Y.M. Atwa, E.F. EI-Saadany, M.M.A. Salama, R. Seethapathy(2016),Optimal renewable resources mix for active loss minimization, IEEE Transaction on Power System, Vol.25, No.1, pp. 360-370
R.S. AI Abri, E.F. EI-Saadany, Y.M. Atwa, (2014), Optimal placement and sizing method to improve active power loss reduction in sub-transmission systems, IEEE Transactions on Power System, Vol. 28, No. 1, pp. 326-334
Julluri Namratha Manohar, Amarnath Jinka, Vemuri Poornachandra Rao(2012 ), Optimization of Loss Minimization Using FACTS in Deregulated Power Systems, Innovative Systems Design and Engineering ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online) Vol 3, No 3 pp.231-239
