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2019 | Vol. 68, nr 3 | 535--551
Tytuł artykułu

A hybrid method for the optimal reactive power dispatch and the control of voltagesin an electrical energy network

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
Wydawca

Rocznik
Strony
535--551
Opis fizyczny
Bibliogr. 27 poz., rys., tab., wz.
Twórcy
  • National Polytechnic School of Oran (ENPO Maurice Audin) Department of Electrical Engineering (SCAMRE Laboratory) Road of Es-Senia, B.P. 1523 El M’Naouer, 31000, Oran, Algeria, aissabenchabira@gmail.com
  • National Polytechnic School of Oran (ENPO Maurice Audin) Department of Electrical Engineering (SCAMRE Laboratory) Road of Es-Senia, B.P. 1523 El M’Naouer, 31000, Oran, Algeria, Khiat2_2000@yahoo.fr
Bibliografia
  • [1] Weber J.D., Implementation of a Newton-Based Optimal Power Flow into a Power System Simulation Environment, B.S., University of Wisconsin, Platteville (1995).
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  • [5] QuintanaV.H., Santos-Nieto M., Reactive-power dispatch by successive quadratic programming, IEEE Transactions on Energy Conversion, vol. 4, no. 3, pp. 425–435 (1989).
  • [6] Soler E.M., Asada E.N., da Costa G.R.M., Penalty-based nonlinear solver for optimal reactive power dispatch with discrete controls, IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 2174–2182 (2013).
  • [7] Liu W.-H.E., Papalexopoulos A.D., Discrete shunt controls in a Newton optimal power flow, IEEE Transactions on Power Systems, vol. 7, no. 4, pp. 1509–1518 (1992).
  • [8] Souza R.R., Balbo A.R., Nepomuceno L., Baptista E.C., Soler E.M., Pinheiro R.B.N., A primal-dual interior/exterior point method, with combined directions and quadratic test in reactive optimal power flow problems, IEEE Latin America Transactions, vol. 15, no. 8, pp. 1413–1421 (2017).
  • [9] Yonghui N., Zhengchun D., Zhongjie W., Haoran F., PCPDIPM based optimal reactive power flow model with discrete variables, Electrical Power and Energy Systems, vol. 69, pp. 116–122 (2015).
  • [10] Yonghui N., Zhengchun D., Jiang L., AC–DC optimal reactive power flow model via predictor-corrector primal–dual interior-point method, IET Generation Transmission Distribution, vol. 7, no. 4, pp. 382–390 (2013).
  • [11] Cong Z., Haoyong C., Honwing N., Zipeng L., Manlan G., Dong H., Solution of reactive power optimization including interval uncertainty using genetic algorithm, IET Generation Transmission Distribution, vol. 11, no. 15, pp. 3657–3664 (2017).
  • [12] Chung C.Y., Liang C.H., Wong K.P., Duan X.Z., Hybrid algorithm of differential evolution and evolutionary programming for optimal reactive power flow, IET Generation Transmission Distribution, vol. 4, no. 1, pp. 84–93 (2010).
  • [13] Das D.B., Patvardhan C., A new hybrid evolutionary strategy for reactive power dispatch, Electric Power Systems Research, vol. 65, no. 2, pp. 83–90 (2003).
  • [14] Ghasemi M., Taghizadeh M., Ghavidel S., Aghaei J., Abbasian A., Solving optimal reactive power dispatch problem using a novel teaching–learning-based optimization algorithm, Engineering Applications of Artificial Intelligence, vol. 39, pp. 100–108 (2015).
  • [15] Sulaiman M.H., Mustaffa Z., Mohamed M.R., Aliman O., Using the gray wolf optimizer for solving optimal reactive power dispatch problem, Applied Soft Computing, vol. 32, pp. 286–292 (2015).
  • [16] Khazali A.H., Kalantar M., Optimal reactive power dispatch based on harmony search algorithm, International Journal of Electronical Power and Energy Systems, vol. 33, no. 3, pp. 684–692 (2011).
  • [17] Valipour K., Ghasemi A., Using a new modified harmony search algorithm to solve multi-objective reactive power dispatch in deterministic and stochastic models, Journal of AI and Data Mining (JAIDM), vol. 5, no. 1, pp. 89–100 (2017).
  • [18] Duman S., Güvenc U., Sönmez Y., Yörükeren N., Optimal power flow using gravitational search algorithm, Energy Conversion and Management, vol. 59, pp. 86–95 (2012).
  • [19] Shaw B., Mukherjee V., Ghoshal S., Solution of reactive power dispatch of power systems by an opposition based gravitational search algorithm, International Journal of Electrical Power and Energy Systems, vol. 55, pp. 29–40 (2014).
  • [20] Dai C., Chen W., Zhu Y., Zhang X., Reactive power dispatch considering voltage stability with seeker optimization algorithm, Electric Power Systems Research, vol. 79, no. 10, pp. 1462–1471 (2009).
  • [21] Rebecca Ng Shin Mei, Sulaiman M.H., Mustaffa Z., Daniyal H., Optimal reactive power dispatch solution by loss minimization using moth-flame optimization technique, Applied Soft Computing, vol. 59, pp. 210–222 (2017).
  • [22] Heidari A.A., Abbaspour R.A., Jordehi A.R., Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch, Applied Soft Computing, vol. 57, pp. 657–671 (2017).
  • [23] Rao N.T., Jagannath Ch Yadav B., Jagannadham A., optimal reactive power flow control for minimization of active power losses using particle swarm optimization, the 2015 Conference on Power, Control, Communication and Computational Technologies for Sustainable Growth (PCCCTSG), Kurnool, Andhra Pradesh, India, pp. 38–41 (2015).
  • [24] MohamedY.A., Kaamran R., Reactive power optimization based on hybrid particle swarmoptimization algorithm, the 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Montreal, QC, Canada (2012).
  • [25] Khiat M., Marano A., A primal dual interior point method to minimize total active power loss in electric power systems, International Review of Electrical Engineering (IREE), vol. 5, no. 4, pp. 1627–1632 (2010).
  • [26] Nie Y., Du Z., Wang Z., Feng H., PCPDIPM based optimal reactive power flow model with discrete Variables, International Journal of Electrical Power and Energy Systems, vol. 69, pp. 116-122 (2015).
  • [27] Ghasemi M., Ghavidel S., Ghanbarian M.M., Habibi A., A new hybrid algorithm for optimal reactive power dispatch problem with discrete and continuous control variables, Applied Soft Computing, vol. 22, pp. 126–140 (2014).
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
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