ORIGINAL_ARTICLE
Constrained Controllability of Linear Discrete Time Systems: A sufficient condition based on Farkas' Lemma
This paper provides sufficient conditions for controllability of discrete time linear systems with input saturation. Controllability is a central notion in linear system theory, optimal quadratic regulators as well as model predictive control algorithms. The more realistic notion of constrained controllability has given less attention probably due to mathematical complications. Most of the existing works on constrained controllability studies the properties of reachable sets. However, there are only a few works which investigate the problem of whether a state is reachable or not. In this paper, a set of sufficient conditions are firstly given for constrained controllability of time varying linear systems in discrete time formulation. The given conditions are obtained using the Farkas’ lemma for alternative inequalities. The obtained results improve existing literature by providing conditions for both null-controllability and controllability regardless of the system stability. A sufficient condition is then given for the special case of time invariant single input linear systems with diagonal Jordan canonical form. Numerical examples are given for clarification.
http://jadsc.aliabadiau.ac.ir/article_679220_283f5face1213c3a3479f79ac3382b24.pdf
2020-12-31
1
10
Controllability
Input constraint
Saturation
Constrained control
Farkas’ lemma
Mohammad mahdi
Share pasand
sharepasand@standard.ac.ir
1
Department of Electrical Engineering, Standard Research Institute, Tehran, Iran
LEAD_AUTHOR
[1] Kalman, Rudolf Emil. "Contributions to the theory of optimal control." Bol. Soc. Mat. Mexicana 5.2 (1960): 102-119.
1
[2] Hu, Tingshu, and Zongli Lin. Control systems with actuator saturation: analysis and design. Springer Science & Business Media, 2001.
2
[3] Share Pasand, Mohammad Mahdi, and Mohsen Montazeri. "Structural properties, LQG control and scheduling of a networked control system with bandwidth limitations and transmission delays." IEEE/CAA Journal of Automatica Sinica (2017).
3
[4] Longo, Stefano, et al. Optimal and robust scheduling for networked control systems. CRC press, 2013.
4
[5] Share Pasand, Mohammad Mahdi, and Mosen Montazeri. "L-Step Reachability and Observability of Networked Control Systems with Bandwidth Limitations: Feasible Lower Bounds on Communication Periods." Asian Journal of Control 19.4 (2017): 1620-1629.
5
[6] Share Pasand, Mohammad Mahdi, and Mohsen Montazeri. "Structural Properties of Networked Control Systems with Bandwidth Limitations and Delays." Asian Journal of Control 19.3 (2017): 1228-1238.
6
[7] Share Pasand, Mohammad Mahdi, and Mohsen Montazeri. "Controllability and stabilizability of multi-rate sampled data systems." Systems & Control Letters 113 (2018): 27-30.
7
[8] Wing, J., and C. Desoer. "The multiple-input minimal time regulator problem (general theory)." IEEE Transactions on Automatic Control 8.2 (1963): 125-136.
8
[9] Son, Nguyen Khoa. "Controllability of linear discrete-time systems with constrained controls in Banach spaces." Control and Cybernetics 10.1-2 (1981): 5-16.
9
[10] Sontag, Eduardo D. "An algebraic approach to bounded controllability of linear systems." International Journal of Control 39.1 (1984): 181-188.
10
[11] Evans, M. E. "The convex controller: controllability in finite time." International journal of systems science 16.1 (1985): 31-47.
11
[12] Nguyen, K. S. "On the null-controllability of linear discrete-time systems with restrained controls." Journal of optimization theory and applications 50.2 (1986): 313-329.
12
[13] d'Alessandro, Paolo, and Elena De Santis. "Reachability in input constrained discrete-time linear systems." Automatica 28.1 (1992): 227-229.
13
[14] Lasserre, Jean B. "Reachable, controllable sets and stabilizing control of constrained linear systems." Automatica 29.2 (1993): 531-536.
14
[15] Van Til, Robert P., and William E. Schmitendorf. "Constrained controllability of discrete-time systems." International Journal of Control 43.3 (1986): 941-956.
15
[16] Hu, Tingshu, Daniel E. Miller, and Li Qiu. "Null controllable region of LTI discrete-time systems with input saturation." Automatica 38.11 (2002): 2009-2013.
16
[17] Hu, Tingshu, Zongli Lin, and Ben M. Chen. "Analysis and design for discrete-time linear systems subject to actuator saturation." Systems & Control Letters 45.2 (2002): 97-112.
17
[18] Heemels, W. P. M. H., and M. Kanat Camlibel. "Null controllability of discrete-time linear systems with input and state constraints." Decision and Control, 2008. CDC 2008. 47th IEEE Conference on. IEEE, 2008.
18
[19] Rakovic, Sasa V., et al. "Reachability analysis of discrete-time systems with disturbances." IEEE Transactions on Automatic Control 51.4 (2006): 546-561.
19
[20] Schmitendorf, W. E., and B. R. Barmish. "Null controllability of linear systems with constrained controls." SIAM Journal on control and optimization 18.4 (1980): 327-345.
20
[21] Klamka, Jerzy. "Constrained approximate controllability." IEEE Transactions on Automatic Control 45.9 (2000): 1745-1749.
21
[22] Fashoro, M., O. Hajek, and K. Loparo. "Controllability properties of constrained linear systems." Journal of optimization theory and applications 73.2 (1992): 329-346.
22
[23] Kurzhanski, Alexander B., and Pravin Varaiya. "Ellipsoidal techniques for reachability under state constraints." SIAM Journal on Control and Optimization 45.4 (2006): 1369-1394.
23
[24] Kerrigan, Eric C., John Lygeros, and Jan M. Maciejowski. "A geometric approach to reachability computations for constrained discrete-time systems." IFAC Proceedings Volumes 35.1 (2002): 323-328.
24
[25] Rakovic, Sasa V., Eric C. Kerrigan, and David Q. Mayne. "Reachability computations for constrained discrete-time systems with state-and input-dependent disturbances." 42nd IEEE International Conference on Decision and Control (IEEE Cat. No. 03CH37475). Vol. 4. IEEE, 2003.
25
[26] Gusev, M. I. "Internal approximations of reachable sets of control systems with state constraints." Proceedings of the Steklov Institute of Mathematics 287.1 (2014): 77-92.
26
[27] Bravo, José Manuel, Teodoro Alamo, and Eduardo F. Camacho. "Robust MPC of constrained discrete-time nonlinear systems based on approximated reachable sets." Automatica 42.10 (2006): 1745-1751.
27
[28] Dueri, Daniel, et al. "Finite-horizon controllability and reachability for deterministic and stochastic linear control systems with convex constraints." 2014 American Control Conference. IEEE, 2014.
28
[29] Faulwasser, Timm, Veit Hagenmeyer, and Rolf Findeisen. "Constrained reachability and trajectory generation for flat systems." Automatica 50.4 (2014): 1151-1159.
29
[30] Border, Kim C. "Alternative linear inequalities." Cal Tech Lecture Notes (2013).
30
[31] Dinh, N., and V. Jeyakumar. "Farkas’ lemma: three decades of generalizations for mathematical optimization." Top 22.1 (2014): 1-22.
31
[32] Dax, Achiya. "Classroom Note: An Elementary Proof of Farkas' Lemma." SIAM review 39.3 (1997): 503-507.
32
[33] Bartl, David. "A short algebraic proof of the Farkas’ lemma." SIAM Journal on Optimization 19.1 (2008): 234-239.
33
[34] Bartl, David. "A very short algebraic proof of the Farkas’ Lemma." Mathematical Methods of operations research 75.1 (2012): 101-104.
34
[35]Antsaklis, Panos J., and Anthony N. Michel. Linear systems. Springer Science & Business Media, 2006.
35
[36] Hristu-Varsakelis, Dimitris. "Short-period communication and the role of zero-order holding in networked control systems." IEEE Transactions on automatic control 53.5 (2008): 1285-1290.
36
ORIGINAL_ARTICLE
Improving the Insulating Properties of Transformer Oil Using Nanomaterials with Regard to Thermal Aging
Incorporation of nanoparticles into transformer oils improves their electrical and insulating properties. However, thermal aging may undesirably decrease the performance of nanomaterials in transformer oils. Herein, pure oil together with TiO2, ZnO, and CNTs incorporated oil (nanofluids) can underwent thermal aging by simulating this phenomenon at 110, 120, and 130 ° C for 30, 30, and 15 days (equivalent of 10, 30, and more than 40 years of normal oil operation, respectively). During the accelerated thermal aging process, the total acid number (TAN), breakdown voltage, and lightning impulse breakdown voltage of all samples were measured periodically. The TAN increased with increasing temperature and time, but never exceeded the allowable level of 1.2 mg KOH/g. As the oil ages, its corrosion rate increases, which is undesirable for the transformer. The results of the breakdown voltage test suggest that the TiO2 was the best candidate, such that the breakdown voltage increased with respect to the pure oil by 17, 27, and 48% at 110, 120, and 130 °C, respectively. The outcome of the lightning breakdown test also indicated that TiO2 still performed better than the other samples. TiO2 was able to improve the lightning voltage at 110, 120, and 130 °C by 33, 8, and 5%, respectively. Therefore, as it was observed, TiO2 has been able to perform the best performance in thermal aging.
http://jadsc.aliabadiau.ac.ir/article_679266_fa8c59ef3bcaf9f5d052860d4af870ee.pdf
2020-12-01
11
16
Transformer oil
Thermal aging
Breakdown voltage
Lightning breakdown
Nanoparticle
Amir
Hamed Mashhadzadeh
amir.hamed.m@gorganiau.ac.ir
1
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran.
AUTHOR
Mahmood
Ghanbari
ghanbari@gorganiau.ac.ir
2
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran.
LEAD_AUTHOR
Amangaldi
Koochaki
koochaki@aliabadiau.ac.ir
3
Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
AUTHOR
Seyyedmeysam
Seyyedbarzegar
seyyedbarzegar@shahroodut.ac.ir
4
Department of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran
AUTHOR
Morteza
Ghorbanzadeh Ahangari
m.ghorbanzadeh@umz.ac.ir
5
Department of Mechanical Engineering, Faculty of Engineering and Technology, University of Mazandaran, Babolsar, Iran
AUTHOR
[1] Loiselle, L., et al., Comparative studies of the stability of various fluids under electrical discharge and thermal stresses. IEEE Transactions on Dielectrics and Electrical Insulation, 2015. 22(5): p. 2491-2499.
1
[2] Meshkatoddini, M.R. and S. Abbospour, Aging study and lifetime estimation of transformer mineral oil. American J. of Engineering and Applied sciences, 2008. 1(4): p. 384-388.
2
[3] Sun, P., et al., Effects of impulse waveform parameters on the breakdown characteristics of nano-TiO 2 modified transformer oil. IEEE Transactions on Dielectrics and Electrical Insulation, 2018. 25(5): p. 1651-1659.
3
[4] Yang, Q., et al., Space charge inhibition effect of nano-Fe3O4 on improvement of impulse breakdown voltage of transformer oil based on improved Kerr optic measurements. AIP Advances, 2015. 5(9): p. 097207.
4
[5] Xiao, G., et al., Competitive adsorption of gases dissolved in transformer oil on Co-doped ZnO (0001) surface. Computational Materials Science, 2018. 142: p. 72-81.
5
[6] Du, Y., et al., Effect of water adsorption at nanoparticle–oil interface on charge transport in high humidity transformer oil-based nanofluid. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2012. 415: p. 153-158.
6
[7] Zhou, Q., et al. Nano-tin oxide gas sensor detection characteristic for hydrocarbon gases dissolved in transformer oil. in 2012 International Conference on High Voltage Engineering and Application. 2012. IEEE.
7
[8] Cui, H., et al., Adsorption and sensing of CO and C2H2 by S-defected SnS2 monolayer for DGA in transformer oil: A DFT study. Materials Chemistry and Physics, 2020: p. 123006.
8
[9] Nagendran, S. and S. Chandrasekar, Investigations on Partial Discharge, Dielectric and Thermal Characteristics of Nano SiO₂ Modified Sunflower Oil for Power Transformer Applications. Journal of Electrical Engineering & Technology, 2018. 13(3): p. 1337-1345.
9
[10] Selvaraj, D.E., Partial discharge characteristics of enamel filled with micro and nano composite of siO2 and TiO2. International Journal of Science and Engineering Applications, 2012. 1(2): p. 95-101.
10
[11] Muangpratoom, P. and N. Pattanadech, Breakdown and partial discharge characteristics of mineral oil-based nanofluids. IET Science, Measurement & Technology, 2018. 12(5): p. 609-616.
11
[12] Aberoumand, S. and A. Jafarimoghaddam, Tungsten (III) oxide (WO3)–Silver/transformer oil hybrid nanofluid: Preparation, stability, thermal conductivity and dielectric strength. Alexandria engineering journal, 2018. 57(1): p. 169-174.
12
[13] Ghaffarkhah, A., et al., On evaluation of thermophysical properties of transformer oil-based nanofluids: a comprehensive modeling and experimental study. Journal of Molecular Liquids, 2020. 300: p. 112249.
13
[14] Wang, Z., et al., Thermal-conductivity and thermal-diffusivity measurements of nanofluids by 3ω method and mechanism analysis of heat transport. International Journal of Thermophysics, 2007. 28(4): p. 1255-1268.
14
[15] Tsuboi, T., et al., Aging effect on insulation reliability evaluation with weibull distribution for oil-immersed transformers. IEEE Transactions on Dielectrics and Electrical Insulation, 2010. 17(6): p. 1869-1876.
15
[16] Segal, V., et al., Accelerated thermal aging of petroleum-based ferrofluids. Journal of magnetism and magnetic materials, 1999. 201(1-3): p. 70-72.
16
[17] Liang, N., et al., Effect of nano Al2O3 doping on thermal aging properties of oil-paper insulation. Energies, 2018. 11(5): p. 1176.
17
[18] Rafiq, M., et al., Transformer oil-based nanofluid: The application of nanomaterials on thermal, electrical and physicochemical properties of liquid insulation-A review. Ain Shams Engineering Journal, 2020.
18
[19] Du, Y., et al., Effect of electron shallow trap on breakdown performance of transformer oil-based nanofluids. Journal of Applied Physics, 2011. 110(10): p. 104104.
19
ORIGINAL_ARTICLE
FTC of Three-phase Induction Motor Drives under Current Sensor Faults
In this study, single-phase current sensor Fault-Tolerant Control (FTC) for Three-Phase Induction Motor (TPIM) drives using a flux observer is proposed. In the proposed FTC scheme, a 3rd difference operator executes the Fault Detection (FD) task and the reconstruction of the faulted current is achieved through a flux observer. The presented FTC system is able to switch TPIM drive systems from normal mode to the faulty mode suitably. The proposed method in this study can be utilized in many industries particularly in electric vehicles, medical devices, and aerospace where TPIM drive systems are needed to continue the desired operation even during fault situations. The effectiveness of the proposed FTC system is confirmed by experiments on a 0.75kW TPIM drive platform.
http://jadsc.aliabadiau.ac.ir/article_679268_9fdc6bd02f814b660655a27dd0144e60.pdf
2020-12-01
17
22
Fault-Tolerant control
flux observer
single-phase current sensor fault
3rd difference operator
three-phase induction motor
Azizollah
Gholipour
a.gholipour@gorganiau.ac.ir
1
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran.
AUTHOR
Mahmood
Ghanbari
ghanbari@gorganiau.ac.ir
2
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran.
LEAD_AUTHOR
Esmaeil
Alibeiki
esmail_alibeiki@aliabadiau.ac.ir
3
Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran.
AUTHOR
Mohammad
Jannati
m.jannati@gorganiau.ac.ir
4
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran.
AUTHOR
[1] T. H. dos Santos, et al., "Scalar control of an induction motor using a neural sensorless technique," Electric power systems research, vol. 108, pp. 322-330, Mar 2014.
1
[2] S. A. R. Kashif, et al., "Implementing the induction-motor drive with four-switch inverter: An application of neural networks," Expert Systems with Applications, vol. 38, pp. 11137-11148, Sep 2011.
2
[3] R. Tabasian, et al., "Direct field-oriented control strategy for fault-tolerant control of induction machine drives based on EKF," IET Electric Power Applications, Apr 2020.
3
[4] M. Jannati, et al., "Experimental evaluation of FOC of 3-phase IM under open-phase fault," International Journal of Electronics, vol. 104, pp. 1675-1688, Oct 2017.
4
[5] M. A. Hannan, et al., "Optimization techniques to enhance the performance of induction motor drives: A review," Renewable and Sustainable Energy Reviews, vol. 81, pp. 1611-1626, Jan 2017.
5
[6] S. Shukla and B. Singh, "Single-stage PV array fed speed sensorless vector control of induction motor drive for water pumping," IEEE transactions on industry applications, vol. 54, pp. 3575-3585, Feb 2018.
6
[7] B. S. G. Yelamarthi and S. R. Sandepudi, "Predictive Torque Control of Three-Phase Induction Motor Drive with Inverter Switch Fault-Tolerance Capabilities," IEEE Journal of Emerging and Selected Topics in Power Electronics, Aug 2020.
7
[8] M. Jannati, et al., "Vector control of star-connected 3-phase induction motor drives under open-phase fault based on rotor flux field-oriented control," Electric Power Components and Systems, vol. 44, pp. 2325-2337, Dec 2016.
8
[9] Y. Liu, et al., "Smooth fault-tolerant control of induction motor drives with sensor failures," IEEE Transactions on Power Electronics, vol. 34, pp. 3544-3552, Jun 2018.
9
[10] A. A. Amin and K. M. Hasan, "A review of fault tolerant control systems: advancements and applications," Measurement, vol. 143, pp. 58-68, Sep 2019.
10
[11] M. Manohar and S. Das, "Current sensor fault-tolerant control for direct torque control of induction motor drive using flux-linkage observer," IEEE Transactions on Industrial Informatics, vol. 13, pp. 2824-2833, Jun 2017.
11
[12] K. S. Lee and J. S. Ryu, "Instrument fault detection and compensation scheme for direct torque controlled induction motor drives," IEE Proceedings-Control Theory and Applications, vol. 150, pp. 376-382, Jul 2003.
12
[13 A. Bernieri, et al., "A neural network approach to instrument fault detection and isolation," In 10th Instrumentation and Measurement Technology Conference, pp. 139-144, May 1994.
13
[14] G. Betta, et al., "An advanced neural-network-based instrument fault detection and isolation scheme," IEEE transactions on instrumentation and measurement, vol. 47, pp. 507-512, Apr 1998.
14
[15] A. B. Youssef, et al., "State observer-based sensor fault detection and isolation, and fault tolerant control of a single-phase PWM rectifier for electric railway traction," IEEE transactions on Power Electronics, vol. 28, pp. 5842-5853,May 2013.
15
[16] X. Zhang, et al., "Sensor fault detection, isolation and system reconfiguration based on extended Kalman filter for induction motor drives," IET Electric Power Applications, vol. 7, pp. 607-617, Aug 2013.
16
[17] D. Diallo, et al., "A fault-tolerant control architecture for induction motor drives in automotive applications," IEEE transactions on vehicular technology, vol. 53, pp. 1847-1855, Nov 2004.
17
[18] P. Vas, "Sensorless vector and direct torque control," Oxford Univ. Press, 1998.
18
[19] M. Jannati, et al., "A review on Variable Speed Control techniques for efficient control of Single-Phase Induction Motors: Evolution, classification, comparison," Renewable and Sustainable Energy Reviews, vol. 75, pp. 1306-1319, Aug 2017.
19
[20] Y. C. Kang, et al., "A CT saturation detection algorithm," IEEE Transactions on Power Delivery, vol. 19, pp. 78-85, Jan 2004.
20
[21] B. K. Bose, "Modern power electronics and AC drives," Upper Saddle River, NJ, Prentice hall, 2002.
21
ORIGINAL_ARTICLE
Optimal Active Distribution Network Reconfiguration for Loss and Supply Cost Minimization Using Grey Wolf Algorithm
In this paper, a novel reconfiguration approach for distribution network incorporating distributed generation is introduced aiming to minimize power losses and energy supply costs. Given the temporally variable consumption of residential, industrial and commercial loads and the time-variant energy prices, an hourly reconfiguration scheme for an entire daily cycle is proposed. Also considering the privately-owned nature of distributed sources, the energy supply is carried out within a competitive market. The optimization is based on grey wolf algorithm (GWO), implemented in MATLAB software on an IEEE 33-bus test network. The simulation is done for four scenarios with respective objective functions for the evaluations of the results thereof. By comparing the obtained results it is concluded the configuration of network will be the unique for each of objective function. Finally, the effects of switching at different hours of day are compared in terms of loss minimization and supply costs against single daily switching scheme.
http://jadsc.aliabadiau.ac.ir/article_679371_4fa3591c50bd016d11f29c22cdca4824.pdf
2020-12-01
23
30
Reconfiguration
Distribution network
energy supply cost reduction
Power Loss
Grey Wolf Algorithm
katayun
Rahmati
rahmati.katayun@gmail.com
1
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran
AUTHOR
Reza
Ebrahimi
r.ebrahimi@gorganiau.ac.ir
2
Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran.
LEAD_AUTHOR
Vahid
Parvin Darabad
v.parvin@gu.ac.ir
3
Department of Electrical Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran.
AUTHOR
[1] Abdelaziz, A.Y., et al., Distribution system reconfiguration using a modified Tabu Search algorithm. Electric Power Systems Research, 2010. 80(8): p. 943-953.
1
[2] Khoa, T. and B. Phan. Ant colony search-based loss minimum for reconfiguration of distribution systems. in 2006 IEEE Power India Conference. 2006. IEEE, April 2006.
2
[3] Franco, J.F., et al., A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation. Electric Power Systems Research, 2013. 97: p. 51-60.
3
[4] Nguyen, T.T., A.V. Truong, and T.A. Phung, A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network. International Journal of Electrical Power & Energy Systems, 2016. 78: p. 801-815.
4
[5] Mendoza, J., et al., Microgenetic multi objective reconfiguration algorithm considering power losses and reliability indices for medium voltage distribution network. IET Generation, Transmission & Distribution, 2009. 3(9): p. 825-840.
5
[6] Gupta, N., A. Swarnkar, and K. Niazi, Distribution network reconfiguration for power quality and reliability improvement using Genetic Algorithms. International Journal of Electrical Power & Energy Systems, 2014. 54: p. 664-671.
6
[7] Tian, Z., et al., Mixed-integer second-order cone programing model for VAR optimisation and network reconfiguration in active distribution networks. IET Generation, Transmission & Distribution, 2016. 10(8): p. 1938-1946.
7
[8] Capitanescu, F., et al., Assessing the potential of network reconfiguration to improve distributed generation hosting capacity in active distribution systems. IEEE Transactions on Power Systems, 2014. 30(1): p. 346-356.
8
[9] Liang, W., et al. A novel reconfiguration strategy for active distribution network considering maximum power supply capability. in Applied Mechanics and Materials. 2014. Trans Tech Publ.448: p.2747-2752.
9
[10] Esmaeili, M., M. Sedighizadeh, and M. Esmaili, Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty. Energy, 2016. 103: p. 86-99.
10
[11] Farahani, V., B. Vahidi, and H.A. Abyaneh, Reconfiguration and capacitor placement simultaneously for energy loss reduction based on an improved reconfiguration method. IEEE Transactions on power systems, 2011. 27(2): p. 587-595.
11
[12] Nikkhah, S. and A. Rabiee, Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives. Renewable energy, 2019. 132: p. 471-485.
12
[13] Hamida, I.B., et al., Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs. Renewable energy, 2018. 121: p. 66-80.
13
[14] Mirjalili, S., S.M. Mirjalili, and A. Lewis, Grey wolf optimizer. Advances in engineering software, 2014. 69: p. 46-61.
14
[15] Sunil, D.V. and N. Yadaiah. A novel improved particle swarm optimization frame work for reconfiguration of radial distribution system. in 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe). 2017. IEEE, june 2017.
15
[16] Ebrahimi, R., M. Ehsan, and H. Nouri, A profit-centric strategy for distributed generation planning considering time varying voltage dependent load demand. International Journal of Electrical Power & Energy Systems, 2013. 44(1): p. 168-178.
16
[17] Alemohammad, S.H., E. Mashhour, and M. Saniei, A market-based method for reconfiguration of distribution network. Electric Power Systems Research, 2015. 125: p. 15-22.
17
[18] Rao, R.S., S. Narasimham, and M. Ramalingaraju, Optimization of distribution network configuration for loss reduction using artificial bee colony algorithm. International Journal of Electrical Power and Energy Systems Engineering, 2008. 1(2): p. 116-122.
18
ORIGINAL_ARTICLE
Optimal Location and Determination of Fault Current Limiters in the Presence of Distributed Generation Sources Using a Hybrid Genetic Algorithm
Nowadays, the presence of distributed generation (DG) units in the distribution network is increasing due to their advantages. Due to the increasing need for electricity, the use of distributed generation sources in the power system is expanding rapidly. On the other hand, in order to respond to the growth of load demand, the network becomes wider and more interconnected. These factors increase the level of fault current in the power system. Sometimes this increase causes the fault current level to exceed the ability to disconnect the protective devices, which can cause serious damage to the equipment in the power system. Using fault current limiters (FCLs) in power system is very promising solution in suppressing short circuit current and leads use of protective equipment with low capacities in the network. In this paper, in order to solve the problem of increasing the fault current, first using sensitivity analysis, network candidate lines are selected to install the fault current limiter, which helps to reduce the time and search space to solve the problem. Simultaneously finding the optimal number, location and amount of impedance for the installation of a resistive superconductor limiter is solved using the multi-objective Non-dominated genetic algorithm with non-dominated sorting (NSGA-II). The method presented in a 20 kV ring sample network, simulated in PSCAD software, is evaluated in the presence of distributed generation sources and its efficiency is shown.
http://jadsc.aliabadiau.ac.ir/article_679372_a84e55d9ec5100a7e3527cbf112c03c6.pdf
2020-12-01
31
38
Superconducting fault current limiters
optimal positioning
Multi-objective genetic algorithm
Non-dominated sorting (NSGA-II)
Sensitivity analysis
Search space reduction
Salman
Amirkhan
salman_amirkhani@yahoo.com
1
Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
LEAD_AUTHOR
Mostafa
Rayatpanah Ghadikolaei
rayatpanah_m@mapnaom-qe.com
2
MAPNA Operation and Maintenance Co. (O&M), Tehran, Iran
AUTHOR
Hassan
Pourvali Souraki
pourvali_h@mapnagroup.com
3
MAPNA Operation and Maintenance Co. (O&M), Tehran, Iran
AUTHOR
[1] H. Zeineldin and W. Xiao, Optimal fault current limiter sizing for distribution systems with DG, IEEE Power and Energy Society General Meeting, 2011, pp. 1-5.
1
[2] H.-C. Jo and S.-K. Joo, Superconducting Fault Current Limiter Placement for Power System Protection Using the Minimax Regret Criterion, IEEE Transactions on Applied Superconductivity, vol. 25, pp. 1-5, 2015.
2
[3] J. Carr, J. C. Balda, Y. Feng, and H. A. Mantooth, Fault current limiter placement strategies and evaluation in two example systems, IEEE Energy 2030 Conference, 2008, pp. 1-7.
3
[4] T.Ghanbari and E.Farjah, A Multiagent-Based Fault-Current Limiting Scheme for the Microgrids, IEEE Transactions on Power Delivery, vol. 29, no. 2, APRIL 2014.
4
[5] Purkivani Nargour, Iraj; Rastegar, Hassan and Asgarian Abyaneh, Hossein, Positioning and determining the optimal type of superconducting type fault current limiters considering the coordination of distance relays, Specialized Conference on Protection and Control of Power Systems, Sixth Volume, Tehran, Association of Electrical and Electronics Engineers Iran, Sharif University of Technology, 2011.
5
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6
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ORIGINAL_ARTICLE
Sport Result Prediction Using Classification Methods
Traditional sport was based on the ability of the players and less science and knowledge was considered. However, sport has become a profession and an industry. Therefore, the use of technology and analysis on data in order to achieve goals is very important. Classification is one of technologies to classify new incoming samples. Furthermore, sports produce considerable information about each season, teams, matches and players. Classification on sport data helps managers and coaches in order to predict the match result, evaluate the player performance, predict the player injury, identify the sports talent and evaluate the match strategy. There are many algorithms to predict the basketball results, track the health of players and determine the strategy of the match against different opponents, which help coaches a lot. Further, preprocessing procedure makes better dataset. In this paper, we use classification methods on sport dataset using preprocessing procedure and without preprocessing. The results show an improvement was obtained results using preprocessing.
http://jadsc.aliabadiau.ac.ir/article_679387_b8dbe74e99f2a02c3d8f33b91baf3ee9.pdf
2020-12-01
39
48
Data mining
Classification
Result Prediction
Basketball match
Arash
Mazidi
arash_mazidi_67@yahoo.com
1
Department of Computer Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran.
LEAD_AUTHOR
Mehdi
Golsorkhtabaramiri
golesorkh@baboliau.ac.ir
2
Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
AUTHOR
Naznoosh
Etminan
etminan.naznoosh@gmail.com
3
Department of Computer Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
AUTHOR
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