ORIGINAL_ARTICLE
A SAIWD-Based Approach for Simultaneous Reconfiguration and Optimal Siting and Sizing of Wind Turbines and DVR units in Distribution Systems
In this paper, a combination of simulated annealing (SA) and intelligent water drops (IWD) algorithm is used to solve the nonlinear/complex problem of simultaneous reconfiguration with optimal allocation (size and location) of wind turbine (WT) as a distributed generation (DG) and dynamic voltage restorer (DVR) as a distributed flexible AC transmission systems (DFACT) unit in a distribution system. The objectives of this research are to minimize active power loss, minimize operational cost, improve voltage stability, and increase the load balancing of the system. For evaluation purposes, the proposed algorithm is evaluated using the Tai-Power 11.4-kV real distribution network. The impacts of the optimal placement of the WT, DVR, and WT with DVR units are separately evaluated. The results are compared in terms of statistical indicators. By comparing all the testing scenarios, it is observed that the multi-objective optimization evolutionary algorithm is more beneficial than its single-objective optimization counterpart. Also, the obtained results show that the proposed SAIWD method outperforms the IWD method and other intelligent search algorithms such as genetic algorithm or particle swarm optimization.
http://joape.uma.ac.ir/article_470_6bea5c53942fa258c2e1ffd88cfaa9da.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
93
103
Distribution system
Dynamic voltage restorer
Intelligent water drops
Reconfiguration
Simulated annealing
Wind turbine
A.
Lashkar Ara
hajarbagheri1@gmail.com
true
1
Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
AUTHOR
H.
Bagheri Tolabi
hajar.bagheri1@gmail.com
true
2
lslamic azad university
lslamic azad university
lslamic azad university
LEAD_AUTHOR
R.
hosseini
hajarb.agheri1@gmail.com
true
3
Department of Artificial Intelligence, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
Department of Artificial Intelligence, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
Department of Artificial Intelligence, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
AUTHOR
[1] H. B. Tolabi, R. Hosseini, M. R. Shakarami “A robust hybrid fuzzy-simulated annealing-intelligent water drops approach for tuning a distribution static compe-nsator nonlinear controller in a distribution system,” Eng. Optim., vol. 48, no. 6, pp. 999-1018, 2016.
1
[2] M. Sedighizadeh, M. Mahmoodi “Optimal reconfig-uration and capacitor allocation in radial distribution systems using the hybrid shuffled frog leaping algorithm in the fuzzy framework,” J. Oper. Autom. Power Eng.,vol. 3, no. 1, pp. 56-70, 2015.
2
[3] A. Merlin, H. Back “Search for a minimal-loss operat-ing spanning tree configuration in an urban power distribution system,” in Proce. of the PSCC, Cambridge, 1975, pp.1-18.
3
[4] K. Nara, A. Shiose, M. Kitagawa, T. Ishihara “Impleme-ntation of genetic algorithm for distribution system loss minimum reconfiguration,” IEEE Trans. Power Delivery, vol. 7, no.3, pp.1044-1051, 1992.
4
[5] B. Venkatesh, R. Ranjan “Optimal radial distribution system reconfiguration using fuzzy adaptation of evolutionary programming,” Int. J. Electr. Power Energy Syst., vol. 25, no. 10, pp. 775-780, 2003.
5
[6] T. Gözel T, M. Hakan Hocaoglu “An analytical method for the sizing and siting of distributed generators in radial systems,” Electr. Power Syst. Res., vol. 79, no. 6, pp. 912-918, 2009.
6
[7] R. Kollu, S. R. Rayapudi, V. L. N. Sadhu “A novel method for optimal placement of distributed generation in distribution systems using HSDO,” Int. Trans. Electric. Energy Syst., vol. 24, pp. 547-561, 2014.
7
[8] D. K. Tanti, M. K. Verma, B. Singh, O. N. Mehrotra, “An ANN based approach for optimal placement of DSTATCOM and DVR in power system for voltage sag mitigation under faults,” presented at the AIATA, IT-BHU Varanasi, 2011.
8
[9] A. Jain, A. R. Gupta, A. Kumar “An efficient method for D-STATCOM placement in radial distribution system,” in Proce of the IICPE, pp. 1-6, 2014.
9
[10] H. B. Tolabi, M. H. Ali, M. Rizwan “Novel hybrid fuzzy-intelligent water drops approach for optimal feeder multi objective reconfiguration by considering multiple-distributed generation,” J. Oper. Autom. Power Eng., vol. 2, no. 2, pp. 91-102, 2014.
10
[11] A. Kavousi-Fard, T. Niknam “Multi-objective stochastic distribution feeder reconfiguration from the reliability point of view,” Energy, vol. 64, pp. 342-354, 2014.
11
[12] H. B. Tolabi, M. H. Ali, S. B. M. Ayob, M. Rizwan “Novel hybrid fuzzy-Bees algorithm for optimal feeder multi-objective reconfiguration by considering multiple-distributed generation,” Energy, vol. 71, pp. 507-515, 2014.
12
[13] R. Srinivasa Rao, K. Ravindra, K. Satish, S. V. L. Narasimham “Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation,” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 317-325, 2013.
13
[14] K. Bhumkittipich, N. Mithulananthan “Performance enhancement of DVR for mitigating voltage sag/swell using vector control strategy,” Energy Procedia, vol. 9, pp. 366-379, 2011.
14
[15] H. Chen, J. Chen, D. Shi, X. Duan “Power flow study and voltage stability analysis for distribution systems with distributed generation,” in Proc. of the IEEE PES General Meeting, pp. 1-8, 2006.
15
[16] K.R. Devabalaji, K Ravi “Optimal size and siting of multiple DG and DSTATCOM in radial distribution system using bacterial foraging optimization algorithm,” Ain Shams Eng. J., vol. 7, no. 3, pp. 959-971, 2016.
16
[17] S. Chandramohan, N. Atturulu, R.P. Kumudini Devi, B. Venkatesh “Operating cost minimization of a radial distribution system in a deregulated electricity market through reconfiguration using NSGA method,” Int. J. Electr. Power Energy Syst., vol. 32, no. 2, pp. 126-132, 2010.
17
[18] Power System Analysis, 1rded., McGraw-Hill Co., New York, US, 1994.
18
[19] N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, E. Teller “Equation of state calculations by fast computing machines,” J. Chem. Phys, vol. 21, no. 6, pp. 1087-1092, 1953.
19
[20] S. Kirkpatrick, C. D. Gelatt, M. P. Vecchi “optimization by simulated annealing,” Science, vol. 220, no. 4598. pp. 671-680, 1983.
20
[21] V. Cerny “A thermodynamical approach to the travelling salesman problem: an efficient simulation algorithm,” J. Optimiz. Theory App., vol. 45, pp. 41-51, 1985.
21
[22] M. Gandomkar, H. B. Tolabi “Investigation of simulated annealing, ant-colony and genetic algorithms for distrib-ution network expansion planning with distributed generation,” in Proce of the WSEAS, pp. 48-52, 2010.
22
[23] S. H. Hosseini “The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm,” Int. J. Bio-Inspir Comput., vol. 1, no. 1/2, pp. 71-79, 2009.
23
[24] L.W. Oliveira, S. Carneiro, E.J. Oliveira, J.L.R. Pereira, I.C. Silva, J.S. Costa, “Optimal reconfiguration and capacitor allocation in radial distribution systems for energy losses minimization,” Int. J. Electr. Power Energy Syst., vol. 32, pp. 840-848, 2010.
24
[25] New Methods To Protect Wind Generators During Voltage Dips Developed, Basque Research, 2015.
25
[26] J. Olamaei, T. Niknam, G. Gharehpetian, “Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators,” Appl. Math. Comput., vol. 201, no.1-2, pp. 575-586, 2008.
26
ORIGINAL_ARTICLE
A New Structure of Buck-Boost Z-Source Converter Based on Z-H Converter
In this paper, a new structure for buck-boost Z-source converter based on Z-H topology is proposed. The proposed converter consists of two LC networks similar to the conventional Z-source and Z-H converters. One of the characteristics of the proposed structure is that, without any changing in its’ power circuit, it can be used in different conversions such as dc/dc, dc/ac and ac/ac. This unique characteristic of the proposed structure is similar to matrix converters. To use this structure in different conversions just control system should be changed. Other main advantages of the proposed converter are simpler topology, step-up and step-down capabilities and low ripple in voltage and current waveforms. Due to capabilities of the proposed converter mentioned above, it can be used in applications such as connect renewable energy sources to the grid, speed control of induction machines, electric vehicles and etc. In this paper, a complete analysis of the proposed converter in dc/dc conversion with details and mathematical equations is presented. Moreover, for the proposed topology, the ripple of inductors and capacitors is given. A suitable control method is presented, too. Also, the power losses and efficiency of the proposed converter are calculated. The correctness operation of the proposed converter is reconfirmed by the experimental results.
http://joape.uma.ac.ir/article_472_4bcae47430593b3db9cdba976c8d4f19.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
117
131
Buck-boost dc/dc converter
LC network
Shoot-through (ST) state
Z-H converter
Z-source inverter
E.
Babaei
e-babaei@tabrizu.ac.ir
true
1
University of Tabriz
University of Tabriz
University of Tabriz
LEAD_AUTHOR
T.
Ahmadzadeh
taher.ahmadzadeh@gmail.com
true
2
University of Tabriz
University of Tabriz
University of Tabriz
AUTHOR
[1] N. Troy, E. Denny, M. O'Malley, “Base-load cycling on a system with signiﬁcant wind penetration,” IEEE Trans. Power Syst., vol. 25, no. 2, pp. 1088-1097, 2010.
1
[2] J. D. Maddaloni, A. M. Rowe, G. C. van Kooten, “Wind integration into various generation mixtures,” Renewable Energy, vol. 34, no. 3, pp. 807-814, 2009.
2
[3] H. Khorramdel, B. Khorramdel, M. T. Khorrami, H. Rastegar, “A multi-objective economic load dispatch considering accessibility of wind power with here-and-now (HN) approach”, J. Oper. Autom. Power Eng., vol. 2 no. 1, pp. 49-59, 2014.
3
[4] P. Siano, “Demand response and smart grids-A survey,” Renewable Sustainable Energy Rev., vol. 30, pp. 461-478, 2014.
4
[5] H. Holttinen, A. Tuohy, M. Milligan, E. Lannoye, V. Silva, S. Muller, “The ﬂexibility workout: managing variable resources and assessing the need for power system modiﬁcation,” IEEE Power Energy Mag., vol. 11, no. 6, pp. 53-62, 2013.
5
[6] G. Papaefthymiou, K. Grave, K. Dragoon, “Flexibility options in electricity systems,” 2014. Report. Available at: http://www.ecofys.com/en/pub-lication/ ﬂexibility-options-in-electricity-systems/.
6
[7] K. Afshar, A. S. Gazafroudi, “Application of stochastic programming to determine operating reserves with considering wind and load uncertainties,” J. Oper. Autom. Power Eng., vol. 1, no, 2, pp. 96-109, 2013.
7
[8] K. Dietrich, J. M. Latorre, L. Olmos, A. Ramos, “Demand response in an isolated system with high wind integration,” IEEE Trans. Power Syst., vol. 27, no. 1, pp. 20-29, 2012.
8
[9] A. Keane, A. Tuohy, P. Meibom, E. Denny, D. Flynn, A. Mullane, M. O'Malley, “Demand side resource operation on the Irish power system with high wind power penetration,” Energy Policy, vol. 39, no. 5, pp. 2925-2934, 2011.
9
[10] M. Parvani, M. Fotuhi-Firuzabad, “Integrating load reduction into wholesale energy market with application to wind power integration,” IEEE Syst. J., vol. 6, no. 1, pp. 35-45, 2012.
10
[11] A. Yousefi, H. C. Iu, T. Fernand, H. Trinh, “An approach for wind power integration using demand side resources,” IEEE Trans. Sustainable Energy, vol. 4, no. 4, pp. 917-924, 2013.
11
[12] H. Falsafi, A. Zakariazadeh, S. Jadid, “The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programm-ing,” Energy, vol. 64, pp. 853-867, 2014.
12
[13] E. Heydarian-Forushani, M.P. Moghaddam, M.K. Sheikh-El-Eslami, M. Shaﬁe-khah, J.P.S. Catalao, “A stochastic framework for the grid integration of wind power using ﬂexible load approach,” Energy Convers. Manage., vol. 88, pp. 985-998, 2014.
13
[14] CAES dispatch modeling. Available online: http://www.smartgrid.gov/sites/default/ﬁles/doc/ﬁles/Exh%2013.13%20Energy%20Market%20Report%20CES%20Part%203.pdf.
14
[15] T. Das, V. Krishnan, J. D. McCalley, “Assessing the beneﬁts and economics of bulk energy storage technologies in the power grid,” Appl. Energy, vol. 139, no. 1, pp. 104-118, 2015.
15
[16] D. Pozo, J. Contreras, EE. Sauma, “Unit commitment with ideal and generic energy storage units,” IEEE Trans. Power Syst., vol. 29, no. 6, pp. 2974-2984, 2014.
16
[17] M. Shafie-khah, M. P. Moghaddam, M. K. Sheikh-El-Eslami, J. P. S. Catalao, “Optimised performance of a plug-in electric vehicle aggregator in energy and reserve markets”, Energy Convers. Manage., vol. 97, pp. 393-408, 2015.
17
[18] A. El-Zonkoly, “Intelligent energy management of optimally located renewable energy systems incorporating PHEV”, Energy Convers. Manage., vol. 84, pp. 427-435, 2014.
18
[19] P. Pinson, H. Madsen, “Benefits and challenges of electrical demand response: A critical review,” Renewable Sustainable Energy Rev., vol. 39, pp. 686-699, 2014.
19
[20] J. Aghaei, M. I. Alizadeh, “Demand response in smart electricity grids equipped with renewable energy sources: A review,” Renewable Sustainable Energy Rev., vol. 18, pp. 64-72, 2013.
20
[21] M. Y. Suberu, M. W. Mustafa, N. Bashir, “Energy storage systems for renewable energy power sector integration and mitigation of intermittency,” Renewable Sustainable Energy Rev., vol. 35, pp. 499-514, 2014.
21
[22] H. Zhao, Q. Wu, S. Hu, H. Xu, C. N. Rasmussen, “Review of energy storage system for wind power integration support,” Appl. Energy, vol. 137, pp. 545-553, 2015.
22
[23] H. A. Aalami, M. P. Moghaddam, G. R. Yousefi, “Modeling and prioritizing demand response programs in power markets,” Electr. Power Syst. Res., vol. 80, no. 4, pp. 426-435, 2010.
23
[24] H. A. Aalami, M. P. Moghaddam, G. R. Yousefi, “Demand response modelling considering interruptib-le/curtailable loads and capacity market programs,” Appl. Energy, vol. 87, no. 1, pp. 243-250, 2010.
24
[25] H. A. Aalami, M. P. Moghaddam, G. R. Yousefi, “Evaluation of nonlinear models for time-based rates demand response programs,” Int. J. Electric. Power Energy Syst., vol. 65, pp. 282-290, 2015.
25
[26] M. Nikzad, B. Mozafari, M. Bashirvand, S. Solaymani, A. M. Ranjbar, “Designing time-of-use program based on stochastic security constrained unit commitment considering reliability index”, Energy, vol. 41, no. 1, pp. 541-548, 2012.
26
[27] A. Abdollahi, M. P. Moghaddam, M. Rashidinejad, M. K. Sheikh-El-Eslami, “Investigation of economic and environmental-driven demand response measures incorporating UC,” IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 12-25, 2012.
27
[28] M. Parvania, M. Fotuhi-Firuzabad, M. Shahidehpour, “Assessing impact of demand response in emission-constrained environments,” Proc. of the IEEE Power and Energy Society General Meeting, pp. 1-6, 2011.
28
[29] The IEEE reliability test system-1996. IEEE Trans. Power Syst., vol. 14, pp. 1010-1020, 1999.
29
[30] H. A. Aalami, S. Nojavan, “Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation,” IET Gener. Transm. Distrib., vol. 10, no. 1, pp. 107-114, 2016.
30
ORIGINAL_ARTICLE
Multi Objective Scheduling of Utility-scale Energy Storages and Demand Response Programs Portfolio for Grid Integration of Wind Power
Increasing the penetration of variable wind generation in power systems has created some new challenges in the power system operation. In such a situation, the inclusion of flexible resources which have the potential of facilitating wind power integration is necessary. Demand response (DR) programs and emerging utility-scale energy storages (ESs) are known as two powerful flexible tools that can improve large-scale integration of intermittent wind power from technical and economic aspects. Under this perspective, this paper proposes a multi objective stochastic framework that schedules conventional generation units, bulk ESs, and DR resources simultaneously with the application to wind integration. The proposed formulation is a sophisticated problem which coordinates supply-side and demand-side resources in energy and up/down spinning reserve markets so that the cost, emission, and multi objective functions are minimized separately. In order to determine the most efficient DR program which can potentially coordinate with bulk ESs in the system with a significant amount of wind power, a comprehensive DR programs portfolio including time- and incentive-based programs is designed. Afterwards, strategy success index (SSI) is employed to prioritize DR programs from independent system operator (ISO) perspective. The IEEE-RTS is used to reveal the effectiveness of the proposed method.
http://joape.uma.ac.ir/article_471_fab4efdf453d9b92525531576d4d34f6.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
104
116
Bulk energy storages
Demand response programs
Electricity market
Wind power generation
E.
Heydarian-Forushani
heydarian.ehsan@yahoo.com
true
1
Isfahan University of Technology
Isfahan University of Technology
Isfahan University of Technology
LEAD_AUTHOR
H.
Aalami
h.aalami41@gmail.com
true
2
Imam Hussein University
Imam Hussein University
Imam Hussein University
AUTHOR
[1] F.Z. Peng, “Z-source inverter,” IEEE Trans. Ind. Appl., vol. 39, no. 2, pp. 504-510, 2003.
1
[2] S. Torabzad, E. Babaei, and M. Kalantari, “Z-source inverter based dynamic voltage restorer,” in Proce. of thePEDSTC, pp. 406-411, 2010.
2
[3] X. Ding, Z. Qian, Y. Xie, and F.Z. Peng, “Transient modeling and control of the novel ZVS Z-source rectifier,” in Proce. of thePESC, pp. 1-5, 2006.
3
[4] M.R. Banaei, R. Alizadeh, N. Jahanyari, and E. Seifi Najmi, “An ac Z-source converter based on gamma structure with safe-commutation strategy,” IEEE Trans. Power Electron., vol. 31, no. 2, pp. 1255-1262, 2016.
4
[5] F. Sedaghati, and E. Babaei, “Double input dc-dc Z-source converter,” in Proce. of thePEDSTC, pp. 581-586, 2011.
5
[6] F.Z. Peng, M. Shen, and Z. Qian, “Maximum boost control of the Z-source inverter,” IEEE Trans. Power Electron., vol. 20, no. 4, pp. 833-838, 2005.
6
[7] M. Shen, J. Wang, A. Joseph, F.Z. Peng, L.M. Tolbert, and D.J Adams, “Constant boost control of the Z-source inverter to minimize current ripple and voltage stress,” IEEE Trans. Ind. Appl., vol. 42, no. 3, pp. 770-778, 2006.
7
[8] S.R. Aghdam, E. Babaei, and S. Laali, “Maximum constant boost control method for switched-inductor Z-source inverter by using battery,” in Proc. of the IECON, 2013, pp. 984-989.
8
[9] N. Mirkazemian and E. Babaei, “A new topology for quasi-Z-source inverter,” in Proce. of the PSC, 2015, pp. 1-7.
9
[10] H. Rostami, and D.A. Khaburi, “Voltage gain comparison of different control methods of the Z-source inverter,” in Proc. of the ELECO, pp. 268-272, 2009.
10
[11] U.S. Ali, and V. Kamaraj, “A novel space vector PWM for Z-source inverter,” in Proc. of the ICEES, pp. 82-85, 2011.
11
[12] J.W. Jung, and A. Keyhani, “Control of a fuel cell based Z-source converter,” IEEE Trans. Energy Convers., vol. 22, no. 2, pp. 467-476, 2007.
12
[13] O. Ellabban, J.V. Mierlo, and P. Lataire, “Experimental study of the shoot-through boost control methods for the Z-source inverter,” EPEJ, vol. 21, no. 2, pp. 18-29, 2011.
13
[14] Y. Liu, B. Ge, F.J.T.E. Ferreira, A.T. de Almeida, and H.A. Rub, “Modelling and SVPWM control of quasi-Z-source inverter,” in Proc. of the EPQU, pp. 1-7, 2011.
14
[15] Y. Liu, B. Ge, H.A. Rub, and F.Z. Peng, “Overview of space vector modulations for three-phase Z-source/quasi-Z-source inverters,” IEEE Trans. Power Electron., vol. 29, no. 4, pp. 2098-2108, 2014.
15
[16] Y. Liu, B. Ge, and H.A. Rub, “Theoretical and experimental evaluation of four space vector modulations applied to quasi-Z-source inverters,” IET Power Electron., vol. 6, no. 7, pp. 1257-1269, 2013.
16
[17] Y.P. Siwakoti, and G.E. Town, “Three-phase transformerless grid connected quasi Z-source inverter for solar photovoltaic systems with minimal leakage current,” in Proc. of the PEDG, pp. 368-373, 2012.
17
[18] F. Bradaschia, M.C. Cavalcanti, P.E.P. Ferraz, F.A.S. Neves, E.C. dos Santos, and J.H.G.M. da Silva, “ Modulation for three-phase transformer-less Z-source inverter to reduce leakage currents in photovoltaic systems,” IEEE Trans. Ind. Electron., vol. 58, no. 12, pp. 5385-5395, 2011.
18
[19] Y.P. Siwakoti, and G.E. Town, “Common-mode voltage reduction techniques of three-phase quasi Z-source inverter for AC drives,” in Proc. of the APEC, 2013, pp. 2247-2252.
19
[20] S.R. Aghdam, E. Babaei, and S. Ghasemzadeh, “Improvement the performance of switched-inductor Z-source inverter,” in Proc. of theIECON, 2013, pp. 876-881.
20
[21] M.S. Zarbil, E. Shokati Asl, E. Babaei, and M. Sabahi, “A new structure for quasi-Z-source inverter based on switched inductors and transformer,” Iran. Electr. Ind. J. Qual. Prod., vol. 4, no. 8, pp. 63-73, 2016.
21
[22] E. Babaei, M. Hasan Babayi, E. Shokati Asl, and S. Laali, “A new topology for Z-source inverter based on switched-inductor and boost Z-source inverter,” J. Oper. Autom. Power Eng., vol. 3, no. 2, pp. 167-184, 2015.
22
[23] E. Babaei, E. Shokati Asl, M.H. Babayi, “Steady-state and small-signal analysis of high voltage gain half-bridge switched-boost inverter,” IEEE Trans. Ind. Electron., vol. 63, no. 6, pp. 3546-3553, 2016.
23
[24] R. Strzelecki, and N. Strzelecka, “Simulation investigation of the Z-source NPC inverter,” Doctoral school of energy- and geo-technology, Kuressaare, Estonia, pp. 213-218, 2007.
24
[25] F. Zhang, F.Z. Peng, and Z. Qian, “Z-H converter,” in Proce. of the PESC, 2008, pp. 1004-1007.
25
[26] T. Ahmadzadeh, and E. Babaei, “Z-H buck converter: Analysis and simulation,” in Proc. of thePEDSTC, pp. 436-441, 2015.
26
[27] E. Babaei, M. Hasan Babayi, E. Shokati Asl, S. Laali, “A new topology for Z-source inverter based on switched-inductor and boost Z-source inverter,” J. Oper. Autom. Power Eng., vol. 2, no. 2, pp. 167-184, 2015.
27
[28] V.P. Galigekere and M.K. Kazimierczuk, “Analysis of PWM Z-source dc-dc converter in CCM for steady-state,” IEEE Trans. Circuits Syst. I Reg. Papers, vol. 59, no. 4, pp. 854-863, 2012.
28
[29] E. Babaei, E. Shokati Asl, M.H. Babayi, and S. Laali, “Developed embedded switched-Z-source inverter,” IET Power Electron., vol. 9, no. 9, pp. 1828-1841, 2016.
29
ORIGINAL_ARTICLE
Two Inputs Five-Level Quasi-Z-Source Inverter
This paper combines quasi-Z-source into a typical five-level inverter, which includes two dc voltage sources, two quasi-Z-sources and five switching devices. In this structure, the output voltage amplitude is not limited to dc voltage source and it can be increased by quasi-Z-source. Besides, due to nature of Z-source families, this new structure is reliable and higher efficiency. Also, in this inverter, two quasi-Z-networks can be controlled independently. This paper also proposes new switching algorithms for proposed five-level dual quasi-Z-Source inverter based on pulse width modulation (PWM) and selective harmonic elimination method (SHEM) algorithms .The performance of proposed inverter and switching algorithm are validated with simulation results using MATLAB/SIMULINK software and experimental results based PCI-1716 data acquisition system.
http://joape.uma.ac.ir/article_473_42c1dab00d842ff8d0e38e5a692e757f.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
132
142
Two inputs five-level inverter
quasi-Z-source
PWM
SHEM
shoot-through implementation
A.
Baghbany Oskouei
true
1
Azarbaijan Shahid Madani University
Azarbaijan Shahid Madani University
Azarbaijan Shahid Madani University
AUTHOR
M. R.
Banaei
m.banaei@azaruniv.ac.ir
true
2
Azarbaijan Shahid Madani University
Azarbaijan Shahid Madani University
Azarbaijan Shahid Madani University
LEAD_AUTHOR
M.
Sabahi
sabahi2@tabrizu.ac.ir
true
3
Tabriz University
Tabriz University
Tabriz University
AUTHOR
[1] M. R. Banaei, M. R. Jannati Oskuee, H. Khounjahan “Reconfiguration of semi-cascaded multilevel inverter to improve systems performance parameters,” IET Power Electron. , vol. 7, no. 5, pp. 1106-1112, 2014.
1
[2] E. Babaei, S. Laali, Z. Bayat “A single-phase cascaded multilevel inverter based on a new basic unit with reduced number of power switche,”IEEE Trans. Ind. Electron., vol. 62, no. 2, pp. 922-929, 2015.
2
[3] E. Babaei and S. Laali “Reduction the number of power electronic devices of a cascaded multilevel inverter based on new general topology,” J. Oper. Autom. Power Eng., vol. 2, no. 2, pp. 81-90, 2015.
3
[4] Z. Li, P. Wang, Y. Li, F. Gao “A novel single-phase five-level inverter with coupled inductors,” IEEE Trans. Power Electron., vol. 27, no. 6, pp. 2716-2725, 2012.
4
[5] M. R. Banaei, A. R. Dehghanzadeh, E. Salary, H. Khounjahan, R. Alizadeh “Z-source-based multilevel inverter with reduction of switches, ” IET Power Electron., vol. 5, no. 3, pp. 385-392, 2011.
5
[6] J. Rodríguez, L. Morán, P. Correa, C. Silva “A vector control technique for medium voltage multilevel inverters,” IEEE Trans. . Ind. Electron., vol. 49, no. 4, pp. 882-888, 2002.
6
[7] J. Rodriguez, J. S. Lai, F. Z. Peng “Multilevel inverters: A survey of topologies, controls, and applications,” IEEE Trans. on Ind. Electron., vol. 49, no. 4, pp. 724-738, 2002.
7
[8] K. El-Naggar, T. H. Abdelhamid “Selective harmonic elimination of new family of multilevel inverters using genetic algorithms,” Energ. Convers. Manage., vol. 49, pp. 89-95, 2008.
8
[9] A. R. Dehghanzadeh, V. Behjat “Experimental and 3D finite element analysis of a slotless air-cored axial flux PMSG for wind turbine application,” J. Oper. Autom. Power Eng., vol. 2, no. 2, pp. 121-128, 2015.
9
[10] A. Baghbany Oskouei, M. R. Banaei, M. Sabahi “Hybrid PV/wind system with quinary asymmetric inverter without increasing DC-link number,” Ain Shams Eng. J., in press.
10
[11] F. Z. Peng “Z-source inverter,” in Proc. of the 37th IAS Annual Meeting, pp. 775-781, 2002.
11
[12] M. R. Banaei, A. Baghbany Oskouei, A. R. Dehghanzadeh “Extended switching algorithms based space vector control for five-level quasi-Z-source inverter with coupled inductors,” IET Power Electron., vol. 7, no. 6, pp. 1509-1518, 2014.
12
[13] M. S. Pilehvar, M. Mardaneh “Phase-shift control and harmonics elimination for H-bridge Z-source inverter, ” IET Power Electron., vol. 8, no. 4, pp. 618-627, 2015.
13
[14] L. Yushan, H. Abu-Rub, G. Baoming “Z-Source/Quasi-Z-Source inverters: derived networks, modulations, controls, and emerging applications to photovoltaic conversion,” IEEE Ind. Electron. Mag., vol. 8, no. 4, pp. 32-44, 2014.
14
[15] F. Z. Peng “Z-source inverter,” IEEE Trans. Ind. Appl., vol. 39, no. 2, pp. 504-510, 2003.
15
[16] J. Anderson, F. Z. Peng “Four quasi-Z-source inverters,” in Proc. of the PESC, pp. 2743-2749, 2008.
16
[17] T. W. Chun, H. H. Lee, H. G. Kim, E. C. Nho “Power control for a PV generation system using a single-phase grid-connected quasi Z-source inverter,” in Proc. of the 8th the International Conference on Power Electronics and ECCE Asia (ICPE & ECCE), pp. 889-893, 2011.
17
[18] W. Qian, F. Z. Peng, H. Cha “Trans-Z-source inverters,” IEEE Trans. Power Electron., vol. 26, no. 12, pp. 3453-3463, 2011.
18
[19] M. R. Banaei, A. R. Dehghanzadeh, A. Fazel, A. Baghbany Oskouei “Switching algorithm for single Z-source boost multilevel inverter with ability of voltage control,” IET Power Electron., vol. 6, no. 7, pp. 1350-1359, 2013.
19
[20] A. Baghbany Oskouei, M. R. Banaei, M. Sabahi “Extended SVM algorithms for multilevel trans-Z-source inverter,” Ain Shams Eng. J., vol.7, no. 1, pp. 265-274..
20
[21] A. Baghbany Oskouei, A. R. Dehghanzadeh “Generalized space vector controls for MLZSI,” Ain Shams Eng. J., in press.
21
[22] S. J. Park, F. S. Kang, M. H. Lee, C. U. Kim “A new single-phase five-level PWM inverter employing a deadbeat control scheme,” IEEE Trans. Power Electron., vol. 18, no. 18, pp. 831-843, 2003.
22
[23] F. Gao, P. C. Loh, F. Blaabjerg, D. M. Vilathgamuwa “Dual Z-source inverter with Three-level reduced common-mode switching,” IEEE Trans. Ind. Appl., vol. 43, no. 6, pp. 1597-1608, 2007.
23
[24] M. S. A. Dahidah, G. Konstantinou, V. G. Agelidis “A review of multilevel selective harmonic elimination PWM: formulations, solving algorithms, implementation and applications,” IEEE Trans. Power Electron., vol. 30, no. 8, pp. 4091-4106, 2015.
24
[25] Y. Zhang, Y. W. Li, N. R. Zargari, Z. Cheng “Improved selective harmonics elimination scheme with online harmonic compensation for high-power PWM converters,” IEEE Trans. Power Electron., vol. 30, no. 7, pp. 3508-3517, 2015.
25
ORIGINAL_ARTICLE
Energy Management Strategy of Stand-alone Photovoltaic System in Cathodic Protection Pipeline
In this paper, the stand-alone photovoltaic system for cathodic protection of underground pipelines is presented. The proposed system offers continuous and automatic adjustment of the applied voltage so that the buried pipelines receive the exact current. A modified perturb and observe (P&O) algorithm for maximum power point tracking (MPPT) is used to improve dynamic and steady state performance. The battery stores excess energy generated by PV array and supplies the load when there is a shortage of the photo voltaic (PV) power. To extend the battery lifetime and the system efficiency, the battery is connected to the DC link by a ZVS bidirectional Buck-Boost converter. A classic PI controller regulates output voltage by controlling the duty cycle of the converter. The supervisor controls the converter to operate system in suitable modes based on the state of charge (SOC) of the battery and DC link voltage. The simulation verified that the output voltage obtains the constant voltage under any climatic conditions.
http://joape.uma.ac.ir/article_474_7a7b1dad127878d367bd9d7eb24d2842.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
143
152
DC-DC converter
Photovoltaic
Maximum power point tracking
Anode-bed
Cathodic protection
J.
Javidan
javidan.javad@gmail.com
true
1
Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran
Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran
Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran
LEAD_AUTHOR
[1] A.W. Peabody, “Control of pipeline corrosion”, by NACE International Second Edition, 2001.
1
[2] B. Laoun, k.N. boucha, L.serir, “Cathodic protection of a buried pipeline by solar energy”, Revue des Energies Renouvelables, vol. 12, no.1, pp. 99-104, 2008.
2
[3] B James, P.E Bushman, “Corrosion and cathodic protection theory”, Bushman & Associates, Inc. -P.O. Box 425 - Medina, Ohio 44256 USA.
3
[4] Adrian L. Verhiel, “The effects of high-voltage dc power transmission systems on buried metallic pipelines”, IEEE Trans. Ind. Appl., vol. 7, no. 3, 1971
4
[5] P.R. Mishra, J.C. Joshi, B. Roy, “Design of a solar photovoltaic-power mini cathodic protection system”, Sol. Energ. Mat. Sol. Cells., vol. 61, pp. 383-391, 2000.
5
[6] R.A. Wagdy, “Design of control circuit of solar photovoltaic powered regulated cathodic protection system”, Sol. Energy, vol. 55, no.5, pp. 363-365, 1995
6
[7] A. A. Ghassami, S. M. Sadeghzadeh, A. Soleimani, “A high performance maximum power point tracker for PV systems” Int. J. Electr. Power Energy Syst., vol. 53, pp. 237-243, 2013
7
[8] T. Zhou, W. Sun, “Study on maximum power point tracking of photovoltaic array in irregular shadow,” Int. J. Electr. Power Energy Syst., vol. 66, pp. 227-234, 2015.
8
[9] N. Ponkarthik, K. Kalidasa Murugavel, “Performance enhancement of solar photovoltaic system using novel maximum power point tracking,” Int. J. Electr. Power Energy Syst., vol. 60, pp.1-5, 2014
9
[10] A. Murtaza, M. Chiaberge, M. D. Giuseppe, D. Boero, “A duty cycle optimization based hybrid maximum power point tracking technique for photovoltaic systems,” Int. J. Electr. Power Energy Syst., vol. 59, pp. 141-154, 2014
10
[11] V. Dash, P. Bajpai, “Power management control strategy for a stand-alone solar photovoltaic-fuel cell-battery hybrid system,” Sustainable Energy Technol. Assess., vol.9, pp. 68-80, 2015.
11
[12] W. Caisheng, H. Nehrir, “Power management of a stand-alone Wind/ Photovoltaic-Fuel cell Energy system,” IEEE Trans. Energy Convers., vol.23, no.3, pp.957-67, 2008.
12
[13] Y. Hung, Y. Tung, C.H. Chang, “Optimal control of integrated energy management/mode switch timing in a three-power-source hybrid powertrain,” Appl. Energy, vol.173, pp.184-196, 2016
13
[14] J.B. Almada, R.P.S. Leão, R.F. Sampaio, G.C. Barroso, “A centralized and heuristic approach for energy management of an AC microgrid,” Renew. Sustainable Energy Rev., vol.60, pp.1396-1404, 2016.
14
[15] B.M. Radhakrishnan, D. Srinivasan, “A multi-agent based distributed energy management scheme for smart grid applications,” Energy, vol. 103, pp.192-204, 2016.
15
[16] Z. Liao, X. Ruan, “A novel power management control strategy for stand-alone photovoltaic power system,” in Proc. of the IEEE 6th International Power Electronics and Motion Control Conference, pp. 445-449, Wuhan, China, 2009.
16
[17] K. Sun, L. Zhang, Y. Xing, J. M. Guerrer, “A distributed control strategy based on dc bus signalling for modular photovoltaic generation systems with battery energy storage,” IEEE Trans. Power Electron., vol. 26, no. 10, 2011.
17
[18] N. Karami, N. Moubayed, R. Outbib, “Energy management for a PEMFC-PV hybrid system,” Energy Conv. Manag., vol. 82, pp. 154-168, 2014.
18
[19] I. Kashif, S. S. Zainal. “A comprehensive MATLAB simulink PV system simulator with partial shading capability based on two-diode model,” Sol. Energy, vol.85, pp.2217-2227, 2011.
19
[20] Faran Electronic Industries Co. , http://www.faranco-rp.net
20
[21] R. W. Erickson, D.Maksimovic,“ Fundamentals of power electronics second edition”, Publisher Kluwer Academic Publishers 25/04,2002.
21
[22] E. shokati asl; M. Shadnam, M. Sabahi, “High performance Cuk converter considering non-linear inductors for photovoltaic system applications,” J. Oper. Autom. Power Eng., vol. 3, no. 2, pp.158-166, 2015.
22
[23] A. Pandey, N. Dasgupta, A. K. Mukerjee , “Design issues in implementing MPPT for improved tracking and dynamic performance”, in Proc. of the 32nd Annual Conference on IEEE Industrial Electronics, pp. 437-439, 2006.
23
[24] S. Kharzi, M. Haddadi, A. Malek, “Optimized design of a photovoltaic cathodic protection”, Arab. J. Sci. Eng., vol. 34, no. 2B, 2009.
24
[25] P. Thounthong, S. Rael, B. Davit, “Control algorithm of fuel cell and batteries for distributed generation system,” IEEE Trans. Energy Convers., vol. 23, no. 1, pp. 148-155, 2008.
25
[26] F. Boico, B. Lehman, and K. Shujaee, “Solar battery chargers for NIMH batteries,” IEEE Trans. Power Electron., vol. 22, no. 5, pp. 1600-1609, 2007.
26
[27] Sababattery Company, http://en.sababattery.ir/”.
27
ORIGINAL_ARTICLE
Capacitor Placement in Distorted Distribution Network Subject to Wind and Load Uncertainty
Utilizing capacitor banks is very conventional in distribution network in order for local compensation of reactive power. This will be more important considering uncertainties including wind generation and loads uncertainty. Harmonics and non-linear loads are other challenges in power system which complicates the capacitor placement problem. Thus, uncertainty and network harmonics have been considered in this paper, simultaneously. Capacitor placement has been proposed as a probabilistic harmonic problem with different objectives and technical constraints in the capacitor placement problem. Minimizing power and energy loss and capacitor prices are considered as objectives. Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms have been used to solve the optimization problem. Loads are subjected to uncertainty with normal probabilistic distribution function (PDF). Auto Regressive and Moving Average (ARMA) time series and two point estimate method have also been utilized to simulate the wind speed and to perform the probabilistic load flow, respectively. Finally, the proposed method has been implemented on standard distorted test cases in different scenarios. Monte Carlo Simulation (MCS) has also been used to verify the probabilistic harmonic power flow. Simulation results demonstrate the efficiency of the proposed method.
http://joape.uma.ac.ir/article_475_c39a1d346c182407978a455c2e9a26ef.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
153
164
Uncertainty
Two point estimate method
Probabilistic harmonic power flow
PSO
DEA
A.
Najafi
arsalan.najafi@gmail.com
true
1
University of Birjand
University of Birjand
University of Birjand
LEAD_AUTHOR
R.
Aboli
rezaaboli@birjand.ac.ir
true
2
University of Birjand
University of Birjand
University of Birjand
AUTHOR
H.
Falaghi
falaghi@birjand.ac.ir
true
3
University of Birjand
University of Birjand
University of Birjand
AUTHOR
M.
Ramezani
mramezani@birjand.ac.ir
true
4
University of Birjand
University of Birjand
University of Birjand
AUTHOR
[1] S. K. Bhattacharya, S. K. Goswami, “A new fuzzy based solution of the capacitor placement problem in radial distribution system”, Expert Syst. Appl., vol. 36, pp. 4207-4212, 2009.
1
[2] M. Ladjavardi, M. A. S. Masoum, “Genetically optimized fuzzy placement and sizing of capacitor banks in distorted distribution networks”, IEEE Trans. Power Delivery,vol. 23, pp. 449-456, 2008.
2
[3] V. Farahani, S. H. H. Sadeghi, H. A. Abyaneh, S. M. M. Agah, K. Mazlumi, “Energy loss reduction by conductor replacement and capacitor placement in distribution systems”, IEEE Trans. Power Syst,,vol. 28, pp. 2077-2085, 2013.
3
[4] A. A. El-Fergany, “Optimal capacitor allocations using evolutionary algorithms,” IET proc. Gener. Trans. Distrib., vol. 7, no. 6, pp. 593-601, 2013.
4
[5] D. Kaur, J. Sharma, “Multiperiod shunt capacitor allocation in radial distribution systems,” Int. J. Electric Power Energy Syst., vol. 52, pp. 247-253, 2013.
5
[6] A. Mendes, P. M. Franca, C. Lyra, C. Pissarra, C. Cavellucci, “Capacitor placement in large-sized radial distribution networks,” IET proc. Gener. Trans. Distrib., vol. 152, no. 4, pp. 496-502, 2013.
6
[7] Y. Baghzouz, “Effects of nonlinear loads on optimal capacitor placement in radial feeders”, IEEE Trans. Power Delivery, vol. 6, pp. 245-251, 1991.
7
[8] Y. Baghzouz and S. Ertem, “Shunt capacitor sizing for radial distribution feeders with distorted substation voltages”, IEEE Trans. Power Delivery, vol. 5, pp. 650-657, 1990.
8
[9] G. Bei, A. Abur, “Optimal capacitor placement for improving power quality”, in Proc. of the IEEE Power & Energy Society General Meeting , vol. 1, pp. 488-492, 1998.
9
[10] E. Baran, F. Wu, “Optimal capacitor placement in distribution systems”, IEEE Trans. Power Delivery, vol. 25, pp. 725-734, 1989.
10
[11] X. Yan, D. Zhao Yang, W. Kit Po, E. Liu, B. Yue, “Optimal capacitor placement to distribution transformers for power loss reduction in radial distribution systems”, IEEE Trans. Power Syst.,, vol. 28, pp. 4072-4079, 2013.
11
[12] S. Nojavan, M. Jalali, K. Zare, “Optimal allocation of capacitors in radial/mesh distribution systems using mixed integer nonlinear programming approach”, Electr. Power Syst. Res., vol. 107, pp. 119-124, 2014.
12
[13] T. S. Abdel-Salam, A. Y. Chikhani, R. Hackam, "A new technique for loss reduction using compensating capacitors applied to distribution systems with varying load condition," IEEE Trans. Power Deliver, vol. 9, pp. 819-827, 1994.
13
[14] M. Sedighizadeh, M. M. Mahmoodi, “Optimal reconfiguration and capacitor allocation in radial distribution systems using the hybrid shuffled frog leaping algorithm in the fuzzy framework”, J. Oper. Autom. Power Eng., vol. 3, no. 1, pp. 56-70, 2015.
14
[15] R. Baghipour, S.M. Hosseini, “A hybrid algorithm for optimal location and sizing of capacitors in the presence of different load models in distribution network”, J. Oper. Autom. Power Eng., vol. 2, no. 1, pp. 10-21, 2014.
15
[16] S. Sundhararajan, A. Pahwa, “Optimal selection of capacitors for radial distribution systems using a genetic algorithm”, IEEE Trans. Power Syst., vol. 9, pp. 1499-1507, 1994.
16
[17] T.-L. Huang, Y.-T. Hsiao, C.-H. Chang, J.-A. Jiang, “Optimal placement of capacitors in distribution systems using an immune multi-objective algorithm”, Int. J. Electr. Power Energy Syst., vol. 30, pp. 184-192, 2008.
17
[18] J.-P. Chiou, C.-F. Chang, C.-T. Su, “Capacitor placement in large-scale distribution systems using variable scaling hybrid differential evolution”, Int. J. Electr. Power Energy Syst., vol. 28, pp. 739-745, 2006.
18
[19] A. A. El-Fergany, A. Y. Abdelaziz, “Capacitor allocations in radial distribution networks using cuckoo search algorithm,” IET Gener. Transm. Distrib, vol. 8, pp. 223-232, 2014.
19
[20] A. Seifi, M. R. Hesamzadeh, “A hybrid optimization approach for distribution capacitor allocation considering varying load conditions,” Int. J. Electr. Power Energy Syst., vol. 31, pp. 589-595, 2009.
20
[21] D. Das, "Optimal placement of capacitors in radial distribution system using a Fuzzy-GA method," Int. J. Electr. Power Energy Syst., vol. 30, pp. 361-367, 2008.
21
[22] A. A. El-Fergany, A. Y. Abdelaziz, "Efficient heuristic-based approach for multi-objective capacitor allocation in radial distribution networks," IET Gener. Transm. Distrib, vol. 8, pp. 70-80, 2014.
22
[23] A. R. Abul’Wafa, “Reliability/cost evaluation of a wind power delivery system,” Electr. Power Syst. Res., vol. 81, pp. 873-879, 2011.
23
[24] G. Verbic, C. A. Canizares, “Probabilistic optimal power flow in electricity markets based on a two-point estimate method”, IEEE Trans. Power Syst,, vol. 21, pp. 1883-1893, 2006.
24
[25] S. Chun-Lien, “Probabilistic load-flow computation using point estimate method,” IEEE Trans. Power Syst,, vol. 20, pp. 1843-1851, 2005.
25
[26] R. Billinton, H. Chen, R. Ghajar, “Time-series models for reliability evaluation of power systems including wind energy,” Microelectron. Reliab., vol. 36, pp. 1253-1261, 1996.
26
[27] R. Billinton, G. Yi, “Multistate wind energy conversion system models for adequacy assessment of generating systems incorporating wind energy,” IEEE Trans. Energy Convers., vol. 23, pp. 163-170, 2008.
27
[28] R. Karki, R. Billinton, “Cost-effective wind energy utilization for reliable power supply,” IEEE Trans. Energy Convers, vol. 19, pp. 435-440, 2004.
28
[29] P. Giorsetto and K. F. Utsurogi, “Development of a new procedure for reliability modeling of wind turbine generators,” IEEE Trans. Power Appl. Syst, vol. PAS-102, pp. 134-143, 1983.
29
[30] D. Xia, G. T. Heydt, “Harmonic power flow studies - part ii implementation and practical application,” IEEE Trans. Power Appl. Syst., vol. PAS-101, pp. 1266-1270, 1982.
30
[31] M. A. S. Masoum, E. F. Fuchs, “Transformer magnetizing current and iron-core losses in harmonic power flow,” IEEE Trans. Power Delivery, vol. 9, pp. 10-20, 1994.
31
[32] Available online, www.digsilent.de/.
32
[33] G. Carpinelli, T. Esposito, P. Varilone, P. Verde, “First-order probabilistic harmonic power flow,” in Proc. of the IEEE Int. Conf. Gener. Trans. Distrib., vol. 148, pp. 541-548, 2001.
33
[34] A. A. Romero, H. C. Zini, G. Ratta, R. Dib, “Harmonic load-flow approach based on the possibility theory,” IET Gener. Transm. Distrib., vol. 5, pp. 393-404, 2011.
34
[35] J. Kennedy, R. C. Eberhart, “Particle swarm optimization”, in Proc. of IEEE Int. Conf. Neural Networks, pp. 1942-1948, 1995.
35
[36] D. Zaharie, “Influence of crossover on the behavior of differential evolution algorithms,” Appl. Soft. Comput., vol. 9, pp. 1126–1138, 2009.
36
[37] W. M. Grady, M. J. Samotyj, A. H. Noyola, “Minimizing network harmonic voltage distortion with an active power line conditioner,” IEEE Trans. Power Delivery, vol. 6, pp. 1690-1697, 1991.
37
[38] M. A. S. Masoum, M. Ladjevardi, A. Jafarian, E. F. Fuchs, “Optimal placement, replacement and sizing of capacitor Banks in distorted distribution networks by genetic algorithms,” IEEE Trans. Power Delivery, vol. 19, pp. 1794-1801, 2004.
38
[39] A. Ulinuha, M.A.S. Masoum, S. Islam, “Hybrid genetic-fuzzy algorithm for volt/var /total harmonic distortion control of distribution systems with high penetration of non-linear loads,” IET Gener. Transm. Distrib., vol. 5, pp. 425-439, 2011.
39
[40] V. R. Pandi, H. H. Zeineldin, X. Weidong, “Determining optimal location and size of distributed generation resources considering harmonic and protection coordination limits,” IEEE Trans. Power Syst,, vol. 28, pp. 1245-1254, 2013.
40
ORIGINAL_ARTICLE
Reliability and Supply Security based Method for Simultaneous Placement of Sectionalizer Switch and DER Units
This paper presents a new and useful methodology for simultaneous allocation of sectionalizer switches and distributed energy resources (DERs) considering both reliability and supply security aspects. The proposed algorithm defines the proper locations of sectionalizer switching devices in radial distribution networks considering the effect of DER units in the presented cost function and other optimization constraints such as providing the maximum number of costumers to be supplied by DER units in islanded distribution systems after possible outages. In this paper, the main goal of cost function is to minimize the total cost of expected energy not supplied (EENS) with regard to impacts of load priority and optimum load shedding in the both grid connected and islanding states after possible outages. The proposed method is simulated and tested on a case study system in both cases of with DER and non DER situations. Also, this paper evaluates the number and amount of DER, switch and different DER penetration percentage effects in cost function value. For solving of mentioned problem, this paper uses a new and strong method based on imperialist competitive algorithm (ICA). Simulation and numerical results show the effectiveness of the proposed algorithm for placement of switch and DER units in the radial distribution network simultaneously.
http://joape.uma.ac.ir/article_476_3e9e375d00cd1f981fbd5e29373239fd.pdf
2016-12-01T11:23:20
2018-02-24T11:23:20
165
174
Optimal switch placement
Optimal DER placement
Reliability assessment
Imperialist competitive algorithm
Supply security aspects
A.
Safari
asafari1650@yahoo.com
true
1
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
LEAD_AUTHOR
B.
Mohammadzadeh
mohammadzadeh@azaruniv.edu
true
2
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
AUTHOR
S.
Najafi Ravadanegh
s.najafi@azaruniv.edu
true
3
Smart Distribution Grid Research Laboratory, Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Smart Distribution Grid Research Laboratory, Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Smart Distribution Grid Research Laboratory, Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
AUTHOR
[1] N. Saito, T. G. T. Heydt, “The next generation of power distribution systems,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 225-235, 2010.
1
[2] N. Hatziargyriou, H. Asano, M. R. Iravani, C. Marnay, “Microgrids: An overview of ongoing research, development and demonstration projects,” IEEE Power Energy Mag., vol. 5, no. 4, pp. 78-94, 2007.
2
[3] Z. T. Griffin, K. Tomsovic, D. Secrest, A. Law. “Placement of dispersed generation systems for reduced losses,” In Proc. of the 33rd annual Hawaii Int. Conf. Syst. Sci., pp. 1-9, 2000.
3
[4] A. Keane, M. O’Malley, “Optimal allocation of embedded generation on distribution networks,” IEEE Trans. Power Syst., vol. 20, no. 3, pp. 1640-1646, 2005.
4
[5] W. Caisheng, M.H Nehrir. “Analytical approaches for optimal placement of distributed generation sources in power systems,” IEEE Trans. Power Syst., vol.19, no. 4, pp. 2068-2076, 2004.
5
[6] MF. AlHajri, ME. El-Hawary. “Optimal distribution generation sizing via fast sequential quadratic programming,” In Proc. of the large Eng. Syst. Conf. Power Eng.; pp. 63-66, 2007.
6
[7] T.Q.D. Khoa, PTT. Binh, HB Tran. “Optimizing location and sizing of distributed generation in distribution systems,” In Proc. of the IEEE PES Power Syst. Conf. Expos., pp. 725-732, 2006.
7
[8] G. Celli, E. Ghiani, S. Mocci, F. Pilo “A multi objective evolutionary algorithm for the sizing and sitting of distributed generation,” IEEE Trans. Power Syst., vol. 20, no. 2, pp. 750-757, 2005.
8
[9] N. Khalesi, N. Rezaei, M.R. Haghifam. “DG allocation with application of dynamic programming for loss reduction and reliability improvement,” Int. J. Electr. Power Energy Syst., vol. 33, no. 2, pp. 288-295, 2011.
9
[10] L. J. Powell, “An industrial view of utility cogeneration protection requirements,” IEEE Trans. Ind. Appl., vol. 24, no. 1, pp. 75-81, 1988.
10
[11] M. Allahnoori, Sh. Kazemi, H. Abdi, R. Keyhani, “Reliability assessment of distribution systems in presence of microgrids considering uncertainty in generation and load demand,” J. Oper. Autom. Power Eng., vol. 2, no. 2, pp. 113-120, 2014.
11
[12] H. Arasteh, M. S. Sepasian, V. Vahidinasab“ Toward a smart distribution system expansion planning by considering demand response resources,” J. Oper. Autom. Power Eng., vol. 3, no. 2, pp. 116-130, 2015.
12
[13] H. Shayeghi, M. Alilou,“ Application of multi objective HFAPSO algorithm for simultaneous placement of DG, capacitor and protective device in radial distribution network,” J. Oper. Autom. Power Eng., vol. 3, no. 2, pp. 131-146, 2015.
13
[14] R. Billinton, S. Jonnavithula, “Optimal switching device placement in radial distribution systems,” IEEE Trans. Power Delivery, vol. 11, no. 3, pp. 1646-1651, 1996.
14
[15] G. Celli, F. Pilo, “Optimal sectionalizing switches allocation in distribution networks,” IEEE Trans. Power Delivery, vol. 14, no. 3 pp. 1167-1172, 1999.
15
[16] C. Chen, etc al. “Optimal placement of line switches for distribution automation systems using immune algorithm,” IEEE Trans. Power Syst., vol. 21, no. 3, pp. 1209-1216, 2006.
16
[17] A. Moradi, M. Fotuhi-Firuzabad, “optimal switch placement in distribution systems using trinary particle swarm optimization algorithm,” IEEE Trans. Power Delivery, vol. 23, no. 1, pp. 271-279, 2008.
17
[18] P. M. S. Carvalho, L. A. F. M Ferreira, A. J. C. da Silva, “A decomposition approach to optimal remote controlled switch allocation in distribution systems,” IEEE Trans. Power Delivery, vol. 20, no. 2, pp. 1031-1036, 2005.
18
[19] Y. Mao, K. N. Miu, “Switch placement to improve system reliability for radial distribution systems with distributed generation,” IEEE Trans. Power Syst., vol. 18, no. 4, pp. 1346-1352, 2003.
19
[20] E. Atashpaz-Gargari, C. Lucas, “Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition”, In Proc. of the IEEE 2007 Congr. Evol. Comput., pp. 4661-4667, 2007.
20
[21] E. Atashpaz Gargari, E. Hashemzadeh, F. Rajabioun, R. Lucas, “Colonial competitive algorithm: a novel approach for PID controller design in MIMO distillation column process,” Int. J. Intell. Comput. Cybern., vol. 1, no. 3, pp. 337-355, 2008.
21