IJSTR

International Journal of Scientific & Technology Research

IJSTR@Facebook IJSTR@Twitter IJSTR@Linkedin
Home About Us Scope Editorial Board Blog/Latest News Contact Us
CALL FOR PAPERS
AUTHORS
DOWNLOADS
CONTACT
QR CODE
IJSTR-QR Code

IJSTR >> Volume 4 - Issue 7, July 2015 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A New Optimization Framework To Solve The Optimal Feeder Reconfiguration And Capacitor Placement Problems

[Full Text]

 

AUTHOR(S)

Mohammad-Reza Askari

 

KEYWORDS

Index Terms: Optimal Distribution Feeder Reconfiguration (DFR), shunt capacitor placement, Point Estimate Method PEM), Bat Algorithm (BA).

 

ABSTRACT

Abstract: This paper introduces a new stochastic optimization framework based bat algorithm (BA) to solve the optimal distribution feeder reconfiguration (DFR) as well as the shunt capacitor placement and sizing in the distribution systems. The objective functions to be investigated are minimization of the active power losses and minimization of the total network costs an. In order to consider the uncertainties of the active and reactive loads in the problem, point estimate method (PEM) with 2m scheme is employed as the stochastic tool. The feasibility and good performance of the proposed method are examined on the IEEE 69-bus test system.

 

REFERENCES

[1] M. Rostami, A. Kavousi-Fard, and T. Niknam, Expected Cost Minimization of Smart Grids with Plug-in Hybrid Electric Vehicles Using Optimal Distribution Feeder Reconfiguration, IEEE Trans. on Industrial Informatics (2015) 11(2) 388 – 397

[2] Kim H., Ko Y., and Jung K. H. (1993) “Artificial neural-network based feeder reconfiguration for loss reduction in distribution systems” IEEE Trans. Power Del, 8(3) 1356-1366.

[3] A. Kavousi-Fard, A.Abunasri, A. Zare, R. Hoseinzadeh, Impact of Plug-in Hybrid Electric Vehicles Charging Demand on the Optimal Energy Management of Renewable Micro-Grids,78 Energy, 2014, 904-915.

[4] A. Kavousi-Fard, T. Niknam, Optimal Stochastic Capacitor Placement Problem from the Reliability and Cost Views using Firefly Algorithm, IET SMT, vol. 8(5), pp. 260 – 269, 2014

[5] A. Kavousi-Fard, T. Niknam, H. Taherpoor, A. Abbasi, Multi-objective Probabilistic Reconfiguration Considering Uncertainty and Multi-Level Load Model, IET SMT, vol 9 (1), 2015, pp.44-55

[6] Kashem M. A., Ganapathy V., and Jasmon G. B. (1999) “Network reconfiguration for load balancing in distribution networks” in Proc. Inst. Elect. Eng.-Gener., Transm, Distrib, 14(6) 563-567.

[7] Morton A. B. and Mareels I. M. Y. (2000) “An efficient brute-force solution to the network reconfiguration problem” IEEE Trans. Power Del, 15(3) 996–1000.

[8] Lopez E., Opaso H. (2004) “Online reconfiguration considering variability demand, Applications to real networks” IEEE Trans. Power Syst, 19(1) 549–553.

[9] Niknam T., Kavousifard A. Aghaei J. (2012) “Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimization” IET Renew. Power Gener, 6(4) 236–247.

[10] Zhou Q., Shirmohammadi D., Liu W. (1997) “Distribution feeder reconfiguration for service restoration and load balancing” IEEE Trans on Power Sys, 2(2) 724–729.

[11] Kavousi-Fard A., Akbari-Zadeh M.R (2013) “Reliability Enhancement Using Optimal Distribution Feeder Reconfiguration” Neurocomputing, 106, 1–11

[12] Ng H.N., Salama M.M.A., Chikhani A.Y. (2000) “Classification of capacitor allocation techniques” IEEE Trans. Power. Del. 15, 387–392.

[13] Civanlar S., Grainger J.J. (1985) “Volt/Var control on distribution systems with lateral branches using shunt capacitors and voltage regulators. Part II. The solution method” IEEE Trans. Power. App. Syst 104, 3284–3290.

[14] A. Kavousi-Fard, M. A. Rostami, and T. Niknam, Reliability-Oriented Reconfiguration of Vehicle-to-Grid Networks, IEEE Trans. on Industrial Informatics (2015) 99 (1), 1-8.

[15] Baldick R., Wu F.F. (1990) “Efficient integer optimization algorithms for optimal coordination of capacitors and regulators” IEEE Trans. Power Syst. 5, 805–812

[16] Chis M., Salama M.M.A., Jayaram S. (1997) “Capacitor placement in distribution systems using heuristic search strategies” IEE Proc. Gen. Trans. Distrib. 144, 225–230.

[17] Carpinelli G., Proto D., Noce C., Russo A., Varilone P. (2010) “Optimal allocation of capacitors in unbalanced multi-converter distribution systems: A comparison of some fast techniques based on genetic algorithms” Electric Power Syst. Res., 80(6) 642-650

[18] Jabr R.A. (2008) “Optimal placement of capacitors in a radial network using conic and mixed integer linear programming” Electric Power Syst. Res., 78(6) 941-948

[19] Kavousi-Fard A., Samet H. (2013) “Multi-objective Performance Management of the Capacitor Allocation Problem in Distributed System Based on Modified HBMO Evolutionary Algorithm” Electric Power and Component systems, 41 (13) 1223:1247.

[20] Masoum M., Jafarian A., Ladjevardi M., Fuchs E.F., Grady W.M. (2004) “Fuzzy approach for optimal placement and sizing of capacitor banks in the presence of harmonics” IEEE Trans. Power Del 19(2) 822–829.

[21] Bhattacharya S.K., Goswami S.K. (2009) “A new fuzzy based solution of the capacitor placement problem in radial distribution system” Expert Syst. Appl. 36, 4207–4212.

[22] A. Kavousi-Fard, A. Abbasi and A. Baziar, A novel adaptive modified harmony search algorithm to solve multi-objective environmental/economic dispatch, Journal of Intelligent & Fuzzy Systems, 26(6) (2014), pp. 2817-2823

[23] A. Baziar, A. Kavoosi-Fard, Jafar Zare, A novel self adaptive modification approach based on bat algorithm for optimal management of renewable MG, Journal of Intelligent Learning Systems and Applications, 5 (2013) 11-18

[24] Kavousi-Fard A., Niknam T. (2014) “Multi-Objective Stochastic Distribution Feeder Reconfiguration from the Reliability Point of View” Energy, 64, 342–354

[25] A. Kavousifard, H. Samet, Power System Load Prediction Based on MHBMO Algorithm and Neural Network, IEEE Conference on Electrical Engineering (ICEE), 2011, pp. 1-8, Iran

[26] A. Baziar and A. Kavousi-Fard, An intelligent multi-objective stochastic framework to solve the distribution feeder reconfiguration considering uncertainty, Journal of Intelligent & Fuzzy Systems, 26 (2014) pp. 2215–2227

[27] A. Kavousi-Fard, T. Niknam, Considering uncertainty in the multi-objective stochastic capacitor allocation problem using a novel self adaptive modification approach, Electric Power Systems Research, 103 (2013), 16-27.

[28] A. Kavousi-Fard, H. Samet, Multi-objective Performance Management of the Capacitor Allocation Problem in Distributed System Based on Modified HBMO Evolutionary Algorithm, Electric Power and Component systems, 41 (13) (2013) 1223-1247.
[29] R. Sedaghati, A. Kavousi-Fard, A hybrid fuzzy-PEM stochastic framework to solve the optimal operation management of distribution feeder reconfiguration considering wind turbines, Journal of Intelligent and Fuzzy Systems 26 (2014) 1711-1721.

[30] A. Baziar, A. Kavousi Fard, Consideration Effect of Uncertainty in the Optimal Energy Management of Renewable Micro-Grids including Storage Devices, Renewable Energy, 59 (2013) 158-166

[31] T. Niknam, A. Kavousifard, A. Baziar, Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants, Energy, 42(1) (2012) 563-573.

[32] A. Kavousi-Fard, M. R. Akbari-Zadeh, Reliability Enhancement Using Optimal Distribution Feeder Reconfiguration, Neurocomputing, 106 (2013) 1–11.

[33] A. Kavousi-Fard, F. Kavousi-Fard, A New Hybrid Correction Method for Short Term Load Forecasting Based on ARIMA, SVR and CSA, Journal of Experimental & Theoretical Artificial Intelligence, 2013. In press. DOI:10.1080/0952813X.2013.782351

[34] A. Kavousi-Fard, T. Niknam, M. Golmaryami, Short Term Load Forecasting of Distribution Systems by a New Hybrid Modified FA-Backpropagation Method, Journal of Intelligent and Fuzzy systems, 2013. DOI: 10.3233/IFS-131025

[35] A. Kavousi-Fard, T. Niknam, Optimal Distribution Feeder Reconfiguration for Reliability Improvement Considering Uncertainty, IEEE Trans. On Power Delivery, 29(3) (2014) 1344 - 1353

[36] A. Kavousi-Fard, T. Niknam, M.R. Akbari-Zadeh, B. Dehghan, Stochastic framework for reliability enhancement using optimal feeder recon figuration, Journal of Systems Engineering and Electronics Vol. 25, No. 5, August 2014, pp.901–910

[37] A. Kavousi-Fard, T. Niknam, M. Khooban, An Intelligent Stochastic Framework to Solve the Reconfiguration Problem from the Reliability view, IET SMT, 8(5), 2014, p. 245 – 259

[38] Zhenkun L., Xingying C., Kun Y., Yi S., Haoming L. (2007) “A hybrid particle swarm optimization approach for Distribution Network reconfiguration problem” IEEE Power and Energy Society General Meeting, 1–7.

[39] Prakash K. and Sydulu M (2007) “Particle swarm optimization based capacitor placement on radial distribution systems” IEEE Power Engineering Society general meeting. 1-5

[40] A. Kavousi-Fard, A. Khosravi, S. Nahavadi, A New Fuzzy Based Combined Prediction Interval for Wind Power Forecasting, IEEE Trans. on Power System (2015)