Optimal fuzzy switch placement to increase automation level of electric distribution network considering asset management principles

Abstract

Since distribution sector is inherent into high amount of failures, distribution companies (DISCOs) are responsible of attaining an acceptable value for the reliability indices and otherwise they will face up to complaints. So they are usually obligated by regulators to invest on reliability improvement of network. But this investment on reliability is usually from the DISCO’s viewpoint and is also irrespective of customer satisfaction level. In other words, customers are not at the same level of sensitivity to interruptions but DISCO improves the reliability of network without considering the differences in importance degree of loads and their level of reliability requirement. On the other hand DISCOs attempt to reduce their investment costs as much as possible. This paper introduces a novel approach in the field of joint switch placement that can reduce the switch cost from the perspective of asset management policies. To this end, two switch placement plannings in different types of strategies are performed to compare their results. Firstly as witch placement is performed based on reducing the total energy not supplied (ENS) of the system. Then by revising the strategy, a fuzzy switch placement is performed from the DISCO’s point of view which just considers the total ENS of load points most sensitive to interruptions known as important or critical loads. Furthermore, by meeting the related constraints, the reliability of low sensitive customers is disregarded. This is a load importance based planning which can result in switch cost reduction relative to the amount achieved in previous strategy and implies the management of risks associated with reliability and respective constraint. Fuzzy method and new switching mechanism in fuzzy environment of network are implemented to modeling and controlling the risks associated to ENS of critical loads and also the ENS of system.

Keywords

fuzzy switch placement / asset management / distribution company / reliability / load importance based planning

References

[1] TorO, ShahidehpourMPower distribution asset management [C]// IEEE Power Engineering Society General Meeting, 2006, Montreal, IEEE: 17

[2] NordgårdD E. A framework for risk-informed decision support in electricity distribution companies utilizing input from quantitative risk assessment [J]. Electrical Power and Energy Systems, 2012, 43(1): 255-261

[3] DehghanianP, FotuhiM, ShourakiS B, KazemiA. Critical component identification in reliability centered asset management of power distribution systems via fuzzy AHP [J]. IEEE Systems Journal, 2012, 6(4): 593-602

[4] MoradkhaniA, HaghifamM R, MohammadzadehM. Failure ratemodelling of electric distribution overhead lines considering preventive maintenance [J]. IET Gen, Trans & Distr, 2013, 8(6): 1028-1038

[5] CatrinuM D, NordgårdD E. Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management [J]. Reliability Engineering and System Safety, 2011, 96(6): 663-670

[6] BillintonR, JonnavithulaS. Optimal switching device placement in radial distribution systems [J]. IEEE Trans Power Delivery, 1996, 11(3): 1646-1651

[7] Abiri-JahromiA, FotuhiM, ParvaniaM, MoslehM. Optimized sectionalizing switch placement strategy in distribution systems [J]. IEEE Trans Power Delivery, 2012, 27(1): 362-370

[8] XuY, LiuC, SchneiderK P, TonD T. Placement of remote-controlled switches toenhance distribution system restoration capability [J]. IEEE Transactions Power Systems, 2016, 31(2): 362-370

[9] SilvaL, GonzalezJ F, UsbertyF, LyraC, CavellucciC, ZobenV. Switch allocation problems in power distribution systems [J]. IEEE Trans Power Syst, 2014, 30(1): 246-253

[10] ShahsavariA, FereidunianA, MazhariS M. A joint automatic and manual switch placement within distribution systems considering operational probabilities of control sequences [J]. Int Tran Electr Energ Syst, 2015, 25(11): 2745-2768

[11] BezerraJ R, BarrosoG, LeaoR, SampioR. Multiobjective optimization algorithm for switch placement in radial power distribution networks [J]. IEEE Trans Power Delivery, 2015, 30(2): 545-552

[12] SardouG, BanejadM, HooshmandR, DastfanA. Modified shuffled frog leaping algorithm for optimal switch placement in distribution automation system using a multi-objective fuzzy approach [J]. IET Gen Trans & Dist, 2012, 6(6): 493-502

[13] FalaghiH, HaghfamM R, SinghC. Ant colony optimization-based method for placement of sectionalizing switches in distribution networks using a fuzzy multiobjective approach [J]. IEEE Trans on Power Delivery, 2009, 24(1): 268-276

[14] SamadiF, SalehiJ. Stochastic multi-objective framework for optimal dynamic planning of interconnected microgrids [J]. IET Renewable Power Generation, 2017, 11(14): 1749-1759

[15] PomboA, PinaJ, PiresV. Multiobjective planning of distribution networks incorperating switches and protective devices using a memetic optimization [J]. Reliability Engineering & System Safety, 2015, 136: 101-108

[16] MAZIDI M R, AGHAZADEH M, TESHNIZI Y, MOHAGHEGHI E. Optimal placement of switching devices in distribution networks using multi-objective genetic algorithm NSGA-II [C]// Electrical Engineering (ICEE). Iranian Conference. Mashhad, Iran, 2013.

[17] ROSADO I, ALBA E. Optimizing the number and location of switching devices in power distribution networks [C]// Advances in Mechanical and Electronic Engineering. 2013: 309–316.

[18] MazhariS M, MonsefH, RomeroR. Ahybrid heuristic and evolutionary algorithm for distribution substation planning [J]. IEEE Systems Journal, 2015, 9(4): 1396-1408

[19] GitizadehM, VahedA, AghaeiJ. Multistage distribution system expansion planning considering distributed generation using hybrid evolutionary algorithms [J]. Applied Energy, 2013, 101: 655-656

[20] PopovichD S, PopovichZ N. A risk management procedure for supply restoration in distribution networks [J]. IEEE Trans Power Syst, 2004, 19(1): 221-228

[21] NazarkoJ, ZalewskiW. The fuzzy regression approach to peak load estimation in power distribution systems [J]. IEEE Trans Power Syst, 1999, 14(3): 809-814

[22] Ramirez-RosadoI J, Domigez-NavaroJ A. Possibilistic modelbased on fuzzy sets for the multiobjective optimal planning of electric power distribution networks [J]. IEEE Trans Power Syst, 2004, 19(4): 1801-1810

[23] ShyamalA K, PalM. Triangualr fuzzy matrices [J]. Iranian Journal of Fyzzy Systems, 2007, 4(1): 75-87

[24] LiW, ZhouJ, XieK, XiongX. Power system risk assessment using a hybrid method of fuzzy set and Monte Carlo simulation [J]. IEEE Transaction on Power Sys, 2008, 23(2): 336-343

[25] BortolanG, DeganiR. A review of some methods for ranking fuzzy subsets [J]. Fuzzy Sets and Systems, 1985, 15(1): 1-19

[26] FortempsP, RoubensM. Ranking and defuzzication methods based on area compensation [J]. Fuzzy Sets and Systems, 1996, 82(3): 319-330

[27] KhademiN, BahaabadiM R, MohaymanyA S, ShahiJ. Deriving fuzzy inequalities using discreteapproximation of fuzzy numbers [J]. International Journal of Industerial Engineering & Production Research, 2013, 24(3): 207-216

[28] TsengY, KleinC M. New algorithm for the ranking procedure in fuzzy decsion making [J]. IEEE Trans Power Syst, 1989, 19(5): 1289-1296

[29] BooksteinA, KulyukinV, RaitaT. Generalized hamming distance [J]. Information Retrieval, 2002, 5(4): 353-375

[30] MohammadiM, AbasiM, RozbahaniA M. Fuzzy-GA based algorithm for optimal placement and sizing of distribution static compensator (DSTATCOM) for loss reduction of distribution network considering reconfiguration [J]. Journal of Central South University, 2017, 24(2): 245-258

[31] MohammadiM, RozbahaniA M, BahmanyarS. Power loss reduction of distribution systems using BFO based optimal reconfiguration along with DG and shunt capacitor placement simultaneously in fuzzy framework [J]. Journal of Central South University, 2017, 24(1): 90-103

[32] DebK, AgrawalS, PratabA. A fast and elisit multiobjective genetic NSGA-II [J]. IEEE Trans Evolutionay Computation, 2002, 6(2): 182-197

[33] ZangenehA, JadidS, Rahimi-KianA. A fuzzy environmental-technical-economic model for distributed generation planning [J]. Energy, 2011, 36(5): 3437-3445

[34] WangL, SinghC. Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm [J]. Elect Power Syst Res, 2007, 77(1): 1654-1664

[35] YinS, LueC N. Distribution feeder scheduling considering variable load profile and outage cost [J]. IEEE Trans Power Syst, 2009, 24(2): 652-660