APPLICATION OF FUZZY MULTI-OBJECTIVE METHOD FOR DISTRIBUTION NETWORK RECONFIGURATION WITH INTEGRATION OF DISTRIBUTED GENERATION

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1 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: APPLICATION OF FUZZY MULTI-OBJECTIVE METHOD FOR DISTRIBUTION NETWORK RECONFIGURATION WITH INTEGRATION OF DISTRIBUTED GENERATION 1 RAMADONI SYAHPUTRA, 2 INDAH SOESANTI 1 Department of Electrcal Engneerng, Faculty of Engneerng, Unverstas Muhammadyah Yogyaarta Jl. Rngroad Barat Tamantrto, Kashan, Yogyaarta INDONESIA Department of Electrcal Engneerng and Informaton Technology, Faculty of Engneerng, Unverstas Gadjah Mada Jl. Grafa 2, Kampus UGM, Yogyaarta INDONESIA e-mal: ramadon@umy.ac.d; ndah@mt.ugm.ac.d ABSTRACT Ths paper proposes an applcaton of fuzzy mult-objectve method for dstrbuton networ reconfguraton wth ntegraton of dstrbuted generaton (DG. The method transforms the multobjectves of the confguraton optmzaton problem nto a sngle objectve problem usng theory of fuzzy set. In fuzzy set, each objectve of optmzaton s assocated wth a membershp functon. The functon represents the level of satsfacton of the objectve. There are four objectves whch are formed n fuzzy membershp functon ncludng mnmum power loss, mum branch current loadng, mum bus voltage magntude and load balancng the entre feeders of electrc power dstrbuton networ whle a radal structure must be mantaned. In ths wor, the fuzzy mult-objectve method has been appled n optmzaton of an IEEE 77-bus dstrbuton networ confguraton wth ntegraton of DG. The results show that effcency of the networ s mproved sgnfcantly. Keywords: Fuzzy Mult-Objectve; Optmzaton; Dstrbuton Networ; Dstrbuted Generaton. 1. INTRODUCTION Electrc power dstrbuton networ have sectonalzng swtches whch reman normally closed and te swtches whch reman normally open. These swtches are operated n order to confgure the networs. Reconfguraton of electrc power dstrbuton networ s bult through operaton of the swtches. In recent years, multobjectve optmzaton for networ reconfguraton problem has been mplemented. The multobjectves n dstrbuton networ optmzaton are consdered for mnmzng power loss, mprovng voltage profle, and balancng the load among the feeders whle a radal structure of the networ n whch all loads must be energzed. The motvaton of ths study s based on that the need for renewable energy sources wth respect to energy reserve and envronmental ssues mae the new power plant technologes such as mcro hydro, solar photovoltacs, wnd farms, fuel cells and other resources more and more popular. The technologes wth the capacty of less than 10 MW powered by renewable energy sources whch are connected to dstrbuton systems s called dstrbuted generaton (DG [1]. The sze and number of DG ntegrated to dstrbuton networ s ncreased rapdly. There are many advantages of DG ntegraton n dstrbuton networ,.e. reducng power losses, mprovng voltage profles and load factors and thus deferrng or elmnatng system upgrades [2-7]. Increasng n levels of DG wll need to change plannng and desgn of dstrbuton networs to harness approaches that use nformaton and communcaton technology to actvely manage the networ [8-9]. In the lterature has been much studed and conducted studes to mnmze the loss of actve power through the reconfguraton of power dstrbuton networs. Networ dstrbuton optmzaton wth networ reconfguraton proved 6668

2 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: most effectve and effcent. These research efforts can be broadly classfed nto two categores: conventonal approaches [3, 10-15] and artfcal ntellgence-based approaches (AI [4-7, 16-28]. The conventonal approach ncludes classcal optmzaton algorthms and heurstcs. The frst attempt at reconfgurng a dstrbuton networ wth a loss reducton goal was proposed by Merln and Bac [10]. They have used conventonal technques that consder a branch and are bound to determne the mnmum loss confguraton. After that, many conventonal methods amed at reducng the loss of actve power dstrbuton networ. In reference [11] t has proposed a reducton of energy loss usng crtcal swtch operatons, whle at t has consdered the applcaton aspect of the optmal dstrbuton networ confguraton. An optmzaton method for determnng networ confguraton has been studed n [14]. In [15] t has proposed a networ reconfguraton technque usng a voltage ndex a decson to determne the swtchng operaton. For most conventonal approaches, ths technque does not guarantee global optmzaton. The current method of optmzaton s the use of artfcal ntellgence (AI. A dstrbuton networ optmzaton effort based on the AI method has been submtted n [16]. They have used two algorthms to optmze dstrbuton networ confguraton for restoraton and load balancng servces. In ther study, a combnaton of heurstc rules and fuzzy logc n goal optmzaton for robust effcency and strong performance were used. The use of a genetc algorthm (GA for reconfguraton of dstrbuton networ technques to mnmze power loss has been proposed at [17], whle at [18] GA has proposed matrx theory based on matrx theory and graph theory. The applcaton of the fuzzy mult-purpose method for optmum dstrbuton networ confguraton has been presented by Das [24], and Syahputra et al. [26]. In ths method, there are several objectves that nclude actve dead power, load balancng between feeders, bus voltage rregulartes, and current branch offenses for smultaneous modelng and resumng. Crtera for choosng membershp functons for each purpose are not gven n ther wor. Also, the weght of each goal s not consdered. In our research, the problem dstrbuton formulaton s subject to electrcal and operatonal constrants. The objectves of ths research are: mnmzaton of actve power loss, mnmzaton of node voltage devaton, mnmzaton of branch offset, and load balancng among varous feeders. The above objectves are converted nto fuzzy crcuts by usng dfferent types of fuzzy membershp functons. Ths s a very nfluental factor n ths study. The radal of the dstrbuton networ must reman after reconfguraton where all loads must be energzed smultaneously. The man advantage of ths research s to propose a new networ reconfguraton method based on a fuzzy mult-purpose algorthm wth DG where all goals can be weghted smultaneously. Weght all goals depend on optmzaton prorty. The objectve functonal weghts are an mportant ssue n multobjectve optmzaton [27-28]. The goal of mnmzng actve power loss s paramount n our wor. Therefore, the proposed method can be used as another useful alternatve for optmzng dstrbuton networ confguraton wth DG ntegraton. 2. FUZZY MULTI-OBJECTIVE METHOD 2.1 Problem Formulaton Optmzaton of dstrbuton networ confguraton s a very mportant functon of dstrbuton system to reduce power loss, mprove bus voltage profle, load balancng, and to mprove system securty. Loads can be transferred from the feeder to the feeder by changng the state of the sectonalzng swtch to te swtch. In ths wor, networ reconfguraton to mnmze actve power loss can be formulated as follows: N 2 2 P Q mn Ploss R (1 2 V 1 where P loss s real power loss; P and Q are the real and reactve powers flowng out the bus, respectvely; n b s the branch number, and R and V are the resstance and magntude of voltage at bus, respectvely. The optmzaton also too nto consderaton the subject to the followng: magntude of voltage constrant, magntude of current constrant, power source lmt constrant, and radal networ constrant. The proposed algorthm alters the mult-purpose reconfguraton problem nto a sngle objectve optmzaton problem usng fuzzy set theory. In the fuzzy doman, each destnaton s assocated wth a membershp functon. Membershp functon ndcates the level of satsfacton of the goal. The functon of fuzzy membershp has an mportant role n optmzaton. The fuzzy membershp functon has not consdered the weghtng factor for each goal. The four objectves bult nto the fuzzy membershp functon nclude: reducton of actve 6669

3 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: power reducton, mum bus voltage devaton, mum branch current load ndex, and load balancng between feeders. 2.2 Membershp Functon of Fuzzy Objectve for Real Power Loss The most mportant goal of networ dstrbuton confguraton optmzaton s to reduce the actve power. Therefore, the frst tas to buld a fuzzy membershp functon s how to reduce the loss of actve power from the dstrbuton system. The total actve power rato lost after and before reconfguraton can be defned as P loss,, for 1,2,3,..., N (2 Ploss, B where, N s the total of swtches n the loop ncludng sectonalyzng-swtch and te- swtch when -th te-swtch s closed; P loss, s the total real power loss of the networ when -th branch n the loop s opened; and P loss,b s the total real power loss before networ optmzaton. It can be seen that f s hgh, real power loss reducton s low and a lower membershp value s appled. If s low, the actve power loss reducton s hgh and a hgher membershp value s appled. In ths study, membershp functon of the fuzzy mult-objectve s assgned to be trapezodal fuzzy as shown n Fg. 1. It s assumed that mn = 0.5, = 1.0, and the factor of weght for the membershp functon s 0.3. µ( Membershp Functon of Fuzzy Objectve for Bus Voltage The am of buldng the membershp functon fuzzy objectve for bus voltage s that the devaton of bus voltage should be less. The mzaton factor of bus voltage devaton may be defned as follow, V, for 1,2,3,..., N j V s, and j 1,2,3,..., N B. (4 where, N B s number of bus of dstrbuton system; V s s substaton voltage, n p.u; and V,j s voltage of node correspondng to the openng of the -th swtch n the loop, n p.u. The membershp functon of the objectve s also assgned to be trapezodal fuzzy as shown n Fg. 2. It has been assumed that mn = 0.05, = 0.1, and the weght factor for the fuzzy membershp functon s In fuzzy doman of ths study, f the mum voltage devaton s less, a hgher membershp value s appled. If devaton s more, a lower membershp value s appled. Fg. 2 shows the fuzzy membershp functon for mum of devaton of node voltage. As can be seen n Fg. 2, the fuzzy membershp value of µ(β can be defned as (, for ( mn ( 1, for mn 0, for µ( mn ( Fg. 1. Fuzzy membershp functon for power loss The value membershp functon of µ( can be expressed as (, ( mn ( 1, for 0, for mn mn for mn (3 0 mn Fg. 2. Fuzzy membershp functon for voltage devaton. 2.4 Membershp Functon of Fuzzy Objectve for Branch Current Loadng The am for buldng membershp functon of fuzzy objectve for branch current loadng s to 6670

4 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: mnmze the branch current constrant volaton. The ndex of branch current loadng could be wrten as I, m Branch current loadng ndex, I (6 for 1,2,3,..., N c, m, and m 1,2,3,..., N B 1. where, I,m s magntude of electrc current n branch-m when the -th swtch n the loop s opened; I c,m s lne capacty of swtch-m. µ( Fg. 3. Fuzzy membershp functon for current loadng ndex The mzaton factor for ndex of branch current loadng may be wrten as I, m, (7 Ic, m for 1,2,3,..., N, and m 1,2,3,..., N 1. mn B 2.5 Membershp Functon of Fuzzy Objectve for Load Balancng of Feeder Load balancng s one of the man goals of reconfguraton of dstrbuton networs. In the reconfguraton of the dstrbuton networ, each buffer must reman n a balanced state n any confguraton. The load balancng ndex (LBI represents the loadng rate between feeders. Ths ndex measures how many branches can be loaded wthout exceedng the rated capacty of the branch. An effort to ncrease the wdely loaded feedng margn s to dvert some of ts cargo to a lghtweght dstrbuton feeder. The load balancng ndex objectve may be expressed as ( IFF, IF, j LBI, j, IFF (9, for 1,2,3,..., N, and j 1,2,3,..., N. where, IF,j s current of feeder correspondng to the openng of the -th swtch n the loop; IFF, s the mum of all the electrc currents correspondng to the openng of the -th swtch n the loop whle IFF, = (IF,j, for j = 1, 2, 3,, N F. The factor of mzaton of load balancng ndex may be wrten as ( LBI, j, for 1,2,3,..., N, and F j 1,2,3,..., N F. (10 The trapezodal form of fuzzy membershp functon of ths objectve s shown n Fg. 3. When the branch current ndex exceeds unty, a lower membershp value s appled. If the branch current ndex s less than or equal to unty, the mum membershp value s assgned. It has been assumed that mn = 1.0, = 1.15, and the weght factor for the fuzzy membershp functon s 0.2. By the Fg. 3, the fuzzy membershp value of µ( can be defned as (, for ( mn ( 1, for mn 0, for mn (8 µ( mn Fg. 4. Fuzzy membershp functon for the load balancng ndex Fg. 4 shows the fuzzy membershp functon for ndex of load balancng. From Fg. 4, the fuzzy membershp value of µ( can be expressed as 6671

5 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: (, for ( mn ( 1, for mn 0, for mn (11 In ths study, t has been assumed that mn = 0.10, = 0.50, and the weght factor for the fuzzy membershp functon s METHODOLOGY In ths research, optmzaton of power dstrbuton networ confguraton by mantanng radal structure. The fuzzy mult-objectve method for dstrbuton networ optmzaton has been expanded by addng weghtng factors to each objectve functon. The addton of ths weght s an extenson of the method that has been done by the researcher presented n reference [11]. It provdes an mportant weghtng factor n mult-objectve optmzaton, but has not been used n the reconfguraton of dstrbuton networs. The weghtng of the objectve functon s to lose power by 0.35, for the purpose functon of the bus voltage of 0.325, for the current branch loadng ndex of 0.3, and for the load balancng at The proposed extended fuzzy mult-purpose algorthm for optmzng the dstrbuton networ confguraton n ths study s shown n Fgure 5. In ths study, the boundary constrants are defned as: DG whch s ntegrated only from wnd and solar power plants. Start Read the bus data, load data, and branch data of dstrbuton networ Run the load-flow program to count real power loss, bus voltage, and branch currents Determne the fuzzy membershp values of objectve functons Determne the weghts of all fuzzy objectve Determne the voltage dfference across the te swtches: Vte,( for = 1,2,, n-te Identfy Vte, =Vte,( Vte,>0.01? Yes No Output results Select the te swtch and dentfy the total number of loop swtch N For = 1 to N, count µ, µ, µ, and µ usng (3, (5, (8, and (11, respectvely, and evaluate: D, = mn{µ,µ,µ,µ}; Stop Count OS = {D,}, for = 1, 2, N = +1 Fg. 5. Fuzzy Mult-Objectve Method For Networ Confguraton Optmzaton 4. RESULTS AND DISCUSSION In ths research, optmzaton of power dstrbuton networ confguraton usng multobjectve fuzzy method. The dstrbuton networ s modelled that DG comes from an ntegrated renewable energy source. There are two types of DGs that are modelled to connect solar photovoltac 6672

6 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: dstrbuton networs and wnd farms. DG operaton s consdered stable. Therefore, DG from solar photovoltacs s modelled only as actve power njected, whereas DG from wnd farms s modelled as ether actve or reactve power, both njecton P and Q. In ths study, a radal dstrbuton networ of 20 V has been examned. Ths system has one substaton, two feeders, and 77 buses as shown n Fgure.6. The swtch from the dstrbuton system conssts of 114 encodng swtches and 10 te swtches. The swtch tes of ths system are open under normal condtons. Fgure 1 shows the ntal confguraton of power dstrbuton networ wthout DG ntegraton. Load and branch data from the IEEE 77-bus dstrbuton networ can be found at [12]. In order to analyze the mpact of DG, some DGs on each bus 5, 7, 14, 22, 28, 34, 36, 41, 46, 54, 59, 68, 70 and 74 are nstalled, as shown n TABLE I. The DG model conssts of both solar photovoltac and wnd farms. DG solar photovoltacs wth unt power factor and wnd farms wth a power factor of (laggng are assumed. Table I Dg Locaton And Capacty On Ieee 77-Bus Dstrbuton System Bus Number DG Capacty (W Power Factor Fg.6. IEEE 77-Bus Dstrbuton Networ 6673

7 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: Fg. 7. Dstrbuton Of Power Loss Before Optmzaton For IEEE 77-Bus Test System Fg. 8. Dstrbuton Of Power Loss After Optmzaton For IEEE 77-Bus Test System In ths research, the IEEE dstrbuton system of 77 buses has been checed, as shown n Fgure.6. The research conducted s the dstrbuton networ optmzaton. Optmzaton s done to mprove dstrbuton networ performance. The ultmate goal s to mprove the effcency of the dstrbuton networ. For the base case, pror to the optmzaton of the networ confguraton, the total actve tssue loss under study was W. The dspersed actve power loss of each dstrbuton networ bus for the base case s shown n Fgure 7. Under these crcumstances, the mnmum voltage s p.u whch occurs on bus 76. From the case study results n ths study, t can be seen from the 77 bus system that ntegrates DG has the effect of reducng actve power loss to the feeder on ths partcular case. Ths result can be seen by runnng the power flow program n Matlab software. Load flow smulaton results show that the total loss of actve power of the system wth DG ntegraton s W, or n other words the dstrbuton networ effcency s 94.73%, as shown n TABLE II. For the evaluaton of the voltage profle t produces a mnmum voltage of p.u on bus 76. Furthermore, the dstrbuton networ confguraton s optmzed. The optmzaton method used s fuzzy based method. After expermentng wth the extended fuzzy multfunctonal technque for reconfguraton purposes, the total actve power loss was W, or n other words, the effcency of the research networ was 96.05%, as shown n TABLE II. The loss of scattered power from each dstrbuton networ bus wth DER ntegraton after reconfguraton s shown n Fgure 8. From our research results shown n Fgures 7 and 8, t was observed that losses n almost every bus were reduced, except at 4, 6, 16, 17, 18, 19, 20, and 53, where losses ncrease due to shftng the load to ths feeder. The mnmum voltage s p.u magntude occurrng on bus 76. TABLE II The Smulaton Results Of IEEE 77-Bus Dstrbuton Networ Test Case Actve Power Loss (W Effcency of Dstrbuton Networ (% Dstrbuton networ wthout DG before reconfguraton Dstrbuton networ wth DG before reconfguraton Dstrbuton networ wth DG after reconfguraton Parameters of Analyss Mnmu m Voltage (p.u (V (V (V76 Te Swtches to be Closed NA NA Lne3, Lne4, Lne6, and Lne7 Sectona -lzng Swtches to be Open NA NA J9, J16, J21, and J

8 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: advantages of the proposed method are the ablty to reduce the loss of actve power and ncrease the voltage quantty of each dstrbuton networ bus to mprove networ performance. The smulaton results show that for the IEEE 77-bus test system, 1.38% mprovement n dstrbuton networ effcency s acheved by ths method. The fuzzy mult-objectve method proposed n ths paper has sgnfcant loss reducton to mprove the performance of electrcal dstrbuton systems by consderng DG ntegraton. Fg. 9. Voltage Profle For Each Bus Of IEEE 77-Bus Test System Analyss of the next smulaton result s on the dstrbuton networ voltage profle. Based on the research results, the voltage profle for each bus from the IEEE 77-bus power dstrbuton networ has been shown n Fgure 9. As can be seen n Fgure 9 and TABLE II that the mnmum voltage value before optmzaton s pu that occurs on bus 76, whle the mnmum magntude of voltage after optmzaton s pu whch also occurs on the same bus. Furthermore, data observed the nfluence of nstallaton of DG n the dstrbuton networ. The mpact of DG deployment n some locatons of the model of IEEE 77-bus bus test system s an ncrease n the voltage of the bus. The mum voltage after optmzaton s p.u n magntude occurrng on bus 36, as shown n Fgure 9. From the test results of networ dstrbuton networ of radal model f IEEE 77-bus whch DG has the effect of loss reducton and ncrease of voltage quantty at feeder, and structure of optmum networ topology n base case s dfferent from DG ntegraton. Based on the radal dstrbuton system of 77 IEEE buses wth DG ntegraton, the fuzzy mult-objectve method proposed n ths paper has sgnfcant loss reducton to mprove the performance of electrcal dstrbuton systems by consderng DG ntegraton. Optmzaton method proved able to ncrease dstrbuton networ effcency sgnfcantly. 5. CONCLUSION In ths study, an effcent, fuzzy mult-objectve method for optmzng dstrbuton networ confguratons wth DG ntegraton to mprove performance has been proposed. The advantages of ths method have been demonstrated by the IEEE 77-bus dstrbuton networ test system. The 6. ACKNOWLEDGEMENTS The research team would le to than profusely to the Mnstry of Research, Technology and Hgher Educaton for fundng ths research. REFRENCES: [1] Syahputra, R., Roband, I., Ashar, M. (2015. Reconfguraton of Dstrbuton Networ wth DER Integraton Usng PSO Algorthm. TELKOMNIKA, 13(3. pp [2] Syahputra, R., Soesant, I., Ashar, M. (2016. Performance Enhancement of Dstrbuton Networ wth DG Integraton Usng Modfed PSO Algorthm. Journal of Electrcal Systems (JES, 12(1, pp [3] Syahputra, R., Soesant, I. (2016. Desgn of Automatc Electrc Bat Stove for Bat Industry. Journal of Theoretcal and Appled Informaton Technology (JATIT, 87(1, pp [4] Soesant, I., Syahputra, R. (2016. Bat Producton Process Optmzaton Usng Partcle Swarm Optmzaton Method. Journal of Theoretcal and Appled Informaton Technology (JATIT, 86(2, pp [5] Syahputra, R., Roband, I., Ashar, M. (2015. PSO Based Mult-objectve Optmzaton for Reconfguraton of Radal Dstrbuton Networ. Internatonal Journal of Appled Engneerng Research (IJAER, 10(6, pp [6] Jamal, A., Surpto, S., Syahputra, R. (2017. Power Flow Optmzaton Usng UPFC Based on Neuro-Fuzzy Method for Mult-machne Power System Stablty. Internatonal Journal of Appled Engneerng Research (IJAER, 12(6, pp [7] D. Das, A Fuzzy Mult-Objectve Approach for Networ Reconfguraton of Dstrbuton Systems, IEEE Transactons on Power Delvery, vol. 21, no. 1, 2006, pp

9 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: [8] Jamal, A., Surpto, S., Syahputra, R. (2016. Performance Evaluaton of Wnd Turbne wth Doubly-Fed Inducton Generator. Internatonal Journal of Appled Engneerng Research (IJAER, 11(7, pp [9] Syahputra, R., Roband, I., Ashar, M. (2015. Performance Improvement of Radal Dstrbuton Networ wth Dstrbuted Generaton Integraton Usng Extended Partcle Swarm Optmzaton Algorthm. Internatonal Revew of Electrcal Engneerng (IREE, 10(2. pp [10] Syahputra, R., Roband, I., Ashar, M. (2014. Optmzaton of Dstrbuton Networ Confguraton wth Integraton of Dstrbuted Energy Resources Usng Extended Fuzzy Mult-objectve Method. Internatonal Revew of Electrcal Engneerng (IREE, 9(3, pp [11] Syahputra, R., Roband, I., Ashar, M. (2014. Performance Analyss of Wnd Turbne as a Dstrbuted Generaton Unt n Dstrbuton System. IJCSIT, Vol. 6, No. 3, pp [12] Syahputra, R., Roband, I., Ashar, M. (2014. Optmal Dstrbuton Networ Reconfguraton wth Penetraton of Dstrbuted Energy Resources, Proceedng of st Internatonal Conference on Informaton Technology, Computer, and Electrcal Engneerng (ICITACEE 2014, UNDIP Semarang, pp [13] Jamal, A., Syahputra, R. (2014. Power Flow Control of Power Systems Usng UPFC Based on Adaptve Neuro Fuzzy. IPTEK Journal of Proceedngs Seres. 2014; 1(1: pp [14] Soedbyo, Ashar, M., Syahputra, R. (2014. Power loss reducton strategy of dstrbuton networ wth dstrbuted generator ntegraton, Proceedng of st Internatonal Conference on Informaton Technology, Computer, and Electrcal Engneerng (ICITACEE 2014, UNDIP Semarang, pp [15] Syahputra, R., Soesant, I. (2016. DFIG Control Scheme of Wnd Power Usng ANFIS Method n Electrcal Power Grd System. Internatonal Journal of Appled Engneerng Research (IJAER, 11(7, pp [16] Syahputra, R., Roband, I., Ashar, M., (2012, Reconfguraton of Dstrbuton Networ wth DG Usng Fuzzy Mult-objectve Method, Internatonal Conference on Innovaton, Management and Technology Research (ICIMTR, May 21-22, 2012, Melacca, Malaysa. [17] Syahputra, R., Soesant, I. (2015. Power System Stablzer model based on Fuzzy-PSO for mprovng power system stablty Internatonal Conference on Advanced Mechatroncs, Intellgent Manufacture, and Industral Automaton (ICAMIMIA, Surabaya, Oct pp [18] Syahputra, R. (2016. Applcaton of Neuro- Fuzzy Method for Predcton of Vehcle Fuel Consumpton. Journal of Theoretcal and Appled Informaton Technology (JATIT, 86(1, pp [19] Syahputra, R., (2013, A Neuro-Fuzzy Approach For the Fault Locaton Estmaton of Unsynchronzed Two-Termnal Transmsson Lnes, IJCSIT, Vol. 5, No. 1, pp [20] Syahputra, R., Soesant, I. (2015. Control of Synchronous Generator n Wnd Power Systems Usng Neuro-Fuzzy Approach, Proceedng of Internatonal Conference on Vocatonal Educaton and Electrcal Engneerng (ICVEE 2015, UNESA Surabaya, pp [21] Jamal, A., Surpto, S., Syahputra, R. (2015. Mult-Band Power System Stablzer Model for Power Flow Optmzaton n Order to Improve Power System Stablty. Journal of Theoretcal and Appled Informaton Technology (JATIT, 80(1, pp [22] Syahputra, R., Wyag, R.O., Sudarsman. (2017. Performance Analyss of a Wnd Turbne wth Permanent Magnet Synchronous Generator. Journal of Theoretcal and Appled Informaton Technology (JATIT, 95(9, pp [23] Syahputra, R. (2017. Dstrbuton Networ Optmzaton Based on Genetc Algorthm. Jurnal Tenolog, Journal of Electrcal Technology UMY (JET-UMY, 1(1, pp [24] Jamal, A., Syahputra, R. (2016. Heat Exchanger Control Based on Artfcal Intellgence Approach. Internatonal Journal of Appled Engneerng Research (IJAER, 11(16, pp [25] Syahputra, R., Soesant, I. (2016. An Optmal Tunng of PSS Usng AIS Algorthm for Dampng Oscllaton of Mult-machne Power System. Journal of Theoretcal and Appled Informaton Technology (JATIT, 94(2, pp [26] Syahputra, R., Roband, I., Ashar, M., (2011, Control of Doubly-Fed Inducton Generator n Dstrbuted Generaton Unts Usng Adaptve Neuro-Fuzzy Approach. Internatonal Semnar on Appled Technology, Scence and 6676

10 Journal of Theoretcal and Appled Informaton Technology 2005 ongong JATIT & LLS ISSN: E-ISSN: Arts (APTECS. 2011; pp [27] Syahputra, R., Soesant, I. (2016. Power System Stablzer Model Usng Artfcal Immune System for Power System Controllng. Internatonal Journal of Appled Engneerng Research (IJAER, 11(18, pp [28] Syahputra, R., Soesant, I. (2016. Applcaton of Green Energy for Bat Producton Process. Journal of Theoretcal and Appled Informaton Technology (JATIT, 91(2, pp