Coordination Improvement of Directional Overcurrent Relays in a Microgrid Using Modified Particle Swarm Optimization Algorithm

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1 Internationa Journa of Eectrica Components and Energy Conversion 2018; 4(1): doi: /j.ijecec ISSN: (Print); ISSN: (Onine) Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm Ukwuoma Pious Akushie *, Adegboye Babatunde, Tsado Jacob Department of Eectrica and Eectronics Engineering, Federa University of Technoogy, Minna, Nigeria Emai address: * Corresponding author To cite this artice: Ukwuoma Pious Akushie, Adegboye Babatunde, Tsado Jacob. Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm. Internationa Journa of Eectrica Components and Energy Conversion. Vo. 4, No. 1, 2018, pp doi: /j.ijecec Received: January 30, 2018; Accepted: February 16, 2018; Pubished: March 19, 2018 Abstract: An accurate and fast reaying scheme is of high importance in a radia distribution network and it becomes compex to reaize in a muti-sourced distribution network with Distribution Generators (DGs). The study of the existing reay coordination of the 33 kv Idu Industria Park Distribution Network, Abuja and its improvement opportunities is presented in this research in other to guarantee safety of operation and protection of the distribution network against the effects of fauts. A proposed 6 Bus Idu microgrid based on panned network expansion program was modeed using DIgSILENT PowerFactory software. Load Fow and Faut Anayses were performed on the modeed network to determine appropriate Overcurrent Reay (DOCR) settings and a Modified Partice Swarm Optimization Agorithm (MPSO) in MATLAB environment was used to optimize the Time Dia (TD) and Pickup (PU) settings of the DOCRs. The modification adopted was to keep the soution space within boundaries so as to achieve fast convergence. The sum of the operating time of the radia feeder was found to be 3.68 s whie that of the proposed 6 Bus Microgrid with 14 DOCRs and 3 DGs was found to be s which was quite fast and satisfactory after vaidation on the modeed microgrid. Keywords: Modified Partice Swarm Agorithm (MPSO), Microgrid, Overcurrent Reays (DOCRs), Reay Coordination 1. Introduction The Power situation in Nigeria has not improved despite the huge investment of the Federa Government of Nigeria. There has not been enough power made avaiabe to the DISCOs hence the need for them to start generating their own power through Embedded Generation. Embedded Generation which is aso caed Distributed Generation can provide many usefu services; it can provide on-site eectricity in the event there is faiure in the utiity power suppy [6]. The main objective of providing protective reays in eectric power system is to ensure the fast isoation of troubed area and reducing the extent of damage to the power equipment and keeping the heathy part sti in service [7]. The aim of DOCRs coordination is basicay to determine the Time Dia (TD) and Pickup Current (PU) of each reay, so as to get the tota operating time of the primary reays reduced [4]. This wi ensure swift isoation of the fauty section. The behavior of protection reays during faut is very critica to the safety of equipment and personne in the power station, because the sequence of operation of the reays is governed by the coordination scheme adopted, whereas a fast agorithm wi go a ong way to improve coordination processes [8]. This paper presents the study of Reay Coordination practice on an existing 33kV radia feeder. It is envisaged that this radia feeder was modified into a 6 Bus microgrid based on proposed network expansion by the utiity company. A case study of Katampe-Life Camp 33kV Feeder that is being managed by the Abuja Eectricity Distribution Company (AEDC) is considered. A Modified Partice Swarm

2 22 Ukwuoma Pious Akushie et a.: Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm Optimization Agorithm (MPSO) is to be deveoped to provide Improved Coordination of Overcurrent Reay (DOCR) of the proposed microgrid. The MPSO Agorithm wi provide a soution to determine vaues of TD and PU settings of each DOCR which reduces the tota sum of reays operating times but subject to known protection constraints [7]. Different researchers have done some work on Overcurrent Reay Coordination. In the course of this research work, some reviews of reated works have been sited. In [5], a research on the Protection of Power Systems with Distributed Generation was conducted. The various ways of DG protections were x-rayed. Finay, a proposa of new approaches of DG protections was made. A methodoogy based on Deveopment of cooperative and coordinated contro for distributed generation was done in [1]. This methodoogy was anchored on Differentia Evoutionary Partice Swarm Agorithm. A Simpified Veocity Modified Partice Swam Optimization (SV-MPSO) for Overcurrent reay coordination research was conducted. A Cut down approach was used to do constraint handing for DOCR coordination probem and it gave a fast convergence for a 6 bus network. The convergence speed and goba optima soution of the agorithm where found to be good when compared with its predecessors in [9]. In [2], the Big-M (penaty) method was used to optimay coordinate overcurrent reays in a distribution system. Here, a method of removing artificia variabes from the objective function by using a inear programming agorithm approach written in MATLAB was used. The agorithm was successfuy tested and found to give satisfactory resuts. In [8], a research on optima coordination for overcurrent reays using Partice Swarm Optimization technique and Linear Programing technique was conducted. The agorithms were tested on 3 and 5 bus networks using MATLAB software and it was discovered to be an improvement with the Partice Swarm Optimization agorithm after comparison with Linear Programing. A Hybrid Partice Swarm Optimization Agorithm was used in [4] to optimay coordinate Overcurrent Reays in a Microgrid. The Time Dia Settings was considered as continuous variabe and the Pickup Current as a discrete variabe. The overa coordinating time of the reays were propery minimized. Overcurrent Reay coordination used tria-and-error approach in the past, after a whie, software was introduced. Optimizing the mode of coordinating the software became a chaenge. In recent years, many research works have been done on Reay coordination studies and optima coordination of DOCRs using different optimization methods. But none has focused on coordinating Overcurrent Reays in a muti-sourced DGs network ike a Combined Heat and Power (CHP) DG. Aso, no work to the best of my knowedge has considered a Nigerian Industria Area ike Idu Industria Park Abuja where arge power suppy is needed to meet up with huge demand capacity. 2 Materias and Methods 2.1. Network Modeing and Simuation The 6 Bus microgrid network with Five (5) Combined Heat and Power (CHP) generators as shown in Figure 1 was modeed using DIgSILENT Powerfactory and the Load Fow, Faut Anaysis and detaied system data/information of the network were propery carried out. Figure 1. 6 Bus Network with 3 DGs.

3 Internationa Journa of Eectrica Components and Energy Conversion 2018; 4(1): The Reays and associated equipment settings of the network were obtained and thereafter a Modified Partice Swarm Optimization Agorithm on MATLAB software was used for the optimization and coordination of the Reay settings. Finay, the new optimized settings were tested on the modeed network to confirm reay coordination improvement. For the purpose of carity, two different case scenarios have been considered: Case 1 and Case 2 respectivey Theory/Cacuations There are two vaues to be set for Overcurrent Reays (DOCR): The Pickup Current Setting (PU) or Pug Setting (PS) and the Time Dia Setting (TD). DOCR have an Operating Characteristic Function shown in equation 1: =. (1) where K 1, K 2 and K 3 are constants depending on the type of time characteristic: Standard Inverse (SI), Very Inverse (VI) or Extremey Inverse (EI). Pug Setting Mutipier (PSM) = If/PU Typica Inverse time characteristics of these reays are known as Standard Inverse (SI), Very Inverse (VI) and Extremey Inverse (EI). Reay coordination probem can be soved optimay by using heuristic and meta heuristic optimization techniques [3]. It can aso be soved by tria and error optimization techniques. The optimization techniques define the objective function for reay coordination by equation (2). The aim of the coordination optimization probem is to cacuate the optima vaues of Time Dia and Pickup current which woud minimize the operating time of the primary reays (Vijayakumar et a., 2008). Minimizing the weighted sum of a the primary reays operating time: = (2) Where, n is the number of reays, is weight coefficient indicating the probabiity of faut occurrence and set as 1, is the operating time of primary reay. The objective function is minimized subject to the foowing constraints: a. Coordinating Criteria The Coordination Time Interva (CTI) must eapse before the backup protection trips. It has a mathematica expression shown in equation 3: T b -T p CTI (3) where T b is the operating time of the backup reay for a given faut in the protection zone k. CTI may be chosen to be equa to 0.3 seconds or ess. b. Bounds on the reay setting and operating times Upper and ower bounds are set on the TD, PU and time of operation of the reay are given in equation 3 to 6: 2.3. Linear Programming TD ijmin TD ij TD ijmax (4) PU ijmin PU ij PU ijmax (5) T imin T i T imax (6) This is a method used to achieve the best outcome (such as maximum profit or owest cost) in a mathematica mode whose requirements are represented by inear reationships. It is aso caed inear optimization. From Equation (1), the noninear equation can be transformed to a inear equation as foows, where a = =. (7) (8) (! "#) Objective function is as given in equation 9 =.. (9) The ony variabe be minimized in the objective function is TD which wi now resut to minimizing the operating time of the primary reays by satisfying the coordination between the primary and backup reays [10] Modified Partice Swarm Optimization (MPSO) The origina PSO is modified by estabishing boundaries for the optima soution space. The main issue in the constrained optimization probem is to hande the system soution within the defined performance constraints for achieving a reaistic and feasibe soution. The agorithm searches the whoe soution space and ony keeps record of feasibe soutions. Figure 2 shows the MPSO Fowchart used for the research.

4 24 Ukwuoma Pious Akushie et a.: Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm Start Initiaize the PSO parameters (parameter size, inertia weights, acceeration factor,constraints etc) Initiaize the Swarm positions/veocity using random generation Find the initia searching point (with constraint satisfied, evauate obj. function) and aso get initia pbest, gbestva, gbest. i = 1 Check the partices are within the constraints aow it or negect it Evauate Objective Function If f(x)>f(pbest) then pbest = x If f(x)>f(gbest) then gbest = x Update the veocity using equation (2.6) VeMin<=i<=VeMax No Yes Update the position using equation (2.7) VarMin<=i<=VarMax Yes No Perform position check i = i + 1 No i>iter.count Yes Dispay the resut End Figure 2. Fow Chart for proposed MPSO.

5 Internationa Journa of Eectrica Components and Energy Conversion 2018; 4(1): Optima Setting of the Overcurrent Reay Resuts Using Modified Partice Swarm Optimization Agorithm The optima settings for TD and PU are obtained by invoking the MPSO agorithm on the power system reay mode as stated in equation 1. The optimization operation was done within the defined constrained in equation 4, 5 and Simuation Resuts After the oad fow and short circuit anayses of the modeed network whie making use of the data presented in Tabes 1 to 4. The Resut for each Feeder s Maximum current eves obtained from Load Fow study for the 6 Bus Network with 3 DGs (Microgrid) are shown in Tabe 5. Aso, the Reay pairs with CT ratios and Faut Currents are shown in Tabe 6. Tabe 1. Overhead Auminum Line Data. Line No R (Ω) X (Ω) Length (km) Bus No. Nomina Apparent Power (MVA) Tabe 2. DG Data. Reactive Power (MVar) Tabe 3. Transformer Data. Nomina Votage (kv) Bus to Bus Rated Power (MVA) Vp (kv) Vs (kv) Tabe 4. Load Data. Bus No. Rea Power (MW) Reactive Power (MVar) Feeder Line Tabe 5. Maximum Current on Each Line Backup Reay Maximum Load Current (ka) Tabe 6. Primary/Backup Reay Pairs for 6 Bus Fauts. Faut Current (ka) Primary Reay Faut Current (ka) CT Ratio R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 R R :1 The optimized settings for the TD and PU of the reays using MPSO are shown in Tabe 7 and the Existing Katampe- Life Camp 33kV Feeder Overcurrent Reay settings before optimization are shown in Tabe 8 whie the Protection Settings (Overcurrent) after optimization are shown in Tabe 9. Figures 4 to 7 and Figures 9 to 12 shows the Time- Overcurrent graphs for the DOCRs using the optimized reay settings. Tabe 7. Optima Vaues of TD and PU using MPSO. Reay No. TD (s) PU Reay No. TD (s) PU Objective Function (T) s

6 26 Ukwuoma Pious Akushie et a.: Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm Tabe 8. Overcurrent Reay Setting Parameters before optimization. S/N Protective Device Location Stage Phase Current (Prim A Current Sec A) Current (p.u) TD (S) Characteristics Direction 1 Reay 1 (Katampe) Bus 1 I>t Inverse None 2 I>>t Definite None 3 Reay 2 (Life Camp) Bus 2 I>t Inverse None 4 I>>t Definit None Tabe 9. Protection Settings (Overcurrent) after optimization. 1 R1 2 R3 3 R12 4 R2 5 R6 6 R10 7 R13 8 R4 9 R5 10 R11 11 R7 12 R9 13 R14 14 R8 Protection Device Location Singe Busbar/BUS 1 Singe Busbar/BUS 1 Singe Busbar (1)/BUS 2 Singe Busbar (1)/BUS 2 Singe Busbar (1)/BUS 2 Singe Busbar (2)/BUS 3 Singe Busbar (2)/BUS 3 Singe Busbar (3)/BUS 6 Singe Busbar (3)/BUS 6 Singe Busbar (4)/BUS 5 Singe Busbar (4)/BUS 5 Singe Busbar (4)/BUS 5 Singe Busbar (5)/BUS 4 Singe Busbar (5)/BUS 4 Branch Manufacturer Mode Line 1 Line 6 Line 2 Line 1 Line 7 Line 2 Line 3 Line 5 Line 6 Line 7 Line 4 Line 5 Line 4 Line 3 Stage (Pha se) Current [pri. A] Current [sec. A] Current [p. u.] Tim e Toc Toc Toc Toc Toc Toc Toc Toc Toc Toc Toc Toc Toc Toc Characteristic Direction a Figure 3. Network with Faut on Singe Busbar 2`.

7 Internationa Journa of Eectrica Components and Energy Conversion 2018; 4(1): Figure 4. Time-Overcurrent Characteristics for Cockwise Loop1. Figure 5. Time-Overcurrent Characteristics for Anticockwise Loop1.

8 28 Ukwuoma Pious Akushie et a.: Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm Figure 6. Time-Overcurrent Characteristics for Cockwise Loop2. Figure 7. Time-Overcurrent Characteristics for Anticockwise Loop2.

9 Internationa Journa of Eectrica Components and Energy Conversion 2018; 4(1): Figure 8. Network with Faut on Line7.` Figure 9. Time-Overcurrent Characteristics for Cockwise Loop1.

10 30 Ukwuoma Pious Akushie et a.: Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm Figure 10. Time-Overcurrent Characteristics for Anticockwise Loop1. Figure 11. Time-Overcurrent Characteristics for Cockwise Loop2.

11 Internationa Journa of Eectrica Components and Energy Conversion 2018; 4(1): Figure 12. Time-Overcurrent Characteristics for Anticockwise Loop2. 4. Discussions The resuts obtained from the proposed MPSO Agorithm dispayed in Tabe 7 shows an improvement in the overa tripping timing of the reays. The optima tripping time of a the primary reays of the 6 Bus microgrid comprising of 14 DOCRs was s whie that obtained for the existing Katempe-Life Camp feeder for just 2 reays was 3.68s. Using the optimized Reay settings to run faut studies on Line 7 and Singe Busbar 2 gave various tripping times for both Cockwise Looping and Anticockwise Looping Reay coordination as shown in Figures 3 to Figures 12. Tabe 8 and 9 shows the Reay settings before and after optimization respectivey Faut on Singe Busbar 2 For a muti-oop network, Reay coordination is impemented in cockwise and anti-cockwise sequence by use of directiona overcurrent reays. From Figure 4: The Time-Overcurrent Characteristics for Cockwise Loop1, the Coordination sequence is as foows: R9 trips at 0.901s whie R1 foows at 1.698s if R9 faied to trip, then R5 trips at 2.012s, finay, R6 trips at 4.178s. From Figure 5: The Time-Overcurrent Characteristics for AntiCockwise Loop1, the Coordination sequence is as foows: R4 trips at 0.540s whie R2 foows at 0.814s if R4 fais to trip, then R11 trips at 1.565, finay, R3 trips at 3.801s. From Figure 6: The Time-Overcurrent Characteristics for Cockwise Loop2, the Coordination sequence is as foows: R11 trips at 1.665s foowed by R13 at 2.083s if R11 faied to trip, then finay R12 trips at 2.734s. From Figure 7: The Time-Overcurrent Characteristics for AntiCockwise Loop2, the Coordination sequence is as foows: R10 trips at 3.789s foowed by R8 at 4.057s if R10 faied to trip, then R6 trips at 4.478s, finay, R7 trips at 6.001s Faut on Line7 From Figure 9: The Time-Overcurrent Characteristics for Cockwise Loop1, the Coordination sequence is as foows: R9 trips at 0.849s foowed by R5 at 1.907s if R9 faied to trip, then R1 trips at 2.087s, finay, R6 trips at 3.112s. From Figure 10: The Time-Overcurrent Characteristics for AntiCockwise Loop1, the Coordination sequence is as foows: R4 trips at 0.515s foowed by R2 at 0.998s if R4 faied to trip, then R11 trips at 1.232s, finay, R3 trips at 3.527s. From Figure 11: The Time-Overcurrent Characteristics for Cockwise Loop2, the Coordination sequence is as foows: R11 trips at 1.232s foowed R14 tripping at s. From Figure 12: The Time-Overcurrent Characteristics for AntiCockwise Loop2, the Coordination sequence is as foows: R6 trips at 3.112s then R7 trips at 4.071s if R6 faied to trip.

12 32 Ukwuoma Pious Akushie et a.: Coordination Improvement of Overcurrent Reays in a Microgrid Using Modified Partice Swarm Optimization Agorithm 5. Concusion It can be confirmed from the Time-Overcurrent Characteristics of the Reays that the proposed agorithm has shown improvement in Overcurrent Reay coordination with very fast tripping coordination as dispayed in Figure 4 to Figure 12 and has reduced the compexity and painstaking method of manuay computing the coordination settings of a muti-sourced microgrid as panned expansion mode by the AEDC. The agorithm has proved very satisfactory with improvement on the reay coordination when tested on the modeed network. Hence, this proposed MPSO Agorithm has satisfied the earier stated aim and objectives of this research work. References [1] Barros, J. A. C. (2008). Deveopment of Cooperative and Coordinated Contro For Distributed Generation. University of Porto Journa, 2 (11), [2] Bedekar, P. P., Bhide, S. R., & Kae, V. S. (2009). Optimum Time Coordination Of Over Current Reays In Distribution System Using Big-M (Penaty) Method. WSEAS Trans. on Power Systems, 4 (11), [3] Buigues, G., Dyśko, A., Vaverde, V., Zamora, I., & Fernández, E. (2013). Microgrid Protection: Technica Chaenges And Existing Techniques. Paper presented at the Internationa Conference on Renewabe Energies and Power Quaity (ICREPQ 13), 20 (10), [4] Damchi, Y., Mashhadi, H. R., Sadeh, J., & Bashir, M. (2011). Optima Coordination Of Overcurrent Reays In A Microgrid System Using A Hybrid Partice Swarm Optimization. Paper presented at the Advanced Power System Automation and Protection (APAP), 2011 Internationa Conference on Power System, 2 (15), [5] Geid, M. (2005). Protection of Power Systems With Distributed Generation: State Of The Art: Citeseer, 53 (12), [6] Ibe, A., Okedu, E., & Eng, M. (2009). A Critica Review Of Grid Operations In Nigeria. Pac J Sci Techno, 10 (2), [7] Papaspiiotopouos, V. A., Kurashvii, T., & Korres, G. N. (2014). Optima Coordination Of Overcurrent Reays In Distribution Systems With Distributed Generation Based On A Hybrid PSO-LP Agorithm. Paper Presented At The Medpower 2014, 80, [8] Rathinam, A., Sattianadan, D., & Vijayakumar, K. (2010). Optima Coordination Of Overcurrent Reays Using Partice Swarm Optimization Technique. Internationa Journa Of Computer Appications ( ), 10 (2). [9] Vijayakumar, D., & Nema, R. (2009). Simpified Veocity MPSO For Over Current Reay Coordination. Internationa Journa Of Recent Trends In Engineering, 1 (3), [10] Yang, H., Wen, F., & Ledwich, G. (2013). Optima Coordination of Overcurrent Reays in Distribution Systems with Distributed Generators based on Differentia Evoution Agorithm. Internationa Transactions on Eectrica Energy Systems, 23 (1), Biography Ukwuoma Pious Akushie received his Bacheor's degree in Eectrica & Computer Engineering from the Federa University of Technoogy, Minna Nigeria in 2004 and Master's degree in Eectrica & Eectronic Engineering (Power System & Machine Option) from same university in He is a corporate member of both the Nigerian society of Engineers (NSE) and The Nigeria Institution of Power Engineers (NIPE) and is registered with the Counci for the Reguation of Engineering in Nigeria (COREN). His research interest incudes Power System Protection, Renewabe Energy Integration and Smart Grid Technoogies. He is invoved in the design and management of Energy Soutions. Adegboye Babatunde hods the BEng, MSc and PhD degrees in Eectrica Engineering of the Ahmadu Beo University, Zaria, Nigeria among others. His research interests incude Power Systems Reiabiity and Powerine Communications, where he has ectured and supervised many postgraduate students (Masters and PhD). He is currenty a Professor of Eectrica Engineering at the Federa University of Technoogy, Minna Nigeria. Professor Adegboye enjoys reading and istening to cassica music. Tsado Jacob obtained his Bacheor of Engineering Degree (B. Eng.) in Eectrica & Computer Engineering from Federa University of Technoogy Minna, Nigeria in He aso obtained M. Eng and Ph.D in Eectrica Power System & Machine from University of Benin, Benin city, Nigeria in 2001 and 2007 respectivey. He is an Associate Professor and the current Head of Department for Eectrica and Eectronics Engineering. He has authored and co-authored quite number of pubished journa papers and conference proceedings. His research area is power system and energy studies with specia interest in Protection Schemes.