Optimal Location of Remote Terminal Units in Distribution System Using Genetic Algorithm

Transcription

1 Proceedngs of the 14 th Internatonal Mddle East Power Systems Conference (MEPCON 10), Caro Unversty, Egypt, December 19-21, 2010, Paper ID 296. Optmal Locaton of Remote Termnal Unts n Dstrbuton System Usng Genetc Algorthm A.A.E. Shammah A. Abou El-Ela Ahmed M. Azmy South Delta Electrcty Dstrbuton Company SDEDC Faculty of Engneerng, Mnoufya Unversty Faculty of Engneerng, Tanta Unversty berosat@yahoo.com draaa50@hotmal.com Azmy.ahmed@hotmal.com Abstract - The paper presents a proposed technque to nvestgate the problem assocated wth the optmal locaton of remote termnal unts (RTUs) wthn dstrbuton networks. The RTUs enable montorng dfferent locatons, whch are lnked to the central control room (CCR) through a communcaton system. The mult-populaton real-coded Genetc Algorthm (GA) s used as an optmzaton technque to select the optmal locatons of RTUs. The objectve functon n the optmzaton technque s to mnmze the total cost ncludng the captal costs and the runnng cost. The captal costs of RTUs represent nstallng and relocatng RTUs. The optmal locaton of the RTUs s based on the load type, load capacty, level of voltage drop and falure rate. A part of the Egyptan dstrbuton network s used as a real test system to show the valdty, capablty and effcency of the proposed technque. Index Terms - Dstrbuton system, Genetc Algorthm, Optmzaton, Remote Termnal Unts I. INTRODUCTION Operaton of dstrbuton systems nvolves a long lst of optmzaton problems, such as: network expanson at mnmum cost and network reconfguraton. Ths can be accomplshed keepng n mnd certan objectve functons (e.g., feeder and/or substaton balancng, loss reducton, voltage-profle mprovement, etc) [1]. When practcally dealng wth those optmzaton problems, t s mportant to recognze that dstrbuton networks operate n a radal confguraton although they are structurally meshed. The optmal operaton of dstrbuton networks are acheved regardng one of the well known crtera. Ths can nvolve: the mnmzaton of network losses [2], the mnmzaton of voltage devatons at the customer loadng ponts and the maxmzaton of the system relablty [1]. Network reconfguraton s the process of alterng the topologcal structures of dstrbuton feeders by changng the states of the sectonalzng and te swtches under both normal and abnormal operatng condtons [3]. Durng normal operatng condtons, networks are reconfgured to reduce the system real power losses, releve loads n the network and ncrease network relablty. The medum voltage dstrbuton system nsde ctes s desgned as loops. These loops are normally opened at normal operatng condtons. The ponts of openng the loops are determned by the operaton and control groups n the electrcty dstrbuton companes. When a fault occurs on a feeder, the faulted secton has to be dentfed and solated [4]. The solated sectons wll have to be fed from alternatve feeders untl the faulty branch s repared. From the optmzaton pont of vew, the tme perod of solatng any secton has to be mnmzed. The mnmzaton process depends on the structure of the dstrbuton system and the capablty of detectng and solvng the problem. In addton, the possblty of provdng alternatve feedng can help n mnmzng the nterrupton perod. In South Delta Electrcty Dstrbuton Company (SDEDC) a Supervsory Control and Data Acquston system (SCADA) s bult based on Remote Termnal Unt (RTU) for customersde Dstrbuton Automaton System (DAS) [5]. It s to apply automaton technque for operatng and controllng low voltage (LV) downstream [6], [7]. The developed SCADA system provdes fault solaton operaton, montorng and controllng functons for the operators and data collecton for future analyss [7]. An embedded Ethernet controller s used as RTU to act as converter for Human Machne Interface (HMI) and to nteract wth dgtal nput and output modules [7], [8]. RTU represents the master and dgtal nput and output modules are the slaves. RTU wll ntate the transacton wth the dgtal nput and output modules. These (RTUs) collect felds of data and send them back to a master staton va a communcatons system [9]. The RTU provdes an nterface to the feld analog and dgtal sensors stuated at each remote ste. The master staton dsplays the acqured data and also allows the operator to perform remote control tasks. So, the RTU nterfaces wth the real-world devces, t s usually consdered as the eyes, ears, and hands of the master staton [10-12]. The ncluson of a mcroprocessor n the RTU enables off-loadng the communcaton channel and the master staton computer. Ths s accomplshed by performng some of the further processng steps prevously done by the master computer. In ths way, overall product cost can be reduced, flexblty can be mproved and performance can be enhanced [13]. A proposed method s presented n [14] for Improvng relablty on electrcal dstrbuton system by consderng annual load curve changes and falure rate. To relocate feederswtches and pole-mounted RTUs n the man feeder, Genetc Algorthm s used as an optmzaton tool to mnmze the outage cost of customers and utlty provders as well as the feeder devce lfe-cycle cost. However, no techncal consderatons are taken nto account. The focus n [15-17] s 847

2 on the nterrupton cost and/or lfecycle cost of the dstrbuton system n [15], wthout consderng outage cost and lfe-cycle cost of large sze systems and load curve of dstrbuton system. To carry out ths task, modern optmzaton technques such as genetc algorthm should be appled. A new remote termnal unt (RTU) placement algorthm s presented n [18]. The objectve of ths algorthm s to place a mnmum set of RTUs, whch satsfes three mportant constrants of the problem; observablty, absence of crtcal measurements, and relablty requrements defned n terms of RTU loss. Ths paper presents an effectve technque to fnd the optmal locaton of Remote Termnal Unts RTUs n a rng dstrbuton system. The mult-populaton real-coded Genetc Algorthm (GA) s a selected technque to carry out ths optmzaton approach. The objectve functon ncludes the captal cost of RTUs and the runnng cost whch s dvded nto customer cost and utlty cost. The mportance of certan nodes s consdered n the optmzaton process snce they represent specal sgnfcance for the utlty and/or the customer. A man pont s to test the ntroduced approach on a real dstrbuton system. Therefore, the technque s mplemented on the 11kv dstrbuton network n Tanta cty as a part of the Egyptan dstrbuton network. The results ensure the capablty of the proposed approach to mnmze the objectve functon as much as possble. II. PROBLEM FORMULATION The followng basc assumptons are used n formulaton of the objectve functon. The man feeder has varous types of customers. There are four types of customers: resdental, commercal, ndustral and mportant-place customers such as hosptals, government etc. The known nformaton of each load pont s the type of customer, permanent falure rate (FR), mean repar tme, and the connected KVA. The length of each secton s known and gven n meters III. OBJECTIVE FUNCTION The research ams to mnmze the total cost of the system ncludng the captal cost and the runnng cost. The captal cost nstallaton cost represents the locatng and relocatng of the RTUs ncludng lfe cycle cost of RTUs that are nstalled on the man feeder. The runnng cost ncludes the summaton of customer and electrcal power utltes outage cost. The outage cost s related to all possble faults at each secton for dfferent possbltes of RTUs exstence. For a fault at secton, the objectve s to mnmze the followng functon: n mn Total Cost = ( IC + UC ) + m * RC + j * RIC (1) = 1 IC s the customer outage cost due to outage n secton, UC s the utlty outage cost due to outage n secton, m s the number of RTUs, n s the number of sectons, j s the number of RTUs that are ntally nstalled and have to be relocated to new postons for economc reasons, and RIC s the average cost of the relocaton process. In the cost functon of Equ.(1), three terms can be recognzed. The frst term " ( IC + UC )" represents the total outage cost ncludng the customer and utlty cost. The second term " m * RC " s the total cost of new RTUs to be nstalled and the last term " j * RIC " s the total cost of relocatng RTUs. A. Customer outage cost due to a fault at secton Ths cost s the summatons of customer outage cost n every secton due to a fault at secton ". Each secton has ts outage cost dependng on ts amount of load, proporton of load types, and correspondng outage duratons. IC = Fr ( C1L1 + C2L2 + C3L CjL j ) (2) Fr s the outage rate of secton (Falure/year), C s the customer outage cost n every secton due to a j fault at secton, and L s the amount of load at each secton. j B. Customer cost multpler of load at secton j due to a fault at secton Customer cost multpler s the cost per klowatt hour: C j = OD *(( Tre * Re + Tm * Im ) + Tco * Co + Tn * In ) (3) OD s the outage duraton of secton j due to a fault n secton, Re s the load percentage of resdental customers, Im s the load percentage of very mportant places, Co s the load percentage of commercal customers, In s the load percentage of ndustral customers, Tre s the average cost damage of resdental customer per kwh, T m s the average cost damage of mportant customer per kwh, Tco s the average cost damage of commercal customer per kwh, and T s the average cost damage of ndustral customer per kwh n C. Customer outage cost due to a fault at secton The cost s the summatons of utlty outage cost of every secton due to a fault at secton : UC = Fr ( B 1 L1 + B 2L B L ) (4) Where, B s the utlty cost multpler of secton j due to a j fault at secton. j j 848

3 D. Utlty cost multpler of load at secton j due to a fault at secton Utlty cost multpler s the cost per klowatt (LE/kW) that depends on amount of outage duraton and prce of electrcty at tme t. B j = OD* ( Cre ( Re + Tm *Im ) + Co Cco + In Cn ) (5) C s the average sale prce of resdental customer per kwh. re Cco s the average sale prce of commercal customer per kwh. C s the average sale prce of ndustral customer per kwh n E. The duraton of servce nterrupton of secton j due to a fault at secton The servce duraton of each secton depends on amount of load n ths secton, number of sectons, poston of sectons, and amount of load that can be transferred. It should be noted that the locaton can be classfed nto three postons: near an orgnal source, near an alternate source, or nether. Tf + Tr, = j n Tf + Tr, > j, Lk > LT k= j ODj = (6) n Tf + Ts, > j, Lk LT k= j Tf, < j T f s the amount of tme for fndng a faulty locaton and solatng t (hours). Tr s the amount of tme for reparng a fault (hours). T s s the amount of tme for swtchng to an alternate source wthout preparaton (hours). L k s the amount of load at secton k. L T s the amount of load that can be transferred to other feeder IV. MULTI-POPULATION REAL- CODED GENETIC ALGORITHM The Genetc Algorthm GA s a stochastc optmzaton technque and a probablstc ntellgent search algorthm that uses the bologcal paradgm of evoluton to resolve very large problems searchng a populaton of ponts n parallel. Bascally, GA dffers from other tradtonal optmzaton methods n three sgnfcant ponts. It searches a populaton of ponts n parallel, t uses probablstc rules rather than determnstc ones, and t can process an encodng set of parameters. It has a concept where good chromosome has a better potental of beng carred to the next generaton than the bad chromosome. It uses mathematcal prncple to ndcate whch chromosome s better or worse than the others. The ablty of GA n fndng good solutons often depends on properly customzng the encodng, breedng operators and ftness measures. The Integer codng s used n ths research snce the decson s ether 1 for connected RTU or 0 for absence of RTU. A. Evoluton process The GA searches for the global optmum value of the objectve functon through a search space, whch s called populaton. The sze of the ntal populaton s vared by the sze of the feeder system. The populaton s consttuted from a number of possble solutons known as ndvduals, where each ndvdual s also called chromosome. In ths mathematcal analyss, a set of chromosomes s randomly generated as ntal populaton. The performance of each ndvdual s evaluated by calculatng the total cost. The ndvduals are then ranked dependng on ther correspondng costs and a sutable ftness value s assgned to each one. The ftness values are calculated dependng on the poston of the ndvduals wthn the populaton rather than ther dstnct performance. Ftness values between maxmum and mnmum lmts are calculated wth fxed ncremental steps and assgned to the ranked ndvduals. The man mplementaton steps of the GA-based optmzaton are summarzed n the flowchart shown n Fg 1. Intalze chromosome populaton Calculate the cost of each member Evaluate ftness of each ndvdual and perform ftness scalng Parent chromosomes selecton Create a new offsprng (Crossover& Mutaton) Evaluate offsprng and nsert the best replacng worst parents No Number Yes of generatons between mgratons s reached? No Yes Start Maxmum number of generaton s reached? Stop Fg. 1 Flowchart of the GA evoluton process Mgrate ndvduals between subpopulatons B. Genetc Algorthm (GA) Parameters In ths research, the GA technque s appled to optmze the locaton of RTUs wthn a rng feeder. Table 1 summarzes the parameters of the GA- based optmzaton process. 849

4 TABLE I PARAMETERS USED IN THE GA-BASED OPTIMIZATION PROCESS Number of subpopulatons 20 Number of ndvduals per subpopulaton 60 Total populaton sze 200 Generaton gap 0.8 Inserton rate 0.8 Crossover rate 0.8 Therefore, Table 3 shows the results of the proposed technque consderng the customer nterrupton cost. There s a sgnfcant reducton n the overall cost,.e. 30.5%, usng the proposed optmzaton technque compared to the ntal locaton of RTUs. Furthermore, the number of RTUs s ncreased compared to the ntal stuaton to reduce the damage cost related to customer. Mutaton rate 0.02 Maxmum no. of generatons 100 Mgraton rate between subpopulatons 0.2 Number of generatons between mgraton 10 V. CASE STUDY A part of the Egyptan dstrbuton network s used as a real dstrbuton test system to show the capablty of the proposed technque to mprove the feeder performance through optmally sttng of the RTUs. There are 28 ponts that are consdered for placng RTUs. Therefore, 28 unknown varables are assocated wth each ndvdual n the GA. A rng dstrbuton system s assumed, whch s dvded nto two radal feeders where each feeder has many sectons and each secton has a lumped load center as shown n Fg. 2. Table 2 shows the results when the optmzaton technque s appled to the nvestgated network to express the postons of RTUs. In addton, the sutable relocatons of RTUs on these feeders can be obtaned. Wth reasonable number of generatons, the optmal locatons n addton to the total cost ncludng utlty cost can be obtaned. TABLE 2 OPTIMAL LOCATIONS OF RTUS USING GA Bus.ID Intal Optmal Bus.ID Intal Optmal Bus.ID Cost functon value (LE) Intal Optmal From Table 2, t s clear that the number of RTUs, usng the proposed optmzaton technque, s the same compared to the ntal stuaton. However, three RTUs have been relocated, whle the total cost s mnmzed compared to the ntal stuaton. The total cost for the ntal condton s about LE whle that for the optmal soluton s about LE. Ths means that the proposed optmzaton technque s about 20% lower than the ntal total cost. It s mportant to notce that the customer cost damage s not consdered n ths stage snce the locatons of RTUs are defned based on the experence neglectng ths damage. Thus, the same damage cost s omtted for comparson reasons. However, due to the sgnfcant mpact on the customer, the damage cost related to customer has to be consdered. Fg. 2 A sngle lne dagram for the nvestgated network There are many techncal factors that affect the decson for the optmal locatons of the RTUs. The man factors nclude the node-voltage level and load mportance (e.g. large 850

5 hosptals and government). Importance nodes are assgned especal mportance n the optmzaton process. In addton, the postons of the loop-open swtch and sectons, whch has the hghest falure rate are consdered as mportant nodes based on the experence of the operators. Importance weghts are defned for each mportant load center to dfferentate between ther mportances. These factors are ncluded to develop realstc results that acheve most possble benefts of the optmzaton process. From Table 4, t s clear that the voltage s lower than the permssble 95% level at sx buses: from B24 to B34, whch has to be mproved. Therefore, there s a sgnfcant mportance for observng such nodes, whch may cause voltage collapse n the system. TABLE 3 OPTIMAL LOCATIONS OF RTUS USING GA CONSIDERING THE CUSTOMER INTERRUPTION COST Bus.ID Intal Optmal Bus.ID Intal Optmal Bus.ID Cost functon value (LE) Intal Optmal Fg 3 Voltage profle for the frst feeder at the left hand sde of test system The nvestgated network has been smulated by the ETAP package to carry out the power flow study. To defne all voltage levels n the network, a power flow calculaton has to be performed on the network, where some results are tabulated as shown n Table 4. TABLE 4 LOAD FLOW RESULTS FOR BUSES Bus ID Voltage (kv) kw Loadng kvar loadng Amp loadng (A) Cable Length (m) B B B B B B B B B B B B B B B B B B B B B B B B B B B B B Fg 4 Voltage profle for the second feeder at the rght hand sde of test system Accordng to the voltage profle, the low-bus voltages are dentfed and consdered to mprove ther voltages. Then, the load flow results are obtaned as techncal factors. Table 5 shows the locaton of RTUs usng the optmal proposed technque takng these factors nto account compared to the ntal stuaton. TABLE 5 OPTIMAL LOCATIONS OF RTUS USING GA TAKING TECHNICAL ASPECTS INTO ACCOUNT Bus.ID Intal Optmal Bus.ID Intal Optmal Bus.ID Cost functon value (LE) Intal Optmal

6 From Table 5, the overall cost s ncreased due to the ncrease of the RTUs number when the mportance of some nodes s consdered. However, ths result s acceptable to ensure fast restoraton after any fault for the system. Although the ntal stuaton does not account for these techncal aspects, the optmal soluton stll provdes more economcal soluton wth a total cost that s 23% lower than the ntal one. From Tables 3 and 5, t s found that the proposed optmzaton technque recommends a logc soluton. The soluton recommends nstallng addtonal RTUs at nodes 24, 26 and 32, whch also have the most voltage drop n the network. VI. CONCLUSIONS In order to enhance the dstrbuton system servce relablty, ths paper presents a capable optmal proposed technque to relocate the RTUs usng the GA. The GA has been effcently appled as an optmzaton technque to mnmze the overall cost, consderng dfferent techncal factors. The overall cost ncludes the captal cost of RTUs and the runnng cost of the customer and utlty costs. The optmal locaton of RTUs has been obtaned n order to mnmze the total costs of the system compared to the ntal stuaton of RTUs wth and wthout consderng the customer nterrupton cost. The power flow calculatons have been performed usng the ETAP package. An addtonal numbers of RTUS have been suggested to ensure fast restoraton after any fault for the system. The proposed technque has been appled on a real part of the Egyptan network. The man techncal factors nclude the node-voltage level, n addton to mportant loads, the postons of the loop-open swtch and sectons wth hgher falure rate. The obtaned results can be used to mnmze total lfe cycle costs of RTUs wth optmal locatons and gve gudance to take nto account the effect of techncal aspects n network management such as n the voltage control process. [7] M. M. Ahmed, and W. L. 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