MULTI-DG PLACEMENT IN PRACTICAL DISTRIBUTION SYSTEM FOR MAXIMUM COST SAVING WITH INCREASING LOAD SCENARIO

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1 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. ULTI-DG PLACEENT IN PRACTICAL DISTRIBUTION SYSTE FOR AIU COST SAVING WITH INCREASING LOAD SCENARIO K. Dhananjaya Babu an A. Lakshm Dev Department of Electrcal an Electroncs Engneerng, Sr Venkateswara Unversty College of Engneerng, Sr Venkateswara Unversty, Trupat, Anhra Praesh, Ina E-al: ABSTRACT The prmary objectve of ths paper s to maxmse the cost savng of the strbuton system when Dstrbute Generaton (DG) s ntegrate. For whch an objectve functon s evelope to represents the savngs of the system. But the maxmzaton of the functon manly reles on the locatons an szes of the DG. Fuzzy logc approach s mplemente for generatng the optmal DG locaton nces base on the rule base frame an wth effectve nputs: real power loss nex an voltage nex. Gravtatonal Search Algorthm (GSA) s compute to fn the approprate capacty of DG n the locatons preferre, so as to maxmse the esre objectve functon. In ths paper, a plannng pero of 10 years s consere for fnng the maxmum cost savngs. Inflaton rate an nterest rate were consere to estmate the present cost value of the system an every year 2% of loa s assume to ncrease w.r.t. the base loa. The results have been compare for the sngle an mult DG placement. The propose algorthm s coe n ATLAB envronment an s teste on an Inan 43-bus practcal strbuton system. The results obtane are scusse an presente. Keywors: strbute generaton, cost analyss of DG, fuzzy logc approach, practcal strbuton systems, gravtatonal search algorthm, ncreasng loa scenaro, nflaton rate, nterest rate. 1. INTRODUCTION Dstrbute Generaton (DG) s a small scale of renewable an conventonal power source, lke solar, wn, small hyro etc... It s connecte at strbuton voltage level near customer en. The DG s well recognse as envronmental frenly whch can mprove the voltage profle, reuce an congeston of the system, prove a proper locaton an sze of the same s concerne [1]. There are plenty of research papers avalable whch eals wth placement, szng an cost analyss of DG nto the strbuton systems. In [2] Naresh et al examne that the ncorrect placement an szng of DG leas to the ncrease of n the system, whch explans the mportance of DG locaton an ts sze. In [3] Wang el al propose an analytcal metho for placng DG wth power factor control to reuce the. Vjaykumar et al [4] propose a metho for maxmzaton of savng an reucng the by optmally placng an szng DG. Satsh et al [5] propose a smple metho base on maxmum beneft for choosng the locaton an ste for optmal capactor an DG. In [6] shukla et al has propose a metho for estmatng the economc savng of the system, whch has translate from the performance mprovement resulte post DG placement. Ths paper s organze as follows secton-2 presents the problem formulaton where the objectve functon s frame for maxmum savng of the system s gven. In secton-3 Fuzzy approach s mplemente for generatng the optmal DG locatons. Secton-4 presents the Gravtatonal Search Algorthm for szng DG the capactes. The last secton scusses the results an ther mplcatons an fnally followe by concluson an references. 2. PROBLE FORULATION The prme objectve of ths stuy s to ncrease the cost savng of the system by optmally placng the DG. The mathematcal moel of the objectve functon representng savng for the system s gven through equaton (1). The maxmzaton of the objectve functon manly epens on the DG locaton an sze. max( F ) C S (1) Where, F s the objectve functon of the system, an C S s the cost of maxmum savng. 2.1 Cost of maxmum savng The cost of maxmum savng s calculate as the cumulatve fference between the benefts obtane an the expenses ncurre for DG placement over a plannng pero of 10 years, as gven n equaton (2). Beneft Expenses CS (2) The beneft of the system s the combnaton of cost of energy loss an cost of DG generate power whch s gven n equaton (3) Benefts Where, K ES C NLR DG K DG, gen C DG, gen NLR (3) 1413

2 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. NLR K ES K DG, Gen DG C NLR C DG, Gen = Net loss reucton whch s the fference of the system loss wthout an wth DG placement, kw. = Cost of energy savng, $/kw-yr, = power generate, $/kw-yr, = Capacty of DG, kw = Cumulatve cost of Net loss reucton, $ = Cumulatve cost of DG generate power, $ The expenses of the system s the summaton of DG nvestment cost an the cumulatve sum of DG operaton an mantenance cost Expenses DG K DG, O& DG K DG, Inv (4) CDG, O& CDG, Inv Where, K DG, O& = Operaton an antenance, $/kw-yr, K DG, Inv = nvestment, $/kw C DG, O& = Cumulatve cost of DG O&, $ C DG, Inv = Total nvestment, $ 2.2 Net present value [5] The present value of varous cost scusse above are calculate usng the equaton (5) shown below. The net present value factor (γ) whch nclues nflaton rate (IF) an nterest rate (IR) [5], s multple wth the varyng costs for estmatng the present value. The cost analyss s been carre over a plannng pero (Np) of 10 years. t N p t 1 IF, Where t = 1,2,3,.,N p (5) t 1 1 IR 3. FUZZY APPROACH FOR FINDING OPTIAL DG PLACES In ths secton Fuzzy logc approach s escrbe whch generates the optmal DG locaton by approxmatng over the nputs usng the rule base (gven n Table-1 [7-8]. loss nex (RLI) an voltage nex (VI) were calculate an gven as nput to the fuzzy nference engne as shown n Fgure-1. The real loss nces are the normalse values of observe real power loss reucton, when the loa at th bus s remove. The buses havng hgh values of ths nex are selecte for conseraton for placng DG. It s gven through equaton (6). The voltage nex s calculate by the normalzng the voltage values between 0 an 1. The buses havng low value of ths nex are gven prorty for selecton. The output of the nference system s the DG locaton nex (DGLI) an the buses havng the hgh value are chosen as optmal choce for placng DG. Fgures (2-4) shows the membershp functon of RLI, VI an DGLI use n the process. Table-2 shows the locaton nex values of the 43 bus practcal system. It can be observe that bus 22 has hghest nex value followe by bus 35 an so on. RLI P P (6) Where, P loss P loss 0 loss loss, 0 = 1, 2 N b buses = Power loss for normal loa,, = Power loss for zero loa at th bus. Table-1. Decson matrx for optmal DG locaton [8]. RLI AND VI L LN N HN H L L L L L L L L L L L H L L L H H H L L H H H L L Voltage nex Fuzzfcaton Fuzzy nference Engne De-Fuzzfcaton DG locaton nex Power Loss nex Rule base Fgure-1. Flow chart for fnng optmal DG locatons. 1414

3 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. Table-2. DG locaton nex for 43-bus practcal system. Bus no. RLI nex Voltage nex DG locaton nex Fgure-4. embershp functon for DGLI nex. Fgure-2. embershp functons for RPL nex. 4. OVERVIEW OF GRAVITATIONAL SEARCH ALGORITH In 2009 Rashe et al [9, 10] propose the GSA algorthm whch manly evelope base on the law of gravty an nteracton of masses. In ths algorthm, base on Newton law of gravty an law of moton, the group of masses whch regare as soluton agents nteracts wth each other. The poston of each mass has a soluton. The poston of heavest mass has the best soluton an t attracts the surrounng masses whch are accelerate by ther gravtatonal an nertal masses. In ths stuy GSA s compute to optmze the sze of DG Algorthm for DG szng usng GSA [10] Step 1: Generate N number of masses,,,,,, an ther N velocty wthn the lmts. Intalze the generaton lmt T = 100 an set current teraton count (t) to one. The poston of the th mass s gven by, 1 2 3,,,,,,, where represents the poston of the th agent n the th menson. n Fgure-3. embershp functon for VI nex. Step 2: Usng equaton (7), calculate the force on the th mass by the j th mass n the th menson. F t j G t p R t j a t j t t (7) Where, p t t a G = Actve gravtatonal mass relate to agent j, = Passve gravtatonal mass relate to agent, = Gravtatonal constant, = Small constant, an 1415

4 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. t Rj Rj = Euclan stance between two agents an j, whch s gven n equaton (8) t t t j The total force that acts on th mass, n a menson be a ranomly weghte sum of th components of the forces exerte from other agents. F t N 1, j ran F j t Where, ran = ranom number generate between 0 an 1. Step 3: Calculate the acceleraton of th mass usng equaton (10) a t F t t 2 (8) (9) (10) Where t s the nertal mass of the th agent. Step 4: Upate the velocty an poston of all the masses usng equatons (11-12) V t ran V t a t 1 (11) t t t V 1 (12) Step 5: Calculate the objectve value of each mass usng equaton (1) Step 6: Check for the tolerance or generaton lmt reache. If yes go to step 8, else go to step 7 Step 7: Increase the teraton count an go to step 3 Step 8: The heavest mass n the populaton gves the best ftness value.e. maxmum loss reucton an poston of that mass gves the optmal DG szes. Table-3. System parameters of 43-bus system for the frst year n plannng pero. Descrpton Wthout DG Sngle DG ult DG,kW Ploss Q, kvar loss Total loss reucton wth DG, kw N/A DG Locaton N/A Bus 22 Bus 22, Bus 35 DG Capacty, kw N/A , Table-4. Cost etals of 43 bus system after one year of plannng pero. Descrpton One DG Two DG C NLR, (K$/yr) C DG, Gen, (K$/yr) C DG C, O&, (K$/yr) DG, Inv, (K$) RESULT AND DISCUSSIONS In ths stuy, a ATLAB coe s evelope for the propose algorthm usng ual core Pentum processor, 2GB RA laptop. The propose algorthm s teste on a 43-bus practcal strbuton system whch s a 11kV feeer wth 43 buses an 42 branches, whch s locate n the regon of a Settpall strbuton system, Trupat DISCO, AP, Ina an the ata of the system s prove n the appenx. The real an reactve loa of the system s 3497 kw an 3567 kvar respectvely. The type of DG consere s a solar PV type an the cost etals are taken from the Natonal Renewable Energy Lmte (NREL) [11] an are shown n Table (10). The cost of power loss reucton s taken as $0.05/kWh an the cost of power generate by DG as $300/kW [6]. The present value of cost n the plannng pero s estmate by nclung nflaton rate of 9% an nterest rate of 12.5% n the NPV factor, whch s then multple wth the varyng costs. 5.1 Sngle DG placement From Table (3), t s ncate that the fuzzy approach generates bus number 22 as optmal locaton for DG placement. When optmze the szng of DG n ths locaton usng GSA t converges at kw. The real an reactve loss wth DG reuces to kw an kvar from kw an kvar respectvely. The objectve functon representng the savng of the system s tune wth szng of the DG, such that the optmal DG sze results n maxmum savng for the system. 1416

5 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. For the frst year n the plannng pero the cost savng through energy loss reucton s K$, the cost of power generate by DG s K$. The nvestment cost of DG whch s DG ratng converge by GSA as K$ an ts O& cost s K$ an s shown n Table-4. The loa of the system s assume to ncrease at 2% every year over the base loa. In Table (5) the system parameters are ncate, where t can be observe that the nvestment cost of DG s gven for each year for the relate optmal ratng of DG. But whle calculatng the maxmzaton of system proft, the DG nvestment cost of the tenth year s consere so as to reflect the nvestment mae rght from the begnnng of the frst plannng year. The penetraton level of DG s ncate as percentage of the system loa, where for the frst year t s 20.2%. In Table-6 the cost etals for sngle placement s gven for each plannng year. The NPV factor column ncates the factor for each plannng year. The cost etals pose the present cost values for the partcular year. Table (9) gves the consolate results for sngle DG placement for the ncreasng loa scenaro, where t s observe that the maxmum cost savng s resulte as $. 5.2 ult DG placement For mult DG placement analyss, two DG locatons are consere. The buses 22 an 35 whch got hgh placement nces are selecte. GSA optmze the DG szes for the locatons at kw an kw respectvely. The loss of the system wth DG s kw an kvar. For the frst year the DG nvestment cost for the converge ratngs s K$ an ts mantenance s K$. The savng cost through energy loss reucton an DG power generaton s K$, an K$ respectvely. Table-7 ncates system parameter for the mult DG placements n ncreasng loa scenaro. Here t can be observe that the penetraton level of DG shoots up when compare to the sngle DG placement. The cost etals are ncate n Table-8. The voltage profle of the system wth sngle an mult DG placement for the frst year of plannng pero s gven n Fgure-5. It s clearly vsble that wth mult DG placement, the voltage profle has a sgnfcant ncrease n magntue at multple places. Table-9 shows the cost savng of the system after the plannng pero. These costs are the cumulatve sums over the plannng pero. The DG nvestment an ts mantenance cost.e. the expenses cost s lower for mult placement (3.86 $) compare to the sngle placement (3.88 $). The benefts of the system (whch s the summaton of the cost of net loss reucton an DG power generaton) for mult placement s $ an for sngle placement t s $. The savng for the system wth mult DG s $ whch s the fference of the cumulatve benefts an expenses an for sngle DG placement t s $. Fgure-6 shows the cost graph for the mult an sngle DG placement. The beneft curve of the mult-dg crosses the nvestment curve at 7.9 of the abscssa, ncatng that the system has a payback pero of 7.9 years for the nvestment mae. For sngle DG placement the nveste amount recovers at approxmately 9.2 years tme. Fgure-5. Voltage profle of 43 bus system for the frst year. 1417

6 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. Plannng year Loa of the system Loa Fgure-6. Cost graph for sngle an mult DG placement. Table-5. System parameters for Sngle DG placement. Reactve Loa Losses Reactve Losses wth DG Reactve wth DG DG ratng Penetraton level (%)

7 Plannng year NPV factor VOL. 12, NO. 5, ARCH 2017 ISSN ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. Wth 2% of loa ncreasng every year Table-6. Cost etals for sngle DG placement. DG ratng kw Cost of Energy savng ($) generate Power ($) Operaton an antenance ($) Investment ($) Plannng year Loa of the system loa Table-7. System parameters for ult DG placement. Reactve loa Reactve wth Reactve wth DG DG ratng at Bus 22 Bus 35 Penetraton level (%) Plannng year NPV factor Wth 2% of loa ncreasng every year Table-8. Cost Detals for ult DG placement. DG ratng at Bus 22 Bus 35 Cost of Energy savng ($) generate Power ($) Operaton an antenance ($) Investment ($)

8 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. Table-9. Cost etals of 43-bus practcal system after plannng pero. Descrpton Sngle DG ult DG C NLR, ($) C DG, Gen, ($) C C DG, O&, ($) DG, Inv, ($) Benefts, ($) Expenses, ($) C S, ($) CONCLUSIONS In ths paper, the cost savng of the system wth ncreasng loa scenaro s stue for a plannng pero of 10 years. An objectve functon representng maxmum savng of the system s evelope. Fuzzy logc approach s mplemente to generate best possble locatons for DG placement. GSA algorthm has optmze the DG ratng such that the value of objectve functon has ncrease. The system savng wth mult DG s $ an has a payback pero of 7.9 years. For sngle DG placement t s $ savng an 9.2 years tme requre for the recovery of the nveste amount. The voltage profle for mult DG placement s better when compare to that of sngle DG placement whch as shown n fgure (5). From the results t can be conclue that, compare to sngle DG placement, the system certanly has better techncal an economc benefts for mult DG placement n ncreasng loa scenaro. REFERENCES [1] Ackermann T., Anersson G., S oer L Dstrbute generaton: a efnton. Electrc Power Systems Research 57(3): DOI [2] Acharya N., ahat P., thulananthan N An analytcal approach for g allocaton n prmary strbuton network. Internatonal Journal of Electrcal Power & Energy Systems. 28(10): DOI [3] Wang, C., Nehrr, Analytcal approaches for optmal placement of strbute generaton sources n power systems. Power Systems, IEEE Transactons on. 19(4): DOI /TPWRS n eregulate power systems. SECCO, 2012, LNCS pp [5] Shukla T.N., Sngh S.P., Srnvasarao V., Nak K.B Optmal szng of strbute generaton place on raal strbuton systems. Electrc Power Components an Systems. 38(3): DOI / [6] Kansal S., Tyag B., Kumar V. Cost beneft analyss for optmal strbute generaton placement n strbuton systems. Internatonal Journal of Ambent Energy. 0(0), 1-10 (0). DOI: / ,URL: [7] Dev A.L., Subramanyam B Optmal g unt placement for loss reucton n raal strbuton system- aaase stuy. ARPN Journal of Engneerng an Apple Scences. 2(6): [8] Rey.D., Rey V. V Optmal capactor placement usng fuzzy an real coe genetc algorthm for maxmum savngs. Journal of Theoretcal an Apple Informaton Technology. pp [9] Esmat Rashe, Hossen Nezamaba-pour, Sae Saryaz, GSA A Gravtatonal Search Algorthm, Informaton Scences, 179(13): , ISSN , [10] K.D Babu an A.L. Dev Applcaton of Gravtatonal search algorthm an fuzzy for loss reucton of networke system usng Dstrbute Generaton. IOSR Journal of Electrcal an Electroncs Engneerng (IOSR-JEEE) e-issn: ,p-ISSN: , 10(1): Ver. II (January- February 2015). pp [11] NREL: Dstrbute generaton renewable energy estmate of costs. URL http: ==www:nrel:gov=analyss=techlcoerecostest:html [12] Trupat urban an rural strbuton system. APSPDCL Govt. of Anhra Praesh Trupat. [4] K. Vjaykumar an R. Jegatheesam Optmal locaton an szng of DG for congeston management 1420

9 ARPN Journal of Engneerng an Apple Scences Asan Research Publshng Network (ARPN). All rghts reserve. APPENDI A. Cost etals of DG The cost ata of DG for solar PV type s gven n Table-10. B. Data for practcal strbuton system The ata corresponng to the Inan 43-bus practcal strbuton system [12] s tabulate n Table-11. The values of the system parameters consere are: Base VA = 100, Base kv = 11 kv, Lne Resstance = 0.55 Ω/km, Lne Reactance = 0.35 Ω/km, Power factor = 0.7 laggng an Dversty factor = 1. Table-10. Cost etals of DG for solar PV type. Solar PV PV <10 kw PV kw PV 100-1,000 kw PV 1-10 W ean nstalle cost($/k W) Fxe O& ($/kw-yr) Varable O& ($/kwh) Lfe tme (yr) $3,897 $21 N/A 33 $3,463 $19 N/A 33 $2,493 $19 N/A 33 $2,025 $16 N/A 33 Table-11. Lne an loa ata of Inan 43-bus practcal strbuton system. Lne En buses of a lne Lne KVA loa Number Bus Bus Y Dstance (km) at Bus Y