MURDOCH RESEARCH REPOSITORY

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1 MURDOCH RESEARCH REPOSITORY Fung, C.C. (2000) Combind fuzzy-logic and gntic algorithm tchniqu for th schduling of rmot ara powr systm. In: IEEE Powr Enginring Socity Wintr Mting, January, Singapor, pp vol.2. Copyright 2000 IEEE Prsonal us of this matrial is prmittd. Howvr, prmission to rprint/rpublish this matrial for advrtising or promotional purposs or for crating nw collctiv works for rsal or rdistribution to srvrs or lists, or to rus any copyrightd componnt of this work in othr works must b obtaind from th IEEE.

2 Combind Fuzzy-Logic and Gntic Algorithm Tchniqu for th Schduling of Rmot Ara Powr Systm Lanc C.C. Fung, Mmbr, IEEE Curtin Univrsity of Tchnology Prth, Wstm Australia ABSTRACT Rmot ara powr supply (RAPS) systms ar commonly usd at isolatd locations whr th mains grid connction is unavailabl. Majority of th RAPS systms consist of ithr singl or multipl disl gnrators. Efficincis of such systms howvr ar low du to th variations in th load dmands. To improv th systm fficincy, Hybrid Enrgy Systms consist of disl gnrator, solar gnrator, storag battry bank and invrtr hav bn dvlopd. Optimal opration of such systms howvr dpnds on th schduling of th battry chargfdischarg cycl and load sttings of th disl gnrator. This papr proposs a nw approach basd on Fuzzy-Logic (FL) and Gntic Algorithm (GA) tchniqus for th schduling of th battry and th disl gnrator of a RAPS systm. Two mthods hav bn dvlopd. On was basd on a Pur Gntic Algorithm (PGA) approach, and th othr was basd on a combind Fuzzy-logic and Gntic Algorithm (FGA) approach. Simulation studis hav bn carrid out with both mthods for singl and multipl gnrators connctd to a typical RAPS systm. In trms of fficincy and chargddischarg cycls, th FGA mthod is found to b capabl of providing a bttr rsult. Kyvords: Fuzzy Logic, Gntic Algorithms, Rmot Ara Powr Supply Systms, Optimization, Schduling and Unit commitmnt. I. INTRODUCTION Whil majority of th populations in industrializd countris such as Australia hav takn constant supply of lctricity for grantd, thr ar many communitis in rmot locations dprivd of such convnincs, as thy ar not connctd to th main lcticity supply grid. Exampls ar isolatd homstads or communitis in th outback of Australia and rsidnts living on Asia-Pacific islands. In addition, country and rural aras in dvloping countis with limitd infrastructurs can b accountd in th sam catgory. Dpnding on th siz of th community and th utilization pattm, th powr consumption may vary from a fw kwh to tns or hundrds of kwh pr day. Exampls ar: Communications and imgation applications in many rmot locations of Australia in th stats of Northm Tmtory and Wstm Australia. Autonomous systms installd for rmot communitis on many Grk islands such as th Kynthos. Community powr gnration in dvloping countris lik India, Indonsia and Thailand. Th nrgy nds of ths locations ar normally mt by rmot, dcntralizd, autonomous, or stand-alon systms. Th most common solution is th utilization of on or mor disl gnrators. Disl ngin drivn gnrating sts hav a low capital cost but thy incur high oprating and maintnanc costs. As load dmand fluctuats during th 24- hour cycl, this normally rquirs ovr-sizing of th gnrators. In addition, th gnrators will not b abl to oprat at thir most fficint conditions constantly. This rducs th fficincy and causs considrabl wastag. Improvmnt can b achivd by using a Hybrid Enrgy Systm [I]. A hybrid nrgy systm utilizs nrgy from multipl sourcs. In conjunction with th disl gnrators, solar clls and storag battris ar incorporatd. Wind gnrators ar also bcoming commonly incorporatd in such systms. In practic, th storag battris ar usd to stor th xcss powr from th disl gnrators and th solar clls if th load dmand is low. Whn th load dmand xcds th capacity of th gnrators, th battris ar usd to supplmnt th supply togthr with th output from th solar clls. In ffct, th battris smoothn th load dmand variation and allow th gnrators to oprat in a mor fficint mannr. This rsults in a rduction of ful consumption and th us of smallr-siz gnrators will b possibl. In ordr to improv th systm fficincy, opration of th gnrator, battris and solar clls must b schduld in accordanc to th forcast load dmand and solar radiation. Du to th non-linar charactristics of th problm, a computational intllignc approach basd on fuzzy logic and gntic algorithm has bn dvlopd to tackl th problm. In rcntly publishd litratur, optimization of hybrid nrgy systms has primarily bn focusd on (a) dsign and sizing of systm componnts such as battry, gnrator and solar panls [2-31, and, (b) opration and dispatch stratgis for th systm. [4-91 In this papr, th problm of dtrmining th short-trm disl gnrator dispatch schdul and th battry bank charg-discharg stratgy of a paralll hybrid systm is addrssd. Two mthods ar rportd. On mthod is basd on gntic algorithm alon and is trmd th Pur Gntic Algorithm (PGA) mthod. Th othr mthod is basd on a combind fuzzy logic and gntic algorithm and is calld th Fuzzy Gntic Algorithm (FGA) mthod. Simulations basd /00/$10.00 (c) 2000 IEEE 1069

3 on both mthods hav bn carrid out. Th proposd approachs wr applid to a singl gnrator systm as wll as a multipl gnrators systm. 11. Schduling of RAPS Systms Dispatch stratgy of hybrid nrgy systms dals with th finding of th optimal schdul for th disl, PV dispatch and th battry charg/discharg stratgis whil mting th load dmands. Wichrt t a1 in [3] givs a dtaild valuation of ths optimization tchniqus. Som of th most commonly usd mthods usd for this optimization problm ar linar programming, non-linar programming and dynamic programming [4,5,10]. Th othr mthods ar thos that com undr th broad classification of computational intllignc including fuzzy logic, simulatd annaling and gntic algorithm [6,8-11,151. Although Gntic Algorithms hav bn usd to solv unit commitmnt problms [7, 12-14], thy hav rarly bn applid to th problm of schduling of RAPS systms. Th problm is particularly challnging bcaus: (a) RAPS systms ar non-linar dynamic systms. (b) Th rnwabl nrgy sourcs ar highly variabl and unprdictabl. (c) Charactristics of lad acid battris ar complx. Many of th optimization tchniqus such as linar programming ar usd to dal with ral world problms whos structurs ar howvr not prcisly known. As most of ths classical procdurs do not tackl th problm of dynamic structur, ths mthods implicitly assum that th systm structur is fixd. Thy do not hav flxibl modls that ar capabl to fac a varity of situations. Thr ar a numbr of computational tchniqus that hav volvd to dal with problms not amnabl to convntional programming tchniqus. A nw approach, combining two such tchniqus, th fuzzy logic and th gntic algorithms is usd in this papr to find th bst opration stratgy of th RAPS systms PROBLEM FORMULATION Th problm of schduling th RAPS systm opration can b statd as follows: Givn th forcast of th load and solar radiation for th short trm schduling priod (nxt 24 hours in this cas), th task is to dtrmin: (a) unit commitmnt and dispatch of disl gnrators for th schduling priod, and, (b) th battry nrgy charg/discharg policy within th sam priod, with an objctiv to minimiz th oprating whil mting th systm constraints. Mathmatically, for a multipl gnrator systm, th objctiv is to minimiz th total oprating cost whil taking into account of th start-up cost, shut-down cost, ful cost of th disl gnrator(s) oprating within a schduling intrval, th numbr of gnrators and th duration bing opratd. A. Th constraints could b broadly classifid as: El. C. D. Disl gnrator constraints: Disl gnrator must b opratd within th minimum and maximum allowabl rating. Disl gnrator must b opratd abov 45 % of th ratd capacity as th fficincy of th gnrator is low at low load. Minimum up and down tims of th gnrator must b obsrvd. In th cas of multipl gnrators, th gnrators cannot b tumd on at th sam tim. Battry storag constraints: Battry must b opratd btwn 20% -90% of th capacity. Battry must b chargd to maximum lvl at th nd of th day so that it can b opratd in th arly hours of th nxt day. Rnwabl nrgy sourc constraints: Rnwabl nrgy should b usd as much as possibl. Gnral constraints: Total powr gnratd must mt th load to minimiz loss of load probability. Th ful consumption Q, to calculat th ful cost TC for ach disl gnrator is givn by a quadratic quation as fallows. Q = a*p2+b*p+c (1) TC=Q*KC (2) whr F a,b,c KC IV. disl gnrator output powr (kw) cofficints whos valus dpnd on th gnrator usd. Cost of th ful (371) PURE GENETIC ALGORITHM (PGA) APPROACH In th RAPS schduling problm, a pur gntic algorithm (PGA) mthod is dvlopd basd on an initial population of individual schduling solutions. Each individual solution is rprsntd by a chromosom string of 24 valus corrsponding to th 24-hour tim priod. Th valu of ach gn is th gnrator powr output lvl for ach tim intrval /00/$10.00 (c) 2000 IEEE 1070

4 Th fitnss function is th total oprating cost obtaind by summing th individual oprating cost for vry hour. Th task is to minimiz th ovrall fitnss. Th initial population is chosn at random. Onc th population is initializd th gntic algorithm s volutionary cycl bgins. Th first stag of th gntic cycl is th valuation of ach of th population mmbrs. To do this, th battry final stat and th ful consumption for ach tim intrval and thn th total ful consumption ar calculatd basd on th chromosom string for ach individual in th population. This is followd by th rpatd application of th biological oprators such as slction, crossovr and mutation. Th procss is rpatd until an individual with th bst chromosomal string is achivd aftr a fixd numbr of gnrations. V. COMBINED FUZZY LOGIC-GENETIC ALGORITHM (FGA) APPROACH This mthod for dtrmining th RAPS dispatch schdul is basd on fuzzy logic and gntic algorithms. A fuzzy logic algorithm is dvlopd to dtrmin th initial hourly disl dispatch stratgy and th battry chargldischarg schdul for th nxt 24 hours. This schdul is thn optimizd using th gntic algorithm to gt th bst oprational schdul. A fuzzy logic systm can b xprssd in four basic moduls [16]. Thy ar th fuzzification unit, infrnc modul, dfuzzification unit and th knowldg bas. Th fuzzification unit consists of a fuzzifir function that convrts th crisp input valus into fuzzy singltons. In th RAPS schduling problm, th thr inputs considrd ar th load, butt and tim. Loud is th load dmand of th systm for th currnt simulation intrval Butt is th battry bank s currnt stord nrgy lvl Tim is th tim of th day for th currnt simulation Only on output variabl is dfind as Gn, which is th powr lvl at which th disl gnrator should b st for th currnt priod. Each of ths fuzzy logic variabls has an associatd univrs of discours structur. Th structur givs th maximum and th minimum valus of th crisp input variabls and th numbr of discrt lmnts that th univrs of discours is dividd into. Th fuzzy trm st associatd with ach variabl is: Loud (vlo, lo, hi, vhi) Butt (vlo, lo, hi, vhi, xhi) Tim (mom, anoon, v, night) Gn (off, md, hi, opt, vhi) Triangular or trapzoidal mmbrship functions hav bn usd to dscrib ach trm. Th knowldg bas contains th ssntial information basd on which th fuzzification, infrnc and dfuzzification procsss ar xcutd. Th knowldg bas consists of a databas and th rul bas. Th databas provids th dfinitions of th fuzzy paramtrs as mmbrship functions dfind by th univrs of discours for ach variabl. Th rul-bas consists of ruls in th form of IF A, THEN B. A rul bas of 80 ruls basd has bn dvlopd for th RAPS schduling problm concming th inputs, output and th oprating conditions. Th ruls ar drivd using a huristic approach basd on th knowldg of th bhavior of th RAPS systm. Th basic structur of th control ruls is: IF Loud is load-trm AND Butt is batt-trm AND Tim is tim-trm THEN Gn is gn-trm. Th load-trm, batt-trm and th tim-trm ar in linguistic forms associatd with th corrsponding input variabls. Eiasd on th information from th rul-bas and th fuzzy singltons from th fuzzification unit, th infrnc ngin will produc an output of th Gn variabl in fuzzy mmbrship trm. In this study, th MAX-MIN fuzzy infrnc mthod is usd. In th RAPS schduling at any givn hour, a maximum of 8 ruls is fird. Thr is a maximum of 31 possibl distributions of th gnrator output dpnding on th ruls fiird. Th fuzzy gnrator output is thn dfuzzifid to anonfiuzy gnrator output valu by th dfuzzification unit. Th cntr of ara (COA) mthod is usd for th dfuzzification procss. It is thn scald basd on th univrs of discours and th output Gn is thn dfind in crisp valu. An initial schdul is gnratd by th fuzzy logic mthod fix th nxt 24-hour intrval. Th information consist of: 0 th fuzzifid valus of load valu, battry nrgy lvl and tim, th ruls fird for ach intrval, th strngth at which it is fird, th rsultant gnrator output distribution, th dfuzzifid gnrator output in kw, th battry final stat in kwh, and ful consumption rat. GA thn works on a population of individuals with a chromosom of a lngth of 24. Each gn of this chromosom rprsnts th rsultant gnrator output distribution in fuzzy trms bfor dfuzzification. For ach chromosom string, th gnrator output, battry nrgy lvl and th ful consumption ar calculatd. Th fitnss function for ach run is th total ful consumption for th day (24 hours). Aftr a numbr of gnrations using th GA approach, a chromosom string that rsults in a schdul with th minimum possibl total ful consumption that mts th systm constraints will b producd /00/$10.00 (c) 2000 IEEE 1071

5 VI. SIMULATION RESULTS Th RAPS systm considrd for singl gnrator simulations is similar to a systm oprating at Epnarra in th Northm Trritory. Th load data, tmpratur data and th solar radiation data usd in th simulation studis ar obtaind from th actual sit data. Th Epnarra powr station is a disl/ battry hybrid systm with a small PV array. Th systm consists of two disl gnrators ratd at 52 kw and 80 kw, an 1 kw solar PV and a 100 kwh battry storag. Th systm in Epnarra uss a control systm that snss both th thr-phas and singl-phas sit load to arrang th disl gnrator dispatch stratgy. Th 52 kw gnrator is usd alon majority of th days to mt th load dmand. An xamination of th load data availabl for a priod of about 10 months indicats that th load can b mt by a disl gnrator of smallr capacity. So for all simulations usd for a singl gnrator RAPS systm a disl gnrator of 40kW siz is usd. Th simulations at carrid out on an hourly basis basd on th hourly data xtractd from th loggd sit data. Th componnt siz and paramtrs considrd for all singl gnrator simulations is givn in Tabl 1. Figur 1: Gnrator schduling for a typical day using PGA and FGA mthods I Battry opration for a typical day Tim m hours Tabl 1: RAPS componnts siz and paramtrs usd in simulation Dscription Disl gnrator ratd powr Battry bank siz Charginddischarging fficincy Maximum storag lvl Minimum storag lvl PV array siz Efficincy Valus 4OkW 100 kwh 80% Dscription 90 kwh Numbr of disl units 20 kwh Disl gnrator sizs (kw) lokw Battry siz (kwh) 100% Systm valus 3 100,60, Dscription of paramtrs PGA Total load (kwh) Total gnrator output (kwh) Load by gnrator (kwh) Load by battry (kwh) Ful consumption (Ih) FGA Battry initlal stat (kwh) I Battry final stat &Wh) I I Gnrator run hours (h) I 18 I 21 J For th simulation of th multipl gnrator RAPS systm, th sit load data usd in th singl gnrator systm simulations is incrasd 5 tims. Two mor gnrators of 60kW and lookw capacitis ar addd to th singl gnrator of 40kW to mak up a 3 gnrators RAPS configuration as givn in th Tabl 3 and th rsults ar shown in Figur /00/$10.00 (c) 2000 IEEE 1072

6 a Minimum down Tim: Onc th disl gnrator is tumd off, it cannot b tumd on again until th minimum down tim spcifid for th unit is lapsd. Crw constraints: Th disl gnrators in th systm cannot b tumd on at th sam tim. Start-up and shut-down costs: Costs associatd with th oprational constraints of starting and stopping disl gnrators. 400 m aa, '100 ~~anfaatypiclday In gnral, th rsults xamind wr basd on th following dsirabl oprational conditions or constraints: Minimum ful consumption Minimum gnrator run hours Maximum final battry stat Minimum cycling of th battry stat of charg Minimum nois in th arly hours of th day by mting th load using battry as much as possibl whil avoiding tuming on th gnratofls). Th battry should oprat btwn 20-90%. Opration of th disl gnrator abov 45% of th ratd capacity lvl for bttr fficincy Lssr start-stops of th disl gnrator From th rsults, th PGA mthod is charactrisd by th bdlowing faturs whn compard to th FGA mthod: 0 Figur 3: Battry opration for a typical day in th multi-gnrator RAPS systm using th FGA and PGA mthod ' z ; Gnrator output curvas using th FGA mthod (whh st8rl.u~ cos ~. ~ Omrator cuws udng PGA mhod with smri-up cost OGsnl olp -U by bl Figur 4: Gnrator output sttings for a typical day using th PGA and FGA mthod 0 Mor ful consumption of about 9.5% mor in th singl gnrator systms and 3.3% mor in th multipl gnrator systms Lss disl gnrator run hours than th FGA mthod in th singl gnrator systm and th first gnrator in th cas of multipl gnrator 0 Mor gnrator-output than th FGA mthod in both th singl and multipl gnrator systms 0 Mor load bing supplid by th battry than th FGA mthod in both th singl and multipl gnrator systms 0 Lss load is supplid by th disl gnrator than th FGA mthod in both th singl and multipl gnrator systms In addition, th following points ar obsrvd: 0 Th gnrator always oprats in th fficint rgion of abov 45% of th ratd capacity in both th FGA and PGA mthods. Basd on a singl day's simulation rsults, th load is mt by th battry in th arly hours of th morning and hnc th nois is rducd in th cas of singl gnrator. Battry oprats btwn 20-90% in both th cass but thr is mor cycling in th cas of PGA mthod. This cycling is undsirabl as far as th battry lif is concmd. It is shown that in th PGA mthod, th gnrator output is high whnvr it is on and th xcss powr is usd to charg th battry bank. Within th schduling priod, th battry dischargs and chargs mor oftn lading to a lowr numbr of gnrator running hours. By considring both th ful c:onsumption and battry opration, th FGA offrs a bttr Epproach than th PGA mthod. Th proposd mthod has an advantag that it is indpndnt of th disl gnrator ful consumption modl. Additional constraints could also b incorporatd into th calculation /00/$10.00 (c) 2000 IEEE 1073

7 VII. Conclusion In this papr a nw mthod is proposd to schdul th RAPS systms. This mthod uss a combind fuzzy and gntic algorithm mthod and can b usd for both singl and multipl disl gnrators RAPS systms. This mthod has th advantag that it is indpndnt of th disl gnrator and th battry modls usd. Th mthod also mts th constraints considrd in th papr for th RAPS schduling. Two mthods hav bn dvlopd and prsntd. Simulation rsults hav shown that th Fuzzy Gntic Algorithm (FGA) approach offrs a bttr solution in trms of ful consumption and th battry charg/discharg cycl. VIII. REFERENCES MacGil1,I. F., Kay, R.J. and Outhrd, H. R., Artificial intllignc approachs to th dsign and opration of rmot ara powr supply systms, Proc. of th Solar 93 confrnc, 1993, pp Skarstin, O., Uhln, K., Dsign considrations with rspct to longtrm disl saving in windldisl plants, Wind nginring, Vo1.13, N0.2, 1989, pp Wichrt., B and Lawranc, W. B., A critical valuation of optimisation tchniqus applid to th dsign and opration of standalon rnwabl nrgy systms, Proc. of th Fourth intrnational confrnc on optimization tchniqus and applications, ICOTA 98, Prth, 1998, pp Bakirtzis, A.G., Dokopoulos, P.S., Short trm gnration schduling in a small autonomous systm with unconvntional nrgy sourcs, IEEE Trans. on Powr Systms, vol. 3, no., 1988, pp Bakirtzis, A.G., Gavanidou, E.S., Optimum opration of a small autonomous systm with unconvntional nrgy sourcs Elctric powr systms rsarch, vol. 23 no. 2, 1992, pp Fung, C.C., Ho, S.C.Y., Nayar, C.V., Optimisation of a hybrid nrgy systm using simulatd annaling tchniqu IEEE Rgion 10 Confrnc, TENCON 93, 1993 pp Or0 S.O., M.R. Irving, M.R, A gntic algorithm for gnrator schduling in powr systms, Elctrical Powr & Enrgy Systms Vol. 18, No.1, 1996,~~ Iyr V., Fung C.C: and Maynard C., Us of a Fuzzy Logic Algorithm for th Powr Gnration Schduling of a Rmot Ara Hybrid Enrgy Systm, Proc. Intrnational Confrnc on Optimization Tchniqus and Applications, ICOTA 98, Prth, 1998, pp Fung C.C., lyr V. and Maynard C., Computational intllignc tchniqus for short trm gnration schduling in a hybrid nrgy systm, Proc. of th Fifth Pacific Rim Confrnc on Artificial Intllignc PRICAI 98: Topics in Artificial Intllignc, Springr- Vrlag, Brlin, 1998, pp [.O] Swaminathan, S., Kottathra, K., Phillips, S., Th, K., A MNLP Formulation for Powr Systm Schduling, hoc. of th Solar 93 Confrnc, 1993, v01.2, pp [.. 11 Mamson, C. and Sling, G., A dsign tool using gntic algorithms to siz hybrid systms for powr supply at rmot sits Part on :Analytic Fram work, Part two: Implmntation, Proc. of Intrnational Confrnc and Exhibition on Villag Elctrification through rnwabl nrgy, pp [ 121 Dasgupta, D., McGrgor, D.R., Short trm unit-commitmnt using gntic algorithms Proc. Of th IEEE, lntmational Confrnc on tools of AI, 1993, pp [ I31 Shbl, G. B., Maifld, T. T. Brittig, K. and Fahd, G., Unit commitmnt by gntic algorithm with pnalty mthods and a comparison of Lagrangian sarch and gntic algorithm-conomic dispatch xampl, Elctrical powr and nrgy systms, vol.18. no.6, 1996, pp [ 141 Kazzrlis, S.A., Bakirtzis, A.G., Ptridis, V., A gntic algorithm solution to th unit commitmnt problm, IEEE Trans. on Powr Systms, vol. 11, no. 1, 1996, pp [ 151 K.P. Wong, C.C. Fung and T. Epskamp, Dvlopmnt of a fuzzylogic-basd control algorithm for th commitmnt of nrgy sourcs in an intgratd nrgy systms. Procdings of th Australian and Nw Zaland Confrnc on Intllignt Information Systms, pp , Prth, Dcmbr [ 161 Yagr, R.R., Zadh, L.A., An introduction to fuzzy logic applications in intllignt systms, Kluwr Acadmic Publishrs, Boston (1992). BIOGRAPHY Dr Lanc Chun Ch Fung (M 1993) was bom in Hong Kong on April, H graduatd from th Hong Kong Polytchnic in 1974 with a Crtificat in Maritim Elctronics. Subsquntly, h rcivd a Diploma and Advancd Diploma from th Brunl Tchnical Collg, Bristol in 1976; a Bachlor of Scinc dgr (Maritim Tchnology) with First Class Honors and a Mastr of Enginring dgr (Systm Tst Tchnology) from th Univrsity of Wals, Institut of Scinc and Tchnology in 1981 and 1982 rspctivly. In 1994, h rcivd his Doctoral dgr from thunivrsity of Wstm Australia. Apart from his mploymnt as a Marin Radio and Elctronic Officr, h has lcturd in th Singapor Polytchnic from 1982 to Sinc 1989, h joind th School of Elctrical and Computr Enginring in Curtin Univrsity of Tchnology, Prth. His spcial filds of intrst includ computational intllignc tchniqus, microcontrollr and microprocssor applications, optimization, instrumntation and control /00/$10.00 (c) 2000 IEEE 1074