Sensitivity Based Optimal Real Power Rescheduling For Congestion Management Using Black Hole Algorithm

Size: px
Start display at page:

Download "Sensitivity Based Optimal Real Power Rescheduling For Congestion Management Using Black Hole Algorithm"

Transcription

1 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: AUSTRALIAN JOURNAL OF BASIC AND ALIED SCIENCES ISSN: EISSN: Journal home page: Senvy Baed Opmal Real ower Rechedulng For Congeon Managemen Ung Black Hole Algorhm Ramachandran R and 2 Arun M &2 Aan rofeor, Deparmen of Elecrcal Engneerng, Annamala Unvery, Annamala nagar, Tamlnadu, Inda Addre For Correpondence: R.Ramachandran, Deparmen of Elecrcal Engneerng, Annamala Unvery, Annamala nagar, Taml nadu, Inda, Emal: A R T I C L E I N F O Arcle hory: Receved 26 Augu 206 Acceped 0 Ocober 206 ublhed 8 Ocober 206 Keyword: Congeon managemen; envy facor; real power rechedulng; deregulaed power yem; black hole algorhm. A B S T R A C T Tranmon congeon managemen crcal ue n he operaon of deregulaed power marke. Enurng uffcen ranmon capacy val o realze all power ranacon. Opmal power chedule correpondng o marke clearng prce may caue overloadng of ranmon lne n compeve marke. Opmal real power chedule relaed o mnmum co need o be recheduled for avodng lne overloadng. In h paper, ranmon congeon allevaon done by changng he paern of real power generaon from he dfferen generaor. The obecve of h work o mnmze he co nvolvng n rechedulng of real power for managng ranmon congeon. Tranmon congeon co he obecve and he conrol varable n h problem are he real power oupu from dfferen generaor of he yem. The generaor ha are more enve o he power flow n he congeed lne are denfed wh he help of real power envy ndex. The generaor ha are more reponble for he congeon n a lne are gven more prory n h rechedulng problem. A new opmzaon mehod baed on he recenly propoed black hole algorhm (BHA) ued for denfyng he opmal generaon paern for avodng congeon. The algorhm mmc he exence of black hole n he pace and eay o be mplemened for any opmzaon problem. The effecvene of he algorhm valdaed by eng on he modfed IEEE-30 bu yem. The reul obaned are compared wh ha of parcle warm opmzaon (SO) and bg bang bg crunch (BBBC) algorhm. The obaned numercal reul are much encouragng and valdaed. INTRODUCTION In general, deregulaed power marke are wh lmed reource of power ranferrng capably becaue of envronmenal, rgh-of-way (ROW) and oco-economc reaon. Generaon chedule correpondng o markeng clearng prce reul moly n ncreaed power lo and poe hrea o he ecury of he power yem nework (De Vre, 200) and (Lommerdal and Soder, 2003).Congeon relef neceary and varou congeon managemen approache applcable for dfferen power marke are dcued n he leraure (Lo e al., 2000) and (Raeh and Jacob Raglend, 205). Sll he necey for new approache for olvng congeon managemen problem connue forever (Shrmohammad e al., 998). In (Verma and Mukheree, 206), opmal real power re-dpach uggeed for ranmon congeon managemen. Socal welfare maxmzaon baed ranmon congeon mehod dcued n Maoud and Aref (20). Drbued power generaor are dcued for congeon relef n power yem (Sarwar and Sddqu, 205). An alernave approach baed on opology change preened n Han and apavalou (205) a an effcen way of congeon mgaon. A coordnaed approach beween generang compane and yem operaor for congeon managemen ung Bender cu dcued by Yamna and Shahdehpour (2003). Open Acce Journal ublhed BY AENSI ublcaon 206 AENSI ublher All rgh reerved Th work lcened under he Creave Common Arbuon Inernaonal Lcene (CC BY). hp://creavecommon.org/lcene/by/4.0/ To Ce Th Arcle: Ramachandran R and Arun M., Senvy Baed Opmal Real ower Rechedulng For Congeon Managemen Ung Black Hole Algorhm. Au. J. Bac & Appl. Sc., 0(5): 83-93, 206

2 84 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: Locaonal Margnal rce (LM) ued a a gnal for congeon managemen (Kumar and Mohan, 206) by adung he generaor power oupu. Flexble AC ranmon yem (FACTS) devce are ued for congeon managemen by changng he power flow paern n a power yem nework. Th approach uable only when he level of congeon mall. Some of he FACTS devce ued for ranmon congeon allevaon are: Thyror-Conrolled Sere Compenaor (TCSC) and Thyror Conrolled hae Angle Regulaor (TCAR) (ael and alwal, 205) and (Hoohmand e al., 205). Congeon caued by volage nably and hermal overload aken n (Suganh e al., 205). Real power rechedulng baed on relave elecrcal dance adoped o allevae lne overload n (Yeuranam and Thukaram, 2007). Th mehod doe no ake no accoun he opmzaon of co when he generaor have dfferen co funcon. Srvaava and Kumar (2000) followed load curalmen mehod for managng congeon n a nework. Recenly, evoluonary algorhm are propoed o opmze he rechedulng co of real power oupu from ynchronou generaor. Evoluonary rogrammng (E) algorhm ued for rechedulng of real power generaon for congeon managemen preened Ramaubramanan e al. (202). Opmal congeon managemen n an elecrcy marke ung baceral foragng opmzaon (BFA) done by angrah and and (2009). Valakh and Bakar (20) ued a modfed NSGA II algorhm baed model for he decenralzed congeon managemen problem n he deregulaed forward power marke. Bo geography algorhm baed loadably lm enhancemen preened n (Arunachalam and Logaman, 205) for congeon allevaon. In he preen work, he recenly developed naure npred mple and effcen echnque of BHA aken for mnmzng oal congeon co by he rechedulng of real power for congeon managemen. In h congeon managemen cheme by real power rechedulng n a generaor, he amoun of rechedulng of power decded by he envy of ha generaor o he power flow n he congeed lne. aern of changng he real power chedule no done n a random manner only he parcpang generaor are aken. Th mnmze he oal congeon co. The algorhm eay o mplemen and wh le number of parameer o be uned n obanng he nearly global be oluon. Black Hole henomenon: John Mchell and erre Laplace denfed he abence of ar by negrang Newon law bu he abence of ar wa no called a black hole n hoe day. John Wheeler, an Amercan phyc fr named he phenomenon of ma collapng or abence of ar a a black hole. A black hole n he pace lef when a ar or mave zed plane ge collaped. Black hole wallow and vanhe any obec ha come nearer o boundary. The phere-haped boundary of a black hole called a he even horzon whoe radu named a he Schwarzchld radu. The Schwarzchld radu calculaed by he followng equaon: 2GM R () 2 C Where, G he gravaonal conan, M he ma of he black hole, and C he velocy of lgh. Black Hole Algorhm (BHA) Haamlou, (203): Lke he oher mea-heurc algorhm, a populaon of randomly drbued canddae oluon are creaed n he problem pace. opulaon-baed algorhm ue dfferen echnque o move he ndvdual oward he global be oluon by a ceran echnque. For nance, muaon and croover are he echnque ued n GA. SO ake he ndvdual be and global be oluon for movng he nal oluon o he global be oluon. In BHA, he evoluon of he populaon acheved by movng all he canddae oward he be canddae n each eraon namely, he black hole and replacng hoe canddae ha ener whn he range of he black hole by newly generaed canddae n he oluon pace. In BHA he be canddae among all he canddae a each eraon eleced a a black hole. Then, all he canddae are moved oward he black hole baed on her curren locaon and a random number. The earchng mechanm of BHA a under: A randomly generaed populaon of oluon aken a he nalzaon proce. Then he fne value of he populaon are evaluaed and he be oluon whoe fne value he be one he black hole. Afer nalzng he black hole and ar, he black hole ar aborbng he ar around and all he ar ar movng oward he black hole. The aborpon of ar by he black hole mahemacally formulaed a follow: x x rand(0,)( xbh, x ( )) (2) Where, x and x are he locaon of he h ar a eraon and, repecvely. x he locaon BH of he black hole n he earch pace. rand a random number n he nerval (0, ). N he number of ar (canddae oluon).whle movng oward he black hole, a ar may reach a locaon wh lower co han he black hole. In uch a cae, he black hole move o he locaon of ha ar and vce vera. Then he BHA wll

3 85 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: connue wh he black hole n he new locaon and hen ar ar movng oward h new locaon. In addon, here he probably of crong he even horzon durng movng ar oward he black hole. Every canddae oluon ha croe he even horzon of he black hole wll be ucked by he black hole. Every me a canddae ar de and anoher canddae oluon born and drbued randomly n he earch pace and ar for a new earch. Th done o keep he number of populaon ze conan. The nex eraon ake place afer all he ar have been moved. The radu of he even horzon n he black hole algorhm calculaed ung he followng equaon: f BH R (3) N f Where, f he fne value of he black hole and BH f he fne value of he h ar. N he number of canddae oluon. When he dance beween a canddae oluon and he black hole le han R, ha canddae collaped and a new canddae creaed and drbued randomly n he earch pace. Baed on he above decrpon he flow char for BHA hown n fgure () Fg. : flow char for Black Hole Algorhm

4 86 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: Implemenaon of BHA for congeon managemen: Sep : Inalze he algorhm parameer lke populaon ze, maxmum number of eraon and black hole. Sep 2: Each ndvdual a vecor of he conrol varable..e. X ]. N he number of [ g, g 2, g3, gn agen are generaed by repecng he lm of conrol parameer. Sep 3: Calculae he fne funcon value of all canddae oluon by runnng he NR load flow. Sep 4: Deermne he cener of ma whch ha global be fne ung equaon (3). Sep 5: Generae new canddae ung he cener of ma, parcle be and global be by addng/ubracng a normal random number accordng o equaon (2). Sep 6: Repea ep ep 2 o ep 5 unl oppng crera ha no been acheved. Mahemacal roblem Formulaon: 2. Formulaon of generaor envy ndex: The generaor n he yem have dfferen enve o he power flow hrough he congeed lne. A change n real power flow n a ranmon lne k conneced beween bue and due o change n real power generaon by generaor g can be ermed a generaor envy o congeed lne (GS) whch can be wren mahemacally a (Dua and Sngh, 2008) and (Venkaah and Kumar, 20). GS GS g (4) Gg Where he real power flow on congeed lne-k; h he real power generaed by he g generaor. Gg The real power flow hrough he congeed lne can be wren a: 2 V G VV G co( ) VV B n( ) (5) The fr erm of he wo produc n (6) are obaned by dfferenang (5) a follow: g Gg Gg (6) VV G n( ) VV B co( ) (7) VV G n( ) VV B co( ) (9) S S V The acve power neced a a bu- can be repreened a: (0) GS DS Where he acve load a bu-. DS V 2 n G can be expreed a S (( G co( ) B n( )) V ) V n {( G co( ) B n( )) V } () Where, n he number of bue n he yem. Dfferenang () w.r.. and S, he followng relaon can be obaned: (8)

5 87 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: V V V { G n( ) B co( )} n {( G n( ) B co( )) V } Neglecng -V couplng, he relaon beween ncremenal change n acve power a yem bue and he phae angle of volage can be wren n marx form a: H (4) n nn n Where, 2 n 2 2 n 2 n H. (5) nn n n n 2 n Thu H M n n (6) (7) Where, M H (8) To fnd he value of / and / Gg Gg n (6), he marx M need o be deermned. However, [H] a ngular marx of rank one defcency. So no drecly nverble. The lack bu n he preen work ha been condered a he reference node and agned a bu number. The elemen of fr row and fr column of [H] can be elmnaed o oban a marx [ H ] whch can be nvered o oban marx [ M ], where (.) repreen a marx whoe fr row and column are deleed. Ung hee relaon he followng equaon can be obaned: M (9) The acual vecor [ ] can be found by mply addng he elemen o (9) a hown by he followng relaon: n 0 0 nn 0 M n (20) n The econd erm of he um n (20) vanhe a, beng he change n phae angle of lack bu zero. Accordngly, (20) reduce o: (2) (3)

6 88 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: n 0 nn 0 M (2) n Thu requred elemen of / and / Gg Gg are found ou from (2). I o be noed ha he generaor envy value hu obaned are wh repec o he lack bu a he reference. So he envy of he lack bu generaor o any congeed lne n he yem alway zero. GS denoe how much acve power flow over a ranmon lne connecng bu and bu would g change due o acve power necon by generaor g. The yem operaor elec he generaor havng non unform and large magnude of envy value a he one mo enve o he power flow on he congeed lne and o parcpae n congeon managemen by rechedulng her power oupu. 3.2 The obecve funcon: The man am of h work o fnd he opmal rechedulng of acve power generaon baed on real power envy ndex of he generaor o a o mnmze he congeon co whle afyng he yem equaly and nequaly conran. The obecve funcon of h congeon managemen problem can be wren mahemacally a (andya and Joh, 203) and Gao e al. (205). ng mn TC ( C D ) $/hr (22) k G Where, TC he oal congeon co n $/hr C he ncremenal bdng co k D he decremened bdng co k k G G he amoun of acve power ncremen n he generaor. G he amoun of acve power decremen n he generaor. Equaly conran: Real power balance: g d N V V Y co( ) 0 (23) Reacve power balance: Q g Q d N V V Y n( ) 0 (24) c g g g g ;,2,3... ng (25) c dk dk ; k,2,3... Nd (26) Inequaly conran: Real power generaon lm: mn max ng (27) G G G,... Reacve power generaon lm: mn max Q Q Q ng (28) G G G,... Incremened or decremened real power lm: mn mn max max ( ) ( ) (29) g g g g g g g 0; 0 (30) g g

7 89 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: RESULTS AND DISCUSSIONS The performance of he propoed algorhm n congeon co mnmzaon problem eed n he modfed IEEE-30 yem. The modfcaon dne n he andard IEEE -30 bu yem ha he generaor bue are numbered fr and he load bue follow. The modfed IEEE-30 bu yem con of 4 ranmon lne, 24 load bue and 6 generaor bue wh a bae load of MW real power and 26.2 MVAR reacve power. Lne daa and bu daa for boh he e cae yem aken from he (Balaraman and Kamara, 200). Here, wo cae congeon have been aken Cae A Ouage of lne -2 and Cae B a Load a all he bue are raed by 20%. 4. Cae: A Ouage of lne -2: Ouage of ranmon lne and conequen congeon condered n h cae. Lne ouage conngency creenng and rankng how ha lne -2 he mo crcal one n IEEE-30 bu yem. ower flow hrough he congeed lne (lne.e.-7 lne 7-8) and correpondng generaor envy ndce are gven n able.when lne -7 and 7-8 are congeed, generaor 3 conrbung more han he oher generaor n congeon. However, can be oberved ha almo all he generaor are conrbung conderably. Th becaue of he cloe nerconnecon among he yem componen. Table : Generaor Senvy facor (cae A) Congeed lne G G2 Lne Lne G3 Real power oupu of generaor 3 adued by large amoun for relevng congeon due o he ouage of he lne -2. erformance we BHA beer han he BBBC and SO algorhm. Toal congeon co uggeed by BHA only $ whle $ by SO and $ by BBBC. The co obaned by BHA, hown n able 2 much low and mprove he rengh of he algorhm. Table 2: Opmal rechedulng Recheduled power BBBC Technque SO Technque BHA Technque G G G G G G6 Congeon Co Lo I obvou from able 3 ha BBBC and BHA are behavng n he ame manner n adung he generaon for reducng congeon co. They ugge decremenal change n generaor and 5 and ncremenal change n he remanng hree generaor. For mnmum congeon co, BHA how relavely large change a generaor 2 han ha hown by. Table 3: Opmal change of real power Technque U/DOWN adumen of parcpang generaor (MW) G G2 G3 G4 G4 G5 G5 G6 G6 BBBC SO BHA ower flow n he lne of he yem under dfferen condon are compared n fgure 2. Ouage of lne - 2 reul n overflow n lne -7 and 7-8. The congeed flow n hee wo lne are removed by rechedulng of generaor power. I obvou from he fgure ha all he hree algorhm are ucceeded n congeon managemen.

8 90 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: Fg. 2: ower flow hrough he lne (Cae A) Srengh of he propoed algorhm analyzed by he number of eraon ake for fndng he global be oluon. The algorhm manan he be oluon over dfferen eraon and converge o he global be oluon a abou he 8 h eraon hown n fgure 3. Tha whn 0 eraon be oluon reached. Th prove he rengh and relably of he algorhm. Fg. 3: Convergence behavour of BHA n cae A 4.2 Cae B: Load a all he bue are raed by 20%.: In h cae, congeon due o ncreaed load aken. Load a all he 24 load bue are ncreaed by 20%. The oal real and reacve power demand are ncreaed o MW and 5.44 MVAR.A a reul, lne -2 ge congeed. For rechedulng of real power, he generaor whoe generaon are more nfluencng he power flow hrough he congeed lne are denfed fr. The generaor envy ndce of all he x generaor are calculaed and gven n able 4. Senvy ndex of generaor 2 he greae among he ndce howng large nfluencng on he power flow n he congeed lne. Amoun of real power oupu from he generaor are adued accordng o he value of envy ndex. The more he value of he ndex he more he amoun of power adued. Table 4: Generaor Senvy facor of congeed lne (cae B) Congeed lne G G2 G3 Lne The new mehod uggeed run for mnmzng he oal congeon co. Congeon co opmal power oupu repored he hree mehod are compared n able 5. Congeon co found by BHA algorhm beer han he co repored by SO and BBBC algorhm. G4 G5 G6

9 9 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: Table 5: Opmal rechedulng Recheduled power BBBC Technque SO Technque BHA Technque G G G G G G6 Congeon Co Lo In rechedulng of real power, all he hree algorhm are behavng n he ame manner. The change n power ncremenal a all he generaor bue. Becaue of hgh envy, amoun of power changed n generaor 2 he hghe one a hown n able 6. Table 6: Change n power Technque U/DOWN adumen of parcpang generaor (MW) G G2 BBBC SO BHA G3 For clear underandng of he congeon relef, power flow hrough he congeed lne -2 depced n fgure 4. BBBC ouperform he oher wo algorhm of SO and BHA n relevng he lne from exceve power flow. However, he obecve of mnmum co for removng congeon acheved only by he propoed BHA algorhm. G4 G5 G6 Fg. 4: ower flow hrough he lne (Cae B) Convergence characerc of BHA n h cae hown n fgure 5. The number of eraon aken o reach he be reul only 30. The number of eraon aken much encouragng and prove he effcency of he algorhm. Fg. 5: Convergence behavor of BHA n cae B

10 92 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: Concluon: In h work, he new naure npred BHA algorhm adoped for he congeon managemen problem. The algorhm found o be wh le number of parameer need ha are o be uned and can be realzed n Malab codng wh lle effor. The man challenge n he operaon of rerucured power marke managng congeon and h work well addreed ung he propoed algorhm. To keep he congeon co mnmum, he parcpang generaor are more mporance for real power generaon adumen Senvy baed rechedulng of real power generaon followed n h work for congeon managemen. Tranmon congeon caued by lne ouage and overload are condered here. Three dfferen algorhm of BBBC, SO and BHA are ued for congeon managemen hrough real power rechedulng. The performance of he BHA eed on Modfed IEEE-30 bu yem. I obvou from he numercal reul ha he BHA algorhm perform beer han he oher wo algorhm. Congeon co repored by he propoed algorhm beer han ha by he oher wo opmzaon mehod. The algorhm relable wh regard o convergence qualy. The algorhm converge o he global be reul and ake le number of eraon. The preen work can be red ung oher conemporary algorhm or he ame work may be exended for addreng he ame problem wh dfferen caue of ranmon congeon. The caue congeon can be due o blaeral and mullaeral ranacon. REFERENCES Arunachalam, R.K. and. Logaman, 205. Enhancemen of Loadably Lm of Deregulaed ower Syem va Adapve Real Coded Bogeography-Baed Opmzaon. Auralan Journal of Bac and Appled Scence, 9(): Balaraman, S. and N. Kamara, 200. Congeon managemen n deregulaed power yem ung real coded genec algorhm. Inernaonal Journal of Engneerng Scence and Technology, 2(): De Vre, L.J., 200. Capacy allocaon n a rerucured elecrcy marke: echncal and economc evaluaon of congeon managemen mehod on nerconnecor. IEEE oro ower ech proceedng, : 6-. Dua, S., and S.. Sngh, Opmal rechedulng of generaor for congeon managemen baed on parcle warm opmzaon. IEEE Tranacon on ower Syem, 23(4): Gao, B., T. Ma and Y. Tang, 205. ower Tranmon Schedulng for Generaor n a Deregulaed Envronmen Baed on a Game-Theorec Approach. Energe, 8(2): Han, J., and A. apavalou, 205. Congeon managemen hrough opologcal correcon: A cae udy of Cenral Weern Europe. Energy olcy, 86: Haamlou, A., 203. Black hole: A new heurc opmzaon approach for daa cluerng. Informaon cence, 22(2): Hoohmand, R.A., M.J. Morhed and M. araegar, 205. Congeon managemen by deermnng opmal locaon of ere FACTS devce ung hybrd baceral foragng and Nelder Mead algorhm. Appled Sof Compung, 28: Kumar, K.R. and S.C. Mohan, 206. LM Congeon Managemen Ung Enhanced STF-LODF n Deregulaed ower Syem. Crcu and Syem, 7(09): Lo, K.L., Y.S. Yuen and L.A. Snder, Congeon managemen n deregulaed elecrcy marke. Inernaonal Conference on Elecrc Uly Deregulaon and Rerucurng and ower Technologe, DRT: Lommerdal, M., and L. Soder, Smulaon of congeon managemen mehod. In IEEE ower Tech. Maoud, M.R.F. and J.I. Aref, 20. Tranmon Congeon Managemen n Elecrcy Marke Rerucured and Increae he Socal Welfare on he Syem IEEE 4-Bu. Auralan Journal of Bac and Appled Scence, 5(2): andya, K.S., and S.K. Joh, 203. Senvy and parcle warm opmzaon-baed congeon managemen. Elecrc ower Componen and Syem, 4(4): angrah, B.K. and V.R. and, Congeon managemen ung adapve baceral foragng algorhm. Energy Converon and Managemen, 50(5): ael, H., and R. alwal, 205. Congeon managemen n deregulaed power yem ung fac devce. Inernaonal Journal of Advance n Engneerng & Technology, 8(2): Raeh, R and Dr. I. Jacob Raglend, 205. Mul-Obecve Congeon Managemen n a Deregulaed ower Syem - A Revew Auralan Journal of Bac and Appled Scence, 9(6): Ramaubramanan,., G.U. raana and K. Sumah, 202. Opmal locaon of FACTS devce by evoluonary programmng baed OF n deregulaed power yem. Brh Journal of Mahemac & Compuer Scence, 2(): Sarwar, M. and A.S. Sddqu, 205. Congeon managemen n deregulaed elecrcy marke ung drbued generaon. Annual IEEE Inda Conference (INDICON): -5

11 93 Ramachandran R and Arun M, 206 Auralan Journal of Bac and Appled Scence, 0(5) Ocober 206, age: Shrmohammad, D., B. Wollenberg, A. Vodan,. Sandrn, M. erera, F. Rahm and B. So, 998. Tranmon dpach and congeon managemen n he emergng energy marke rucure. IEEE Tranacon on ower Syem, 3(4): Srvaava, S.C. and. Kumar, Opmal power dpach n deregulaed marke conderng congeon managemen. Inernaonal Conference on Elecrc Uly Deregulaon and Rerucurng and ower Technologe, pp: Suganh, S.T., D. Devara and S.H. Thlagar, 205. An Improved Dfferenal Evoluon Algorhm for Congeon Managemen Conderng Volage Sably. Indan Journal of Scence and Technology, 8(24): -9. Venkaah, C., and D.V. Kumar, 20. Fuzzy adapve baceral foragng congeon managemen ung envy baed opmal acve power re-chedulng of generaor. Appled Sof Compung, (8): Verma, S., and V. Mukheree, 206. Opmal real power rechedulng of generaor for congeon managemen ung a novel an lon opmer. IET Generaon, Tranmon & Drbuon, 0(0): Valakh, S., and S. Bakar, 20. Mulobecve decenralzed congeon managemen ung modfed NSGA-II. Araban Journal for Scence and Engneerng, 36(5): Yamna, H.Y. and S.M. Shahdehpour, Congeon managemen coordnaon n he deregulaed power marke. Elecrc ower Syem Reearch, 65(2): Yeuranam, G. and D. Thukaram, Congeon managemen n open acce baed on relave elecrcal dance ung volage ably crera. Elecrc power yem reearch, 77(2):

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,

More information

ISSN MIT Publications

ISSN MIT Publications MIT Inernaonal Journal of Elecrcal and Insrumenaon Engneerng Vol. 1, No. 2, Aug 2011, pp 93-98 93 ISSN 2230-7656 MIT Publcaons A New Approach for Solvng Economc Load Dspach Problem Ansh Ahmad Dep. of Elecrcal

More information

SSRG International Journal of Thermal Engineering (SSRG-IJTE) Volume 4 Issue 1 January to April 2018

SSRG International Journal of Thermal Engineering (SSRG-IJTE) Volume 4 Issue 1 January to April 2018 SSRG Inernaonal Journal of Thermal Engneerng (SSRG-IJTE) Volume 4 Iue 1 January o Aprl 18 Opmal Conrol for a Drbued Parameer Syem wh Tme-Delay, Non-Lnear Ung he Numercal Mehod. Applcaon o One- Sded Hea

More information

Cooling of a hot metal forging. , dt dt

Cooling of a hot metal forging. , dt dt Tranen Conducon Uneady Analy - Lumped Thermal Capacy Model Performed when; Hea ranfer whn a yem produced a unform emperaure drbuon n he yem (mall emperaure graden). The emperaure change whn he yem condered

More information

Deregulation, a new paradigm in the electric supply. Comparative studies of congestion management in deregulated electricity market

Deregulation, a new paradigm in the electric supply. Comparative studies of congestion management in deregulated electricity market 6h NATIONAL POWER SYSTEMS CONFERENCE, 5h-7h DECEMBER, 00 68 Comparave sudes of congeson managemen n deregulaed elecrcy mare Manasaran Mandala and C. P. upa, Member, IEEE Absrac-One of he man ssues ha hreaen

More information

Graduate Macroeconomics 2 Problem set 5. - Solutions

Graduate Macroeconomics 2 Problem set 5. - Solutions Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K

More information

Multiple Failures. Diverse Routing for Maximizing Survivability. Maximum Survivability Models. Minimum-Color (SRLG) Diverse Routing

Multiple Failures. Diverse Routing for Maximizing Survivability. Maximum Survivability Models. Minimum-Color (SRLG) Diverse Routing Mulple Falure Dvere Roung for Maxmzng Survvably One-falure aumpon n prevou work Mulple falure Hard o provde 100% proecon Maxmum urvvably Maxmum Survvably Model Mnmum-Color (SRLG) Dvere Roung Each lnk ha

More information

Control Systems. Mathematical Modeling of Control Systems.

Control Systems. Mathematical Modeling of Control Systems. Conrol Syem Mahemacal Modelng of Conrol Syem chbum@eoulech.ac.kr Oulne Mahemacal model and model ype. Tranfer funcon model Syem pole and zero Chbum Lee -Seoulech Conrol Syem Mahemacal Model Model are key

More information

Fundamentals of PLLs (I)

Fundamentals of PLLs (I) Phae-Locked Loop Fundamenal of PLL (I) Chng-Yuan Yang Naonal Chung-Hng Unvery Deparmen of Elecrcal Engneerng Why phae-lock? - Jer Supreon - Frequency Synhe T T + 1 - Skew Reducon T + 2 T + 3 PLL fou =

More information

Chapter 6: AC Circuits

Chapter 6: AC Circuits Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.

More information

MANY real-world applications (e.g. production

MANY real-world applications (e.g. production Barebones Parcle Swarm for Ineger Programmng Problems Mahamed G. H. Omran, Andres Engelbrech and Ayed Salman Absrac The performance of wo recen varans of Parcle Swarm Opmzaon (PSO) when appled o Ineger

More information

EEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment

EEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment EEL 6266 Power Sysem Operaon and Conrol Chaper 5 Un Commmen Dynamc programmng chef advanage over enumeraon schemes s he reducon n he dmensonaly of he problem n a src prory order scheme, here are only N

More information

A Demand System for Input Factors when there are Technological Changes in Production

A Demand System for Input Factors when there are Technological Changes in Production A Demand Syem for Inpu Facor when here are Technologcal Change n Producon Movaon Due o (e.g.) echnologcal change here mgh no be a aonary relaonhp for he co hare of each npu facor. When emang demand yem

More information

Solution in semi infinite diffusion couples (error function analysis)

Solution in semi infinite diffusion couples (error function analysis) Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of

More information

Lecture 11: Stereo and Surface Estimation

Lecture 11: Stereo and Surface Estimation Lecure : Sereo and Surface Emaon When camera poon have been deermned, ung rucure from moon, we would lke o compue a dene urface model of he cene. In h lecure we wll udy he o called Sereo Problem, where

More information

Study on Distribution Network Reconfiguration with Various DGs

Study on Distribution Network Reconfiguration with Various DGs Inernaonal Conference on Maerals Engneerng and Informaon Technology Applcaons (MEITA 205) Sudy on Dsrbuon ework Reconfguraon wh Varous DGs Shengsuo u a, Y Dng b and Zhru Lang c School of Elecrcal Engneerng,

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he

More information

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen

More information

A. Inventory model. Why are we interested in it? What do we really study in such cases.

A. Inventory model. Why are we interested in it? What do we really study in such cases. Some general yem model.. Inenory model. Why are we nereed n? Wha do we really udy n uch cae. General raegy of machng wo dmlar procee, ay, machng a fa proce wh a low one. We need an nenory or a buffer or

More information

PARTICLE SWARM OPTIMIZATION BASED ON BOTTLENECK MACHINE FOR JOBSHOP SCHEDULING

PARTICLE SWARM OPTIMIZATION BASED ON BOTTLENECK MACHINE FOR JOBSHOP SCHEDULING Proceedng 7 h Inernaonal Semnar on Indusral Engneerng and Managemen PARTICLE SWARM OPTIMIZATION BASED ON BOTTLENECK MACHINE FOR JOBSHOP SCHEDULING Rahm Mauldya Indusral Engneerng Deparmen, Indusral Engneerng

More information

A Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed

A Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed IJCSI Inernaonal Journal of Compuer Scence Iue, Vol. 9, Iue 3, No, ay ISSN (Onlne): 694-84 www.ijcsi.org 8 A Nonlnear ILC Scheme for Nonlnear Dynamc Syem o Improve Convergence Speed Hoen Babaee, Alreza

More information

A Profit-Based Unit Commitment using Different Hybrid Particle Swarm Optimization for Competitive Market

A Profit-Based Unit Commitment using Different Hybrid Particle Swarm Optimization for Competitive Market A.A. Abou El Ela, e al./ Inernaonal Energy Journal 9 (2008) 28-290 28 A rof-based Un Commmen usng Dfferen Hybrd arcle Swarm Opmzaon for Compeve Marke www.serd.a.ac.h/rerc A. A. Abou El Ela*, G.E. Al +

More information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy

More information

Security Constrained Economic Dispatch: A Markov Decision Process Approach with Embedded Stochastic Programming

Security Constrained Economic Dispatch: A Markov Decision Process Approach with Embedded Stochastic Programming Secury Conraned Economc Dpach: A Markov Decon Proce Approach wh Embedded Sochac Programmng Lzh Wang an aan profeor n Indural and Manufacurng Syem Engneerng a Iowa Sae Unvery, and he alo hold a courey jon

More information

Variants of Pegasos. December 11, 2009

Variants of Pegasos. December 11, 2009 Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

FTCS Solution to the Heat Equation

FTCS Solution to the Heat Equation FTCS Soluon o he Hea Equaon ME 448/548 Noes Gerald Reckenwald Porland Sae Unversy Deparmen of Mechancal Engneerng gerry@pdxedu ME 448/548: FTCS Soluon o he Hea Equaon Overvew Use he forward fne d erence

More information

Robustness Experiments with Two Variance Components

Robustness Experiments with Two Variance Components Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference

More information

CTLS 4 SNR. Multi Reference CTLS Method for Passive Localization of Radar Targets

CTLS 4 SNR. Multi Reference CTLS Method for Passive Localization of Radar Targets دا ند رعا ل» ی و ناوری ج ه ع ی و ی «ع وم 79-85 9 C 4 * Donloaded from ad.r a 9:06 +040 on Frda arch nd 09-4 - - - - (9/06/4 : 90/05/7 : ) DOA. DOA. C DOA.. C.. C SR.. C.C DOA : ul Reference C ehod for

More information

WiH Wei He

WiH Wei He Sysem Idenfcaon of onlnear Sae-Space Space Baery odels WH We He wehe@calce.umd.edu Advsor: Dr. Chaochao Chen Deparmen of echancal Engneerng Unversy of aryland, College Par 1 Unversy of aryland Bacground

More information

Single-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method

Single-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method 10 h US Naonal Congress on Compuaonal Mechancs Columbus, Oho 16-19, 2009 Sngle-loop Sysem Relably-Based Desgn & Topology Opmzaon (SRBDO/SRBTO): A Marx-based Sysem Relably (MSR) Mehod Tam Nguyen, Junho

More information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () we define the interaction representation by the unitary transformation () = () Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger

More information

Matrix reconstruction with the local max norm

Matrix reconstruction with the local max norm Marx reconrucon wh he local max norm Rna oygel Deparmen of Sac Sanford Unvery rnafb@anfordedu Nahan Srebro Toyoa Technologcal Inue a Chcago na@cedu Rulan Salakhudnov Dep of Sac and Dep of Compuer Scence

More information

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study)

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study) Inernaonal Mahemacal Forum, Vol. 8, 3, no., 7 - HIKARI Ld, www.m-hkar.com hp://dx.do.org/.988/mf.3.3488 New M-Esmaor Objecve Funcon n Smulaneous Equaons Model (A Comparave Sudy) Ahmed H. Youssef Professor

More information

An Effective League Championship Algorithm for the Stochastic Multi- Period Portfolio Optimization Problem

An Effective League Championship Algorithm for the Stochastic Multi- Period Portfolio Optimization Problem An Effecve League Champonhp Algorhm for he Sochac Mul- Perod Porfolo Opmzaon Problem Al Huenzadeh Kahan *1, Mohammad Eyvaz 2, Amn Abba-Pooya 3 Faculy of Indural and Syem Engneerng, Tarba Modare Unvery,

More information

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes. umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal

More information

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae

More information

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts nernaonal ournal of Appled Engneerng Research SSN 0973-4562 Volume 13, Number 10 (2018) pp. 8708-8713 Modelng and Solvng of Mul-Produc nvenory Lo-Szng wh Suppler Selecon under Quany Dscouns Naapa anchanaruangrong

More information

Laplace Transformation of Linear Time-Varying Systems

Laplace Transformation of Linear Time-Varying Systems Laplace Tranformaon of Lnear Tme-Varyng Syem Shervn Erfan Reearch Cenre for Inegraed Mcroelecronc Elecrcal and Compuer Engneerng Deparmen Unvery of Wndor Wndor, Onaro N9B 3P4, Canada Aug. 4, 9 Oulne of

More information

Lecture 11 SVM cont

Lecture 11 SVM cont Lecure SVM con. 0 008 Wha we have done so far We have esalshed ha we wan o fnd a lnear decson oundary whose margn s he larges We know how o measure he margn of a lnear decson oundary Tha s: he mnmum geomerc

More information

Theoretical Analysis of Biogeography Based Optimization Aijun ZHU1,2,3 a, Cong HU1,3, Chuanpei XU1,3, Zhi Li1,3

Theoretical Analysis of Biogeography Based Optimization Aijun ZHU1,2,3 a, Cong HU1,3, Chuanpei XU1,3, Zhi Li1,3 6h Inernaonal Conference on Machnery, Maerals, Envronmen, Boechnology and Compuer (MMEBC 6) Theorecal Analyss of Bogeography Based Opmzaon Aun ZU,,3 a, Cong U,3, Chuanpe XU,3, Zh L,3 School of Elecronc

More information

H = d d q 1 d d q N d d p 1 d d p N exp

H = d d q 1 d d q N d d p 1 d d p N exp 8333: Sacal Mechanc I roblem Se # 7 Soluon Fall 3 Canoncal Enemble Non-harmonc Ga: The Hamlonan for a ga of N non neracng parcle n a d dmenonal box ha he form H A p a The paron funcon gven by ZN T d d

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,

More information

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current :

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current : . A. IUITS Synopss : GOWTH OF UNT IN IUIT : d. When swch S s closed a =; = d. A me, curren = e 3. The consan / has dmensons of me and s called he nducve me consan ( τ ) of he crcu. 4. = τ; =.63, n one

More information

The Dynamic Programming Models for Inventory Control System with Time-varying Demand

The Dynamic Programming Models for Inventory Control System with Time-varying Demand The Dynamc Programmng Models for Invenory Conrol Sysem wh Tme-varyng Demand Truong Hong Trnh (Correspondng auhor) The Unversy of Danang, Unversy of Economcs, Venam Tel: 84-236-352-5459 E-mal: rnh.h@due.edu.vn

More information

Online EM Algorithm for Background Subtraction

Online EM Algorithm for Background Subtraction Avalable onlne a www.cencedrec.com Proceda Engneerng 9 (0) 64 69 0 Inernaonal Workhop on Informaon and Elecronc Engneerng (IWIEE) Onlne E Algorhm for Background Subracon Peng Chen a*, Xang Chen b,bebe

More information

Fast Method for Two-dimensional Renyi s Entropy-based Thresholding

Fast Method for Two-dimensional Renyi s Entropy-based Thresholding Adlan Ym al. / Inernaonal Journal on Compuer Scence and Engneerng IJCSE Fa Mehod for Two-dmenonal Reny Enropy-baed Threholdng Adlan Ym Yohhro AGIARA 2 Tauku MIYOSI 2 Yukar AGIARA 3 Qnargul Ym Grad. School

More information

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times Reacve Mehods o Solve he Berh AllocaonProblem wh Sochasc Arrval and Handlng Tmes Nsh Umang* Mchel Berlare* * TRANSP-OR, Ecole Polyechnque Fédérale de Lausanne Frs Workshop on Large Scale Opmzaon November

More information

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005 Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc

More information

Genetic Algorithm in Parameter Estimation of Nonlinear Dynamic Systems

Genetic Algorithm in Parameter Estimation of Nonlinear Dynamic Systems Genec Algorhm n Parameer Esmaon of Nonlnear Dynamc Sysems E. Paeraks manos@egnaa.ee.auh.gr V. Perds perds@vergna.eng.auh.gr Ah. ehagas kehagas@egnaa.ee.auh.gr hp://skron.conrol.ee.auh.gr/kehagas/ndex.hm

More information

Chapters 2 Kinematics. Position, Distance, Displacement

Chapters 2 Kinematics. Position, Distance, Displacement Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

Cubic Bezier Homotopy Function for Solving Exponential Equations Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.

More information

Lecture 6: Learning for Control (Generalised Linear Regression)

Lecture 6: Learning for Control (Generalised Linear Regression) Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson

More information

Dual Approximate Dynamic Programming for Large Scale Hydro Valleys

Dual Approximate Dynamic Programming for Large Scale Hydro Valleys Dual Approxmae Dynamc Programmng for Large Scale Hydro Valleys Perre Carpener and Jean-Phlppe Chanceler 1 ENSTA ParsTech and ENPC ParsTech CMM Workshop, January 2016 1 Jon work wh J.-C. Alas, suppored

More information

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon

More information

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal

More information

ACTIVE LOAD MANAGEMENT STRATEGY CONSIDERING FLUCTUATION CHARACTERISTICS OF INTERMITTENT ENERGY

ACTIVE LOAD MANAGEMENT STRATEGY CONSIDERING FLUCTUATION CHARACTERISTICS OF INTERMITTENT ENERGY 23 rd naonal Conference on Elecrcy Drbuon Lyon 15-18 June 2015 ACTIVE LOAD MANAGEMENT STATEGY CONSIDEING FLCTATION CHAACTEISTICS OF INTEMITTENT ENEGY Fe CHEN Dong LI Qngheng LI Shangha Jao Tong nvery Chna

More information

Energy-Efficiency Joint Cooperative Spectrum Sensing and Power Allocation Scheme for Green Cognitive Radio Network: A Soft Decision Fusion Approach

Energy-Efficiency Joint Cooperative Spectrum Sensing and Power Allocation Scheme for Green Cognitive Radio Network: A Soft Decision Fusion Approach Amercan Journal of Nework and ommuncaon 8; 7(: 6-6 hp://www.cencepublhnggroup.com/j/ajnc do:.68/j.ajnc.87. ISSN: 36-893X (rn; ISSN: 36-896 (Onlne Energy-Effcency Jon ooperave Specrum Senng and ower Allocaon

More information

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5 TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres

More information

On computing differential transform of nonlinear non-autonomous functions and its applications

On computing differential transform of nonlinear non-autonomous functions and its applications On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy,

More information

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran

More information

FI 3103 Quantum Physics

FI 3103 Quantum Physics /9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon

More information

Planar truss bridge optimization by dynamic programming and linear programming

Planar truss bridge optimization by dynamic programming and linear programming IABSE-JSCE Jon Conference on Advances n Brdge Engneerng-III, Augus 1-, 015, Dhaka, Bangladesh. ISBN: 978-984-33-9313-5 Amn, Oku, Bhuyan, Ueda (eds.) www.abse-bd.org Planar russ brdge opmzaon by dynamc

More information

MATHEMATICAL MODEL OF THYRISTOR INVERTER INCLUDING A SERIES-PARALLEL RESONANT CIRCUIT

MATHEMATICAL MODEL OF THYRISTOR INVERTER INCLUDING A SERIES-PARALLEL RESONANT CIRCUIT 78 Avance n Elecrcal an Elecronc Engneerng MATHEMATIA MODE OF THYRISTOR INVERTER INUDING A SERIESPARAE RESONANT IRUIT M. uf, E. Szycha Faculy of Tranpor, Techncal Unvery of Raom, Polan ul. Malczewkego

More information

Time-interval analysis of β decay. V. Horvat and J. C. Hardy

Time-interval analysis of β decay. V. Horvat and J. C. Hardy Tme-nerval analyss of β decay V. Horva and J. C. Hardy Work on he even analyss of β decay [1] connued and resuled n he developmen of a novel mehod of bea-decay me-nerval analyss ha produces hghly accurae

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4 CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

More information

Thruster Modulation for Unsymmetric Flexible Spacecraft with Consideration of Torque Arm Perturbation

Thruster Modulation for Unsymmetric Flexible Spacecraft with Consideration of Torque Arm Perturbation hruer Modulaon for Unymmerc Flexble Sacecraf wh onderaon of orue rm Perurbaon a Shgemune anwak Shnchro chkawa a Yohak hkam b a Naonal Sace evelomen gency of Jaan 2-- Sengen ukuba-h barak b eo Unvery 3--

More information

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2)

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2) Company LOGO THERMODYNAMICS The Frs Law and Oher Basc Conceps (par ) Deparmen of Chemcal Engneerng, Semarang Sae Unversy Dhon Harano S.T., M.T., M.Sc. Have you ever cooked? Equlbrum Equlbrum (con.) Equlbrum

More information

Open Access An Improved Particle Swarm Optimization Approach for Unit Commitment

Open Access An Improved Particle Swarm Optimization Approach for Unit Commitment Send Orders for Reprns o reprns@benhamscence.ae The Open Auomaon and Conrol Sysems Journal, 204, 6, 629-636 629 Open Access An Improved Parcle Swarm Opmzaon Approach for Un Commmen Problem Yran Guo,2,

More information

Motion in Two Dimensions

Motion in Two Dimensions Phys 1 Chaper 4 Moon n Two Dmensons adzyubenko@csub.edu hp://www.csub.edu/~adzyubenko 005, 014 A. Dzyubenko 004 Brooks/Cole 1 Dsplacemen as a Vecor The poson of an objec s descrbed by s poson ecor, r The

More information

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class

More information

NPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management

NPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management P age NPTEL Proec Economerc Modellng Vnod Gua School of Managemen Module23: Granger Causaly Tes Lecure35: Granger Causaly Tes Rudra P. Pradhan Vnod Gua School of Managemen Indan Insue of Technology Kharagur,

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure

More information

Research Article Solving Unit Commitment Problem Using Modified Subgradient Method Combined with Simulated Annealing Algorithm

Research Article Solving Unit Commitment Problem Using Modified Subgradient Method Combined with Simulated Annealing Algorithm Hndaw Publshng Corporaon Mahemacal Problems n Engneerng Volume 2010, Arcle ID 295645, 15 pages do:10.1155/2010/295645 Research Arcle Solvng Un Commmen Problem Usng Modfed Subgraden Mehod Combned wh Smulaed

More information

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas)

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas) Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on

More information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

Equivalent Ramp Rate Function for Thermal Power Systems

Equivalent Ramp Rate Function for Thermal Power Systems > 15ESGM1 < 1 Equvalen amp ae Funcon for Thermal ower Syem Hawan Zhon Member IEEE Safur ahman Fellow IEEE Qn Xa Senor Member IEEE and Chonqn Kan Senor Member IEEE Abrac The equvalen modeln mehod exenvely

More information

Short-Term Load Forecasting Using PSO-Based Phase Space Neural Networks

Short-Term Load Forecasting Using PSO-Based Phase Space Neural Networks Proceedngs of he 5h WSEAS In. Conf. on SIMULATION, MODELING AND OPTIMIZATION, Corfu, Greece, Augus 7-9, 005 (pp78-83) Shor-Term Load Forecasng Usng PSO-Based Phase Space Neural Neworks Jang Chuanwen, Fang

More information

Meta-Heuristic Optimization techniques in power systems

Meta-Heuristic Optimization techniques in power systems Proceedngs of he 2nd IASME / WSEAS Inernaonal Conference on Energy & Envronmen (EE07), Pororoz, Slovena, May 15-17, 2007 163 Mea-Heursc Opmzaon echnques n power sysems Vlachos Arsds Deparmen of Informacs

More information

Evaluating Topological Optimized Layout of Building Structures by Using Nodal Material Density Based Bilinear Interpolation

Evaluating Topological Optimized Layout of Building Structures by Using Nodal Material Density Based Bilinear Interpolation Evaluang opologcal Opmzed Layou of Buldng Srucure by Ung Nodal Maeral Deny Baed Blnear Inerpolaon Dongkyu Lee* 1, Jaehong Lee, Khak Lee 3 and Namhk Ahn 4 1 Aan Profeor, Deparmen of Archecural Engneerng,

More information

Hongyuan Gao* and Ming Diao

Hongyuan Gao* and Ming Diao In. J. odellng, Idenfcaon and Conrol, Vol. X, No. Y, 200X Culural frework algorhm and s applcaon for dgal flers desgn Hongyuan Gao* and ng Dao College of Informaon and Communcaon Engneerng, Harbn Engneerng

More information

PRIMARY FREQUENCY CONTROL PARTICIPATION PROVIDED BY DOUBLY FED INDUCTION WIND GENERATORS

PRIMARY FREQUENCY CONTROL PARTICIPATION PROVIDED BY DOUBLY FED INDUCTION WIND GENERATORS RIMARY FREQUENCY CONTROL ARTICIATION ROIDED BY DOUBLY FED INDUCTION WIND GENERATORS Rogéro G. de Almeda INESC ORTO oro, orugal ralmeda@necporo.p Abrac Th paper decrbe a conrol approach appled on doubly

More information

Generation Scheduling in Large-Scale Power Systems with Wind Farms Using MICA

Generation Scheduling in Large-Scale Power Systems with Wind Farms Using MICA Journal of Arfcal Inellgence n Elecrcal Engneerng, Vol. 4, No. 16, March 2016 Generaon Schedulng n Large-Scale Power Sysems wh Wnd Farms Usng MICA Hossen Nasragdam 1, Narman Najafan 2 1 Deparmen of Elecrcal

More information

Lecture VI Regression

Lecture VI Regression Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M

More information

Power Loss Reduction in Radial Distribution System by Placing Optimal Capacitor Banks

Power Loss Reduction in Radial Distribution System by Placing Optimal Capacitor Banks ISS (rn) : 30 3765 ISS (Onlne): 78 8875 Inernaonal Journal of Advanced Research n Elecrcal Elecroncs and Insrumenaon Engneerng (An ISO 397: 007 erfed Organzaon) Vol. 5 Issue February 016 ower Reducon n

More information

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer d Model Cvl and Surveyng Soware Dranage Analyss Module Deenon/Reenon Basns Owen Thornon BE (Mech), d Model Programmer owen.hornon@d.com 4 January 007 Revsed: 04 Aprl 007 9 February 008 (8Cp) Ths documen

More information

Developing A Model-Based Software To Optimize Wheat Storage and Transportation System: A Real-World Application

Developing A Model-Based Software To Optimize Wheat Storage and Transportation System: A Real-World Application Developng A odel-baed Sofware To Opmze Whea Sorage and Tranporaon Sem: A Real-World Applcaon Reza Zanran Farahan a,b,c*, Narn Agar c, Hoen Hoabr a and Amr Ardean Jaafar a a Logc & Suppl Chan Reearche &

More information

Optimal environmental charges under imperfect compliance

Optimal environmental charges under imperfect compliance ISSN 1 746-7233, England, UK World Journal of Modellng and Smulaon Vol. 4 (28) No. 2, pp. 131-139 Opmal envronmenal charges under mperfec complance Dajn Lu 1, Ya Wang 2 Tazhou Insue of Scence and Technology,

More information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

Scattering at an Interface: Oblique Incidence

Scattering at an Interface: Oblique Incidence Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may

More information

Department of Economics University of Toronto

Department of Economics University of Toronto Deparmen of Economcs Unversy of Torono ECO408F M.A. Economercs Lecure Noes on Heeroskedascy Heeroskedascy o Ths lecure nvolves lookng a modfcaons we need o make o deal wh he regresson model when some of

More information

Bi-Level Optimization based Coordinated Bidding Strategy of a Supplier in Electricity Market

Bi-Level Optimization based Coordinated Bidding Strategy of a Supplier in Electricity Market Inernaonal Journal of Engneerng Research and Developmen e-issn: 2278-067X, p-issn: 2278-800X, www.jerd.com Volume 11, Issue 06 (June 2015), PP.04-13 B-Level Opmzaon based Coordnaed Bddng Sraegy of a Suppler

More information

Parameter Estimation of Three-Phase Induction Motor by Using Genetic Algorithm

Parameter Estimation of Three-Phase Induction Motor by Using Genetic Algorithm 360 Journal of Elecrcal Engneerng & Technology Vol. 4, o. 3, pp. 360~364, 009 Parameer Esmaon of Three-Phase Inducon Moor by Usng Genec Algorhm Seesa Jangj and Panhep Laohacha* Absrac Ths paper suggess

More information

A new topology for quasi-z-source inverter

A new topology for quasi-z-source inverter pp.: A new opology or qua-z-ource nerer Negar Mrkazeman, Ebrahm Babae Elecrcal Engneerng Deparmen, Shabear Branch, Ilamc Azad Unery, Shabear, Iran, Emal:negarmrkazeman@auhab.ac.r Elecrcal and Compuer Engneerng,

More information

Refined Binary Particle Swarm Optimization and Application in Power System

Refined Binary Particle Swarm Optimization and Application in Power System Po-Hung Chen, Cheng-Chen Kuo, Fu-Hsen Chen, Cheng-Chuan Chen Refned Bnary Parcle Swarm Opmzaon and Applcaon n Power Sysem PO-HUNG CHEN, CHENG-CHIEN KUO, FU-HSIEN CHEN, CHENG-CHUAN CHEN* Deparmen of Elecrcal

More information

Particle Filter Based Robot Self-localization Using RGBD Cues and Wheel Odometry Measurements Enyang Gao1, a*, Zhaohua Chen1 and Qizhuhui Gao1

Particle Filter Based Robot Self-localization Using RGBD Cues and Wheel Odometry Measurements Enyang Gao1, a*, Zhaohua Chen1 and Qizhuhui Gao1 6h Inernaonal Conference on Elecronc, Mechancal, Informaon and Managemen (EMIM 206) Parcle Fler Based Robo Self-localzaon Usng RGBD Cues and Wheel Odomery Measuremens Enyang Gao, a*, Zhaohua Chen and Qzhuhu

More information

Example: MOSFET Amplifier Distortion

Example: MOSFET Amplifier Distortion 4/25/2011 Example MSFET Amplfer Dsoron 1/9 Example: MSFET Amplfer Dsoron Recall hs crcu from a prevous handou: ( ) = I ( ) D D d 15.0 V RD = 5K v ( ) = V v ( ) D o v( ) - K = 2 0.25 ma/v V = 2.0 V 40V.

More information