VOLTAGE stability issue remains a major concern in
|
|
- Kathleen Ariel Sharp
- 8 years ago
- Views:
Transcription
1 Impacts of Mert Order Based Dspatch on Transfer Capablty and Statc Voltage Stablty Cuong P. guyen, Student Member, IEEE, and Alexander J. Flueck, Member, IEEE Abstract In ths paper, the goal s to nvestgate the mpacts of generaton mert order based dspatch on transfer capablty and statc voltage stablty. The concept of generaton mert order can be based on tradtonal costs or market bds. The new mert order feature has been ncorporated nto the exstng Contnuaton Method Trace Tool (CMTRACE). More specfcally, the wellknown contnuaton power flow problem s reformulated to take nto account the mert order effect of dspatchng generators on the statc P-V curve, gven a power system operatng pont, a load demand forecast and a table of generaton MW blocks and prces. The modelng dffcultes n dealng wth sequentally ordered generaton block dspatches, such as exact transton pont search and soluton tme, are effcently solved. The numercal results on two case studes of a 3493-bus system show that the mert order of dspatchng generaton has sgnfcant mpacts on the P-V curve and the smulaton tme. Index Terms Contnuaton power flow, dstance to collapse, statc bfurcaton, voltage stablty I. ITRODUCTIO VOLTAGE stablty ssue remans a major concern n the operaton and control of power systems nowadays. The lmt of exstng transmsson resources, the hgh growth rate of power demand and supply, together wth the ncrease n electrc power transactons are pushng power systems to operate closer to ther stablty boundary. Contnuaton power flow s an effcent method to address the quas-statc voltage stablty problem, whch has been well studed for the past 7 years [],[4],[5],[6],[7]. Typcally n ths study, the generaton/demand level of a set of partcpatng buses s consdered to vary slowly, hence quas-statcally, from a base case level to some pre-defned level. Snce all partcpatng generators are parameterzed to ncrease or decrease ther power output at the same tme, ths way of dspatchng generaton s called smultaneous dspatch. Recently n [0], an mproved CPFLOW tool consderng multple load varaton and generaton re-dspatch patterns was developed but the generators are stll dspatched n a smlar manner. The exstng CMTRACE tool [2], on whch the Mert Order Based Dspatch (MOBD) algorthm s developed, s a comprehensve tool for tracng power system steady-state behavor due to load and generaton varatons. CMTRACE s a contnuaton power flow tool wth some enhanced features such as effcent step sze selecton and an embedded algorthm to search for breakng ponts due to the lmted reactve capablty of generators. A common drawback n CMTRACE C. P. guyen (emal: cnguyen7@t.edu) and A. J. Flueck (emal: flueck@t.edu) are wth the Department of Electrcal and Computer Engneerng, Illnos Insttute of Technology, Chcago, IL, 6066 USA. as well as other avalable tools s that they can only generate P-V curves gven a power system operatng pont and a sngle drecton of load growth and generaton dspatch. As such, those tools are better suted for generalzed voltage studes. On the other hand, n specalzed voltage studes, generaton blocks wth dfferent prces are dspatched based on the mert order table. Ths table s created smply by sortng all generaton blocks n non-decreasng order of prce. The cheaper blocks wll be dspatched before the more expensve ones. Conversely when decreasng the generaton, the more expensve generators should respond before the less expensve ones. Ths paper s organzed as follows: Secton II dscusses the formulaton of the MOBD problem. In Secton III, some background on the contnuaton method s brefly ntroduced. The soluton algorthm of MOBD s presented n Secton IV. umercal results are gven n Secton V. Fnally, conclusons and contrbutons are summarzed n Secton VI. A. Smultaneous Dspatch II. PROBLEM FORMULATIO Let F (x, λ) represent the parameterzed power flow equatons. The smultaneous generaton dspatch [] has the followng formulaton: [ ] P (x) P nj F (x, λ) = Q(x) Q nj λb () where vector [ x = ( V, θ) represents ] the state varables and ˆP vector b = nj P nj ˆQ nj Q nj, whch parameterzes the total scheduled transfer, represents the change n bus njectons due to varatons n generaton dspatch and load demand. ˆP nj, ˆQ nj are target real, reactve power njecton levels and λ s the (controllng) parameter subject to varaton. The Lmt Pont (LP), ether a saddle-node bfurcaton pont or a breakng pont, corresponds to the maxmum value of the physcal parameter λ n the drecton gven by the parameterzaton vector b. In ths smultaneous parameterzaton scheme all actve generators are parameterzed n a sngle vector b, hence they are dspatched at the same tme. However, ths doesn t make sense when each generator has generaton blocks wth dfferent prces. B. Sequental Dspatch The sequental generaton dspatch algorthm consders generaton prce as a key factor n power transfer studes. Two
2 2 Pgen2 Lmt pont of sequental dspatch Gen bus 52 Sequental Dspatch Pgen Qgen ETP Target generaton schedule Base generaton Lmt pont of smultaneous dsptach MW, MVAr Qmax Pgen 0 Fg.. Real power generaton pattern of smultaneous dspatch and sequental dspatch Fg. 2. Output of generator 52 n MOBD common types of transfer are typcally of nterest n studyng statc voltage collapse: Generaton to Load Transfer: one set of pckup generators, called the source, ncreases ts generaton and another set of loads, called the snk, ncreases ts consumpton (Fg. 3). Generaton to Generaton Transfer: one set of generators, consdered as the source, ncreases ts output and another set of generators, called the snk, decreases ts output (Fg. 4). In ether case, the mert order of each generator or load partcpatng n the transfer must be determned frst based on the bddng prces. Then, a seres of bus njecton vectors b,..., b m can be bult up correspondngly. Whle Fg. 3 shows smultaneous schedulng of load, t s possble to schedule load sequentally based on prce. The sequental dspatch power flow equaton s reformulated based on (), as follows: [ ] P (x) P nj F (x, λ,..., λ m ) = Q(x) Q nj (2) λ b... λ m b m where λ s the (controllng) parameter assocated wth vector b, =,..., m. Intally, all λ = 0. The physcal parameter λ [0, ] assocated wth generators partcpatng n b s nterpreted as follows: f λ = 0 then b s nactve (generators parameterzed n b are nactve) else f λ 0 then b s actve (generators parameterzed n b are actve) else f λ = then b becomes an addtonal constant bus njecton vector n (2). ow when b s fully dspatched, the next step s to actvate b +. ote that each b represents a subtransfer, the sum of all subtransfers yelds the total scheduled transfer as seen n the smultaneous dspatch case. Fg. s an llustratve example of smultaneous dspatch versus sequental dspatch where two generators, expensve generator and cheap generator 2, are scaled up to serve the ncreased demand. There are two subtransfers n ths case, generator whch s parameterzed n b s actve before generator 2 n b 2. C. Exact Transton Pont (ETP) Search In mert order based dspatch often tmes there s more than one subtransfer. The Exact Transton Pont s the pont where b s fully dspatched,.e. λ =, so there can be as many as m transton ponts. The strategy to solve for ETP s as follows: ) Detect f the predcted parameter ˆλ >, f true then goto 2) else go to 5) 2) Rescale predctor step sze such that ˆλ = 3) Correct the predcted ETP. If the corrected λ s wthn the desred tolerance of.0, then go to 4) else go to 2) 4) Done wth b 5) Correct the predctor pont as normal It can easly be seen n Fg. that at the ETP, unt 2 generates power at ts target level whle unt stll produces power at the base case level. D. Generator Reactve Power Modelng Reactve power generaton of actve generators s a dependent varable but t can be modeled va parameterzng maxmum reactve power capablty Qmax [3]. Fg. 2 ndcates that generator 52 reactve power output for some transfer study keeps ncreasng n order to support ts termnal voltage as the system becomes more stressed. Eventually t hts Qmax at 83 MVAr before the generator tself actually becomes actve to decrease the MW and MVAr outputs down to zero. III. BACKGROUD O COTIUATIO METHOD Ths secton presents background materal on contnuaton methods for tracng soluton branches of general nonlnear algebrac systems.
3 3 Generaton to Load Transfer ) Input the nformaton of the source: generator bus, bddng block and prce 2) Input the nformaton of the snk: load bus, real/reactve power change 3) Rank the partcpatng generators based on the prce. Generaton blocks wth the same prce are grouped together 4) Set =,.e. the cheapest generaton 5) Parameterze load buses β = Pgen / P gen Pload = β P load; Q load = β Q load ote: Q gen s parameterzed as n subsecton II.D 6) Form[ vector b ] P b = gen Pload Q gen Q load 7) Increment, f > m then go to step (9) 8) Go to step (5) 9) Stop Fg. 3. Generaton to Load transfer parameterzaton strategy A. Basc Elements of Contnuaton Method The theory of contnuaton methods has been studed extensvely and has ts roots n algebrac topology and dfferental topology [8]. A contnuaton method has four basc elements: ) parameterzaton, 2) predctor, 3) step length control and 4) corrector. B. Local Parameterzaton Local parameterzaton s chosen due to ts effcency n capturng transton ponts. Gven the prevous soluton pont (x k, λ k ) and the prevous step s tangent vector (ẋ k, λ k ), local parameterzaton tes the ewton corrector solutons trajectory to a contnuaton parameter that s determned at each contnuaton step by the tangent vector. If λ k s chosen for example, the parameterzaton equaton s λ k+ = λ k + λ (3) where λ s the step sze along the soluton path. λ can be the desred MW step sze, as n ths paper, that the user wshes to take along the soluton trajectory toward the next soluton pont. C. Corrector The ewton corrector solves the augmented set of equatons wth actve b and an ntal guess (ˆx k+ k+, ˆλ ) provded by the predctor, as follows: [ ] P (x k+ ) P nj Q(x k+ ) Q nj b... b (4) λ k+ b = 0 = λ k + λ λ k+ In the curved part of the soluton curve t s possble that some x j other than λ s selected as a contnuaton parameter. Generaton to Generaton Transfer ) Input the nformaton of the source: generator bus, bddng block and prce 2) Input the nformaton of the snk: generator bus, generaton block and prce 3) Rank the source generators n the non-decreasng order of prce and the snk generators n the nonncreasng order of prce 4) Set = source =,.e. cheapest generaton block(s) snk =,.e. most expensve generaton block(s) 5) Parameterze generator buses γ = P snk snkgen / P f γ < then Pgen = P snk snkgen + γ P source P source = ( γ) P source snk = snk + else f γ > Pgen = γ P snk snkgen + P source P snk snkgen = ( γ ) P snk snkgen source = source + else Pgen = P snk snkgen + P source snk = snk + source = source + end ote: Q gen s parameterzed as n subsecton II.D 6) Form vector b ] [ P b = gen Q gen 7) Check lmt of snk, source, f any volaton then go to step (9) 8) Increment, go to step (5) 9) Stop Fg. 4. Then x k+ j (4). Generaton to Generaton transfer parameterzaton strategy = x k j + x j wll substtute as the last equaton of IV. SOLUTIO ALGORITHM Ths paper uses a predctor-corrector contnuaton method to trace soluton paths. The tangent method serves as a predctor. The ewton method s chosen as the corrector. The soluton algorthm proposed n ths paper s llustrated n Fg. 5. In tracng the soluton curve n whch there are multple tny subtransfers, solvng for each subtransfer costs at least one contnuaton step. If an exact contnuaton trajectory wth every sngle transton pont s not of nterest, then lumpng small subtransfers would save a consderable amount of smulaton tme. One opton, newly added to CMTRACE, s the user can specfy the mnmum subtransfer level. If the th subtransfer parameterzed n b s less than the threshold, then vector b wll be combned wth b +. The process s repeated untl the total combned subtransfer s greater than or equal to the mnmum subtransfer value.
4 4 TABLE I CASE STUDIES O 3493 BUS SSTEM start Case Transfer Total scheduled transfer (MW) Area 2(Gen) Area (Gen) Area 4(Gen) Area (Load) form b(),...,b(m) solve base case power flow TABLE II SIMULTAEOUS VS SEQUETIAL DISPATCH RESULTS (CASE ) Dspatch DtoC Dto V mn 242 Tme to pass Total tme type (MW) (MW) LP (m:ss) (m:ss) Sm :28 0:38 Seq :37 0:5 Dstance to Collapse pont or equvalently total feasble transfer Dstance to the crossng pont of the soluton trajectory and V mn 242 actvate b() (= ntally) compute tangent vector pass LP = + V. UMERICAL STUDIES Ths secton presents the effectveness of ths new algorthm va two smulatons, see Table I, wth the followng power system: Buses: 3493; Generators: 83; Loads: 2565; Fxed shunts: 957; Swtchable shunts: 25; Lnes: 5953; Fxed transformers: 654; Fxed phase shfter: ; ULTC transformers: 82; ULTC phase shfters: 8; Areas: 30. The test bed used n ths paper s a SU 420R Worksever wth four Processors and 4 GB of Ram, runnng the Solars operatng system. solve for LP select contnuaton parameter predct pass ETP A. Case Study : Generaton to Generaton Transfer Ths case smulates a total scheduled transfer of MW from nexpensve generaton n Area 9 to expensve generaton n Area. The output of all generators n Area 9 s scaled up by 36.0% whle that n Area s decreased by 00%. A step sze of 200 MW and no mnmum subtransfer level are selected n ths study. The voltage magntude trajectores of generator 242 n the mportng Area are presented n Fg. 6 and Fg. 8. In smultaneous dspatch, all MW and MVAr generaton n the snk area s decreased at the same tme regardless of prce. The voltage at bus 242 decreases gradually, see Fg. 6. Ths trend s also observed n other buses n Area. In the sequental case however, snce generator 242 s ranked as the second most expensve generator after generator 243 n Area, t s parameterzed n the second subtransfer. The voltage magntude shown n Fg. 8 drops quckly to 72 pu when generator 242 decreases ts output to zero. Ths s ntutve snce generator 242 s the only one n the mportng area partcpatng n the second subtransfer. The sold horzontal lnes n these fgures represent the mnmum allowed voltage level, whch s 6 pu, at the measured bus. Table II ndcates that the maxmum transfers or dstances to collapse for smultaneous and sequental methods are 2958 MW and 3346 MW respectvely. The mnmum voltage constrant further shortens the maxmum transfers to MW and MW respectvely. The sequental method clearly shows more negatve mpact from the voltage pont of vew for ths example. Fg. 5. correct Done wth b() = m stop reset state back to ETP Flowchart of mert order based dspatch algorthm In terms of power output, the expensve generator 242 s brought out of servce n the sequental dspatch (see Fg. 9) whle t stll onlne wth an output of about 45 MW just before encounterng the lmt pont n the smultaneous case (see Fg. 7). Tme statstcs of the two dspatches are depcted n Table II. Obvously, the sequental process s more tme consumng than the smultaneous counterpart, an ncrease of 34% n total CPU tme. Ths s expected, as smultaneous dspatch has only one sngle transfer whereas sequental dspatch has sequental subtransfers. Interestngly, t happens that sequental dspatch has a longer dstance to collapse compared to smultaneous
5 5..05 Bus 242 Smultaneous Dspatch pred corr..05 Bus 242 Sequental Dspatch pred corr tran 5 5 Fg. 6. Voltage magntude at bus 242 n smultaneous dspatch Fg. 8. Voltage magntude at bus 242 n sequental dspatch Gen bus 242 Smultaneous Dspatch Pgen Qgen Gen bus 242 Sequental Dspatch Pgen Qgen MW, MVAr MW, MVAr Fg. 7. Output of generator 242 n smultaneous dspatch Fg. 9. Output of generator 242 n sequental dspatch dspatch, about 3% ncrease. B. Case Study 2: Generaton to Load Transfer Ths case smulates a total scheduled transfer of MW from nexpensve generaton n Area 4 to the ncreased load n Area. The output of all generators n Area 4 s scaled up by 25.3% and the load growth rate n Area s assumed to be 94.2%. Fg. 0 shows that there are many transton ponts,.e. many tny subtransfers, n the range of 500 MW to 500 MW. Therefore the total soluton tme wthout combnng any subtransfers n sequental dspatch s 56% longer than smultaneous dspatch, see Table III. When the mnmum subtransfer threshold s ncreased, the soluton tme decreases, see Table IV. However there sn t any tme mprovement between the 00 MW and 200 MW mnmum lmts because the total contnuaton steps reman the same. Moreover, for mnmum subtransfers larger than 400 MW, the smulaton tme ncreases a bt as the step sze s stll fxed at 50 MW. Therefore, further ncreasng the threshold beyond 400 MW wll not yeld any tme mpovement. Fg. depcts the P-V curve at bus 6 wth the mnmum transfer set at 200 MW. VI. COCLUSIOS Investgatng transfer capablty and statc voltage stablty s of great mportance n power system operaton. However usng the exstng statc voltage stablty analyss tools to obtan P-V curves n the case of mert order based dspatch can be very tedous, even mpossble. Wth the support of the enhanced CMTRACE tool ths procedure can be effcently automated. The numercal studes prove that MOBD has sgnfcant mpacts on system voltage profle, dstance to collapse as well as smulaton tme compared to the smultaneous dspatch. The contrbutons of ths paper are:
6 6. Bus 6 - Sequental Dspatch tran. Bus 6 Sequental Dspatch tran Tny subtransfers 5 Fg. 0. Voltage magntude at bus 6 n sequental dspatch wthout mn subtransfer constrant TABLE III SIMULTAEOUS VS SEQUETIAL DISPATCH RESULTS (CASE 2, O MIIMUM SUBTRASFER COSTRAIT, STEP SIZE = 50 MW) Dspatch DtoC Dto V mn 242 Tme to pass Total tme type (MW) (MW) LP (m:ss) (m:ss) Sm :29 0:32 Seq :46 0:50 TABLE IV SEQUETIAL DISPATCH WITH DIFFERET MIIMUM SUBTRASFER COSTRAITS (CASE 2, STEP SIZE = 50 MW) Mn subtransfer (MW) Tme to pass LP (m:ss) 0:46 0:37 0:37 0:27 0:29 Total tme (m:ss) 0:50 0:44 0:44 0:30 0:3 Reformulatng the exstng contnuaton power flow problem to take nto account the mert order based dspatch of generaton or load bddng blocks. Handlng effcently the transton ponts between any two subtransfers. The newly mproved CMTRACE tool fnds ts applcaton n near term power transacton studes as well as long term plannng n modern power systems n whch power transfers are ncreasng both n magntude and multtude. VII. REFERECES [] H. D. Chang, A. J. Flueck, K. S. Shah and. Balu, CPFLOW: A Practcal Tool for Tracng Power System Steady-state Statonary Behavor Due to Load and Generaton Varatons, IEEE Trans. on Power Systems, vol. 0, no. 2, pp , May 995. [2] A. J. Flueck, J. R. Dondet, A ew Contnuaton Power Flow Tool for Investgatng the onlnear Effects of Transmsson Branch Parameter Varatons, IEEE Trans. on Power Systems, vol. 5, no., pp , Feb [3] A. J. Flueck, H. D. Chang, K. S. Shah, Investgatng The Installed Real Power Transfer Capablty of a Large Scale Power System Under a Proposed Multarea Interchange Schedule Usng CPFLOW, IEEE Trans. on Power Systems, vol., no. 2, pp , May 996. [4] V. A. Ajjarapu and C. Chrsty, The Contnuaton Power Flow: A Tool for Steady State Voltage Stablty Analyss, IEEE Trans. on Power Systems, vol. 7, no., pp , Feb Fg.. Voltage magntude at bus 6 n sequental dspatch wth mn subtransfer constrant of 200 MW [5] C. A. Cañzares and F. L. Alvarado, Pont of Collapse and Contnuaton Methods for Large AC/DC System, IEEE Trans. on Power Systems, vol. 8, no., pp. -8, Feb [6] S. Greene, I. Dobson, F. L. Alvarado, Senstvty of the Loadng Margn to Voltage Collapse wth respect to Arbtrary Parameters, IEEE Trans. on Power Systems, vol. 2, no., pp , Feb [7] A. Sode-ome,. Mthulananthan, K.. Lee, A maxmum loadng margn method for statc voltage stablty n power systems, IEEE Trans. on Power Systems, vol. 2, no. 2, pp , May [8] R. Seydel, From Equlbrum to Chaos: Practcal Bfurcaton and Stablty Analyss, ew ork: Elsever, 988. [9] H. B. Keller, umercal Soluton of Bfurcaton and onlnear Egenvalue Problems, Applcatons of Bfurcaton Theory, ew ork, Academc Press, pp , 977. [0] S. H. L, H. D. Chang, Contnuaton Power Flow wth Multple Load Varaton and Generaton Re-Dspatch Patterns, IEEE Power Engneerng Socety General Meetng [] A. J. Flueck, Advances n umercal Analyss of onlnear Dynamcal Systems and The Applcaton to Transfer Capablty of Power Systems, Ph.D. thess, Cornell Unversty, Ithaca,, Aug VIII. BIOGRAPHIES Cuong P. guyen receved the B.S. degree (2003) n power system engneerng from Hano Unversty of Technology, Vetnam and the M.S. degree (2005) n electrcal engneerng from Southern Illnos Unversty at Carbondale, USA. He s currently workng toward the Ph.D. degree wth Prof. A. J. Flueck n the Department of Electrcal and Computer Engneerng, Illnos Insttute of Technology, Chcago. Hs research nterests nclude modelng of power system components, contnuaton methods for parameterzed nonlnear systems, and contngency screenng. Alexander J. Flueck receved the B.S. degree (99), the M.Eng. degree (992) and the Ph.D. degree (996) n electrcal engneerng from Cornell Unversty. He s currently an Assocate Professor at Illnos Insttute of Technology n Chcago. Hs research nterests nclude transfer capablty of large-scale electrc power systems, contngency screenng of multple branch or generator outages wth respect to voltage collapse, contnuaton methods for parameterzed nonlnear systems, transent stablty and parallel smulaton of power systems va message-passng technques on dstrbuted-memory computer clusters.
The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis
The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationIMPACT ANALYSIS OF A CELLULAR PHONE
4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng
More informationOn the Optimal Control of a Cascade of Hydro-Electric Power Stations
On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationDynamic Pricing for Smart Grid with Reinforcement Learning
Dynamc Prcng for Smart Grd wth Renforcement Learnng Byung-Gook Km, Yu Zhang, Mhaela van der Schaar, and Jang-Won Lee Samsung Electroncs, Suwon, Korea Department of Electrcal Engneerng, UCLA, Los Angeles,
More informationPerformance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application
Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,
More informationAn Alternative Way to Measure Private Equity Performance
An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate
More informationChapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT
Chapter 4 ECOOMIC DISATCH AD UIT COMMITMET ITRODUCTIO A power system has several power plants. Each power plant has several generatng unts. At any pont of tme, the total load n the system s met by the
More informationA Secure Password-Authenticated Key Agreement Using Smart Cards
A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,
More informationResponse Coordination of Distributed Generation and Tap Changers for Voltage Support
Response Coordnaton of Dstrbuted Generaton and Tap Changers for Voltage Support An D.T. Le, Student Member, IEEE, K.M. Muttaq, Senor Member, IEEE, M. Negnevtsky, Member, IEEE,and G. Ledwch, Senor Member,
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationAnswer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy
4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.
More informationDynamic Constrained Economic/Emission Dispatch Scheduling Using Neural Network
Dynamc Constraned Economc/Emsson Dspatch Schedulng Usng Neural Network Fard BENHAMIDA 1, Rachd BELHACHEM 1 1 Department of Electrcal Engneerng, IRECOM Laboratory, Unversty of Djllal Labes, 220 00, Sd Bel
More informationInstitute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic
Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange
More informationPower-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts
Power-of-wo Polces for Sngle- Warehouse Mult-Retaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
More informationANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING
ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,
More informationProject Networks With Mixed-Time Constraints
Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationAn Interest-Oriented Network Evolution Mechanism for Online Communities
An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne
More informationHow To Understand The Results Of The German Meris Cloud And Water Vapour Product
Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller
More informationThe OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
More informationForecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems
More informationINVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS
21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS
More informationCalculating the high frequency transmission line parameters of power cables
< ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,
More informationA Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression
Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,
More informationPAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign
PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of Illnos-Urbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng
More informationData Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819-840 (2008) Data Broadcast on a Mult-System Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,
More informationComparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions
Comparson of Control Strateges for Shunt Actve Power Flter under Dfferent Load Condtons Sanjay C. Patel 1, Tushar A. Patel 2 Lecturer, Electrcal Department, Government Polytechnc, alsad, Gujarat, Inda
More informationNumber of Levels Cumulative Annual operating Income per year construction costs costs ($) ($) ($) 1 600,000 35,000 100,000 2 2,200,000 60,000 350,000
Problem Set 5 Solutons 1 MIT s consderng buldng a new car park near Kendall Square. o unversty funds are avalable (overhead rates are under pressure and the new faclty would have to pay for tself from
More informationSupport Vector Machines
Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.
More informationDEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
More informationUsing Series to Analyze Financial Situations: Present Value
2.8 Usng Seres to Analyze Fnancal Stuatons: Present Value In the prevous secton, you learned how to calculate the amount, or future value, of an ordnary smple annuty. The amount s the sum of the accumulated
More informationFeasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid
Feasblty of Usng Dscrmnate Prcng Schemes for Energy Tradng n Smart Grd Wayes Tushar, Chau Yuen, Bo Cha, Davd B. Smth, and H. Vncent Poor Sngapore Unversty of Technology and Desgn, Sngapore 138682. Emal:
More informationPeriod and Deadline Selection for Schedulability in Real-Time Systems
Perod and Deadlne Selecton for Schedulablty n Real-Tme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng
More informationJoint Scheduling of Processing and Shuffle Phases in MapReduce Systems
Jont Schedulng of Processng and Shuffle Phases n MapReduce Systems Fangfe Chen, Mural Kodalam, T. V. Lakshman Department of Computer Scence and Engneerng, The Penn State Unversty Bell Laboratores, Alcatel-Lucent
More information2. SYSTEM MODEL. the SLA (unlike the only other related mechanism [15] we can compare it is never able to meet the SLA).
Managng Server Energy and Operatonal Costs n Hostng Centers Yyu Chen Dept. of IE Penn State Unversty Unversty Park, PA 16802 yzc107@psu.edu Anand Svasubramanam Dept. of CSE Penn State Unversty Unversty
More informationAn Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services
An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao
More informationRESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.
ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract
More informationTraffic State Estimation in the Traffic Management Center of Berlin
Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,
More informationJ. Parallel Distrib. Comput.
J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n
More informationEnabling P2P One-view Multi-party Video Conferencing
Enablng P2P One-vew Mult-party Vdeo Conferencng Yongxang Zhao, Yong Lu, Changja Chen, and JanYn Zhang Abstract Mult-Party Vdeo Conferencng (MPVC) facltates realtme group nteracton between users. Whle P2P
More informationbenefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
More informationHowHow to Find the Best Online Stock Broker
A GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION Helena Vasconcelos INESC Porto hvasconcelos@nescportopt J N Fdalgo INESC Porto and FEUP jfdalgo@nescportopt
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationFault tolerance in cloud technologies presented as a service
Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance
More informationDamage detection in composite laminates using coin-tap method
Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the
More informationWhen Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services
When Network Effect Meets Congeston Effect: Leveragng Socal Servces for Wreless Servces aowen Gong School of Electrcal, Computer and Energy Engeerng Arzona State Unversty Tempe, AZ 8587, USA xgong9@asuedu
More informationOptimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account
Amercan J. of Engneerng and Appled Scences (): 8-6, 009 ISSN 94-700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a Day-Ahead Electrcty Market wth Rsk Management Taken nto Account
More informationA DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña
Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION
More informationFormulating & Solving Integer Problems Chapter 11 289
Formulatng & Solvng Integer Problems Chapter 11 289 The Optonal Stop TSP If we drop the requrement that every stop must be vsted, we then get the optonal stop TSP. Ths mght correspond to a ob sequencng
More informationDevelopment of TIF for transaction cost allocation in deregulated power system
ISSN (Onlne) 31 004 ISSN (Prnt) 31 556 Development of TIF for transacton cost allocaton n deregulated power system Noolu.Narendra Reddy 1, Kurakula.Vmala Kumar P.G. Scholar, Department of EEE, JNTUA College
More informationSection 5.4 Annuities, Present Value, and Amortization
Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today
More informationHeuristic Static Load-Balancing Algorithm Applied to CESM
Heurstc Statc Load-Balancng Algorthm Appled to CESM 1 Yur Alexeev, 1 Sher Mckelson, 1 Sven Leyffer, 1 Robert Jacob, 2 Anthony Crag 1 Argonne Natonal Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439,
More informationActivity Scheduling for Cost-Time Investment Optimization in Project Management
PROJECT MANAGEMENT 4 th Internatonal Conference on Industral Engneerng and Industral Management XIV Congreso de Ingenería de Organzacón Donosta- San Sebastán, September 8 th -10 th 010 Actvty Schedulng
More informationSmall pots lump sum payment instruction
For customers Small pots lump sum payment nstructon Please read these notes before completng ths nstructon About ths nstructon Use ths nstructon f you re an ndvdual wth Aegon Retrement Choces Self Invested
More information7.5. Present Value of an Annuity. Investigate
7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on
More informationSPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:
SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and
More informationA New Task Scheduling Algorithm Based on Improved Genetic Algorithm
A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng
More informationAn Analysis of Central Processor Scheduling in Multiprogrammed Computer Systems
STAN-CS-73-355 I SU-SE-73-013 An Analyss of Central Processor Schedulng n Multprogrammed Computer Systems (Dgest Edton) by Thomas G. Prce October 1972 Techncal Report No. 57 Reproducton n whole or n part
More informationAn MILP model for planning of batch plants operating in a campaign-mode
An MILP model for plannng of batch plants operatng n a campagn-mode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafe-concet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño
More informationA Replication-Based and Fault Tolerant Allocation Algorithm for Cloud Computing
A Replcaton-Based and Fault Tolerant Allocaton Algorthm for Cloud Computng Tork Altameem Dept of Computer Scence, RCC, Kng Saud Unversty, PO Box: 28095 11437 Ryadh-Saud Araba Abstract The very large nfrastructure
More informationThe Effect of Mean Stress on Damage Predictions for Spectral Loading of Fiberglass Composite Coupons 1
EWEA, Specal Topc Conference 24: The Scence of Makng Torque from the Wnd, Delft, Aprl 9-2, 24, pp. 546-555. The Effect of Mean Stress on Damage Predctons for Spectral Loadng of Fberglass Composte Coupons
More informationMooring Pattern Optimization using Genetic Algorithms
6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May - 03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz
More informationTrade Adjustment and Productivity in Large Crises. Online Appendix May 2013. Appendix A: Derivation of Equations for Productivity
Trade Adjustment Productvty n Large Crses Gta Gopnath Department of Economcs Harvard Unversty NBER Brent Neman Booth School of Busness Unversty of Chcago NBER Onlne Appendx May 2013 Appendx A: Dervaton
More informationA GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES
82 Internatonal Journal of Electronc Busness Management, Vol. 0, No. 3, pp. 82-93 (202) A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES Feng-Cheng Yang * and We-Tng Wu
More informationCausal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting
Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of
More informationCan Auto Liability Insurance Purchases Signal Risk Attitude?
Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang
More informationRobust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School
Robust Desgn of Publc Storage Warehouses Yemng (Yale) Gong EMLYON Busness School Rene de Koster Rotterdam school of management, Erasmus Unversty Abstract We apply robust optmzaton and revenue management
More informationUTILIZING MATPOWER IN OPTIMAL POWER FLOW
UTILIZING MATPOWER IN OPTIMAL POWER FLOW Tarje Krstansen Department of Electrcal Power Engneerng Norwegan Unversty of Scence and Technology Trondhem, Norway Tarje.Krstansen@elkraft.ntnu.no Abstract Ths
More informationRecurrence. 1 Definitions and main statements
Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.
More informationSolution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt.
Chapter 9 Revew problems 9.1 Interest rate measurement Example 9.1. Fund A accumulates at a smple nterest rate of 10%. Fund B accumulates at a smple dscount rate of 5%. Fnd the pont n tme at whch the forces
More informationForecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network
700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School
More informationSoftware project management with GAs
Informaton Scences 177 (27) 238 241 www.elsever.com/locate/ns Software project management wth GAs Enrque Alba *, J. Francsco Chcano Unversty of Málaga, Grupo GISUM, Departamento de Lenguajes y Cencas de
More informationHow Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence
1 st Internatonal Symposum on Imprecse Probabltes and Ther Applcatons, Ghent, Belgum, 29 June 2 July 1999 How Sets of Coherent Probabltes May Serve as Models for Degrees of Incoherence Mar J. Schervsh
More informationLogical Development Of Vogel s Approximation Method (LD-VAM): An Approach To Find Basic Feasible Solution Of Transportation Problem
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME, ISSUE, FEBRUARY ISSN 77-866 Logcal Development Of Vogel s Approxmaton Method (LD- An Approach To Fnd Basc Feasble Soluton Of Transportaton
More informationL10: Linear discriminants analysis
L0: Lnear dscrmnants analyss Lnear dscrmnant analyss, two classes Lnear dscrmnant analyss, C classes LDA vs. PCA Lmtatons of LDA Varants of LDA Other dmensonalty reducton methods CSCE 666 Pattern Analyss
More informationResearch Article A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service
Hndaw Publshng Corporaton Dscrete Dynamcs n Nature and Socety Volume 01, Artcle ID 48978, 18 pages do:10.1155/01/48978 Research Artcle A Tme Schedulng Model of Logstcs Servce Supply Chan wth Mass Customzed
More informationForm-finding of grid shells with continuous elastic rods
Page of 0 Form-fndng of grd shells wth contnuous elastc rods Jan-Mn L PhD student Insttute of Buldng Structures and Structural Desgn (tke), Unversty Stuttgart Stuttgar, Germany quantumamn@gmal.com Jan
More informationPrice Competition in an Oligopoly Market with Multiple IaaS Cloud Providers
Prce Competton n an Olgopoly Market wth Multple IaaS Cloud Provders Yuan Feng, Baochun L, Bo L Department of Computng, Hong Kong Polytechnc Unversty Department of Electrcal and Computer Engneerng, Unversty
More informationConferencing protocols and Petri net analysis
Conferencng protocols and Petr net analyss E. ANTONIDAKIS Department of Electroncs, Technologcal Educatonal Insttute of Crete, GREECE ena@chana.tecrete.gr Abstract: Durng a computer conference, users desre
More informationApplication of Multi-Agents for Fault Detection and Reconfiguration of Power Distribution Systems
1 Applcaton of Mult-Agents for Fault Detecton and Reconfguraton of Power Dstrbuton Systems K. Nareshkumar, Member, IEEE, M. A. Choudhry, Senor Member, IEEE, J. La, A. Felach, Senor Member, IEEE Abstract--The
More informationSection 5.3 Annuities, Future Value, and Sinking Funds
Secton 5.3 Annutes, Future Value, and Snkng Funds Ordnary Annutes A sequence of equal payments made at equal perods of tme s called an annuty. The tme between payments s the payment perod, and the tme
More informationForecasting Spot Electricity Market Prices Using Time Series Models
C:\Documents and Settngs\Ethopa\Desktop\Forecastng Spot Electrcty Market Prces Usng Tme Seres Models.doc Forecastng Spot Electrcty Market Prces Usng Tme Seres Models by Dawt Halu Mazenga A thess Presented
More informationHow To Solve An Onlne Control Polcy On A Vrtualzed Data Center
Dynamc Resource Allocaton and Power Management n Vrtualzed Data Centers Rahul Urgaonkar, Ulas C. Kozat, Ken Igarash, Mchael J. Neely urgaonka@usc.edu, {kozat, garash}@docomolabs-usa.com, mjneely@usc.edu
More informationProfit-Aware DVFS Enabled Resource Management of IaaS Cloud
IJCSI Internatonal Journal of Computer Scence Issues, Vol. 0, Issue, No, March 03 ISSN (Prnt): 694-084 ISSN (Onlne): 694-0784 www.ijcsi.org 37 Proft-Aware DVFS Enabled Resource Management of IaaS Cloud
More informationHow To Plan A Network Wide Load Balancing Route For A Network Wde Network (Network)
Network-Wde Load Balancng Routng Wth Performance Guarantees Kartk Gopalan Tz-cker Chueh Yow-Jan Ln Florda State Unversty Stony Brook Unversty Telcorda Research kartk@cs.fsu.edu chueh@cs.sunysb.edu yjln@research.telcorda.com
More informationAvailability-Based Path Selection and Network Vulnerability Assessment
Avalablty-Based Path Selecton and Network Vulnerablty Assessment Song Yang, Stojan Trajanovsk and Fernando A. Kupers Delft Unversty of Technology, The Netherlands {S.Yang, S.Trajanovsk, F.A.Kupers}@tudelft.nl
More informationCost Minimization using Renewable Cooling and Thermal Energy Storage in CDNs
Cost Mnmzaton usng Renewable Coolng and Thermal Energy Storage n CDNs Stephen Lee College of Informaton and Computer Scences UMass, Amherst stephenlee@cs.umass.edu Rahul Urgaonkar IBM Research rurgaon@us.bm.com
More informationAN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION
The Medterranean Journal of Computers and Networks, Vol. 2, No. 1, 2006 57 AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION L. Bada 1,*, M. Zorz 2 1 Department of Engneerng,
More informationKiel Institute for World Economics Duesternbrooker Weg 120 24105 Kiel (Germany) Kiel Working Paper No. 1120
Kel Insttute for World Economcs Duesternbrooker Weg 45 Kel (Germany) Kel Workng Paper No. Path Dependences n enture Captal Markets by Andrea Schertler July The responsblty for the contents of the workng
More informationPortfolio Loss Distribution
Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment
More informationCloud-based Social Application Deployment using Local Processing and Global Distribution
Cloud-based Socal Applcaton Deployment usng Local Processng and Global Dstrbuton Zh Wang *, Baochun L, Lfeng Sun *, and Shqang Yang * * Bejng Key Laboratory of Networked Multmeda Department of Computer
More informationSelf-Motivated Relay Selection for a Generalized Power Line Monitoring Network
Self-Motvated Relay Selecton for a Generalzed Power Lne Montorng Network Jose Cordova and Xn Wang 1, Dong-Lang Xe 2, Le Zuo 3 1 Department of Electrcal and Computer Engneerng, State Unversty of New York
More informationExhaustive Regression. An Exploration of Regression-Based Data Mining Techniques Using Super Computation
Exhaustve Regresson An Exploraton of Regresson-Based Data Mnng Technques Usng Super Computaton Antony Daves, Ph.D. Assocate Professor of Economcs Duquesne Unversty Pttsburgh, PA 58 Research Fellow The
More informationAN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE
AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE Yu-L Huang Industral Engneerng Department New Mexco State Unversty Las Cruces, New Mexco 88003, U.S.A. Abstract Patent
More informationCooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing
Cooperatve Load Balancng n IEEE 82.11 Networks wth Cell Breathng Eduard Garca Rafael Vdal Josep Paradells Wreless Networks Group - Techncal Unversty of Catalona (UPC) {eduardg, rvdal, teljpa}@entel.upc.edu;
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationQoS-based Scheduling of Workflow Applications on Service Grids
QoS-based Schedulng of Workflow Applcatons on Servce Grds Ja Yu, Rakumar Buyya and Chen Khong Tham Grd Computng and Dstrbuted System Laboratory Dept. of Computer Scence and Software Engneerng The Unversty
More informationTime Domain simulation of PD Propagation in XLPE Cables Considering Frequency Dependent Parameters
Internatonal Journal of Smart Grd and Clean Energy Tme Doman smulaton of PD Propagaton n XLPE Cables Consderng Frequency Dependent Parameters We Zhang a, Jan He b, Ln Tan b, Xuejun Lv b, Hong-Je L a *
More information8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by
6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng
More information1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)
6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes
More information