9,418 research outputs found
Optimization of Reactive Power Expansion Planning
No full textThis article presents a penalty successive linear programming approach for optimum investment of reactive power in networks. Unlike many successive linear programming algorithms, the proposed approach is based on a successive linear programming framework that admits a convergence proof for non-linearly constrained problems of general form. The penalty successive linear programming approach produces a pattern of new reactive sources that satisfy voltage profile requirements in normal and contingent states of operation, and it also accounts for voltage stability constraints that guard against voltage collapse. Numerical test results are presented and compared with an optimal power flow based planning method that processes the system states sequentially. © Taylor and Francis Group, LLC.[Anonymous], MOSEK OPT TOOLS VERS; BAKER TE, 1985, MANAGE SCI, V31, P264, DOI 10.1287-mnsc.31.3.264; Barros F. G. N., 2009, IEEE POW TECHN C POW, P1; Bhattacharyya B, 2009, ELECTR POW COMPO SYS, V37, P287, DOI 10.1080-15325000802454468; Boyd S.P., 2004, CONVEX OPTIMIZATION, P291; Chang CF, 2007, ELECTR POW SYST RES, V77, P430, DOI 10.1016-j.epsr.2006.04.002; Chattopadhyay D, 2002, INT J ELEC POWER, V24, P185, DOI 10.1016-S0142-0615(01)00025-4; COVA B, 1995, IEEE T POWER SYST, V10, P602, DOI 10.1109-59.387894; Dandachi NH, 1996, IEEE T POWER SYST, V11, P226, DOI 10.1109-59.486099; Donoho DL, 2006, COMMUN PUR APPL MATH, V59, P797, DOI 10.1002-cpa.20132; EL-Dib AA, 2007, ELECTR POW SYST RES, V77, P965, DOI 10.1016-j.epsr.2006.08.023; Estevam CRN, 2010, IET GENER TRANSM DIS, V4, P963, DOI 10.1049-iet-gtd.2009.0422; Fletcher R., 1987, PRACTICAL METHOD OPT, P296; GRANVILLE S, 1994, IEEE T POWER SYST, V9, P1780, DOI 10.1109-59.331432; GRANVILLE S, 1988, IEEE T POWER SYST, V3, P549, DOI 10.1109-59.192906; HAN SP, 1979, MATH PROGRAM, V17, P251, DOI 10.1007-BF01588250; Hsiao YT, 2000, INT J ELEC POWER, V22, P1, DOI 10.1016-S0142-0615(99)00028-9; Jabr RA, 2008, IEEE T POWER SYST, V23, P1000, DOI 10.1109-TPWRS.2008.926439; Keko H., 2007, INT C INT SYST APPL, P1; Lai LL, 1997, IEEE T POWER SYST, V12, P198, DOI 10.1109-59.574940; Liu HF, 2009, IEEE T POWER SYST, V24, P1029, DOI 10.1109-TPWRS.2009.2016059; MALISZEW.RM, 1968, IEEE T POWER AP SYST, VPA87, P1963, DOI 10.1109-TPAS.1968.292155; MERRITT WC, 1988, IEEE T POWER SYST, V3, P970, DOI 10.1109-59.14549; OBADINA OO, 1989, IEEE T POWER SYST, V4, P677, DOI 10.1109-59.193843; Thomas W. R., 1995, IEEE POW IND COMP AP, P79; Thorp J. D., 1993, Annals of Operations Research, V43, DOI 10.1007-BF02024843; Urdaneta AJ, 1999, IEEE T POWER SYST, V14, P1292, DOI 10.1109-59.801887; Vaahedi E, 2001, IEEE T POWER SYST, V16, P38, DOI 10.1109-59.910779; Wang Y, 2010, MODELLING SIMULATION, V1, P1; Yang N, 2007, INT J ELEC POWER, V29, P650, DOI 10.1016-j.ijepes.2006.09.008; ZHANG JH, 1985, MANAGE SCI, V31, P1312, DOI 10.1287-mnsc.31.10.1312; Zhang WJ, 2007, IEEE T POWER SYST, V22, P2177, DOI 10.1109-TPWRS.2007.90745211
Bear Lake development [05]: E.A. Woodhead and R.A. Sutherland
No full textScan of a photo of "Mr. E.A. Woodhead, Supt of Power Plants, Idaho Power Co. Mr. R.A. Sutherland, EBASCO Services. March 6, 1952. Showing the switchboard with 2,100 KV indicated." Location unidentifie
Impact of wind power on the unit commitment, operating reserves and market design
No full textPaper presented at the 2011 IEEE Power and Energy Society General Meeting, San Diego, CA, 24-29 July 2011This article highlights and demonstrates the new requirements variable and partly unpredictable wind power will bring to unit commitment and power system operations.
Current practice is described and contrasted against the new requirements. Literature specifically addressing questions about wind power and unit commitment related power system operations is surveyed. The scope includes forecast errors, operating reserves, intra-day markets, and sharing reserves across interconnections. The discussion covers the critical issues arising from the research.Science Foundation Irelandau, ti, ke, ab, co - TS 10.04.1
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No full textHere is a curious book. Its title-page declares "The Artist's Book of Fables" but its pre-title-page has "Fables, Original and Selected, with a Memoir of the Author." After that title-page, it is identical with "Fables, Original and Selected" as in our copy printed by John Murray in 1833. There is again an AI at the front and an index of engravings and engravers at the back. I found that copy twenty years ago. I had found an inferior copy twenty-two years before that. At that time, I noted Aesopic fables here including "Stone Broth" and "The Mouse and the Oyster."This is a hardbound book (hard cover)James Northcote, R.A
Application of semidefinite programming relaxation and selective pruning to the unit commitment problem
No full textThe objective of this paper is to introduce a semidefinite programming relaxation based technique combined with selective pruning (SDPSP) to achieve faster convergence to a (near)-optimal solution of the unit commitment problem. The compact form of the SDP variable matrix and the concise formulation of the start-up cost constraints contribute to a reduced constraint framework dimension which has profound implications on performance. The computation time is also significantly enhanced by the selective pruning algorithm that prunes all the feasible periods and effectively shrinks the scheduling horizon as the solution is approached. The selective pruning algorithm incorporates two complementary repair mechanisms that exploit the characteristics of the constraint formulation and the properties of SDP relaxation to correct the binary variable violations. The method efficiently handles inter-temporal constraints such as ramp rates that are deemed crucial in practical systems. The prowess of the method is demonstrated by comparing it with other recently proposed techniques. © 2012 Elsevier B.V. All rights reserved.[Anonymous], MOSEK OPT TOOLS VERS; Carrion M, 2006, IEEE T POWER SYST, V21, P1371, DOI 10.1109-TPWRS.2006.876672; COHEN AI, 1983, IEEE T POWER AP SYST, V102, P444, DOI 10.1109-TPAS.1983.317714; Damousis IG, 2004, IEEE T POWER SYST, V19, P1165, DOI 10.1109-TPWRS.2003.821625; Jabr R.A., IEEE T POWER SYSTEMS; Jeong YW, 2010, IEEE T POWER SYST, V25, P1486, DOI 10.1109-TPWRS.2010.2042472; Juste KA, 1999, IEEE T POWER SYST, V14, P1452, DOI 10.1109-59.801925; Kazarlis SA, 1996, IEEE T POWER SYST, V11, P83, DOI 10.1109-59.485989; Lau TW, 2009, IEEE T POWER SYST, V24, P1503, DOI 10.1109-TPWRS.2009.2021220; Li CA, 1997, IEEE T POWER SYST, V12, P113; Madrigal M., 1999, IEEE POWER ENG SOC S, V2, P697; Ongsakul W, 2004, IEEE T POWER SYST, V19, P620, DOI 10.1109-TPWRS.2003.820707; Padhy NP, 2004, IEEE T POWER SYST, V19, P1196, DOI 10.1109-TPWRS.2003.821611; Pappala VS, 2010, IEEE T POWER SYST, V25, P1696, DOI 10.1109-TPWRS.2009.2038921; Park J.-H., 2010, IEEE POWER ENERGY SO, V1-7, P25; PETERSON WL, 1995, IEEE T POWER SYST, V10, P1077, DOI 10.1109-59.387954; Rajan CCA, 2004, IEEE T POWER SYST, V19, P577, DOI 10.1109-TPWRS.2003.821472; Rajan D, 2005, MINIMUM POLYTOPES UN; Senjyu T, 2003, IEEE T POWER SYST, V18, P882, DOI 10.1109-TPWRS.2003.811000; Senjyu T, 2006, ELECTR POW SYST RES, V76, P283, DOI [10.1016-j.epsr.2005.07.002, 10.1016-j.espr.2005.07.002]; Senjyu T, 2006, ELECTR POW COMPO SYS, V34, P619, DOI 10.1080-15325000500419185; Simopoulos DN, 2006, IEEE T POWER SYST, V21, P68, DOI 10.1109-TPWRS.2005.860922; Sturm JF, 1999, OPTIM METHOD SOFTW, V11-2, P625, DOI 10.1080-10556789908805766; Sun LY, 2006, ELECTR POW SYST RES, V76, P716, DOI 10.1016-j.epsr.2005.10.005; Ting TO, 2006, IEEE T POWER SYST, V21, P411, DOI 10.1109-TPWRS.2005.860907; Vandenberghe L, 1996, SIAM REV, V38, P49, DOI 10.1137-1038003; Withironprasert K., 2009, IEEE INT C IND TECHN, V1-6, P10; Yuan XH, 2009, ENERG CONVERS MANAGE, V50, P2449, DOI 10.1016-j.enconman.2009.05.033; Zhai QZ, 2002, IEEE T POWER SYST, V17, P1250, DOI 10.1109-TPWRS.2002.805003; Zhao B, 2006, INT J ELEC POWER, V28, P482, DOI 10.1016-j.ijepes.2006.02.01166
Smoky Mt. Power Plant, Bryson City, Oct. 18, 1937
No full textThis photograph of the Smoky Mountain Power Plant at Ela, North Carolina, near Bryson City, N.C., by R.A. Romanes (1896-1978) was dated October 18, 1937. The dam, which is on the Oconaluftee River near its confluence with the Tuckasegee River, was built in the mid-1920s as a municipal power plant and purchased by the Nantahala Power & Light Company in 1942. The picture highlights the dam's construction with curved retaining walls
Adjustable robust OPF with renewable energy sources
No full textThis paper presents an adjustable robust optimization approach to account for the uncertainty of renewable energy sources (RESs) in optimal power flow (OPF). It proposes an affinely adjustable robust OPF formulation where the base-point generation is calculated to serve the forecast load which is not balanced by RESs, and the generation control through participation factors ensures a feasible solution for all realizations of RES output within a prescribed uncertainty set. The adjustable robust OPF framework is solved using quadratic programming with successive constraint enforcement and can coordinate the computation of both the base-point generation and participation factors. Numerical results on standard test networks reveal a relatively small increase in the expected operational cost as the uncertainty level increases. In addition, solutions of networks that include both uncertain wind generation and Gaussian distributed demand are shown to have less cost and a higher level of robustness as compared to those from a recent robust scheduling method. © 2013 IEEE.ADLER RB, 1977, IEEE T POWER AP SYST, V96, P347, DOI 10.1109-T-PAS.1977.32343; [Anonymous], 2011, REC ISO SOFTW ENH FU; Baringo L, 2011, IEEE T POWER SYST, V26, P1418, DOI 10.1109-TPWRS.2010.2092793; Ben-Tal A, 2004, MATH PROGRAM, V99, P351, DOI 10.1007-s10107-003-0454-y; Bertsimas D, 2013, IEEE T POWER SYST, V28, P52, DOI 10.1109-TPWRS.2012.2205021; Conejo AJ, 2004, IEEE T POWER SYST, V19, P1569, DOI 10.1109-TPWRS.2004.831652; ELHAWARY ME, 1989, INT J ELEC POWER, V11, P85, DOI 10.1016-0142-0615(89)90015-X; Gilneur F., 2000, 0001 FAC POL MONS; Guigues V., 2011, ROBUST PRODUCTION MA; Hodge B., 2011, P IEEE POW EN SOC GE, P1; Hu ZC, 2010, INT J ELEC POWER, V32, P615, DOI 10.1016-j.ijepes.2009.11.018; Jabr RA, 2007, IET GENER TRANSM DIS, V1, P23, DOI 10.1049-iet-gtd:20050039; Jiang RW, 2012, IEEE T POWER SYST, V27, P800, DOI 10.1109-TPWRS.2011.2169817; Li G. J., 2011, P 10 INT C ENV EL EN, P1; Liu X, 2010, IEEE T SMART GRID, V1, P347, DOI 10.1109-TSG.2010.2057458; Madrigal M, 1998, P IEEE CAN C EL COMP, V1, P385; Mansfield E. R., 1996, PRIMUS, V6, P245, DOI 10.1080-10511979608965827; Street A, 2011, IEEE T POWER SYST, V26, P1581, DOI 10.1109-TPWRS.2010.2087367; Taha H. A., 1992, OPERATIONS RES INTRO; Usaola J, 2009, INT J ELEC POWER, V31, P474, DOI 10.1016-j.ijepes.2009.02.003; Walpole R. E., 1993, PROBABILITY STAT ENG; Wang Q., IEEE T POWE IN PRESS; Wang Q, 2013, IEEE T POWER SYST, V28, P1666, DOI 10.1109-TPWRS.2012.2219080; Wang QF, 2012, IEEE T POWER SYST, V27, P206, DOI 10.1109-TPWRS.2011.2159522; Wood A. J., 1996, POWER GENERATION OPE; Yu H, 2012, IEEE T POWER SYST, V27, P1808, DOI 10.1109-TPWRS.2012.2194517; Yuan Y, 2011, IET RENEW POWER GEN, V5, P194, DOI 10.1049-iet-rpg.2009.0107; Zhang H, 2011, IEEE T POWER SYST, V26, P2417, DOI 10.1109-TPWRS.2011.2154367; Zhang H, 2010, IET GENER TRANSM DIS, V4, P553, DOI 10.1049-iet-gtd.2009.0374; Zheng T., 2012, CIGRE; Zimmerman RD, 2011, IEEE T POWER SYST, V26, P12, DOI 10.1109-TPWRS.2010.205116825
Optimization of AC transmission system planning
No full textThis paper presents a mixed-integer optimization approach for transmission system planning with an AC network model. The approach makes use of the conic programming relaxation of the optimal power flow problem to define a disjunctive program that takes into account both the network power flow and the voltage limits. The proposed mixed-integer optimization program has a convex relaxation and can be solved using a branch-and-cut algorithm. Planning results show that the method produces solutions that satisfy the AC network model constraints without further reinforcement and are at less cost as compared to solutions reported in the literature. © 2013 IEEE.[Anonymous], IBM ILOG CPLEX V 12; Bent R, 2012, IEEE T POWER SYST, V27, P904, DOI 10.1109-TPWRS.2011.2169994; Binato S, 2001, IEEE T POWER SYST, V16, P235, DOI 10.1109-59.918292; da Silva EL, 2001, IEEE T POWER SYST, V16, P62, DOI 10.1109-59.910782; da Silva EL, 2000, IEEE T POWER SYST, V15, P1168, DOI 10.1109-59.871750; Fang RS, 2003, IEEE T POWER SYST, V18, P374, DOI 10.1109-TPWRS.2002.807083; Gallego RA, 1998, IEE P-GENER TRANSM D, V145, P329, DOI 10.1049-ip-gtd:19981895; GARVER LL, 1970, IEEE T POWER AP SYST, VPA89, P1688, DOI 10.1109-TPAS.1970.292825; Haffner S, 2000, IEE P-GENER TRANSM D, V147, P149, DOI 10.1049-ip-gtd:20000337; Haffner S, 2001, IEE P-GENER TRANSM D, V148, P482, DOI 10.1049-ip-gtd:20010502; Jabr RA, 2012, IEEE T POWER SYST, V27, P1138, DOI 10.1109-TPWRS.2011.2170772; Lavaei J, 2012, IEEE T POWER SYST, V27, P92, DOI 10.1109-TPWRS.2011.2160974; Rahmani M, 2010, ELECTR POW SYST RES, V80, P1056, DOI 10.1016-j.epsr.2010.01.012; Rider M. J, COMMUNICATION; Rider MJ, 2007, IET GENER TRANSM DIS, V1, P731, DOI 10.1049-iet-gtd:20060465; Romero R, 2005, IEE P-GENER TRANSM D, V152, P277, DOI 10.1049-ip-gtd:20041196; Romero R, 2002, IEE P-GENER TRANSM D, V149, P27, DOI 10.1049-ip-gtd:20020026; Romero R, 2007, IET GENER TRANSM DIS, V1, P318, DOI 10.1049-iet-gtd:20060239; Silva ID, 2005, IEE P-GENER TRANSM D, V152, P828, DOI 10.1049-ip-gtd:20045217; Silva ID, 2006, IEEE T POWER SYST, V21, P1565, DOI 10.1109-TPWRS.2006.881159; Sojoudi S., 2012, P 2012 IEEE POW EN S, P1; TAYLOR J, 2011, TLS TIMES LIT S 0422, P26; Taylor J. A., IEEE T POWE IN PRESS; Verma A, 2010, IET GENER TRANSM DIS, V4, P663, DOI 10.1049-iet-gtd.2009.0611; VILLASANA R, 1985, IEEE T POWER AP SYST, V104, P349, DOI 10.1109-TPAS.1985.319049; Vinasco G, 2011, IEEE T POWER SYST, V26, P2574, DOI 10.1109-TPWRS.2011.2126291; Yu H, 2011, IEEE T POWER SYST, V26, P1573, DOI 10.1109-TPWRS.2010.2082576; Yu H, 2009, IEEE T POWER SYST, V24, P1568, DOI 10.1109-TPWRS.2009.2021202; Zimmerman RD, 2011, IEEE T POWER SYST, V26, P12, DOI 10.1109-TPWRS.2010.205116812
Polyhedral formulations and loop elimination constraints for distribution network expansion planning
No full textDistribution network expansion planning (DNEP) aims at minimizing the capital and operational cost of the expansion plan; the plan entails choosing conductor types and line construction routes together with substation installation and reinforcement that allow serving the demand while satisfying the physical and technical constraints of the expanded network. Two findings are reported in this paper. First, DNEP can be exactly formulated as a disjunctive conic program, in two equivalent formulations; both formulations admit a tight polyhedral approximation and can be solved for the globally optimal solution using software for mixed-integer linear programming (MILP). Second, the DNEP solution can be computed more efficiently when the linear relaxations of the MILP formulations are strengthened using loop elimination constraints. Numerical results on practical DNEP problems reveal that combining the parallel equivalent-circuit polyhedral formulation with the spanning tree loop elimination constraints yields MILP planning solutions with a tight relative optimality gap and within reasonable computing time. In addition, the results are at least of the same quality if not better than those reported in the recent literature. © 2012 IEEE.Achterberg T, 2008, 0829 ZIB; [Anonymous], 2011, REC ISO SOFTW ENH FU; AOKI K, 1990, IEEE T POWER SYST, V5, P126, DOI 10.1109-59.49096; Bose S., 2011, P 49 ANN ALL C, P1342; Brown H. E, IEEE T SMAR IN PRESS; Diaz-Dorado E, 2003, IEEE T POWER SYST, V18, P1594, DOI 10.1109-TPWRS.2003.818741; Gilneur F, 2000, COMPUTATIONAL EXPT L, P0001; Gomez JF, 2004, IEEE T POWER SYST, V19, P996, DOI 10.1109-TPWRS.2004.825867; GONEN T, 1987, IEEE T POWER DELIVER, V2, P512, DOI 10.1109-TPWRD.1987.4308135; Goswami SK, 1997, IEEE T POWER SYST, V12, P718, DOI 10.1109-59.589662; Haffner S, 2008, IEEE T POWER DELIVER, V23, P924, DOI 10.1109-TPWRD.2008.917911; Haffner S, 2008, IEEE T POWER DELIVER, V23, P915, DOI 10.1109-TPWRD.2008.917916; Lavaei J, 2012, IEEE T POWER SYST, V27, P92, DOI 10.1109-TPWRS.2011.2160974; Lavorato M, 2012, IEEE T POWER SYST, V27, P172, DOI 10.1109-TPWRS.2011.2161349; Lavorato M, 2010, IEEE T POWER SYST, V25, P1734, DOI 10.1109-TPWRS.2009.2038164; MARTIN RK, 1991, OPER RES LETT, V10, P119, DOI 10.1016-0167-6377(91)90028-N; Miguez E, 2002, IEEE T POWER SYST, V17, P931, DOI 10.1109-TPWRS.2002.804998; MIRANDA V, 1994, IEEE T POWER SYST, V9, P1927, DOI 10.1109-59.331452; MUNOZ JMR, 1992, IEEE T POWER SYST, V7, P513, DOI 10.1109-59.141753; Nahman JM, 2008, IEEE T POWER SYST, V23, P790, DOI 10.1109-TPWRS.2008.920047; Paiva PC, 2005, IEEE T POWER SYST, V20, P1134, DOI 10.1109-TPWRS.2005.846108; Ramirez-Rosado IJ, 1998, IEEE T POWER SYST, V13, P696, DOI 10.1109-59.667402; Rider M. J, COMMUNICATION; Romero R, 2002, IEE P-GENER TRANSM D, V149, P27, DOI 10.1049-ip-gtd:20020026; Sojoudi S., 2012, P 2012 IEEE POW EN S, P1; Wong R. T, P 1980 IEEE INT C CI, P149; Zimmerman RD, 2011, IEEE T POWER SYST, V26, P12, DOI 10.1109-TPWRS.2010.205116854
Know your weeds provides an easy way of learning how to identify about 100 most common weeds in the United States.
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