Monte Carlo simulation techniques and electric utility resource decisions

被引:41
|
作者
Spinney, PJ
Watkins, GC
机构
[1] Charles River Associates, Boston, MA 02116
关键词
electric utilities; integrated resource planning; Monte Carlo simulation techniques;
D O I
10.1016/0301-4215(95)00094-1
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper explores the use of Monte Carlo simulation techniques as an approach to electric utility integrated resource planning (IRP) that explicitly identifies key risks imposed on decision makers and/or shareholders, We discuss in general methods of examining risk, including sensitivity analysis, decision analysis and Monte Carlo simulation. We also present an example of how Monte Carlo simulation can be used in the context of resource planning, When used in conjunction with a model that captures the main engineering, economic acid financial operations of a utility, Monte Carlo simulation can be used to account for planning uncertainties and examine tradeoffs between expected costs and risk.
引用
收藏
页码:155 / 163
页数:9
相关论文
共 50 条
  • [11] The Monte-Carlo simulation of nanosecond electric breakdown.
    Starikovskaia, SM
    Starikovskii, AY
    INTERNATIONAL CONFERENCE ON PHENOMENA IN IONIZED GASES, VOL V, PROCEEDINGS, 1999, : 81 - 81
  • [12] Monte carlo techniques
    S. Youssef
    The European Physical Journal C - Particles and Fields, 2000, 15 (1-4): : 202 - 204
  • [13] MONTE CARLO TECHNIQUES
    K.A.Olive
    K.Agashe
    C.Amsler
    M.Antonelli
    J.-F.Arguin
    D.M.Asner
    H.Baer
    H.R.Band
    R.M.Barnett
    T.Basaglia
    C.W.Bauer
    J.J.Beatty
    V.I.Belousov
    J.Beringer
    G.Bernardi
    S.Bethke
    H.Bichsel
    O.Biebe
    E.Blucher
    S.Blusk
    G.Brooijmans
    O.Buchmueller
    V.Burkert
    M.A.Bychkov
    R.N.Cahn
    M.Carena
    A.Ceccucci
    A.Cerr
    D.Chakraborty
    M.-C.Chen
    R.S.Chivukula
    K.Copic
    G.Cowan
    O.Dahl
    G.D’Ambrosio
    T.Damour
    D.de Florian
    A.de Gouvea
    T.DeGrand
    P.de Jong
    G.Dissertor
    B.A.Dobrescu
    M.Doser
    M.Drees
    H.K.Dreiner
    D.A.Edwards
    S.Eidelman
    J.Erler
    V.V.Ezhela
    W.Fetscher
    Chinese Physics C, 2014, (09) : 485 - 487
  • [14] MONTE CARLO TECHNIQUES
    TAYYABKHAN, MT
    RICHARDS.TC
    CHEMICAL ENGINEERING PROGRESS, 1965, 61 (01) : 78 - +
  • [15] Variance Reduction Techniques for Monte Carlo Simulation of Coincidence Circuits
    Tsvetkov, E. A.
    BULLETIN OF THE LEBEDEV PHYSICS INSTITUTE, 2021, 48 (08) : 232 - 235
  • [16] Advanced Monte Carlo Techniques in the Simulation of CMOS Devices and Circuits
    Asenov, Asen
    NUMERICAL METHODS AND APPLICATIONS, 2011, 6046 : 41 - 49
  • [17] A benchmark study on intelligent sampling techniques in Monte Carlo simulation
    dos Santos, K. R. M.
    Beck, A. T.
    LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES, 2015, 12 (04): : 624 - 648
  • [18] ON THE ANALYSIS OF MICROBIOLOGICAL PROCESSES BY MONTE-CARLO SIMULATION TECHNIQUES
    BERMUDEZ, J
    LOPEZ, D
    VALLS, J
    WAGENSBERG, J
    COMPUTER APPLICATIONS IN THE BIOSCIENCES, 1989, 5 (04): : 305 - 312
  • [19] Variance Reduction Techniques for Monte Carlo Simulation of Coincidence Circuits
    E. A. Tsvetkov
    Bulletin of the Lebedev Physics Institute, 2021, 48 : 232 - 235
  • [20] Improved sampling techniques for the direct simulation Monte Carlo method
    Sun, Quanhua
    Fan, Jing
    Boyd, Iain D.
    COMPUTERS & FLUIDS, 2009, 38 (02) : 475 - 479