Monte Carlo Simulation

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G Campbell Watkins - One of the best experts on this subject based on the ideXlab platform.

  • Monte Carlo Simulation techniques and electric utility resource decisions
    Energy Policy, 1996
    Co-Authors: Peter J. Spinney, G Campbell Watkins
    Abstract:

    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 and financial operations of a utility, Monte Carlo Simulation can be used to account for planning uncertainties and examine tradeoffs between expected costs and risk.

E Pyrgioti - One of the best experts on this subject based on the ideXlab platform.

  • optimal placement of wind turbines in a wind park using Monte Carlo Simulation
    Renewable Energy, 2008
    Co-Authors: Grigorios E Marmidis, Stavros Lazarou, E Pyrgioti
    Abstract:

    Abstract In the present study, a novel procedure is introduced for the optimal placement and arrangement of wind turbines in a wind park. In this approach a statistical and mathematical method is used, which is called ‘Monte Carlo Simulation method’. The optimization is made by the mean of maximum energy production and minimum cost installation criteria. As a test case, a square site is subdivided into 100 square cells that can be possible turbine locations and as a result, the program presents us the optimal arrangement of the wind turbines in the wind park, based on the Monte Carlo Simulation method. The results of this study are compared to the results of previous studies that handle the same issue.

Witold Pedrycz - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy Monte Carlo Simulation and risk assessment in construction
    Computer-aided Civil and Infrastructure Engineering, 2010
    Co-Authors: Naimeh Sadeghi, Aminah Robinson Fayek, Witold Pedrycz
    Abstract:

    Monte Carlo Simulation has been used extensively for addressing probabilistic uncertainty in range estimating for construction projects. However, subjective and linguistically expressed information results in added non-probabilistic uncertainty in construction management. Fuzzy logic has been used successfully for representing such uncertainties in construction projects. In practice, an approach that can handle both random and fuzzy uncertainties in a risk assessment model is necessary. This article discusses the deficiencies of the available methods and proposes a Fuzzy Monte Carlo Simulation (FMCS) framework for risk analysis of construction projects. In this framework, a fuzzy cumulative distribution function constructed as a novel way to represent uncertainty. To verify the feasibility of the FMCS framework and demonstrate its main features, the authors have developed a special purpose Simulation template for cost range estimating. This template is employed to estimate the cost of a highway overpass project.

Peter J. Spinney - One of the best experts on this subject based on the ideXlab platform.

  • Monte Carlo Simulation techniques and electric utility resource decisions
    Energy Policy, 1996
    Co-Authors: Peter J. Spinney, G Campbell Watkins
    Abstract:

    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 and financial operations of a utility, Monte Carlo Simulation can be used to account for planning uncertainties and examine tradeoffs between expected costs and risk.

Grigorios E Marmidis - One of the best experts on this subject based on the ideXlab platform.

  • optimal placement of wind turbines in a wind park using Monte Carlo Simulation
    Renewable Energy, 2008
    Co-Authors: Grigorios E Marmidis, Stavros Lazarou, E Pyrgioti
    Abstract:

    Abstract In the present study, a novel procedure is introduced for the optimal placement and arrangement of wind turbines in a wind park. In this approach a statistical and mathematical method is used, which is called ‘Monte Carlo Simulation method’. The optimization is made by the mean of maximum energy production and minimum cost installation criteria. As a test case, a square site is subdivided into 100 square cells that can be possible turbine locations and as a result, the program presents us the optimal arrangement of the wind turbines in the wind park, based on the Monte Carlo Simulation method. The results of this study are compared to the results of previous studies that handle the same issue.