Combining analytical models and Monte-Carlo techniques in probabilistic power system analysis

The authors describe a general framework for combining analytical models and Monte Carlo simulation. The basic idea is to use a simpler analytical model as an approximation to a more detailed model in a Monte Carlo simulation scheme. The simulation then deals with the residual, i.e. the difference b...

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Bibliographic Details
Published inIEEE transactions on power systems Vol. 7; no. 1; pp. 265 - 272
Main Authors Pereira, M.V.F., Maceira, M.E.P., Oliveira, G.C., Pinto, L.M.V.G.
Format Journal Article Conference Proceeding
LanguageEnglish
Published New York, NY IEEE 01.02.1992
Institute of Electrical and Electronics Engineers
Subjects
130000 - Hydro Energy
240100 - Power Systems- (1990-)
Analytical models
Applied sciences
Computational modeling
COST
Costing
Costs
ELECTRIC UTILITIES
Electrical engineering. Electrical power engineering
Electrical power engineering
EVALUATION
Exact sciences and technology
HYDRO ENERGY
HYDROELECTRIC POWER PLANTS
MONTE CARLO METHOD
Monte Carlo methods
OPERATION
Operation. Load control. Reliability
Power networks and lines
POWER PLANTS
Power system analysis computing
Power system modeling
Power system planning
Power system reliability
POWER SYSTEMS
POWER TRANSMISSION AND DISTRIBUTION
PROBABILISTIC ESTIMATION
Production systems
PUBLIC UTILITIES
RELIABILITY
SIMULATION
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Summary:The authors describe a general framework for combining analytical models and Monte Carlo simulation. The basic idea is to use a simpler analytical model as an approximation to a more detailed model in a Monte Carlo simulation scheme. The simulation then deals with the residual, i.e. the difference between the result of the detailed model and the approximation. The component of probabilistic indices which can be explained by the analytical model is factored out of the Monte Carlo sampling scheme, which then handles only the unexplained residuals. The proposed scheme is flexible and easy to implement, as no modification of existing analytical models is required. The approach is illustrated in case studies with utility-derived systems in several application areas: composite reliability evaluation, multi-area production costing, chronological production costing with ramping constraints, and operation of a multireservoir hydroelectric system.< >
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0885-8950
1558-0679
DOI:10.1109/59.141713