Monte Carlo computation of power generation production costs under operating constraints

2001 ◽  
Vol 16 (4) ◽  
pp. 671-677 ◽  
Author(s):  
J. Valenzuela ◽  
M. Mazumdar
Keyword(s):  
Power Generation ◽  
Monte Carlo ◽  
Production Costs ◽  
Monte Carlo Computation ◽  
Operating Constraints

Experimental and Numerical Analyses of a Pressurized Air Receiver for Solar-Driven Gas Turbines

2010 ◽  
Author(s):  
Illias Hischier ◽  
Pascal Leumann ◽  
Aldo Steinfeld
Keyword(s):  
Power Generation ◽  
Monte Carlo ◽  
Steady State ◽  
Gas Turbines ◽  
Porous Ceramic ◽  
Operating Pressure ◽  
Radiative Fluxes ◽  
Monte Carlo Techniques ◽  
Concentrated Solar Radiation ◽  
Solar Receiver

A high-temperature pressurized air-based receiver for power generation via solar-driven gas turbines is experimentally and theoretically examined. It consists of an annular reticulate porous ceramic (RPC) foam concentric with an inner cylindrical cavity-receiver exposed to concentrated solar radiation. Absorbed heat is transferred by combined conduction, radiation, and convection to the pressurized air flowing across the RPC. The governing steady-state mass, momentum and energy conservation equations are formulated and solved numerically by coupled Finite Volume and Monte Carlo techniques. Validation is accomplished with experimental results using a 1 kW solar receiver prototype subjected to average solar radiative fluxes in the range 1870–4360 kW m−2. Experimentation was carried out with air and helium as working fluids, heated from ambient temperature up to 1335 K at an absolute operating pressure of 5 bars.

scholarly journals Technical-Economic Analysis of Grapple Saw

2020 ◽  
Vol 41 (2) ◽  
pp. 219-229 ◽  
Author(s):  
Ricardo Hideaki Miyajima ◽  
Paulo Torres Fenner ◽  
Gislaine Cristina Batistela ◽  
Danilo Simões
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distributions ◽  
Simulation Method ◽  
Forest Harvesting ◽  
Production Costs ◽  
Wood Harvesting ◽  
Food And Agriculture ◽  
The Monte Carlo Method

The processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some associated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic technical-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost.

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