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A model for the location and scheduling of the operation of second-generation ethanol biorefineries
by
Francisco Venegas Martínez
, Cisneros-López, Miguel A
, Pérez-Lechuga, Gilberto
, Aguilar-Velázquez, Silvia L
in
Economic models
/ Energy management
/ Ethanol
/ Gasoline
/ Integer programming
/ Linear programming
/ Mathematical models
/ Mixed integer
/ Operation scheduling
/ Optimization
/ Refining
/ Stochastic processes
/ Sugarcane
2019
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A model for the location and scheduling of the operation of second-generation ethanol biorefineries
by
Francisco Venegas Martínez
, Cisneros-López, Miguel A
, Pérez-Lechuga, Gilberto
, Aguilar-Velázquez, Silvia L
in
Economic models
/ Energy management
/ Ethanol
/ Gasoline
/ Integer programming
/ Linear programming
/ Mathematical models
/ Mixed integer
/ Operation scheduling
/ Optimization
/ Refining
/ Stochastic processes
/ Sugarcane
2019
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Do you wish to request the book?
A model for the location and scheduling of the operation of second-generation ethanol biorefineries
by
Francisco Venegas Martínez
, Cisneros-López, Miguel A
, Pérez-Lechuga, Gilberto
, Aguilar-Velázquez, Silvia L
in
Economic models
/ Energy management
/ Ethanol
/ Gasoline
/ Integer programming
/ Linear programming
/ Mathematical models
/ Mixed integer
/ Operation scheduling
/ Optimization
/ Refining
/ Stochastic processes
/ Sugarcane
2019
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A model for the location and scheduling of the operation of second-generation ethanol biorefineries
Journal Article
A model for the location and scheduling of the operation of second-generation ethanol biorefineries
2019
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Overview
This document presents an economic optimization model which identifies the location, the nominal plant capacity and the operation scheduling for set of biorefineries of second-generation ethanol using the biomass obtained as waste in the sugarcane industry. The model also determines the gasoline volumes that will be mixed with ethanol in order to produce a mixed fuel. Given a planning horizon of the operation of the system, the model obtains its optimal parameters at fixed time intervals (annual) so the global optimum is obtained by minimizing the mathematical expectation of the stochastic process generated when the product demand is assumed random with known density. Partial optimization of the process is achieved using a mixed integer linear programming model. Real information obtained from the Secretariat of Energy for the management of biorefineries in the state of Veracruz of the Mexican Republic is included and numerical results are reported.
Publisher
Springer Nature B.V
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