In this paper a techno-economic and environmental analysis for a sugar cane bagasse biorefinery in Colombia is presented as a case study. An optimization procedure is shown in order to select the most promising process pathway for the production of fuel ethanol, poly-3-hydroxybutyrate (PHB), and electricity. Once the optimization procedure was done, the results served as criteria for the selection of technologies and raw materials distribution. The distribution results and technologies were used to feed the knowledge-based approach in process synthesis. Then three scenarios were simulated using the Aspen Plus software. The first scenario consisted of energy cogeneration, the second one was an arbitrary distribution, and the third one corresponded to the preselected pathway using the optimization subroutine. Each scenario was assessed from the technoeconomic and environmental point of view according to the Colombian conditions. The best was subjected to the configuration previously designed through the optimization subroutine. For this case, the obtained economic margin was 53.83%, the potential environmental impact was 0.16 PEI/kg products, and the biological GHG emissions of the processing stage represented 1.55 kg of biological CO 2 -e/kg of bagasse.
In this paper a methodology for the estimation of domains of attraction of stable equilibriums based on maximal Lyapunov functions is proposed. The basic idea consists in finding the best level set of a Lyapunov function which is fully contained in the region of negative definiteness of its time derivative. An optimization problem is formulated, which includes a tangency requirement between the level sets and constraints on the sign of the numerator and denominator of the Lyapunov function. Such constraints help in avoiding a large number of potential dummy solutions of the nonlinear optimization model. Moreover, since global optimality is also required for proper estimation, a deterministic global optimization solver of the branch and bound type is adopted. The methodology is applied to several examples to illustrate different aspects of the approach.
a b s t r a c tIn this paper an optimization-based methodology for the design of the operating equilibrium of a nonlinear dynamic system based on a measure of the extension of its domain of attraction is proposed. The approach consists in maximizing the radius of a ball in the state space contained in the region of negative definiteness of the time derivative of a quadratic Lyapunov function, using a two level optimization strategy.A deterministic global optimization problem is solved at the inner level to ensure proper estimation of the domain of attraction for each feasible realization of the design variables which are optimized at the outer level. In order to cope with the non-differentiable nature of the inner problem, a stochastic algorithm is applied to manipulate the design variables at the outer level.The methodology is applied to several examples to illustrate different aspects of the approach.
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