A. Geraili

A modeling framework for design of nonlinear renewable energy systems through integrated simulation modeling and metaheuristic optimization: Applications to biorefineries

Abstract This study presents the development and implementation of a novel framework for optimal design of new and emerging renewable energy production systems by considering an iterative strategy which integrates the Net Present Value optimization along with detailed mechanistic modeling, simulation, and process optimization which yields optimal capacity plan, and operating conditions for the process. Due to the non-linear nature of process conversion mechanisms, metaheuristic algorithms are implemented in the framework to optimize operating conditions of process. Further, to apply complex kinetics in the process, we have made a linkage between process simulator (Aspen Plus) and Matlab. To demonstrate the effectiveness of the proposed methodology, a hypothetical case study of a lignocellulosic biorefinery is utilized. The proposed framework results reveal a deviation in optimal process yields and production capacities from initial literature estimates. These results indicate the importance of developing a multi-layered framework to optimally design a renewable energy production system.

An active specification switching strategy that aids in solving nonlinear sets and improves a VNS/TA hybrid optimization methodology

Abstract A method to aid in convergence of nonlinear equations by relocating the solver is introduced. Deactivating known variables and activating intelligently chosen unknown variables at predicted values efficiently formulates initial conditions. This repair strategy is integrated into an optimization procedure. The repair algorithm has the ability to (1) relocate the solver for non-converged models caused by poor initial conditions and (2) utilize points formulated in relocating non-converged models caused by infeasible sets of decision variables as a perturbation phase of a stochastic optimization algorithm. To show the effectiveness of the proposed repair strategy, a hybrid metaheuristic of a Variable Neighborhood Search (VNS) and Threshold Accepting (TA) is tested on the optimization of a large-scale industrial process, the primary units of a crude oil refinery. The performance of the hybrid VNS/TA Metaheuristic with repair is compared to the algorithm without the repair technique.

First Steps towards Online Optimal Control of Molecular Weight in Batch and Semi-batch Free-Radical Polymerization Reactors

Abstract This paper discusses the first steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization systems. Off-line capabilities of the framework were fully tested experimentally for model validations, parameter estimation as well as for process optimization using the Automatic Continuous Online Monitoring of Polymerization reactions (ACOMP). A brief analysis on the controllability of the system under feedback conditions was also performed through a combination of simulation and experimental runs. Results are provided for free radical solution polymerization of methyl methacrylate system (MMA).

A Modeling Framework for Optimal Design of Renewable Energy Processes Under Market Uncertainty

Abstract A distributed optimization strategy for development of a reliable framework to address optimal design of renewable energy systems under uncertainty is presented. A structural approach is utilized for production capacity design, simulation of the process in detail, and optimizing the operating condition of the plant. To demonstrate the effectiveness of the proposed approach, a hypothetical multiproduct lignocellulosic biorefinery is considered as a case study. The results prove the efficiency of the proposed approach, and provide a quantitative analysis to determine the optimal design in the face of uncertainty.