A Comprehensive Optimization Framework for Designing Sustainable Renewable Energy Production Systems

As the world has recognized the importance of diversifying its energy resource portfolio away from fossil resources and more towards renewable resources such as biomass, there arises a need for developing strategies which can design renewable sustainable value chains that can be scaled up efficiently and provide tangible net environmental benefits from energy utilization. The objective of this research is to develop and implement a novel decision-making framework for the optimal design of renewable energy systems. The proposed optimization framework is based on a distributed, systematic approach which is composed of different layers including systems-based strategic optimization, detailed mechanistic modeling and operational level optimization. In the strategic optimization the model is represented by equations which describe physical flows of materials across the system nodes and financial flows that result from the system design and material movements. Market uncertainty is also incorporated into the model through stochastic programming. The output of the model includes optimal design of production capacity of the plant for the planning horizon by maximizing the net present value (NPV). The second stage consists of three main steps including simulation of the process in the simulation software, identification of critical sources of uncertainties through global sensitivity analysis, and employing stochastic optimization methodologies to optimize the operating condition of the plant under uncertainty. To exemplify the efficacy of the proposed framework a hypothetical lignocellulosic biorefinery based on sugar conversion platform that converts biomass to value-added biofuels and biobased chemicals is utilized as a case study. Furthermore, alternative technology options and possible process integrations in each section of the plant are analysed by exploiting the advantages of process simulation and the novel hybrid optimization framework. In conjunction with the simulation and optimization studies, the proposed framework develops quantitative metrics to associate economic values with technical barriers. The outcome of this work is a new distributed decision support framework which is intended to help economic development agencies, as well as policy makers in the renewable energy enterprises

Modeling, Simulation and Analysis of Renewable Energy Production Systems: Application to Multi-Product Biorefineries

The primary purpose of this research is to investigate the design and modelling of fully integrated processes which utilize renewable feedstock as raw materials and evaluate the alternative technology and possible process integration options for biorefinery processes to select the optimal configuration based on the production yields and economical profit criteria. The case study considered in this work is a lignocellulosic biorefinery plant which has different technology choices for each section of the process and the ability to produce multi-products from lignocellulosic raw materials. We analyzed different scenarios by simulating the superstructures in Aspen Plus. To incorporate more non-linarites in the process and put more realism in simulations, complex kinetics of bio-reactions are modeled in Matlab based on the experimentally calculated kinetics from literature. To reduce the toxicity of hydrolysates generated from pretreatment, detoxification is necessary as the by-products can have negative impact on downstream process sections such as enzymatic hydrolysis and fermentation. Two technology options are considered for detoxification process in our study. Additionally, two alternative solid separation routes are proposed and evaluated. Sustainable biorefinery requires a portfolio of products to produce different bio-fuels and bio-chemicals. In this work, one of the proposed scenarios considers succinic acid as a co-product of the plant. Final results show the optimal biorefinery process by evaluating the alternative process configurations based on the product yields and economic parameters. Succinic acid production makes a huge increase in the profitability of the plant. Ammonia conditioning is selected as detoxification technology, and separating solids after the first distillation column is the preferable technology