Sara Giarola

Spatially explicit multi-objective optimisation for design and planning of hybrid first and second generation biorefineries

Abstract Climate change mitigation has become a binding driver in biofuels production. First generation bioethanol, initially indicated as the most competitive option, is now incurring in ever increasing discredits forcing the transition towards more sustainable productions (i.e. second and third generation technologies). This paper addresses the strategic design and planning of corn grain- and stover-based bioethanol supply chains through first and second generation technologies. A Mixed Integer Linear Programming framework is proposed to optimise the environmental and financial performances simultaneously. Multi-period, multi-echelon and spatially explicit features are embodied within the formulation to steer decisions and investments through a global approach. A demonstrative case study is proposed involving the future Italian biomass-based ethanol production. Results show the effectiveness of the optimisation tool at providing decision makers with a quantitative analysis assessing the economic and environmental performance of different design configuration and their effect in terms of technologies, plant sizes and location, and raw materials.

A comprehensive approach to the design of ethanol supply chains including carbon trading effects

The optimal design of biofuels production systems is a key component in the analysis of the environmental and economic performance of new sustainable transport systems. In this paper a general mixed integer linear programming modelling framework is developed to assess the design and planning of a multi-period and multi-echelon bioethanol upstream supply chain under market uncertainty. The optimisation design process of biofuels production systems aims at selecting the best biomass and technologies options among several alternatives according to economic and environmental (global warming potential) performance. A key feature in the proposed approach is the acknowledgement of an economic value to the overall GHG emissions, which is implemented through an emissions allowances trading scheme. The future Italian biomass-based ethanol production is adopted as a case study. Results show the effectiveness of the model as a decision making-tool to steer long-term decisions and investments.

Capacity planning and financial optimization of the bioethanol supply chain under price uncertainty

This work addresses the development of a dynamic spatially explicit MILP (Mixed Integer Linear Programming) modeling framework devised to optimize the design and planning of biomass-based fuel supply networks according to financial criteria and accounting for uncertainty on market conditions. The model capabilities in steering strategic decisions are assessed through a real-world case study related to the emerging corn-based bioethanol production system in Northern Italy. Two optimization criteria are considered, based on a risk-seeking or, alternatively, on a risk-adverse-approach.

Optimal design of ethanol supply chains considering carbon trading effects and multiple technologies for side-product exploitation

This work proposes a spatially explicit mixed integer linear programming modelling framework representing the dynamic evolution of a bioethanol supply chain (SC) under increasing biofuel demand and greenhouse gas (GHG) emission savings over time. Key features of the proposed framework comprise: (i) the incorporation of available set-aside rural surfaces for energy crop cultivation; (ii) the acknowledgement of an economic value to the overall GHG emissions through the introduction of an Emission Trading System. Multiple technological options are assessed to exploit the co-product Distillers Dried Grains with Solubles either as animal fodder (standard usage) or as fuel for heat and power generation or as raw material for biogas production (and hence heat and power). Bioethanol production in Northern Italy is chosen as a demonstrative case study.

RETRACTED: Biomass supply chain optimisation for Organosolv-based biorefineries

This work aims at providing a Mixed Integer Linear Programming modelling framework to help define planning strategies for the development of sustainable biorefineries. The up-scaling of an Organosolv biorefinery was addressed via optimisation of the whole system economics. Three real world case studies were addressed to show the high-level flexibility and wide applicability of the tool to model different biomass typologies (i.e. forest fellings, cereal residues and energy crops) and supply strategies. Model outcomes have revealed how supply chain optimisation techniques could help shed light on the development of sustainable biorefineries. Feedstock quality, quantity, temporal and geographical availability are crucial to determine biorefinery location and the cost-efficient way to supply the feedstock to the plant. Storage costs are relevant for biorefineries based on cereal stubble, while wood supply chains present dominant pretreatment operations costs.

A spatially-explicit approach to the design of ethanol supply chains considering multiple technologies and carbon trading effects

Abstract This work proposes a spatially explicit Mixed Integer Linear Programming (MILP) modelling framework representing the dynamic evolution of a bioethanol supply chain (SC) under increasing biofuel demand and GHG emissions savings over the time. Key features of the proposed framework comprise: i) the incorporation of available set-aside rural surfaces for energy crop cultivation; ii) the acknowledgement of an economic value to the overall GHG emissions through the introduction of an Emission Trading System. Multiple technological options are assessed to exploit the co-product DDGS either as animal fodder (standard usage) or as fuel for heat and power generation or as raw material for biogas production (and hence heat and power). Bioethanol production in Northern Italy is chosen as a demonstrative case study.

Lignocellulosic supply chain MILP model: a Hungarian case study

Abstract The optimal design of lignocellulosic-based products (i.e. biofuels and platform chemicals) production systems represent a key components in the development of biobased economies. A crucial part of such complex problems is the use of efficient decision-making tools, enabling a proper evaluation of the potential investment options. The study of the economical sustainability of advanced biorefineries requires a holistic optimisation approach along the entire biorefining supply chain (i.e. biomass cultivation, storage, transportation, processing as well as products storage and delivery) over the long-term in order to simultaneously achieve a full exploitation of lignocellulosic biomass (and its macrocomponents) as well as to identify the optimal logistics and configurations of the biorefining network. In this paper, a maximum profit-based mixed integer linear programming modelling framework is developed to assess the systematic design and planning of a spatially explicit, multi-feedstock, multi-period and multi-echelon lignocellulosic biomass-to-biobased products supply chain. A Hungarian real case study is proposed to demonstrate the feasibility of the model. Results show the effectiveness of the model as a decision-making tool for the biorefinery design, highlighting the major cost drivers.

An approach to optimize multi-enterprise biofuel supply chains including Nash equilibrium models

Abstract An increasing concern in the supply chain management field is the determination of policies aiming at improving the performance of the whole system while preserving an adequate reward for each partaker. The work presented here deals with this critical issue applying the Nash game theory to the development of bioenergy systems. The supply chain planning problem was formulated as a Mixed Integer Linear Programming (MILP) model using a linearized Nash-type objective function. The approach was demonstrated through a case study concerning the bioethanol production in Northern Italy. Result show significant improvements in the mechanisms of transfer price formation towards a fair profit allocation between partakers in bioenergy systems.

Towards second generation bioethanol: Supply chain design and capacity planning.

Abstract This work proposes a multi-period and spatially explicit framework conceived to drive strategic policies on biofuels. A Mixed Integer Linear Programming (MILP) model is proposed as quantitative tool to optimise the oncoming transition towards more sustainable infrastructures. This paper addresses the design of bioethanol supply chains where both corn grain and stover are considered as suitable biomass. A Mixed Integer Linear Program is proposed to optimise the system financial performance and to comply with EU environmental regulation by taking into account a wide number of technological options. Bioethanol production in Northern Italy is chosen as a demonstrative case study.

Production of phthalic anhydride from biorenewables: process design

Abstract Phthalic anhydride is widely used worldwide for an extremely broad range of applications spanning from the plastics industry to the synthesis of resins, agricultural fungicides and amines. Its production is currently based on the vapor phase oxidation of o-xylene and naphthalene. The development of an alternative production route to the petrochemical one is highly desirable to reduce the pressure on fossil use and effects of oil depletion concerns. This work proposes the process modelling of a bio-based route to phthalic anhydride. Results show how the valorization of all the carbohydrate-rich fractions present in the biomass is crucial to obtain an economically viable process.