Optimization models for biofuel logistic systems
Abstract
The short overview of the strategies and action plans in production and use of biofuels in Europe and Latvia is given. The characteristic of biofuel supply chain as a system is explained. Existing solutions in improvement of biofuel logistic systems are analysed as well as available tools for the modelling of biofuel supply chains. As the first system for modelling the pure vegetable oil from rapeseed was chosen and first results of modelling are discussed. Introduction Biofuels are transport fuels made from organic material. The most common biofuels today are biodiesel (made from vegetable oils) and bioethanol (made from sugar and starch crops). Research is under way to commercialise "second-generation" production techniques that can make biofuels from woody material, grasses and some additional types of waste. Biofuels have a unique role to play in European energy policy. They are today the only direct substitute for oil in transport that is available on a significant scale. Other technologies, such as hydrogen, have enormous potential. However, they are far away from large-scale viability and will require major changes to the fuel distribution system. Europe is supporting the production and use of biofuels via several strategies and action plans: • In 2003, the EU adopted Directive 2003/30/EC on the promotion of the use of biofuels for transport [1]. This directive urged member states to set indicative targets for a minimum proportion of biofuels to be placed on the market (2 % in 2005 and 5.75 % in 2010); • Directive 2003/96/EC restructuring the Community framework for the taxation of energy products and electricity [2]. As biofuels are currently more expensive than traditional fuels, directive allows Member States to apply a total or partial exemption of taxation for biofuels; • In view of higher oil prices and the urgency of a new debate on security of energy supply, the Commission presented a Biomass Action Plan in December 2005, setting out measures to increase the development of biomass energy from wood, wastes and agricultural crops [3]; • In February 2006, the Commission published a new Communication entitled "An EU Strategy for Biofuels" preparing the ground for a review of the Biofuels Directive by the end of 2006, which might include mandatory targets instead of the indicative ones set in 2003. The aim of the strategy was to further promote biofuels in the EU, to prepare for the large scale use of biofuels, and to explore opportunities to build plants for biofuel production [4]; • In January 2007, the Commission proposed its strategic Energy Policy for Europe. Central to the proposals is a binding target to slash the EU's greenhouse gas (GHG) emissions by 20 % in 2020 compared with 1999 levels, a binding target for 20 % of the EU's energy mix to come from renewables by 2020, and an obligation for each Member State to have 10 % biofuels in their transport fuel mix by 2020 [5].
... У Нідерландах і Великій Британії були проведені дослідження за допомогою моде-лей BIOTRANS і The Chalmers VIEWLS у моде-люванні ланцюга постачання біопалива, а саме відносно постачання біомаси для па-лива та її зберігання [6]. ...
... Модель була використана для генерації найменших витрат ланцюга постачання із сировини для кінцевого використання з метою реалізації спеціального попиту на біопаливо для За-хідної та Центральної і Східної Європи від-повідно до Директиви ЄС щодо біопалива з показником 5,75 % частки використання біо-палива в 2010 р. Враховуючи їх характерис-тики, кожний вид біопалива замінює чи бен-зин, чи дизель, як біокомпонент чи у чистій формі [6]. ...
... Щодо біопалива, для яких BIOTRANS модель використовується, вона фокусується на витратах, виробничих поту-жностях, торгівлі і на викидах. Щодо біое-нергії, для якої була використана Chalmers VIEWLS, увагу було сконцентровано на оп-тимізації витрат загальної енергії (включаю-чи біомасу, відновлювані джерела енергії і паливо традиційні) на засадах політики і припущень щодо викидів парникових газів СО 2 (ліміти і політика) [6]. ...
... Comparisons for these simulation programs have been made by Yakimov et al. [35]. AnyLogic is a simulation software that is widely used in the simulation of manufacturing, road traffic and logistics, also it can be used to simulate the passenger flow or crowd in public places such as stations or airports [36][37][38]. Since AnyLogic can provide a graphical interface for modelling without carrying out field experiments, it is widely applied. ...
The Guangzhou Metro Authority implemented health condition registration and temperature checks to curb the spread of the virus during the COVID-19 pandemic. However, it is important to investigate how these measures may have impacted the get-through efficiency and whether they caused the increased crowding at entrances and the station hall. To address these questions, simulation models based on the T Station were developed using AnyLogic. The model compared the get-through efficiencies with and without the anti-epidemic measures, while also analysing the risk of crowding at entrances and within the station hall after their implementation. Results revealed an increase in the number of passengers unsuccessfully passing through the check-in gate machines from 15% to 53% within 5 minutes, and 10% to 45% within 10 minutes when the anti-epidemic measures were in place. It was also observed that some entrances experienced significant crowding. Three measures were simulated to find effective ways to increase the get-through efficiency and mitigate the crowding – increasing the distance between security and health checks, utilising automatic infrared thermometers, and arranging volunteers or staff to assist with the registration process. The results demonstrated that using automatic infrared thermometers instead of handheld forehead thermometers proved to be effective in improving passenger efficiency and alleviating crowding at entrances and within the station hall.
... However, the linearity of intrinsic constraints in cost-effectiveness models makes it difficult to predict all the effects of cascading events. Therefore, whole linear programs with mixtures of continuous and binary variables are also widely used, although computationally more difficult than pure linear programs [104]. However, polynomial models, with analysis of linear and quadratic effects and bilinear interactions, provide more information, including interaction effects and confidence intervals for polynomial coefficients. ...
The global concerns about climate change have stimulated scientific researches and the establishment of governmental policies in order to slow greenhouse gases emissions, or even to mitigate them. Bioethanol and biodiesel, the most important transportation biofuels, play a central role in this scenario. Global bioethanol production has reached almost 30 billion gallons in 2019, the United States, Brazil, China, and the EU being the main producers, and sugarcane and corn being its main sources. Biodiesel global production is expected to pass 40 billion liters in the next 5 years, and the main producers are the EU, the United States, Brazil, and Indonesia. Both bioethanol and biodiesel strongly depend on governmental policies for their use in blended transportation fuels; in this context, this chapter details the chronology of the most important policies and programs implemented all over the world since the first decades of 20th century, including Brazil, the EU, the United States, and Indonesia among others, the important players in the scenario. The following sections present an overview of the deterministic mathematical tools used to analyze the environmental impacts/benefits of biofuels, with emphasis on life-cycle analysis (LCA). The final section cites a previous work with a deterministic model to estimate bioethanol contribution for greenhouse gas mitigation and presents a model to estimate biodiesel contribution: while bioethanol was responsible for a reduction of around 500 million ton CO2 equivalent (from 2008 to 2018), biodiesel still has a negative overall impact (around 71 million ton CO2 equivalent). However, the contribution of biodiesel tends to be positive when a larger fraction of its production comes from nonedible sources (such as oil wastes), which is the case of EU. These results must be taken into consideration with much care, and the future of biofuels will depend on both research/technological improvements and governmental regulation policies.
... The study of biomass-to-fuel supply models has been broadly approached in the literature. Dukulis et al. (2008) explain the main characteristics of the biofuel supply chain, exploring the available tools in the market. Allen et al. (1996) propose a "supply chain option models" to explore the total delivered costs of biomass fuel associated with different supply systems in order to make cost comparisons between them for one fuel and between different biomass fuel types. ...
... Sharma et al. [17] presented a comprehensive review of mathematical programming models developed for biomass supply chain design as well as the key challenges faced by the bioenergy industry and adapted the classification taxonomies proposed by [18,19] for the classification of bioenergy supply chain models. Following, a brief discussion on these different conceptual models is presented to properly situate the present review. ...
Bioenergy is a new source of energy that accounts for a substantial portion of the renewable energy production in many countries. The production of bioenergy is expected to increase due to its unique advantages, such as no harmful emissions and abundance. Supply-related problems are the main obstacles precluding the increase of use of biomass (which is bulky and has low energy density) to produce bioenergy. To overcome this challenge, large-scale optimization models are needed to be solved to enable decision makers to plan, design, and manage bioenergy supply chains. Therefore, the use of effective optimization approaches is of great importance. The traditional mathematical methods (such as linear, integer, and mixed-integer programming) frequently fail to find optimal solutions for non-convex and/or large-scale models whereas metaheuristics are efficient approaches for finding near-optimal solutions that use less computational resources. This paper presents a comprehensive review by studying and analyzing the application of metaheuristics to solve bioenergy supply chain models as well as the exclusive challenges of the mathematical problems applied in the bioenergy supply chain field. The reviewed metaheuristics include: (1) population approaches, such as ant colony optimization (ACO), the genetic algorithm (GA), particle swarm optimization (PSO), and bee colony algorithm (BCA); and (2) trajectory approaches, such as the tabu search (TS) and simulated annealing (SA). Based on the outcomes of this literature review, the integrated design and planning of bioenergy supply chains problem has been solved primarily by implementing the GA. The production process optimization was addressed primarily by using both the GA and PSO. The supply chain network design problem was treated by utilizing the GA and ACO. The truck and task scheduling problem was solved using the SA and the TS, where the trajectory-based methods proved to outperform the population-based methods.
... While, there are various theoretical approaches and case study applications of the biomass supply chain modeling in the literature [5,[13][14][15][16], few studies have addressed the logistics of sugarcane GHR. Michelazzo and Braunbeck [17] analyzed six collection scenarios of sugarcane GHR in Brazil. ...
Sugarcane-based ethanol in Colombia has a prospective opportunity to explore the production of ethanol from lignocellulosic biomass taking into account that a large amount of generated residues (between 50 and 100 t/ha) are left on the field after green harvesting. The use of sugarcane green harvesting residues for ethanol production could be considered as a feasible solution but it is facing high supply costs. A bottom-up engineering cost model was used to estimate the green harvesting residues supply cost for three collection strategies. The model took into account the investment and operation costs of the residues collection, processing, delivery, and machineries including depreciations, repair and maintenance, and labor cost. Overall energy consumptions and life-cycle GHG emissions of the three strategies were analyzed. The integral harvesting showed the best performance in costs (6.01 USD/dry-t), energy consumptions (125.32 MJ/dry-t), and GHG emissions (7.74 kg CO 2-eq/dry-t), followed by the baled and chopped residues.
... The aim is generally to minimize the total cost of the chain or to maximize the total profit. However, as pointed by Ref. [33], the most common models nowadays are mixed integer linear programs (MILP), which mix continuous variables and integer variables (e.g., number of trucks required). The latter may include binary variables, very useful to model assignment and location decisions. ...
Diatoms are among the opaquest photosynthetic microorganism found in oceans, rivers, and freshwaters. They play a major role in reducing global warming as they fix more than 25% of atmospheric carbon di oxide (CO2). They are a reservoir of untapped potential with the multifaceted application including CO2 mitigation, play a vital role in the aquatic food web as primary producers, and wastewater remediation by quenching pollutants originating from diverse sources such as industries, agricultural, and human sources. Despite their abundance and diversity in nature, only a few species are currently used for biotechnological applications. Diatom biorefinery has gained importance in recent years as more and more algae are identified and explored as a source for lipids, pigments, and other biomolecules. In this chapter, the role of diatom biorefinery has been elaborated extensively displaying the potential of diatoms in carbon dioxide (CO2) mitigation, lipid production for biofuel, nutraceutical potential, and development of new-age drug molecules for therapeutic applications.
Les travaux de cette thèse concernent la modélisation et l'optimisation de chaînes d’approvisionnement en biomasses pour de futures bio-raffineries. En effet, des chaînes d'approvisionnement efficaces sont essentielles pour fournir aux installations de conversion, de façon régulière, des quantités suffisantes de biomasse de qualité à des prix raisonnables. Le problème est tout d'abord décrit puis modélisé.Un modèle de réseau et un modèle de données sont ensuite développés pour permettre de décrire la structure de la chaîne d'approvisionnement et ses données, sans affecter le modèle mathématique sous-jacent. Ce dernier (MILP) combine pour la première fois divers aspects, soit originaux, soit gérés séparément dans la littérature. A partir des demandes de la raffinerie, une résolution exacte précise les activités logistiques dans le réseau et les équipements nécessaires, afin de minimiser le coût total composé des coûts de récoltes, de transport et de stockage. Des études de cas sont décrites pour illustrer ce modèle de planification tactique multi-biomasse et multi-période. Un modèle plus compact est aussi élaboré pour traiter des instances de très grandes tailles. Il est illustré par une étude de cas réelle pour une bio-raffinerie prévue près de Compiègne. Pour finir, les développements effectués pour la mise en place d’un prototype logiciel d’aide à la décision sont présentés et des recommandations d’un futur logiciel commercial sont proposées
Biomass is currently one of the most preferred clean and sustainable energy sources. The fastest-growing biomass energy application today is the production of biofuel, particularly ethanol and biodiesel for transportation. There are some challenges being faced by aspects of biofuel such as production, transportation, storage, and logistics. Principles of lean thinking are universal and have been applied successfully across many disciplines such as construction, healthcare, manufacturing, and service industry. They promise the benefits of waste reduction, higher productivity, better quality, and faster responsiveness. However, there is no published report concerning the introduction of lean thinking principles into biofuel manufacture. This paper proposes the application of fundamental lean thinking principles to the manufacturing of biofuels. In a hypothetical case study, the manufacture of ethanol from cellulosic biomass is studied from a systematic perspective. The manufacturing system is analyzed to identify sources of "muda" (waste) and avenues for improvement. Initial results show that when correctly implemented, lean thinking practices can yield significant productivity benefits which would enable biofuels and biomass energy as a whole to become more commercially successful on a large scale.
Biomass fuel costs depend for a great part on the logistics of biomass fuel collection. The logistics, including pre-treatments, from source locations to energy plant can be modelled by means of a network structure. Nodes correspond to source locations, collection sites, trans-shipment sites, pre-treatment sites or the energy plant and arcs correspond to transport. Two models were developed to gain insight into the costs and energy consumption of the logistics: a simulation model and an optimization model. Both models are described, together with some results of an example, and the differences are discussed. Model choice depends mostly on the objectives of the user.
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Discusses part of a project conducted by the authors into the logistics planning and management and costs of supplying biomass fuels to biomass-fired power stations in the UK. Defines biomass fuels and the reasons for the growth in interest in their use for electricity generation. The activities and parties involved in the biomass fuel supply chain are discussed together with the management of the chain in order to achieve smooth and consistent flow of biomass fuel to power stations. Explains the approach used to modelling the delivered costs of biomass fuels for four types of biomass fuel included in the project: forest fuel, short rotation coppice, straw and miscanthus. Comments are given on the environmental impacts of the fuel supply chains. The results indicate that straw supply systems are capable of producing the lowest delivered costs of the four fuels studied. Short rotation coppice and miscanthus, two new energy crops, are likely to have the highest delivered costs at present. This is due to the cost of growing these fuels and the financial incentives required by farmers to persuade them to grow these crops. Logistics costs (i.e. transport, storage and handling) are shown to represent a significant proportion of total delivered cost in biomass supply. Careful supply chain planning and logistics management will be of central importance to the success of the biomass industry.
The design of complex systems is viewed as a blend of the art of architecture with the science of engineering. The principles of systems are discussed, with examples to illustrate each point. The artistic elements of architecture are then considered, and four methods in common use, depending on the nature and phase of the project, the particular problem to be solved, and the style of the architect, are described. The role of architecting throughout the system development cycle is examined. Architecting and concurrent engineering are compared and seem to be complementary strategies.< >
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