Biodiesel Supply Research Articles

Robust optimization on sustainable biodiesel supply chain produced from waste cooking oil under price uncertainty

Waste cooking oil (WCO)-for-biodiesel conversion is regarded as the “waste-to-wealthy” industry. This paper addresses the design of a WCO-for-biodiesel supply chain at both strategic and tactical levels. The supply chain of this problem is studied, which is based on a typical mode of the waste collection (from restaurants’ kitchen) and conversion in the cities. The supply chain comprises three stakeholders: WCO supplier, integrated bio-refinery and demand zone. Three key problems should be addressed for the optimal design of the supply chain: (1) the number, sizes and locations of bio-refinery; (2) the sites and amount of WCO collected; (3) the transportation plans of WCO and biodiesel. A robust mixed integer linear model with muti-objective (economic, environmental and social objectives) is proposed for these problems. Finally, a large-scale practical case study is adopted based on Suzhou, a city in the east of China, to verify the proposed models.

A conceptual framework for the analysis of the effect of institutions on biofuel supply chains

The economic performance of biofuels supply chains depends on the interaction of technical characteristics as technological pathways and logistics, and social structures as actor behavior, their interactions and institutions. Traditional approaches focus on the technical problems only. Little attention has been paid to the institutional analysis of biofuel supply chains. This paper aims to extend the analysis of the effect of institutions on the emergence of biofuel supply chains by developing a conceptual framework that combines elements of complex adaptive systems, (neo) institutional economics and socio-technical systems theory. These elements were formalized into an agent-based model. The proposed method is illustrated by a case study on a biodiesel supply chain in Germany. It was found that the patterns in production capacity result from investors basing their decisions on optimistic perceptions of the market development that increase with a favorable institutional framework. Conversely, patterns in biodiesel production cannot be completely explained by this mechanism. The proposed framework assisted the model conceptualization phase and allowed the incorporation of social structures into the agent-based model. This approach could be developed further to provide insights on the effect of different future deployment strategies on bioenergy systems emergence and development.

A three-stage stochastic optimization model for the Brazilian biodiesel supply chain

The Brazilian program for biodiesel use highlights the production of biodiesel from castor seeds. Biodiesel is a non-polluting energy source that has the potential to promote prosperity by creating jobs in poor regions of Brazil. However, the infrastructure, logistics, and proper facilities are lacking. A variety of approaches to optimizing the biodiesel supply chain have been proposed. The goal is to minimize the grain storage and transportation costs. This paper presents a comparison between a two-stage model and a multistage (three-stage) stochastic model to optimize the biodiesel supply chain. The comparison between these formulations shows that the flexibility gain provided by the multistage model results in a lower total logistic cost. The optimum for the three-stage model was 7,700,019 (BRL), compared to 8,628,002 (BRL) for the two-stage model, representing a savings of 927,983 (BRL). We highlight that this model offers a real solution for castor supply chain design (considering uncertainty) in the Brazilian semiarid region, which is a poorer region of the country, thus making cost reduction mandatory.

Robust design and planning of microalgae biomass-to-biodiesel supply chain: A case study in Iran

Microalgae have emerged as one of the most promising sources for biodiesel production because they yield a substantial amount of oil. In order to accelerate the commercialization of microalgal biodiesel, this paper proposes a two-stage model for the design and planning of a microalgae-based biodiesel supply chain. The macro-stage performs a spatial filtering using GIS and AHP to identify the most suitable candidate locations to establish biodiesel production facilities. These potential locations are later applied in the supply chain design model of the micro-stage. Consequently, the macro-stage obviates the need to consider a large set of candidate locations which is the main reason for the computational complexity of the supply chain optimization problems. In the micro-stage, a robust mixed-integer linear programming (RMILP) optimization model, which provides a trade-off between system cost and reliability, is elaborated to determine the strategic and tactical supply chain decisions that remain optimal for almost all possible realizations of the uncertain parameters. The applicability of the proposed framework is demonstrated through a case study considering different uncertainty settings. The results show that the proposed model outperforms the traditional supply chain design models in terms of solution robustness and computational time.

Optimal design of supply chains for second generation biofuels incorporating European biofuel regulations

Expected changes in European biofuel regulations lead to uncertainty in supply chain planning for second generation biofuel industries. Previous studies used optimization to design biofuels' supply chains and a few of them analyzed the impact of selected biofuel policy instruments on sustainability targets. This study presents a mixed integer programming model for the optimal design of second generation biofuel supply chains considering all policy instruments of European biofuel regulations. The model maximizes the net present value of second generation biofuel supply chains considering time-dependent quotas for biofuel market shares and greenhouse gas emission savings. The model includes multiple counting of second generation biofuel towards meeting biofuel market share targets and captures all greenhouse gas emissions of the second generation biofuel supply chain including land use change emissions. We demonstrated the use of the model through the case study of second generation biodiesel in a German region, and evaluated the sensitivity of the optimal solution to model parameters and policy instruments' levels. A set of remarks were made regarding the impact of policy instruments on the performance of second generation biodiesel supply chain under study. Future work entails the application of the analysis to the aggregate level in the European Union.

Risks, determinants, and perspective for creating a railway biodiesel supply chain: case study of India

Globally, the demand for energy is increasing, and the transportation sector is a major consumer of energy. There has been a momentum and a mandate to promote the use of biofuels. Although biofuel usage has been analysed extensively from the technological viewpoint, very few researchers have studied biofuel implementation and the supply chain. Biodiesel is being considered as an alternative fuel for railway transportation, which poses some challenges given the structural constraints of the industry. As has been argued, for the successful implementation and adoption of biodiesel in the railway sector, a tailor-made country-specific supply chain should be designed. The paper discusses how geographically diverse demand and common technological usage points complicate the decision to make or buy in the context of railway transportation. Furthermore, the biodiesel and diesel supply chains are compared, risks of a biodiesel supply chain are identified, and implementable strategies are suggested. Indian Railways is a bulk consumer of fuel, and as a public sector focal firm, it should take the lead in sustainable transportation solutions in view of energy security requirements. This study is unique because it deals with a biodiesel supply chain in a public sector transport organization in an emerging economy.

Penentuan Prioritas Risiko pada Rancangan Rantai Pasok Biodiesel dari Minyak Goreng Bekas di Kota Padang

<p><em>A design of biodiesel supply chain from </em><em>waste</em><em> cooking oil conducted in previous studies. Implementation of supply chain design needs to be studied more in</em><em> </em><em>depth and comprehensive. One aspect of the study is a supply chain risk management. Supply chain risk </em><em>management</em><em> is important because many events in supply chain which raises operational problems and the cessation of business activity. Because of vulnerability of the supply chain to various internal and external risks, the study of risk sources is needed. This study examines the sources of risk and the weighting that may occur along the supply chain for the distribution of biodiesel </em><em>from waste</em><em> cooking oil from suppliers</em><em> that</em><em> located in various places until the sale of biodiesel to consumers that are targeted to the public</em><em> in</em><em> Padang.</em><em> The method used in this research is fuzzy AHP with triangular fuzzy number approach. Risk identification is done with the study of literature and assessment by experts. Based on the results obtained sequences risks from largest to smallest weight are raw materials, market, quality, production, transportation, and partnerships.</em></p>

Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach

Development of biofuels causes reduction of environmental pollution, but certain limitations affect their production. In this research, a hybrid system dynamics-mathematical programming approach is developed to design and plan a biodiesel supply chain from biomass fields to consumption markets. The supply chain faces limitations in biodiesel production. Water resource limitations for biodiesel production, land limitations for biomass procurement, and technological issues are the most important limitations considered in the system dynamics model. In addition, competition between fossil fuels and biodiesel is taken into account. The proposed methodology, firstly, estimates the most important parameters in biodiesel supply chain in a given planning horizon. Then, estimated parameters are used as inputs of the mathematical model and the optimal supply chain decisions are made by means of a stochastic mixed-integer programming model. Besides, a scenario-based approach is used to model the disruption risks for links and biomass fields. Finally, a numerical experiment is presented to show the applicability of the methodology according to some interviews with experts in Iran. Results demonstrate the potential appropriate market of biodiesel in Iran while several resource and technology limitations and environmental pollution avoid growth of biodiesel market. Moreover, a sensitivity analysis is performed on risk preferences of decision makers and government policies adopted to improve the biodiesel market.

A sustainable second-generation biodiesel supply chain network design problem under risk

This paper presents a multi-objective possibilistic programming model to design a second-generation biodiesel supply chain network under risk. The proposed model minimizes the total costs of biodiesel supply chain from feedstock supply centers to customer centers besides minimizing the environmental impact (EI) of all involved processes under a well-to-wheel perspective. Non-edible feedstocks are considered for biodiesel production. Variable cultivation cost of non-edible feedstock is assumed to be non-linear and dependent upon the amount of cultivated area. New formulation of possibilistic programming method is developed which is able to minimize the total mean and risk values of problems with possibilistic-based uncertainty. To solve the proposed multi-objective model, a hybrid solution approach based on flexible lexicographic and augmented ɛ-constraint methods is proposed which is capable to find appropriate efficient solutions from the Pareto-optimal set. The performance of the proposed possibilistic programming method as well as the developed solution approach are evaluated and validated through conducting a real case study in Iran. The outcome of this study demonstrates that high investment cost is required for improving the environmental impact and risk of sustainable biodiesel supply chain network design under risk. Decision maker preferences are required for suitable trade-off among total costs, risk values and environmental impact.

Supply chain network of Jatropha based biodiesel industry in North East India

India’s biofuel policy is mostly confined to Jatropha based biodiesel, as the demand for diesel in India is five times more than the demand for petrol. The policy seeks to increase the demand for biodiesel to 16.72 million tons by 2017 and encourages 20% blending of biodiesel with other fuels. This is a major challenge as Jatropha is a new perennial crop for the farmers, who see considerable risk and uncertainty in its production, profitability and employment generation. The present study tries to investigate the supply chain network and related problems of the biodiesel industry in North East India. The Jatropha based biodiesel supply chain includes stages like feedstock production, feedstock logistics (collection, storage, and transportation), biodiesel production, biodiesel distribution, and biodiesel end-use. The major challenge in feedstock production stage is to achieve a seed production level sufficient for ensuring a stable supply of biodiesel. Poor seed processing infrastructure is another bottleneck in the Jatropha value chain in NE India. Establishing market for Jatropha by-products is also crucial for sustainability of the industry. Collective efforts from public and private sectors are needed along with increase in the market price of biodiesel, which will motivate the farmers and infuse confidence to continue with Jatropha.

Robust Optimization on Regional WCO-for-Biodiesel Supply Chain under Supply and Demand Uncertainties

This paper aims to design a robust waste cooking oil- (WCO-) for-biodiesel supply chain under WCO supply and price as well as biodiesel demand and price uncertainties, so as to improve biorefineries’ ability to cope with the poor environment. A regional supply chain is firstly introduced based on the biggest WCO-for-biodiesel company in Changzhou, Jiangsu province, and it comprises three components: WCO supplier, biorefinery, and demand zone. And then a robust mixed integer linear model with multiple objectives (economic, environmental, and social objectives) is proposed for both biorefinery location and transportation plans. After that, a heuristic algorithm based on genetic algorithm is proposed to solve this model. Finally, the 27 cities in Yangtze River delta are adopted to verify the proposed models and methods, and the sustainability and robustness of biodiesel supply are discussed.

Supply Chain Optimization of Biodiesel Produced from Waste Cooking Oil

Producing biodiesel using waste cooking oil is a substantial instrument for solving the intense problems caused by energy crisis and environment pollutions. This paper focuses on the design of the biodiesel supply chain using waste cooking oil as feedstock in China and establishes a mixed integer linear programming model for both economic and environmental optimization. The model considers a three level network including waster cooking oil production points, distribution centers and factories. And four aspects of decisions are made: (1) the number of distribution centers and factories to locate; (2) the locations of the distribution centers and factories; (3) the allocations of the waste cooking oil among supply chain members; (4) the decisions of factories’ technology choice. Finally, the model is applied to a real network in Nanjing and the genetic algorithm is developed to solve this problem.

An integrated data envelopment analysis–mathematical programming approach to strategic biodiesel supply chain network design problem

Global warming, environmental issues, food crisis and energy security are the main concerning problems which have triggered a sense of urgency among policymakers and development practitioners to find sustainable and viable solutions in the area of bioenergy. Among various edible and non-edible bioenergy feedstocks specified for biodiesel production, Jatropha curcas L. (JCL) and waste cooking oil (WCO) have been introduced to be promising and sustainable. In this study, an integrated hybrid approach based on a data envelopment analysis (DEA) and mathematical programming techniques is presented for the strategic design of biodiesel supply chain network in Iran. In the first phase, JCL cultivation areas are assessed according to climatic and social criteria by a unified DEA (UDEA) model. In the second phase, the locations which have achieved desired efficiency scores are considered as candidate locations for JCL cultivation within a mathematical programming model developed for designing the biodiesel supply chain network. The proposed mathematical programming model optimizes the numbers, locations and capacities of JCL cultivation centers, JCL seeds and WCO collection centers, bio-refineries, and distribution centers. The proposed approach is implemented in Iran for 10 years planning horizon. The results show the usefulness and efficiency of the proposed method in assisting the policymakers to take suitable strategic and tactical level decisions related to biodiesel supply chain planning.

Introducing measurement science into sustainability systems

In this paper, we discuss perspectives of adopting procedures of metrology, the science of measurements, into sustainability assessments. We present an overview of general concepts of system theory, sustainability, and sustainability metrics. We use these concepts together with the Guide to the Expression of Uncertainty in Measurement (GUM) metrological approach to include estimation of uncertainties and sensitivity analysis in the model framework to construct aggregated sustainability indicators proposed by Santos and Brandi. To illustrate the method, we apply Canberra distance to study the sustainability of the integration and logistic infrastructure dimension of the biodiesel supply chain in Brazil and Germany. Sustainability has been embodied into government, industries and corporations’ policies through standards, conformity assessment, and metrology. This increases the need for sound measurements to address sustainability. To perform sensitivity analysis, we propose an expression to evaluate changes in the sustainability index due to variations in a given indicator, generalizing the linear approximation of the GUM framework. We concluded that metrological procedures can be applied to estimate uncertainties of sustainability systems and their components. Adopting metrological procedures may be an important step to harmonize approaches involving measurements in sustainability systems. Sensitivity analysis provides information about the influence on the sustainability index due to variations of indicators from sustainability systems.

Concurrent production of biodiesel and chemicals through wet in situ transesterification of microalgae

This work addresses an unprecedented way of co-producing biodiesel (FAEE) and valuable chemicals of ethyl levulinate (EL), ethyl formate (EF) and diethyl ether (DEE) from wet in situ transesterification of microalgae. EL, EF, and DEE were significantly produced up to 23.1%, 10.3%, and 52.1% of the maximum FAEE mass with the FAEE yield higher than 90% at 125°C. Experiments to elucidate a detailed route of EL and EF synthesis were fulfilled and it was found that its main route to the production of EL and EF was the acid hydrolysis of algal cells and esterification with ethanol. To investigate the effect of reaction variables on the products yields, comprehensive experiments were carried out with varying temperatures, solvent and alcohol volumes, moisture contents and catalyst amounts. Coproduction of DEE, EL, EF and FAEE can contribute to elevating the economic feasibility of microalgae-based biodiesel supply chain.

Factor Influencing Crude Palm Oil (CPO) Biodiesel Supply in Indonesia Using Error Correction Model (ECM)

Indonesia is in a good position to develop biodiesel industry for alternative energy supply. The government issued legislations to accelerate the development of biodiesel industry. However, the growth was relatively slow and unstable, especially during the initiating stage of the new policy. The purpose of this study was to know the factors affecting supply of biodiesel in Indonesia, using Error Correction Model (ECM) to determine the long term and short term relationship. Monthly data from January 2010 to December 2013 was used for the estimation. The results showed that in the short term, the price of biodiesel and production capacity has a significant influence on the supply of biodiesel in Indonesia. In the long term, production capacity, price of CPO, and supply of biodiesel in previous year has a significant influence on the supply of biodiesel in Indonesia. The coefficient of Error Correction Term (ECT), which showed how quickly equilibrium is reached again into the long term equilibrium, was estimated -0.0310 indicated that disequilibrium in the previous period corrected in the current period amounted to 3.10 percent. Biodiesel supply elasticity in short term tend to elastic because quantity of supply in the short term is not too sensitive to price changes. Biodiesel supply elasticity in short term tend to inelastic, which if there is a change in these variables will not cause great shock on the level of biodiesel supply in Indonesia.

Environmental implications of crude glycerin used in special products for the metalworking industry and in biodegradable mulching films

Crude glycerin from biodiesel supply chain can replace synthetic glycerol or other chemicals in industrial applications. To improve sustainability according to the biorefinery perspective, a purification phase will be carried out only if it is really necessary to reach standards for industrial processes or final products. In metal working, the use of crude glycerin-based hydraulic fluids, replacing mineral oil-based and glycol-based ones, has fulfilled industrial requirements and made it possible to increase (i) worker safety because of its non-flammability; (ii) biodegradability and (iii) time-life of the product due to anti-wear properties; in addition, post-use waste management will be simplified, due to the possibility to declassify fluids as special waste. In biodegradable mulching films, the replacement of synthetic glycerol was successful because it made it possible both to maintain the same compounding conditions and to obtain the same yields and film biodegradation in an agronomic trial on muskmelon. The benefits compared with conventional polyethylene films are the same as conventional readily biodegradable films. The key parameters in the analytical composition of glycerin concerning specific industrial applications are discussed; the environmental benefits in metal working fluid formulation and in mulching film compounding are then assessed.

Mobile-Apps Development for Biodiesel Distribution Tracking System and Supply Chain Monitoring

Biodiesel is considered as the most prominent alternative to replacing or complement petroleum-diesel in the future. It is slowly gaining its importance in our daily life. Nevertheless, there are several problems emerged in the biodiesel supply chain, e.g. biodegradability, quality control, disturbance in the distribution of biodiesel, interrupted feedstock, supply and lack of governance. A new approach of biodiesel supply chain management has been developed based on mobile-application to overcome such problems. Determining the fact that biodiesel is degradable over time, the system also possessed by feature to maintain the biodiesel quality during transport, besides bringing-out simple and user-friendly supply-trading application on hand to hand. A wide range of biodiesel supply chain monitoring, distribution tracking and quality checking are demonstrated during the process of ordering, stocking, buying and sending biodiesel. The mobile-application has been tested for performance analysis on processor, battery and data usage. All menus, performance test and survey show good responses although at the security aspect is found the necessity of extra-development. Further analysis indicates that such system also fit for feedstock plantation, cultivation, harvesting and procurement. Overall, this method is worthy suggested to be implemented on the accreditation board of biodiesel that manages the entire supply, orders, trades and quality of biodiesel from upstream to the downstream.

Uncertainties in the Bidirectional Biodiesel Supply Chain

For remote areas, small-scale local biodiesel production is particularly attractive if producers and consumers are the same. Such supply chains are labeled as bidirectional. However, little is known on how raw material supply, transportation, logistics, production and operations uncertainties impact the operational performance of such Bidirectional Biodiesel Supply Chains. This paper contributes by exploring these uncertainties in a multiple case study, directed at mobile processing of rubber seeds, in a remote area. Scientifically, the paper contributes by identifying several novel sources of uncertainty: a short-term perspective, lack of knowledge and the previously unrecognized influence of the local government. Additionally, based on these findings, an extended theoretical framework is proposed which links sources of uncertainty to operational performance. The study provides also insights for stakeholders aiming to increase local biofuel production and provides a stepping-stone to investigate adequate measures to manage the identified uncertainties.

Model framework to construct a single aggregate sustainability indicator: an application to the biodiesel supply chain

In the present work, we propose a model framework to select a set of sustainability indicators that provides reliable information on the system and use the results to analyze the suitability of four different metrics to describe the sustainability in a given context. We consider an approach that may be applied to study sustainability of a variety of systems and to aggregate 3D indicators into a single metric. Firstly, we identify an initial set of indicators that provides an adequate description of the sustainability conditions of a particular system and satisfy some criteria well established in the literature. Then, we use statistical tools to group the indicators into a valid set, according to their similarity using the inherent statistical information on their structure. This procedure simplifies the analyses of the complex system resulting in an optimum subset of indicators, reducing the dimension and improving the quality of the indicators. Once selected the indicators, established rules are used to aggregate commensurable indicators in a methodological manner into a single aggregate indicator. There is no generally accepted standard methodology to aggregate indicators into a single sustainability indicator. In general, the choice of a metric depends on the problem and on the units expressing the indicators. In the present work, this is analyzed studying four different metrics: Euclidean, Mahalanobis, Canberra, and z-score-normalized Canberra distances. This model framework is then applied to analyze a specific sustainability dimension of a biofuel supply chain in six countries, and compare and discuss the results obtained with the four metrics. It was found that among the four metrics, Canberra distance and Mahalanobis distance are the most adequate single aggregate metrics to describe the sustainability biodiesel chain in countries.