14 resultados para Petroleum refineries.

em Aston University Research Archive


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Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

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The quest for sustainable resources to meet the demands of a rapidly rising global population while mitigating the risks of rising CO2 emissions and associated climate change, represents a grand challenge for humanity. Biomass offers the most readily implemented and low-cost solution for sustainable transportation fuels, and the only non-petroleum route to organic molecules for the manufacture of bulk, fine and speciality chemicals and polymers. To be considered truly sustainable, biomass must be derived fromresources which do not compete with agricultural land use for food production, or compromise the environment (e.g. via deforestation). Potential feedstocks include waste lignocellulosic or oil-based materials derived from plant or aquatic sources, with the so-called biorefinery concept offering the co-production of biofuels, platform chemicals and energy; analogous to today's petroleum refineries which deliver both high-volume/low-value (e.g. fuels and commodity chemicals) and lowvolume/ high-value (e.g. fine/speciality chemicals) products, thereby maximizing biomass valorization. This article addresses the challenges to catalytic biomass processing and highlights recent successes in the rational design of heterogeneous catalysts facilitated by advances in nanotechnology and the synthesis of templated porous materials, as well as the use of tailored catalyst surfaces to generate bifunctional solid acid/base materials or tune hydrophobicity.

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Petroleum pipelines are the nervous system of the oil industry, as this transports crude oil from sources to refineries and petroleum products from refineries to demand points. Therefore, the efficient operation of these pipelines determines the effectiveness of the entire business. Pipeline route selection plays a major role when designing an effective pipeline system, as the health of the pipeline depends on its terrain. The present practice of route selection for petroleum pipelines is governed by factors such as the shortest distance, constructability, minimal effects on the environment, and approachability. Although this reduces capital expenditure, it often proves to be uneconomical when life cycle costing is considered. This study presents a route selection model with the application of an Analytic Hierarchy Process (AHP), a multiple attribute decision making technique. AHP considers all the above factors along with the operability and maintainability factors interactively. This system has been demonstrated here through a case study of pipeline route selection, from an Indian perspective. A cost-benefit comparison of the shortest route (conventionally selected) and optimal route establishes the effectiveness of the model.

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The Indian petroleum industry is passing through a very dynamic business environment due to the liberalisation of many government policies, vertical integration among organisations and the presence of multinational companies. This caused a competitive environment among the organisations in the Indian petroleum industry in the public sector. Effective project management for developing new infrastructures and maintaining the existing facilities has been considered one of the means for remaining competitive in this business environment. However, present project management practices suffer from many shortcomings, as time, cost and quality non-achievements are part and parcel of almost every project. This study focuses on identifying the issues in managing projects of the organisation in the Indian petroleum sector with the involvement of the executives in a workshop environment. This also suggests some remedial measures for resolving those issues through identifying critical success factors and enablers. The enablers not only resolve the present issues but also ensure superior performance. These are analysed in a quantitative framework to derive improvement measures in project management practices.

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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

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Currently, the main source for the production of liquid transportation fuels is petroleum, the continued use of which faces many challenges including depleting oil reserves, significant oil price rises, and environmental concerns over global warming which is widely believed to be due to fossil fuel derived CO2 emissions and other greenhouse gases. In this respect, lignocellulosic or plant biomass is a particularly interesting resource as it is the only renewable source of organic carbon that can be converted into liquid transportation fuels. The gasification of biomass produces syngas which can then be converted into synthetic liquid hydrocarbon fuels by means of the Fischer-Tropsch (FT) synthesis. This process has been widely considered as an attractive option for producing clean liquid hydrocarbon fuels from biomass that have been identified as promising alternatives to conventional fossil fuels like diesel and kerosene. The resulting product composition in FT synthesis is influenced by the type of catalyst and the reaction conditions that are used in the process. One of the issues facing this conversion process is the development of a technology that can be scaled down to match the scattered nature of biomass resources, including lower operating pressures, without compromising liquid composition. The primary aims of this work were to experimentally explore FT synthesis at low pressures for the purpose of process down-scaling and cost reduction, and to investigate the potential for obtaining an intermediate FT synthetic crude liquid product that can be integrated into existing refineries under the range of process conditions employed. Two different fixed-bed micro-reactors were used for FT synthesis; a 2cm3 reactor at the University of Rio de Janeiro (UFRJ) and a 20cm3 reactor at Aston University. The experimental work firstly involved the selection of a suitable catalyst from three that were available. Secondly, a parameter study was carried out on the 20cm3 reactor using the selected catalyst to investigate the influence of reactor temperature, reactor pressure, space velocity, the H2/CO molar ratio in the feed syngas and catalyst loading on the reaction performance measured as CO conversion, catalyst stability, product distribution, product yields and liquid hydrocarbon product composition. From this parameter study a set of preferred operating conditions was identified for low pressure FT synthesis. The three catalysts were characterized using BET, XRD, TPR and SEM. The catalyst selected was an unpromoted Co/Al2O3 catalyst. FT synthesis runs on the 20cm3 reactor at Aston were conducted for 48 hours. Permanent gases and light hydrocarbons (C1-C5) were analysed in an online GC-TCD/FID at hourly intervals. The liquid hydrocarbons collected were analyzed offline using GC-MS for determination of fuel composition. The parameter study showed that CO conversion and liquid hydrocarbon yields increase with increasing reactor pressure up to around 8 bar, above which the effect of pressure is small. The parameters that had the most significant influence on CO conversion, product selectivity and liquid hydrocarbon yields were reactor temperature and catalyst loading. The preferred reaction conditions identified for this research were: T = 230ºC, P = 10 bar, H2/CO = 2.0, WHSV = 2.2 h-1, and catalyst loading = 2.0g. Operation in the low range of pressures studied resulted in low CO conversions and liquid hydrocarbon yields, indicating that low pressure BTL-FT operation may not be industrially viable as the trade off in lower CO conversions and once-through liquid hydrocarbon product yields has to be carefully weighed against the potential cost savings resulting from process operation at lower pressures.

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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

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The Indian Petroleum Industry is passing through a very dynamic business environment due to liberalization. Effective project management for developing new infrastructures and maintaining the existing facilities has been considered as one of the means for remaining competitive but these practices suffer from many shortcomings, as time, cost and quality non-achievements are part and parcel of almost every project. This study focuses on identifying the specific causes of project failure by demonstrating first the characteristics of projects in Indian Petroleum industry and suggests some remedial measures for resolving these issues. The suggested project management model is integrated through information management system and demonstrated through a case study.

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Projects exposed to an uncertain environment must be adapted to deal with the effective integration of various planning elements and the optimization of project parameters. Time, cost, and quality are the prime objectives of a project that need to be optimized to fulfill the owner's goal. In an uncertain environment, there exist many other conflicting objectives that may also need to be optimized. These objectives are characterized by varying degrees of conflict. Moreover, an uncertain environment also causes several changes in the project plan throughout its life, demanding that the project plan be totally flexible. Goal programming (GP), a multiple criteria decision making technique, offers a good solution for this project planning problem. There the planning problem is considered from the owner's perspective, which leads to classifying the project up to the activity level. GP is applied separately at each level, and the formulated models are integrated through information flow. The flexibility and adaptability of the models lies in the ease of updating the model parameters at the required level through changing priorities and/or constraints and transmitting the information to other levels. The hierarchical model automatically provides integration among various element of planning. The proposed methodology is applied in this paper to plan a petroleum pipeline construction project, and its effectiveness is demonstrated.

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A cross-country pipeline construction project is exposed to an uncertain environment due to its enormous size (physical, manpower requirement and financial value), complexity in design technology and involvement of external factors. These uncertainties can lead to several changes in project scope during the process of project execution. Unless the changes are properly controlled, the time, cost and quality goals of the project may never be achieved. A methodology is proposed for project control through risk analysis, contingency allocation and hierarchical planning models. Risk analysis is carried out through the analytic hierarchy process (AHP) due to the subjective nature of risks in construction projects. The results of risk analysis are used to determine the logical contingency for project control with the application of probability theory. Ultimate project control is carried out by hierarchical planning model which enables decision makers to take vital decisions during the changing environment of the construction period. Goal programming (GP), a multiple criteria decision-making technique, is proposed for model formulation because of its flexibility and priority-base structure. The project is planned hierarchically in three levels—project, work package and activity. GP is applied separately at each level. Decision variables of each model are different planning parameters of the project. In this study, models are formulated from the owner's perspective and its effectiveness in project control is demonstrated.

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Projects that are exposed to uncertain environments can be effectively controlled with the application of risk analysis during the planning stage. The Analytic Hierarchy Process, a multiattribute decision-making technique, can be used to analyse and assess project risks which are objective or subjective in nature. Among other advantages, the process logically integrates the various elements in the planning process. The results from risk analysis and activity analysis are then used to develop a logical contingency allowance for the project through the application of probability theory. The contingency allowance is created in two parts: (a) a technical contingency, and (b) a management contingency. This provides a basis for decision making in a changing project environment. Effective control of the project is made possible by the limitation of the changes within the monetary contingency allowance for the work package concerned, and the utilization of the contingency through proper appropriation. The whole methodology is applied to a pipeline-laying project in India, and its effectiveness in project control is demonstrated.

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In this paper we analyse rigidities in the behaviour of the mark-up on regular, midgrade and premium varieties of petrol in the New York area using a set of weekly frequency data and a methodology that analyses the pricing process using deterministic and stochastic techniques. The results are consistent across methodologies and indicate that the speeds of adjustment to the long-run equilibrium mark-up differ across varieties of petrol with margins of the premium variety falling faster than they rise, contrary to the popular claim of welfare-decreasing asymmetries in price transmission. © 2012 The Authors. The Manchester School © 2012 Blackwell Publishing Ltd and The University of Manchester.

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This article employs nonlinear smooth transition models to analyze the relationship between upstream and midstream prices of petroleum products. We test for the presence of nonlinearities in price linkages using both weekly series constructed using official EU procedures and also daily industry series applied for the first time. Our results show that the estimated shape of the transition function and equilibrium reversion path depend on the frequency of the price dataset. Our analysis of the crude oil to wholesale price transmission provides evidence of nonlinearities when prices are observed with daily frequency. The nature of the nonlinearities provides evidence in support of the existence of menu costs or, more generally, frictions in the markets rather than supply adjustment costs. This result differs from that found for the U.S. petroleum markets. © 2012 American Statistical Association.

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This research investigates the determinants of asymmetric price transmission (APT) in European petroleum markets. APT is the faster response of retail prices to cost increases than to cost decreases; resulting in a welfare transfer from consumers to fuel retailers. I investigate APT at 3 different levels: the EU, the UK and at the Birmingham level. First, I examine the incidence of asymmetries in the retail markets of six major EU countries; significant asymmetries are found in all countries except from the UK. The market share data suggest that asymmetries are more important in more concentrated markets; this finding supports the collusion theory. I extend the investigation to 12 EU countries and note that APT is greater in diesel markets. The cross-country analysis suggests that vertical and horizontal concentration at least partly explains the degree of asymmetry. I provide evidence justifying scrutiny over retail markets’ pricing and structure. Second daily data unveil the presence of APT in the UK fuel markets. I use break tests to identify segments with different pricing regimes. Two main types of periods are identified: periods of rising oil price exhibit significant asymmetries whilst periods of recession do not. Our results suggest that oligopolistic coordination between retailers generate excess rents during periods of rising oil price whilst the coordination fails due to price wars when oil prices are going downwards. Finally I investigate the pricing behaviour of petroleum retailers in the Birmingham (UK) area for 2008. Whilst the market structure data reveals that the horizontal concentration is higher than the national UK average, I find no evidence of APT. In contrast, I find that retail prices are sticky upwards and downwards and that firms with market power (majors and supermarkets) adjust their prices slower than other firms.