Optimal offering strategies for wind power producers considering uncertainty and risk

This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

Aplicação de métodos estocásticos na gestão de custos de construção de condutas de saneamento

O trabalho apresentado centra-se na determinação dos custos de construção de condutas de pequenos e médios diâmetros em Polietileno de Alta Densidade (PEAD) para saneamento básico, tendo como base a metodologia descrita no livro Custos de Construção e Exploração – Volume 9 da série Gestão de Sistemas de Saneamento Básico, de Lencastre et al. (1994). Esta metodologia descrita no livro já referenciado, nos procedimentos de gestão de obra, e para tal foram estimados custos unitários de diversos conjuntos de trabalhos. Conforme Lencastre et al (1994), “esses conjuntos são referentes a movimentos de terras, tubagens, acessórios e respetivos órgãos de manobra, pavimentações e estaleiro, estando englobado na parte do estaleiro trabalhos acessórios correspondentes à obra.” Os custos foram obtidos analisando vários orçamentos de obras de saneamento, resultantes de concursos públicos de empreitadas recentemente realizados. Com vista a tornar a utilização desta metodologia numa ferramenta eficaz, foram organizadas folhas de cálculo que possibilitam obter estimativas realistas dos custos de execução de determinada obra em fases anteriores ao desenvolvimento do projeto, designadamente numa fase de preparação do plano diretor de um sistema ou numa fase de elaboração de estudos de viabilidade económico-financeiros, isto é, mesmo antes de existir qualquer pré-dimensionamento dos elementos do sistema. Outra técnica implementada para avaliar os dados de entrada foi a “Análise Robusta de Dados”, Pestana (1992). Esta metodologia permitiu analisar os dados mais detalhadamente antes de se formularem hipóteses para desenvolverem a análise de risco. A ideia principal é o exame bastante flexível dos dados, frequentemente antes mesmo de os comparar a um modelo probabilístico. Assim, e para um largo conjunto de dados, esta técnica possibilitou analisar a disparidade dos valores encontrados para os diversos trabalhos referenciados anteriormente. Com os dados recolhidos, e após o seu tratamento, passou-se à aplicação de uma metodologia de Análise de Risco, através da Simulação de Monte Carlo. Esta análise de risco é feita com recurso a uma ferramenta informática da Palisade, o @Risk, disponível no Departamento de Engenharia Civil. Esta técnica de análise quantitativa de risco permite traduzir a incerteza dos dados de entrada, representada através de distribuições probabilísticas que o software disponibiliza. Assim, para por em prática esta metodologia, recorreu-se às folhas de cálculo que foram realizadas seguindo a abordagem proposta em Lencastre et al (1994). A elaboração e a análise dessas estimativas poderão conduzir à tomada de decisões sobre a viabilidade da ou das obras a realizar, nomeadamente no que diz respeito aos aspetos económicos, permitindo uma análise de decisão fundamentada quanto à realização dos investimentos.

Establishment of optimal physical assets inspection frequency based on risk principles

Risk Based Inspection (RBI) is a risk methodology used as the basis for prioritizing and managing the efforts for an inspection program allowing the allocation of resources to provide a higher level of coverage on physical assets with higher risk. The main goal of RBI is to increase equipment availability while improving or maintaining the accepted level of risk. This paper presents the concept of risk, risk analysis and RBI methodology and shows an approach to determine the optimal inspection frequency for physical assets based on the potential risk and mainly on the quantification of the probability of failure. It makes use of some assumptions in a structured decision making process. The proposed methodology allows an optimization of inspection intervals deciding when the first inspection must be performed as well as the subsequent intervals of inspection. A demonstrative example is also presented to illustrate the application of the proposed methodology.

Maintenance of fire sprinkler systems based on the dynamic assessment of its condition

Safety is one of the major concerns of process safety engineers in most industrial facilities all over the world. To this scope, some events play an important role once the effect of their consequences can be assumed as totally undesirable. One of these events refers to the occurrence of a fire. Such event can result in catastrophic consequences for life, equipment, and continuity of activities or even leading to environmental damage. A fire protection equipment with low reliability means that this equipment are often unavailable and thus the risk of a fire increases. Maintenance of fire protection equipment is very important because this kind of systems is mostly in a dormant mode, which gives uncertainty about their operability when demanded in a real situation of fire. This article outlines the importance of tests, inspection, and maintenance operations in the context of a fire sprinkler system and proposes a methodology based on international standards and supported by test/inspection reports to correct the frequency of these actions according to the level of degradation of the components and regarding safety purposes. © 2015 American Institute of Chemical Engineers.

Risk-based decision support system for life cycle management of industrials plants

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Segurança contra incêndios na reabilitação sustentável de edifícios antigos

Dissertação de mestrado em Construção e Reabilitação Sustentáveis

Handheld-assisted field data collection for occupational risk assessment.

A computerized handheld procedure is presented in this paper. It is intended as a database complementary tool, to enhance prospective risk analysis in the field of occupational health. The Pendragon forms software (version 3.2) has been used to implement acquisition procedures on Personal Digital Assistants (PDAs) and to transfer data to a computer in an MS-Access format. The data acquisition strategy proposed relies on the risk assessment method practiced at the Institute of Occupational Health Sciences (IST). It involves the use of a systematic hazard list and semi-quantitative risk assessment scales. A set of 7 modular forms has been developed to cover the basic need of field audits. Despite the minor drawbacks observed, the results obtained so far show that handhelds are adequate to support field risk assessment and follow-up activities. Further improvements must still be made in order to increase the tool effectiveness and field adequacy.

Rockfall hazard and risk assessments along roads at a regional scale: Example in Swiss Alps

Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes.

Bacillus thuringiensis: fermentation process and risk assessment: a short review

Several factors make the local production of Bacillus thuringiensis (Bt) highly appropriate for pest control in developing nations. Bt can be cheaply produced on a wide variety of low cost, organic substrates. Local production results in considerable savings in hard currency which otherwise would be spent on importation of chemical and biological insecticides. The use of Bt in Brazil has been limited in comparison with chemical insecticides. Although Bt is imported, some Brazilian researchers have been working on its development and production. Fermentation processes (submerged and semi-solid) were applied, using by-products from agro-industries. As the semi-solid fermentation process demonstrated to be interesting for Bt endotoxins production, it could be adopted for small scale local production. Although promising results had been achieved, national products have not been registered due to the absence of a specific legislation for biological products. Effective actions are being developed in order to solve this gap. Regardless of the biocontrol agents being considered atoxic and harmless to the environment, information related to direct and indirect effects of microbials are still insufficient in many cases. The risk analysis of the use of microbial control agents is of upmost importance nowadays, and is also discussed.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Angiotensin converting enzyme inhibitor induced angio-oedema: a review of the pathophysiology and risk factors.

Angio-oedema (AE) is a known adverse effect of angiotensin converting enzyme inhibitor (ACE-I) therapy. Over the past several decades, evidence of failure to diagnose this important and potentially fatal reaction is commonly found in the literature. Because this reaction is often seen first in the primary care setting, a review was undertaken to analyse and document the keys to both diagnostic criteria as well as to investigate potential risk factors for ACE-I AE occurrence. A general review of published literature was conducted through Medline, EMBASE, and the Cochrane Database, targeting ACE-I-related AE pathomechanism, diagnosis, epidemiology, risk factors, and clinical decision making and treatment. The incidence and severity of AE appears to be on the rise and there is evidence of considerable delay in diagnosis contributing to significant morbidity and mortality for patients. The mechanism of AE due to ACE-I drugs is not fully understood, but some genomic and metabolomic information has been correlated. Additional epidemiologic data and clinical treatment outcome predictors have been evaluated, creating a basis for future work on the development of clinical prediction tools to aid in risk identification and diagnostic differentiation. Accurate recognition of AE by the primary care provider is essential to limit the rising morbidity associated with ACE-I treatment-related AE. Research findings on the phenotypic indicators relevant to this group of patients as well as basic research into the pathomechanism of AE are available, and should be used in the construction of better risk analysis and clinical diagnostic tools for ACE-I AE.

Todennäköisyyspohjaisen paloanalyysimenetelmän kehittäminen ydinvoimalaitoksella

Diplomityössä on tutustuttu ydinvoimalaitosten paloriskejä käsittelevään todennäköisyyspohjaiseen turvallisuusanalyysiin. Tavoitteena on ollut Olkiluoto 1 ja 2 laitosyksiköiden paloanalyysimenetelmän kehittäminen. Työssä esitetään paloanalyysin pääpiirteet, kaksi erilaista palotaajuuksien estimointimenetelmää sekä palojen leviämisen arviointimenetelmiä. Palotaajuuksien estimointimenetelmistä keskitytään Berryn menetelmän sekä NUREG/CR-6850-palotaajuuslaskentamenetelmän tarkasteluun. Palon leviämisen arvioinnissa on esitetty kolmen erilaisen virtausteknisen laskentatyökalun perusteet sekä palon leviämistodennäköisyyksiä arvioivan Probabilistic Fire Simulator (PFS) -ohjelman käyttöä. Työn aikana on laskettu molemmilla palotaajuuden estimointimenetelmillä palotaajuuksia eri tyyppisille huonetiloille. Berryn menetelmän palotaajuudet olivat pääosin alhaisempia kuin NUREG/CR-6850-menetelmällä lasketut palotaajuudet. Palon leviämistarkastelussa on tutkittu ydinvoimalaitoksen relehuoneen tulipaloa. PFS:n avulla laskettujen leviämistodennäköisyyksien arvoja on vertailtu TVO:n paloanalyysissa käytettyihin kvalitatiivisiin peittokertoimiin. Palon leviämistodennäköisyys eri osajärjestelmien välillä todettiin suuresti riippuvan analyysissaoletetuista vaurioitumislämpötiloista. Tutkittuja menetelmiä hyödyntäen diplomityössä kehitettiin paloanalyysimenetelmäkuvaus. Menetelmäkuvauksessa huonetilojen paloriskit kartoitetaan aluksi Berryn menetelmällä. Näin kaikille laitoksen huonetiloille saadaan arvioitua palotaajuus sekä paloalkutapahtumaluokkien sydänvauriotaajuus. Seuraavaksi suoritetaan valintamenettely, jossa valitut kriteerit täyttäville huonetiloille tehdään tarkentava palotaajuuslaskenta. Tarkentava palotaajuuslaskenta perustuu NUREG/CR-6850-menetelmän mukaisesti huonetilojen realistisiin syttymislähteisiin. Kriittisimpien huonetilojen osalta palon leviämisen arviointiin on tarkoitus hyödyntää numeerista simulointia.

Sensitivity analysis, dominant factors, and robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 occupational exposure models

Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.

CITRICULTURE ECONOMIC AND FINANCIAL EVALUATION UNDER CONDITIONS OF UNCERTAINTY

ABSTRACT The citriculture consists in several environmental risks, as weather changes and pests, and also consists in considerable financial risk, mainly due to the period ofreturn on the initial investment. This study was motivated by the need to assess the risks of a business activity such as citriculture. Our objective was to build a stochastic simulation model to achieve the economic and financial analysis of an orange producer in the Midwest region of the state of Sao Paulo, under conditions of uncertainty. The parameters used were the Net Present Value (NPV), the Modified Internal Rate of Return(MIRR), and the Discounted Payback. To evaluate the risk conditions we built a probabilistic model of pseudorandom numbers generated with Monte Carlo method. The results showed that the activity analyzed provides a risk of 42.8% to reach a NPV negative; however, the yield assessed by MIRR was 7.7%, higher than the yield from the reapplication of the positive cash flows. The financial investment pays itself after the fourteenth year of activity.