Fernando Luiz Cyrino Oliveira

Pontifical Catholic University of Rio de Janeiro · Department of Industrial Engineering (IND)

The Amazon region faces signifiant challenges in accessing electricity in isolated systems. Solar photovoltaic energy with batteries is a promising alternative that aligns with the Sustainable Development Goals. However, its implementation is hindered by complex barriers. Previous studies have addressed specifi aspects, but there is a need for a co...

This study presents an analysis of portfolio optimization methodology applied to the Brazilian electric sector, focusing on decision-making in energy contracts and the construction of renewable power plants. The approach aims for efficient resource allocation for companies in the electric sector, emphasizing risk aversion. Two case studies are cond...

Copula theory is a statistical approach that allows for the joint modeling of dependencies between random variables, surpassing traditional correlation measures by capturing multivariate dependency structures. This study employs copula theory to expand a renewable energy database, emphasizing the interaction between a wind turbine’s capacity factor...

This work proposes a methodology based on Markov Chains for simulating stochastic processes of Variable Renewable Energy (VRE) sources production. The main objective is to capture, in the scenarios, both the influence of climate phenomena and the complementarity between different sources. Case studies are developed based on data from three renewabl...

Power output from wind turbines is influenced by wind speed, but the traditional theoretical power curve approach introduces uncertainty into wind energy forecasting models. This is because it assumes a consistent power output for a given wind speed. To address this issue, a new nonparametric method has been proposed. It uses K-means clustering to...

The Oil & Gas companies have an important role in the nation's development and the economy. High investments are necessary for an effective, safe, and profitable E&P. The most expensive are the rig costs, which are the main resource for drilling and maintenance of wells. This paper proposes a Rig Scheduling Monte Carlo Simulation for offshore wells...

Drought is recognized as a devastating natural hazard, affecting human livelihood and causing a substantial economic impact. Consequently, experts and decision-makers concentrate on new approaches to reducing droughts’ economic and social effects through studies that focus on the monitoring, prediction, and risk analysis of drought to inform drough...

The generation from renewable sources has increased significantly worldwide, mainly driven by the need to reduce the global emissions of greenhouse gases, decelerate climate changes, and meet the environmental, social, and governance agenda (ESG). The main characteristics of variable renewable energy (VRE) are the stochastic nature, its seasonal as...

The article proposes a new definition of environmental competencies that facilitates the incidence of the organization in the development of people, which will show the reduction of the harmful impact on the environment, sustainable competitive advantages, and better performance in the medium and long term because of an increasingly competent staff...

The article proposes a new definition of environmental competencies that facilitates the incidence of the organization in the development of people, which will show the reduction of the harmful impact on the environment, sustainable competitive advantages, and better performance in the medium and long term because of an increasingly competent staff...

In recent years, consideration of reanalysis data has gained space and importance globally as a promising alternative for climate studies that suffer from an absence or scarcity of data. Wind speed time series can be obtained from these bases for various purposes, such as inferring the potential of sites for wind power generation. These projections...

Accurate electricity demand forecasting, especially in the short run, is critical for the optimal management of power systems. However, high-frequency time series usually contain unique stylized facts, such as multiple seasonal patterns, which imposes an extra challenge in accurate estimation and forecasting. Aiming to contribute to the reliable op...

The increased participation of renewable variable energy sources (RVS) in the Brazilian electricity matrix brings several challenges to the planning and operation of the Brazilian Electricity System (BES) due to the stochasticity present in RVS. Such challenges involve the modeling and simulation of intermittent generation processes. In this contex...

The concern with global warming and pollution has increased interest in the development of renewable energy sources, which are less aggressive to the environment. Wind energy can provide adequate solutions to the above-mentioned problems. The use of this energy eliminates unwanted waste that is harmful to health and the environment from other energ...

Purpose The length of stay (LoS) is one of the most used metrics for resource use in Intensive Care Units (ICU). We propose a structured data-driven methodology to predict the ICU length of stay and the risk of prolonged stay, and its application in a large multicenter Brazilian ICU database. Methods Demographic data, comorbidities, complications,...

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...

A prediction model is an indispensable tool in business, helping to make decisions, whether in the short, medium, or long term. In this context, the implementation of machine learning techniques in time series forecasting models has a notorious relevance, as information processing and efficient and dynamic knowledge uncovering are increasingly dema...

Hierarchical forecasting methods take advantage of the hierarchical structure of the data through base forecast reconciliation, generating results that are usually unbiased and more accurate than those provided by benchmark methods. When combining base forecasts through regression-based reconciliation strategies, however, some forecasts may behave...

The relationship of dependence between wind speed and wind power variables has a degree of complexity that has motivated several scientific studies over the years. Much of this research seeks to understand the stochastic nature of both phenomena, either for the purpose of marginal analysis or for joint analyses, aiming to improve prediction of wind...

This paper develops a new approach to forecast natural gas consumption via ensembles. It combines Bootstrap Aggregation (Bagging), univariate time series forecasting methods and modified regularization routines. A new variant of Bagging is introduced, which uses Maximum Entropy Bootstrap (MEB) and a modified regularization routine that ensures that...

Knowledge of temperature distribution in power transformers is essential for the management of electrical distribution systems. Monitoring the hot-spot temperature of a power transformer can extend its lifetime. This paper introduces two novel models called Modified Set-Membership evolving multivariable Gaussian (MSM-eMG) and variable step-size evo...

The present work aims to obtain a ranking of hydro generating units using the analytic hierarchy process (AHP) method, based on the maintenance indicators of the Santo Antônio Hydroelectric Plant (SAHP). The purpose of the generated classification is to provide subsidies to assist maintenance planning, determining the most critical turbines for per...

Drought is one of the most critical meteorological hazards that has a devastating effect on natural habitats, ecosystems, and many economic and social sectors. Due to these severe impacts of drought events, many studies have focused on drought monitoring, prediction, and risk analysis to aid drought preparedness plans and mitigation measures. This...

Fuel represents one of the main transport costs and, consequently, of a logistical operation. So, a computational tool that allows reliable forecasts on the fuel prices becomes a competitive differential for the logistics operator, especially in a country of continental dimensions such as Brazil. The present study developed a participatory evolving...

In this work we present two new models based on Evolving Multivariable Gaussian approach and on the Set-Membership/Enhanced Set-Membership adaptive filtering framework to model the thermal behavior of power transformers. In these new models, adaptive filtering approaches work to adjust the learning rates of the evolutionary model, while the use of...

This paper develops a new ensemble-based approach to point and interval forecasting, and focus on total electricity supply. The proposed approach combines Bootstrap Aggregation (Bagging), time series methods and a novel pruning routine that performs feature selection before the aggregation of forecasts. Monthly time series of the total electricity...

The Weibull distribution is commonly used to model wind speed data, mainly due to its good fit to asymmetric positive variables. Several proposals have extended this approach to accommodate realistic features of wind data such as nonstationary behavior due to changes in atmospheric regimes. The present work considers wind speed modeling over time t...

ABSTRACT Recent empirical results show that forecast combinations and cross-learning schemes are winning approaches in the time series field. Although many competition-winning combination methods - with cross-learning or not - use static weights along the forecasting horizon, we could not find extensive work about the effects of using horizon-optim...

O transporte representa um dos principais custos de uma operação logística e está presente em toda a cadeia de suprimentos, já que conecta fornecedores, produção e consumidores. Dessarte, um modelo que permita prever os preços dos combustíveis se torna um diferencial competitivo para o operador logístico. O presente estudo desenvolveu um modelo neb...

O presente trabalho propõe a obtenção de um ranking de unidades geradoras com a utilização do método Analytic Hierarchy Process (AHP), baseado nos indicadores de manutenção da Usina Hidrelétrica Santo Antônio (SAE). O intuito da classificação gerada é fornecer subsídio para auxiliar o planejamento das manutenções, determinando as turbinas mais crít...

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...

Diversos estudos tem sido orientados no sentido de desenvolver modelos térmicos mais precisos e com menor custo computacional para transformadores de potência. Motivados pela necessidade de sistemas adaptáveis, os sistemas inteligentes evolutivos vêm recebendo grande atenção em problemas de vários tipos de problemas. Este trabalho apresenta um novo...

Neste trabalho é apresentado um novo sistema fuzzy evolutivo baseado no conceito de filtragem Set-Membership e no agrupamento Gaussiano Multivariado para a modelagem térmica de transformadores de potência. Este novo sistema, denominado Set-Membership evolutivo Gaussiano Multivariado, atua ajustando a taxa de aprendizagem no sistema de modelagem fuz...

The increasing presence of intermittent renewables in modern power systems motivates the development of methods for renewables forecasting. More accurate forecasts may implicate less operational costs for power systems. In this context, this paper proposes a family of architectures based on fully convolutional neural networks for wind speed predict...

The increasing penetration of intermittent renewable energy in power systems brings operational challenges. One way of supporting them is by enhancing the predictability of renewables through accurate forecasting. Convolutional Neural Networks (Convnets) provide a successful technique for processing space-structured multi-dimensional data. In our w...

The deployment of strategic objectives into indicators that portray organizational performance to the operational level is the main focus of performance measurement systems. The selection of indicators and the mapping of relationships between them and the objectives using quantitative methods are an important research aspect, given that several ini...

Since Twitter covers a broad spectrum of topics, this study aimed to evaluate the consumer perception of an agri‐food product using its data as source of information. The keyword “eggs” was searched in different languages (English, French, Spanish, and Portuguese) and a content analysis was performed in tweets that had terms referring to the produc...

The Unmanned Aerial Vehicles (UAV) are an important technology with multiple applications. It is an object of study for researchers aiming to improve the performance of these vehicles, especially in flight stages as the landing. Therefore, this paper presents a method for the landing of a UAV based on Type-2 Fuzzy Logic System considering static ta...

Purpose Studies have shown that a small percentage of ICU patients have prolonged length of stay (LoS) and account for a large proportion of resource use. Therefore, the identification of prolonged stay patients can improve unit efficiency. In this study, we performed a systematic review and meta-analysis to understand the risk factors of ICU LoS....

We propose a new way of selecting among model forms in automated exponential smoothing routines, consequently enhancing their predictive power. The procedure, here addressed as treating, operates by selectively subsetting the ensemble of competing models based on information from their prediction intervals. By the same token, we set forth a pruning...

This paper analyzes the permutation flow‐shop problem with delivery dates and cumulative payoffs (whenever these dates are met) under uncertainty conditions. In particular, the paper considers the realistic situation in which processing times are stochastic. The main goal is to find the permutation of jobs that maximizes the expected payoff. In ord...

A factor that directly impacts the lifespan of a power transformer is the hot-spot temperature, and its monitoring is vital to prevent faults, reduce costs, keep the safety, and provide a reliable service to consumers. In this paper, we propose two forecasting models to predict the hot-spot temperature of power transformers. The first is the implem...

In this paper, we forecast residential electricity consumption in Brazil considering the variability in consumption behavior in different regions. In order to do so, we use a bottom-up approach to estimate long-term electricity consumption that considers three technology-driven scenarios: one assuming reference efficiency development, another one b...

Once energy is a social good, this study proposes a methodology to select the most appropriate wind turbine power curve models for Brazilian wind farms. To do so, we compare our proposal with the observed values in a monthly and annual base.

In order to ensure competitiveness in the market, electricity distribution companies must accurately estimate future electricity generation. To do so, this work uses time series models that correlate future inflow and past generation in space and time. The methodology proposed shows reduced errors and satisfactory predictability.

We apply process modeling and simulation to improve surgery planning, through the coordination of operation rooms and intensive care unit (ICU). A case study was carried out in a Brazilian hospital. With the proposed changes, we obtained a 39% reduction in surgery cancelations and a 61% decrease in preoperative length of stay.

This paper analyzes the evolution of research on drought mitigation and prevention over the years through a systematic literature review. The results indicate the publication trends for future studies.

The practiced freight rates have a great impact on the international trade of crude oil and oil products. This paper aims to verify the performance of dynamic regression models in short-term maritime freight forecasts in the spot market of a crude oil export route.

Métodos de amortecimento exponencial são formulações versáteis para a previsão de séries temporais univariadas conhecidas desde a década de 1960. Modelos mais recentes tem feito uso do bagging para melhorar a qualidade das previsões com estes modelos. Um destes modelos, BaggedETS, desenvolvido em 2016, trouxe melhorias na qualidade de previsão e es...

Resumo. O futebol é o esporte mais popular do mundo e uma paixão nacional brasileira. Seu sucesso se deve muito ao aspecto imprevisível do jogo em que a probabilidade de ocorrência de placares inesperados (as chamadas "zebras") neste esporte é maximizado comparado a outros, em que o melhor geralmente vence. Esta propriedade torna as partidas um obj...

To contribute to overcoming global sustainability challenges, investors have been increasingly interested in making sustainable investments and incorporating environmental, social and governance (ESG) criteria into their portfolio selection decisions and managerial activities. However, these investors and other agents interested in sustainable inve...

This study aimed to evaluate the application of preferred attribute elicitation (PAE) methodology for assessing the perceptions of consumers from different regions of Brazil (Northeast, Southeast or South, n = 20) about Coalho cheese samples. Northeast Brazilian consumers elicited a higher number of attributes (22 vs. 13–15) and had a higher freque...

Unmanned Aerial Vehicles are an important technol-ogy in which multiple applications can be designed, such as envi-ronmental, emergency-security, communication and monitoring.Thus, it is an object of study for researchers aiming to improvethe performance of these vehicles, especially in flight stages asthe landing. Therefore, this paper presents a...

This paper puts forward an in-depth investigation of the nonlinear associations between Gross Domestic Product (GDP) and international crude oil prices using the Brazilian aggregate as case study. We provide evidence on the existence of two sharply defined regimes in the Brazilian GDP since 1947: the first, very oil-dependent in the short-run and m...

Purpose Appointment scheduling systems traditionally book patients at fixed intervals, without taking into account the complexity factors of the health system. This paper analyzes several appointment scheduling policies of the literature and proposes the most suitable to a bariatric surgery clinic, considering the following complexity factors: (i)...

Empirical studies have revealed that the conditional Capital Asset Pricing Model (CAPM) has a higher explanatory power than its unconditional version, particularly for the model in state-space form where the beta is estimated using Kalman filter. Most empirical analyses are based on stock portfolios to explain financial anomalies, but only a few st...

ABSTRACT This paper describes a study of the dispatch planning/scheduling process for inbound containers handled with a reach stacker. Client container pickup is scheduled at least one day in advance for one of six two-hour time windows (six five-container-high stacks per time window) on a given day. A buffer area is available for the containers to...

In the past two decades, wind power’s share of the energy mix has grown significantly in Brazil. However, nowadays planning electricity operation in Brazil basically involves evaluating the future conditions of energy supply from hydro and thermal sources over the planning horizon. In this context, wind power sources are not stochastically treated....

The use of renewable energy resources, especially wind power, is receiving strong attention from governments and private institutions, since it is considered one of the best and most competitive alternative energy sources in the current energy transition that many countries around the world are adopting. Wind power also plays an important role by r...

Purpose The purpose of this paper is to analyse the determinants of technical efficiency (TE) in dairy farms located in the South of Brazil, aiming for a better understanding of the topic for academics, dairy farmers and policymakers to improve the productivity and competitiveness of dairy farms. Design/methodology/approach This study was develo...

Purpose No-shows of patients to their scheduled appointments have a significant impact on healthcare systems, including lower clinical efficiency and higher costs. The purpose of this study was to investigate the factors associated with patient no-shows in a bariatric surgery clinic. Materials and Methods We performed a retrospective study of 13,2...

O artigo propõe uma nova abordagem para problema de flowshop scheduling com datas de entrega e ganhos cumulativos em um ambiente de digitalização de livros, a partir da consideração da incerteza presente no processo, representada por uma distribuição de probabilidade associada aos tempos de processamento das tarefas. Para a solução do problema, uma...