Papers by Fernando Luiz Cyrino Oliveira
Journal of Intelligent & Fuzzy Systems, 2013
ABSTRACT The non-payment rate has been one of the main problems faced by the electric power distr... more ABSTRACT The non-payment rate has been one of the main problems faced by the electric power distribution utilities. It is therefore essential that the utilities provide a methodology to assess the capability of a residential consumer to pay on time his/her electricity bill. As such, the utility will be able to simulate strategies and mitigate the risk of non-payment. This article presents a proposal based on fuzzy logic approach to compute a “Payment Capability Index” PCI for residential customers. A spatial view of PCI is provided by illustrative maps obtained by Geographic Information System GIS.
To produce accurate prediction of time series, it is first necessary to know and understanding al... more To produce accurate prediction of time series, it is first necessary to know and understanding all the historical information available. This way, the series of electrical energy consumption and production in Brazil were collected and analysed by descriptive statistics in order to find the presence of Stylized Facts before submitting them to standard forecasting methods. Two well known forecasting approaches were used in the modelling stage of the series. The first one, the Two Parameters Holt method as the univariate method and Dynamic Regression method as a causal model, using the Brazilian GDP as the unique explanatory variable. The results obtained by the fitted models show that the gap between the energy consumption and production series tends to increase with the time horizon (up to 2050 in this paper). However, if the energy generation do not materialize, there will be problems to supply the projected consumption.
In Brazil, the behavior of electrical load, particularly in energy consumption, has been widely i... more In Brazil, the behavior of electrical load, particularly in energy consumption, has been widely investigated over the past years. In general, this interest is due to the great financial and social importance of this input, as its failure or shortage can have a variety of damaging impacts to the country. This paper proposes a method to generate monthly load series freed from variations arising from two sources: calendar and temperature. To find the best fitting approach to removing these effects, we considered a totally empirical method and one with hybrid features, as it uses both empirical procedures and time series models. The data set used comes from daily observations from each one of the four subsystems that form the Brazilian Electricity Grid. However, the final task is to obtain unique monthly series for the entire grid, and not only the four subsystems. The quarterly GDP series was used to check the performance of the two proposed methods. It was noted that the adjustment di...
Revista de Administração de Empresas
Empirical studies have revealed that the conditional Capital Asset Pricing Model (CAPM) has a hig... more 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 studies proposed improving investment fund performance. The main contribution of this study is the assessment of Brazilian investment funds through traditional measures estimated from the CAPM model in state-space form with heteroscedastic and homoscedastic errors compared to alternative models, such as the unconditional CAPM and a four-factor model. Using a sample of stock funds from May 2005-April 2015, the results indicate that the conditional CAPM model produces better results than the alternative models, providing better performance evaluation practices for funds in both stock-picking and market-timing ability.
Pesquisa Operacional
This paper describes a study of the dispatch planning/scheduling process for inbound containers h... more 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 be moved in when clients are being served. The aim of this study was to determine the conditions required to ensure that all the containers are dispatched within the scheduled time window and so meet the clients' requirements. To this end, the performance indicators were identified and compared using simulations as an analytical tool. The results indicate that the shortest-processing-time (SPT) queueing discipline is preferable to the first-come-first-served (FCFS) discipline and that client arrivals can usefully be restricted to periods shorter than two hours in order to meet container-dispatch and service-quality objectives.
Physica A: Statistical Mechanics and its Applications
Numbers of studies have proved the significant influence of climate variables on hydrological ser... more Numbers of studies have proved the significant influence of climate variables on hydrological series. Considering the pivotal role of the hydroelectric power plants play in the electricity production in Brazil this paper considers the natural hydrological inflow data from 15 major basins and 8 climate variables containing 7 El Niño Southern Oscillation proxies and the sunspot numbers. The causal relationships between hydrological natural inflows and climate variables are investigated by adopting and comparing 5 different causality detection methods (Granger Causality test, Frequency Domain Causality test, Convergent Cross Mapping Causality test, Single Spectrum Analysis (SSA) Causality test and Periodic Autoregressive Model Causality test) that cover both well established and novel empirical approaches. Both time domain and frequency domain causality tests gain valid evidences of unidirectional causality for a group of series; CCM achieved unidirectional causality for 18% of pairs and overwhelmingly indicated the opposite direction of causality; a mixture of results are concluded by SSA causality test; PAR based causality test obtained six unidirectional causality, but only one is really significant.
Gestão & Produção
Resumo: No Brasil, o comportamento da carga, em especial do consumo de energia, tem sido amplamen... more Resumo: No Brasil, o comportamento da carga, em especial do consumo de energia, tem sido amplamente investigado nos últimos anos. Esse interesse, em geral, é devido à grande importância financeira e social desse insumo, pois sua falta pode causar todo tipo de dano ao país. O objetivo do presente trabalho é a geração de uma série mensal de carga elétrica livre das variações de ofensores não econômicos, no caso, calendário e temperatura. Foram comparadas duas abordagens com vistas à seleção da mais eficiente na remoção dos efeitos dos referidos ofensores: a primeira de natureza empírica e a segunda com características híbridas, utilizando métodos empíricos e modelos de Séries Temporais. Os dados utilizados são provenientes de observações diárias de cada um dos quatro subsistemas que integram o Sistema Interligado Nacional (SIN), porém a ideia é produzir séries mensais do SIN e não apenas de cada um dos subsistemas. A série trimestral do PIB foi utilizada para decidir qual abordagem me...
DYNA
Una parte fundamental del proceso de previsión probabilística de energía eólica es tener en cuent... more Una parte fundamental del proceso de previsión probabilística de energía eólica es tener en cuenta las previsiones de la velocidad del viento. Para obtener pronósticos probabilísticos precisos de la producción eólica ha sido desarrollada una metodología híbrida utilizando técnicas no paramétricas conocidas como SSA (Análisis Singular Espectral) y Estimación Condicional de la Densidad por Kernel (CKDE). SSA es empleada para predecir la velocidad del viento y CKDE para obtener previsiones probabilísticas de la energía eólica, dado que la generación de la energía eólica tiene una relación no lineal con la velocidad del viento y ambas son variables aleatorias distribuidas que siguen una función de densidad conjunta. Haciendo uso de una base de datos brasilera horaria que incluye la velocidad del viento y la energía eólica es ilustrada dicha metodología. Una vez que las previsiones de la velocidad del viento son obtenidas, los correspondientes pronósticos probabilísticos de la generación...
Procedia Computer Science, 2015
The importance of the residential class in the consumption of electricity in the Brazilian Electr... more The importance of the residential class in the consumption of electricity in the Brazilian Electric System (BES) can be recognized by its quantitative size, as it, in 2013, concentrates 27% of the total consumption and 85% among all consumers. Also, in this class are the main public policies such as subsidies for consumer units inhabited by low-income families, labelling and increased energy efficiency of appliances used in the home and others. This paper aims to model and forecast the Brazilian residential energy consumption, up to 2050, with Pegels exponential smoothing techniques. In addition to the forecasts with the best model in sample, an optimization procedure of the model's hyper parameters is carried out in order to adjust the projections provided by the Energy Research Company (ERC). The results obtained show that it is possible to predict satisfactorily the electricity consumption for the proposed horizon with minimum error in sample. And the exercise of optimization proved to be important for providing level and trend equations for the official expectations regarding the residential electricity consumption in Brazil.
Procedia Computer Science, 2015
Energy planning and management have always represented a great challenge for most countries all o... more Energy planning and management have always represented a great challenge for most countries all over the world. Since the beginning of industrial revolution, one of the main bottlenecks to economy growth was energy availability, not just due to electricity shortage but also to the scarcity of other energy resources. So the necessity to construct methodologies and procedures to predict electricity needs became prominent and a major issue both for academics, government and electricity companies. Based on the methodologies and framework constructed, it is possible to define what actions should be taken to fulfill the electricity demanded by the society. The objective of the article represents the first step towards understanding and analyzing the state of art of models applied to electricity long-term forecasts, which is to define and apply a concise methodology to make a systematic review on academic articles from indexed journals.
arXiv: Applications, 2020
Forecasting has always been in the forefront of decision making and planning. The uncertainty tha... more Forecasting has always been in 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 lack of a free-lunch theorem implies the need for a diverse set of forecasting methods to tackle an array of applications. This unique article provides a non-systematic review of the theory and the practice of forecasting. We offer a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts, including operations, economics, finance, energy, environment, and social good. We do not claim that this review is an exhaustive list of methods and applications. The list was compiled based on the expertise and interests of the authors. However, we wish that our encyclopedic p...
International Journal of Productivity and Performance Management, 2016
Socio-Economic Planning Sciences, 2016
Renewable and Sustainable Energy Reviews, 2016
RESUMO No Brasil a geração de energia elétrica depende essencialmente dos aproveitamentos hidroel... more RESUMO No Brasil a geração de energia elétrica depende essencialmente dos aproveitamentos hidroelétricos, sendo as usinas termoelétricas a segunda maior fonte de geração de energia. No entanto, como essas têm custos mais elevados, é importante o estudo do comportamento das séries de vazões, objetivando otimizar as vazões fluviais. Estudos mostram ser bastante adequado para este tipo de dados o modelo Periódico Autorregressivo – PAR (p), cuja fase de identificação é importante e os métodos adotados nesta fase interferem no resultado final. Assim, este trabalho tem por finalidade discutir o melhor critério a ser adotado na fase de identificação do modelo autorregressivo periódico aplicado à série citada. Os dois critérios adotados se diferem por admitir ou não lags intermediários não significativos na fase de identificação. Ver-se-á que o critério que não utiliza os lags intermediários têm como resultado, cenários hidrológicos mais parcimoniosos e, por conseguinte, um aprimoramento do...
International Association for Statistical Education IASE 2015 Satellite Conference, Jul 22, 2015
We describe examples based on real wind speed data designed to introduce engineering students at
... more We describe examples based on real wind speed data designed to introduce engineering students at
the post-calculus level to statistical methods and theory with real engineering problems. The
examples cover some steps of the traditional wind power data analysis in order to develop in the
student the data analysis capabilities and the statistical reasoning applied to the engineering
problems.
Energy Economics, 2015
ABSTRACT
Electric Power Systems Research, 2015
ABSTRACT One of the most important techniques used to study long-term energy operation planning i... more ABSTRACT One of the most important techniques used to study long-term energy operation planning is the stochastic dual dynamic programme (SDDP). In large systems, hydraulic power plants are aggregated in so-called equivalent energy systems, where the inflows into hydro reservoirs are represented by the affluent natural energy (ANE) and the stored volumes are represented by the stored energy. The stochasticity of energy inflows is captured by the historical series ANE. Currently, ANEs are studied using the Box–Jenkins methodology to fit periodic autoregressive models (PAR(p)) and their order (p). A three-parameter log-normal distribution is applied to the residuals generated via PAR(p) modelling to generate synthetic hydrological series similar to the original historical series. However, the log-normal transformation incorporates non-linearities that affect the convergence in SDDP. This study incorporates the bootstrap statistical technique to determine the order p of the PAR(p) model to generate synthetic scenarios that will serve as a basis for SDDP application. The results indicate the adherence of the proposed method on the operational planning of hydrothermal systems. The proposed methodology in this article could successfully be applied in hydro-dominated systems such as Brazilian, Canadian and Nordic systems.
International Journal of Electrical Power & Energy Systems, 2015
ABSTRACT Given the dependence on hydrologic regimes, the uncertainty in energy planning in Brazil... more ABSTRACT Given the dependence on hydrologic regimes, the uncertainty in energy planning in Brazil requires adequate and coherent stochastic modelling. The structure used to simulate synthetic series in the current Brazilian Electrical Sector model generates nonlinearity in the model equation via lognormal distribution adopted for the model residuals. This nonlinearity can cause non-convexity problems in calculating the Cost to Go Functions, which are formed by convex polyhedral approximation through piecewise linear functions. Given the above considerations, the stochastic model characteristics used to generate a scenarios tree and its use in optimisation models, this study proposes the development of an alternative methodology for scenario construction. Thus, a new general approach is proposed for constructing trees used in the stochastic optimisation processes. This simulation structure combines the computationally intensive Bootstrap technique and Monte Carlo simulation method. Scenario trees were generated using a time horizon consistent with the long-term hydrothermal dispatch planning. The synthetic series were compared to the historical series through statistical tests, which demonstrated that the developed model was sustainable during the stochastic portion of the experiment. Finally, the tree paths were applied to the Stochastic Dual Dynamic Programming, and various response variables were analysed. Such analysis support the conclusion that the model herein can reproduce structures that are compatible with the current model without nonlinearity in the stochastic model equation and non-convexity in the Cost to Go Functions.
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Papers by Fernando Luiz Cyrino Oliveira
the post-calculus level to statistical methods and theory with real engineering problems. The
examples cover some steps of the traditional wind power data analysis in order to develop in the
student the data analysis capabilities and the statistical reasoning applied to the engineering
problems.
the post-calculus level to statistical methods and theory with real engineering problems. The
examples cover some steps of the traditional wind power data analysis in order to develop in the
student the data analysis capabilities and the statistical reasoning applied to the engineering
problems.