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Paulo Rotela Junior
Faculty of Finance and Accounting, Prague University of Economics and Business, 130 67 Prague, Czech Republic

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Review
Published: 27 April 2021 in Energies
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Sources such as solar and wind energy are intermittent, and this is seen as a barrier to their wide utilization. The increasing grid integration of intermittent renewable energy sources generation significantly changes the scenario of distribution grid operations. Such operational challenges are minimized by the incorporation of the energy storage system, which plays an important role in improving the stability and the reliability of the grid. This study provides the review of the state-of-the-art in the literature on the economic analysis of battery energy storage systems. The paper makes evident the growing interest of batteries as energy storage systems to improve techno-economic viability of renewable energy systems; provides a comprehensive overview of key methodological possibilities for researchers interested in economic analysis of battery energy storage systems; indicates the need to use adequate economic indicators for investment decisions; and identifies key research topics of the analyzed literature: (i) photovoltaic systems with battery energy storage systems for residential areas, (ii) comparison between energy storage technologies, (iii) power quality improvement. The last key contribution is the proposed research agenda.

ACS Style

Paulo Rotella Junior; Luiz Rocha; Sandra Morioka; Ivan Bolis; Gianfranco Chicco; Andrea Mazza; Karel Janda. Economic Analysis of the Investments in Battery Energy Storage Systems: Review and Current Perspectives. Energies 2021, 14, 2503 .

AMA Style

Paulo Rotella Junior, Luiz Rocha, Sandra Morioka, Ivan Bolis, Gianfranco Chicco, Andrea Mazza, Karel Janda. Economic Analysis of the Investments in Battery Energy Storage Systems: Review and Current Perspectives. Energies. 2021; 14 (9):2503.

Chicago/Turabian Style

Paulo Rotella Junior; Luiz Rocha; Sandra Morioka; Ivan Bolis; Gianfranco Chicco; Andrea Mazza; Karel Janda. 2021. "Economic Analysis of the Investments in Battery Energy Storage Systems: Review and Current Perspectives." Energies 14, no. 9: 2503.

Journal article
Published: 10 March 2021 in Energies
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Brazil is currently undergoing changes to regulations on distributed generation (DG), specifically for solar energy micro-generation. The changes proposed by the Brazilian Regulatory Agency suggest that only the cost of energy be compensated to investors. The service costs and other charges related to energy tariffs must be divided among consumers. Investors with existing installations and class entities have contested these proposals, calling them “sun-fees”. To date, no scientific papers have been published discussing these changes. The new regulations propose an end to cross subsidies, where all consumers (even those who do not have DG) pay for the transmission and distribution systems. This study compares the economic feasibility of micro-generation before and after implementing the new standards proposed by the regulatory agency. We used data on average electrical energy demand, energy price, and solar radiation in different regions. The national averages were used as a base comparison with other scenarios. The results show that projects are viable for all analyzed scenarios, however, after implementing the proposed changes, the discounted payback time is extended. This, however, does not make projects unfeasible.

ACS Style

Gabriel de Doile; Paulo Rotella Junior; Priscila Carneiro; Rogério Peruchi; Luiz Rocha; Karel Janda; Giancarlo Aquila. Economic Feasibility of Photovoltaic Micro-Installations Connected to the Brazilian Distribution Grid in Light of Proposed Changes to Regulations. Energies 2021, 14, 1529 .

AMA Style

Gabriel de Doile, Paulo Rotella Junior, Priscila Carneiro, Rogério Peruchi, Luiz Rocha, Karel Janda, Giancarlo Aquila. Economic Feasibility of Photovoltaic Micro-Installations Connected to the Brazilian Distribution Grid in Light of Proposed Changes to Regulations. Energies. 2021; 14 (6):1529.

Chicago/Turabian Style

Gabriel de Doile; Paulo Rotella Junior; Priscila Carneiro; Rogério Peruchi; Luiz Rocha; Karel Janda; Giancarlo Aquila. 2021. "Economic Feasibility of Photovoltaic Micro-Installations Connected to the Brazilian Distribution Grid in Light of Proposed Changes to Regulations." Energies 14, no. 6: 1529.

Journal article
Published: 21 February 2021 in Entropy
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The high proportion of CO2/CH4 in low aggregated value natural gas compositions can be used strategically and intelligently to produce more hydrocarbons through oxidative methane coupling (OCM). The main goal of this study was to optimize direct low-value natural gas conversion via CO2-OCM on metal oxide catalysts using robust multi-objective optimization based on an entropic measure to choose the most preferred Pareto optimal point as the problem’s final solution. The responses of CH4 conversion, C2 selectivity, and C2 yield are modeled using the response surface methodology. In this methodology, decision variables, e.g., the CO2/CH4 ratio, reactor temperature, wt.% CaO and wt.% MnO in ceria catalyst, are all employed. The Pareto optimal solution was obtained via the following combination of process parameters: CO2/CH4 ratio = 2.50, reactor temperature = 1179.5 K, wt.% CaO in ceria catalyst = 17.2%, wt.% MnO in ceria catalyst = 6.0%. By using the optimal weighting strategy w1 = 0.2602, w2 = 0.3203, w3 = 0.4295, the simultaneous optimal values for the objective functions were: CH4 conversion = 8.806%, C2 selectivity = 51.468%, C2 yield = 3.275%. Finally, an entropic measure used as a decision-making criterion was found to be useful in mapping the regions of minimal variation among the Pareto optimal responses and the results obtained, and this demonstrates that the optimization weights exert influence on the forecast variation of the obtained response.

ACS Style

Luiz Rocha; Mariana Rocha; Paulo Rotella Junior; Giancarlo Aquila; Rogério Peruchi; Karel Janda; Rômulo Azevêdo. Robust Multi-Objective Optimization for Response Surface Models Applied to Direct Low-Value Natural Gas Conversion Processes. Entropy 2021, 23, 248 .

AMA Style

Luiz Rocha, Mariana Rocha, Paulo Rotella Junior, Giancarlo Aquila, Rogério Peruchi, Karel Janda, Rômulo Azevêdo. Robust Multi-Objective Optimization for Response Surface Models Applied to Direct Low-Value Natural Gas Conversion Processes. Entropy. 2021; 23 (2):248.

Chicago/Turabian Style

Luiz Rocha; Mariana Rocha; Paulo Rotella Junior; Giancarlo Aquila; Rogério Peruchi; Karel Janda; Rômulo Azevêdo. 2021. "Robust Multi-Objective Optimization for Response Surface Models Applied to Direct Low-Value Natural Gas Conversion Processes." Entropy 23, no. 2: 248.

Journal article
Published: 16 February 2021 in Renewable and Sustainable Energy Reviews
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This present study proposes the stochastic approach Omega-LCOE to compare a Levelized Costa of Electricity (LCOE) between different locations. To validate the proposed approach, an investigation to compare the wind energy LCOE of 63 main cities in São Paulo state (Brazil) in relation to world LCOE average. Therefore, the Omega value estimated by a ratio of potential gains (costs reductions) and losses (costs inflations) in relation to a benchmarking (world LCOE average) is calculated for each city, based on 10,000 values of LCOE obtained by Simulation of Monte Carlo. Omega-LCOE results shows significant differences from results obtained by deterministic LCOE. Eight cities that presented LCOE below the world average from a deterministic approach, prove to be superior to the world average through the Omega-LCOE approach. Jundiaí, Franco da Rocha and Guarulhos present a deterministic LCOE higher than several cities, however when analyzing the uncertainties and risks these cities appear among those with the best LCOE performance in São Paulo state. In addition, it is observed that most cities in North and Northeast of São Paulo present LCOE performance better than world LCOE average, proving that these regions have the best wind potential in state. In turn, the South of São Paulo and the region called Vale do Paraíba present the worst results, being considered the highest cost places to install wind farms in São Paulo.

ACS Style

Giancarlo Aquila; Wilson Toshiro Nakamura; Paulo Rotella Junior; Luiz Celio Souza Rocha; Edson De Oliveira Pamplona. Perspectives under uncertainties and risk in wind farms investments based on Omega-LCOE approach: An analysis in São Paulo state, Brazil. Renewable and Sustainable Energy Reviews 2021, 141, 110805 .

AMA Style

Giancarlo Aquila, Wilson Toshiro Nakamura, Paulo Rotella Junior, Luiz Celio Souza Rocha, Edson De Oliveira Pamplona. Perspectives under uncertainties and risk in wind farms investments based on Omega-LCOE approach: An analysis in São Paulo state, Brazil. Renewable and Sustainable Energy Reviews. 2021; 141 ():110805.

Chicago/Turabian Style

Giancarlo Aquila; Wilson Toshiro Nakamura; Paulo Rotella Junior; Luiz Celio Souza Rocha; Edson De Oliveira Pamplona. 2021. "Perspectives under uncertainties and risk in wind farms investments based on Omega-LCOE approach: An analysis in São Paulo state, Brazil." Renewable and Sustainable Energy Reviews 141, no. : 110805.

Journal article
Published: 07 December 2020 in IEEE Access
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This study analyzes the concentration and conglomerate spatial distribution of forest-based thermoelectric plants in Brazil, in 2018. Herein, we spatially identified thermoelectric plants in different Brazilian regions and states, and measured the state concentrations (levels 1 and 2 of forest) using various indicators, including the concentration ratio (CR(k)), the Herfindahl-Hirschman index (HHI), Theil’s entropy (E), and the Gini coefficient (G). Meanwhile, each state’s conglomerates were evaluated using the Scan statistic. We found that there are 98 forest-base thermoelectric plants in Brazil, most of which are located in the south-central portion of the country where there is rapid forest growth. The southern region contains 32.65% of the identified plants as a result of the presence of level 2 forest resources (black liquor and forest waste). Regarding the state’s concentration (forest level 1), CR(k) revealed a moderate concentration, the HHI and E indices demonstrated low concentrations, and G suggested null to weak inequality. Of these Brazilian forest bioelectricity plants (level 1), 4 clusters were identified, but only one was statistically significant, located in the southern region. Concerning level 2 sources, the only statistically significant conglomerate regarding charcoal was centered in Açailândia (Maranhão). These findings will provide information to assist industry decision-making processes and help guide public policies for forest bioelectricity development in Brazil that favor energy security and improve resource utilization.

ACS Style

Luiz Moreira Coelho Junior; Edvaldo Pereira Santos Junior; Anna Manuella Melo Nunes; Flavio Jose Simioni; Raphael Abrahao; Paulo Rotella Junior. Concentration and Spatial Clustering of Forest-Based Thermoelectric Plants in Brazil. IEEE Access 2020, 8, 221932 -221941.

AMA Style

Luiz Moreira Coelho Junior, Edvaldo Pereira Santos Junior, Anna Manuella Melo Nunes, Flavio Jose Simioni, Raphael Abrahao, Paulo Rotella Junior. Concentration and Spatial Clustering of Forest-Based Thermoelectric Plants in Brazil. IEEE Access. 2020; 8 (99):221932-221941.

Chicago/Turabian Style

Luiz Moreira Coelho Junior; Edvaldo Pereira Santos Junior; Anna Manuella Melo Nunes; Flavio Jose Simioni; Raphael Abrahao; Paulo Rotella Junior. 2020. "Concentration and Spatial Clustering of Forest-Based Thermoelectric Plants in Brazil." IEEE Access 8, no. 99: 221932-221941.

Original article
Published: 30 November 2020 in Journal of Food Process Engineering
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In food industry, high variability is quite common due to seasonality of raw materials and perishable products. Statistical Process Control (SPC) is an effective methodology to reduce variability and to make predictable processes. Literature still lacks of practical approaches of SPC implementation in food operations. Thus, this paper aims to propose a SPC method for quality control of a packaging process of fruit pulp sachets. This method is based on phase I and II study of P control chart for process stability and capability assessment. In phase I, special causes of variation were found and corrected in order to prevent against recurrence. After eliminating special causes of variation, the process capability has been reported as 2 sigma quality level. In phase II, an online monitoring procedure has been implemented and there was no special causes of variation in the packaging operation, assuring process stability. Practical applications The proposed method provides to the production supervisor a very powerful and straightforward tool for quality control. Basically, if at any daily production the fraction of defectives goes below lower control limit or above upper control limit, immediately, the supervisor has to conduct the procedure for detecting special cause of variation. The proposed method was very successful for assuring process stability during online monitoring. The fraction of defectives items was remained in statistical control while the ongoing monitoring was being performed.

ACS Style

José Flávio Rique Junior; Rogério Santana Peruchi; Paulo Rotella Junior; Robson Bruno Dutra Pereira. Statistical process control of the vertical form, fill and seal packaging machine in food industry. Journal of Food Process Engineering 2020, 44, 1 .

AMA Style

José Flávio Rique Junior, Rogério Santana Peruchi, Paulo Rotella Junior, Robson Bruno Dutra Pereira. Statistical process control of the vertical form, fill and seal packaging machine in food industry. Journal of Food Process Engineering. 2020; 44 (2):1.

Chicago/Turabian Style

José Flávio Rique Junior; Rogério Santana Peruchi; Paulo Rotella Junior; Robson Bruno Dutra Pereira. 2020. "Statistical process control of the vertical form, fill and seal packaging machine in food industry." Journal of Food Process Engineering 44, no. 2: 1.

Journal article
Published: 02 November 2020 in Measurement
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This research presents an experimental study for measurement system analysis of angle of repose in fertilizers with variable granulometry (1.5 mm < d50 < 5.0 mm). In the literature, there are different procedures for determining this angle of repose, which often result on a variety of measurements for one measurand. Thus, the main objective of this work is to propose a method for measurement system validation of angle of repose. The statistical validation was based on Nested Gage Repeatability and Reproducibility (NGR&R) and the experiment was conceived through a technical apparatus built to measure the angle of repose of fertilizers. Experiments was conducted by using available resources in a typical industrial laboratory of fertilizer characterization. Among the measuring procedures, the fixed funnel has been used and an image analyzer software has been adopted to gather the data. The experiment was planned with 3 (three) operators, 10 (ten) samples with distinct granulometries and 3 (three) replicates. The result analysis has shown that the measurement error through the first measuring procedure was deemed unacceptable. After investigating the root cause of measurement error, a new standard measurement procedure was proposed. The new procedure was able to measure the angle of repose precisely, reducing measurement error from 59.93% to 4.82%.

ACS Style

I.S.B. Ferreira; R.S. Peruchi; N.J. Fernandes; P. Rotella Junior. Measurement system analysis in angle of repose of fertilizers with distinct granulometries. Measurement 2020, 170, 108681 .

AMA Style

I.S.B. Ferreira, R.S. Peruchi, N.J. Fernandes, P. Rotella Junior. Measurement system analysis in angle of repose of fertilizers with distinct granulometries. Measurement. 2020; 170 ():108681.

Chicago/Turabian Style

I.S.B. Ferreira; R.S. Peruchi; N.J. Fernandes; P. Rotella Junior. 2020. "Measurement system analysis in angle of repose of fertilizers with distinct granulometries." Measurement 170, no. : 108681.

Review paper
Published: 24 October 2020 in International Journal of Energy Research
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The growing energy demand in the world and the concern for environmentally damaging energy sources have led to an increased interest in seeking alternative renewable energy sources, such as wind energy. Furthermore, choosing effective locations for wind power plants has become a key issue in project planning. However, prior to implementation, such projects should be confirmed as economically viable. This article is a systematic review of the literature carried out with the aim to identify the main factors that impact the economic feasibility of wind energy investments. The search was performed in the ISI Web of Science (WoS) electronic database, from which 120 papers were extracted after a selection process, and were analyzed individually. As a result of the review analysis, 23 factors that have an impact on feasibility analysis were identified and organized in five categories: location (surface roughness, turbine location), economic (investment costs, operation and maintenance costs, avoided energy cost, depreciation, land rent), political (interest rates and taxes, energy sales price, inflation, financing conditions), climatic (wind speed, air density, temperature, air pressure), and technical (turbine height, installed wind power, lifetime, efficiency, rotor diameter, operation time, number of turbine blades, construction time). These factors can directly impact the cost of capital and/or energy production, affecting the economic viability of wind farms. In the last decade, there has been an exponential growth in publications about economic feasibility of wind investments. The wind investments growth has been accompanied by financial studies about this subject. This study provides insights on the main variables used in wind energy feasibility studies. The results may assist researchers and investors to identify the key parameters that are being examined in the literature, and to evaluate which ones should be considered in their study to ensure a sustainable development of power generation through the wind source.

ACS Style

Rômulo De Oliveira Azevêdo; Paulo Rotela Junior; Gianfranco Chicco; Giancarlo Aquila; Luiz Célio Souza Rocha; Rogério Santana Peruchi. Identification and analysis of impact factors on the economic feasibility of wind energy investments. International Journal of Energy Research 2020, 45, 3671 -3697.

AMA Style

Rômulo De Oliveira Azevêdo, Paulo Rotela Junior, Gianfranco Chicco, Giancarlo Aquila, Luiz Célio Souza Rocha, Rogério Santana Peruchi. Identification and analysis of impact factors on the economic feasibility of wind energy investments. International Journal of Energy Research. 2020; 45 (3):3671-3697.

Chicago/Turabian Style

Rômulo De Oliveira Azevêdo; Paulo Rotela Junior; Gianfranco Chicco; Giancarlo Aquila; Luiz Célio Souza Rocha; Rogério Santana Peruchi. 2020. "Identification and analysis of impact factors on the economic feasibility of wind energy investments." International Journal of Energy Research 45, no. 3: 3671-3697.

Review
Published: 02 September 2020 in Sustainability
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The introduction of environmental impact targets around the world has highlighted the need to adopt alternative sources of energy, which can supply the demand and mitigate the damage caused to the environment. Solar energy is one of the main sources of alternative energy, and is considered an abundant source of clean energy. However, to facilitate and encourage investors interested in the installation of photovoltaic energy systems for electricity production, it is essential to evaluate the factors that impact the economic viability of the projects. Therefore, the objective of this research is to present a systematic analytical framework, in order to identify and analyze the main factors that impact the financial feasibility of projects for the installation of photovoltaic energy plants. For this purpose, a systematic literature review was carried out, analyzing the main studies related to the topic and identifying the main factors that may financially affect investments in photovoltaic energy systems. From this review, 29 influencing factors were identified and separated into five categories, namely, location, economic, political, climatic and environmental, and technical factors. The main factors highlighted are the investment cost, power generation, operation and maintenance costs, solar radiation, lifetime, energy tariff, efficiency, electricity consumption, and interest and taxes. The results may assist policy makers, investors, researchers, and other stakeholders to identify the key factors that are being examined in the literature, and to evaluate which ones should be considered in their study to ensure the sustainable development of power generation through the solar source.

ACS Style

Rômulo De Oliveira Azevêdo; Paulo Rotela Junior; Luiz Rocha; Gianfranco Chicco; Giancarlo Aquila; Rogério Peruchi. Identification and Analysis of Impact Factors on the Economic Feasibility of Photovoltaic Energy Investments. Sustainability 2020, 12, 7173 .

AMA Style

Rômulo De Oliveira Azevêdo, Paulo Rotela Junior, Luiz Rocha, Gianfranco Chicco, Giancarlo Aquila, Rogério Peruchi. Identification and Analysis of Impact Factors on the Economic Feasibility of Photovoltaic Energy Investments. Sustainability. 2020; 12 (17):7173.

Chicago/Turabian Style

Rômulo De Oliveira Azevêdo; Paulo Rotela Junior; Luiz Rocha; Gianfranco Chicco; Giancarlo Aquila; Rogério Peruchi. 2020. "Identification and Analysis of Impact Factors on the Economic Feasibility of Photovoltaic Energy Investments." Sustainability 12, no. 17: 7173.

Journal article
Published: 23 June 2020 in Sustainable Energy Technologies and Assessments
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Methods for supporting the bidding processes of hybrid wind-photovoltaic (W-PV) farms are scarce, especially when numerous goals are included in the optimization problem. Therefore, the primary objective of this study is to develop a novel model that can help bidding of W-PV farms considering a range of objectives that maximize the environmental and welfare benefits. This new approach contributes to energy planning for any type of hybrid farm through multi-objective programming, even in cases where the optimization of several correlated outputs is desired. Using the proposed approach the optimal system configuration can be obtained in these cases with low computational costs. A non-linear multi-objective optimization (NL-MO) is proposed to optimize the area occupied by the W-PV farm, minimum feasibility price, electricity production expected, and standard-deviation of the electricity produced. The model has been elaborated from non-linear optimization using the normal-boundary intersection (NBI) method, exploratory factor analysis (EFA), and Taguchi signal-to-noise ratio (SNR). The optimal values for the response variables are an area of 132.92 km2, minimum price of 182.95 R$/MWh, annual electricity production of 72.17 GWh, with a standard deviation of 1.74 GWh and the ideal share is 41% wind power and 59% PV power.

ACS Style

Giancarlo Aquila; Anderson Rodrigo de Queiroz; Paulo Rotela Junior; Luiz Célio Souza Rocha; Edson De Oliveira Pamplona; Pedro Paulo Balestrassi. Contribution for bidding of wind-photovoltaic on grid farms based on NBI-EFA-SNR method. Sustainable Energy Technologies and Assessments 2020, 40, 100754 .

AMA Style

Giancarlo Aquila, Anderson Rodrigo de Queiroz, Paulo Rotela Junior, Luiz Célio Souza Rocha, Edson De Oliveira Pamplona, Pedro Paulo Balestrassi. Contribution for bidding of wind-photovoltaic on grid farms based on NBI-EFA-SNR method. Sustainable Energy Technologies and Assessments. 2020; 40 ():100754.

Chicago/Turabian Style

Giancarlo Aquila; Anderson Rodrigo de Queiroz; Paulo Rotela Junior; Luiz Célio Souza Rocha; Edson De Oliveira Pamplona; Pedro Paulo Balestrassi. 2020. "Contribution for bidding of wind-photovoltaic on grid farms based on NBI-EFA-SNR method." Sustainable Energy Technologies and Assessments 40, no. : 100754.

Journal article
Published: 08 June 2020 in IEEE Access
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Hard turning processes have several advantages against traditional turning. Improved surface integrity and short process time are some examples. Surface integrity is one of the most important issues in modeling of machining processes. Multiple roughness parameters are observed in relation to several controllable and uncontrollable input parameters. Since these multiple roughness parameters are correlated, multivariate methods are the most suitable approach for process control. This research aims to propose a method for assessing stability and performance of multivariate processes in the presence of noise variables. A hybrid method based on design of experiment, statistical process control and principal component analysis was applied to AISI 52100 hardened steel turning. The process performance index was obtained within the range of 0.18 to 1.11. The best process performance was achieved taking cutting speed of 170m/min and lubricating fluid flow of 3 L/min.

ACS Style

George Evangelista; Rogerio Santana Peruchi; Tarcisio Goncalves Brito; Paulo Rotela Junior; Luiz Celio Souza Rocha. A Multivariate Statistical Quality Control of AISI 52100 Hardened Steel Turning. IEEE Access 2020, 8, 109092 -109104.

AMA Style

George Evangelista, Rogerio Santana Peruchi, Tarcisio Goncalves Brito, Paulo Rotela Junior, Luiz Celio Souza Rocha. A Multivariate Statistical Quality Control of AISI 52100 Hardened Steel Turning. IEEE Access. 2020; 8 ():109092-109104.

Chicago/Turabian Style

George Evangelista; Rogerio Santana Peruchi; Tarcisio Goncalves Brito; Paulo Rotela Junior; Luiz Celio Souza Rocha. 2020. "A Multivariate Statistical Quality Control of AISI 52100 Hardened Steel Turning." IEEE Access 8, no. : 109092-109104.

Journal article
Published: 05 June 2020 in Renewable Energy
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One of the challenges of energy regulatory-agencies is to guide the agents decision-making process towards maximization of the overall welfare of the electricity sector. However, this is not a simple task since it requires meeting expectations of many stakeholders, from investors to consumers. This paper proposes an optimization methodology aimed at helping define the optimal combination of wind farm layout and type of equipment deployed, so that the electricity sector overall welfare is maximized in the process. The optimization objectives are (i) the energy density and (ii) the Net Present Value (NPV), and the parameters are (a) the power levels and (b) the selling price of the energy. The objective functions are modelled with the aid of a design-of-experiment technique known as Response Surface Methodology, relying on the multi-objective programming method of Normal Boundary Intersection for the optimization. The methodology is applied to four different scenarios arising from the combination of two different locations (Santa Vitória do Palmar-RS and Macau-RN, both in Brazil), and two different wind turbine manufacturers (A and B). The final step comprises the application of the Data Envelopment Analysis technique in order to sort one from the set of optimal solutions identified by the four different scenarios. The results show that the proposed methodology is capable of supporting bidding processes and wind farms certification programs, in line with what should be expected by regulatory agencies, investors and electricity consumers alike. The deployment of the methodology proved discriminant and allowed selection of one final scenario (Macau-RN, brand A equipment) as overall optimal. It was also observed that equipment efficiency is dependent on siting location.

ACS Style

Giancarlo Aquila; Luiz Célio Souza Rocha; Paulo Rotela Junior; Joseph Youssif Saab Junior; João De Sá Brasil Lima; Pedro Paulo Balestrassi. Economic planning of wind farms from a NBI-RSM-DEA multiobjective programming. Renewable Energy 2020, 158, 628 -641.

AMA Style

Giancarlo Aquila, Luiz Célio Souza Rocha, Paulo Rotela Junior, Joseph Youssif Saab Junior, João De Sá Brasil Lima, Pedro Paulo Balestrassi. Economic planning of wind farms from a NBI-RSM-DEA multiobjective programming. Renewable Energy. 2020; 158 ():628-641.

Chicago/Turabian Style

Giancarlo Aquila; Luiz Célio Souza Rocha; Paulo Rotela Junior; Joseph Youssif Saab Junior; João De Sá Brasil Lima; Pedro Paulo Balestrassi. 2020. "Economic planning of wind farms from a NBI-RSM-DEA multiobjective programming." Renewable Energy 158, no. : 628-641.

Journal article
Published: 17 April 2020 in IEEE Access
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To reduce the risks of a new energy crisis and increase energy availability, the use of renewable energy sources (RES) is important and recommended. In Brazil, micro and small companies contribute about 25% of gross domestic product (GDP), and electric energy is employed intensively, so the importance of microgeneration is observable. This research aims to analyze the economic viability of the micro-generation wind energy project for micro and small businesses. Thus, three Brazilian states, Rio Grande do Norte, Rio Grande do Sul and Minas Gerais were considered, and different scenarios were proposed. A feasibility analysis is then performed, followed by a stochastic analysis using Monte Carlo simulation (MCS). Finally, models of artificial neural networks (ANN) are used to evaluate the relative importance (RI) of the variables. The results show that none of the states appears economically feasible under the conditions presented. In the stochastic analysis, the probability of viability is between 17% and 24% in all states, which shows the low probability of viability for microgeneration. Through ANN training, it was possible to calculate the RI, in which it is possible to identify the variables that have most impact on the net present value (NPV) in all states; it is considered the most important variable in the project’s viability. In addition, the discussion explores the importance of public incentives for promoting investment in renewable energy, which can reduce investment costs and make it attractive to small and medium-sized businesses.

ACS Style

Liviam Soares Lacerda; Paulo Rotella Junior; Rogerio Santana Peruchi; Gianfranco Chicco; Luiz Celio Souza Rocha; Giancarlo Aquila; Luiz Moreira Coelho Junior. Microgeneration of Wind Energy for Micro and Small Businesses: Application of ANN in Sensitivity Analysis for Stochastic Economic Feasibility. IEEE Access 2020, 8, 73931 -73946.

AMA Style

Liviam Soares Lacerda, Paulo Rotella Junior, Rogerio Santana Peruchi, Gianfranco Chicco, Luiz Celio Souza Rocha, Giancarlo Aquila, Luiz Moreira Coelho Junior. Microgeneration of Wind Energy for Micro and Small Businesses: Application of ANN in Sensitivity Analysis for Stochastic Economic Feasibility. IEEE Access. 2020; 8 (99):73931-73946.

Chicago/Turabian Style

Liviam Soares Lacerda; Paulo Rotella Junior; Rogerio Santana Peruchi; Gianfranco Chicco; Luiz Celio Souza Rocha; Giancarlo Aquila; Luiz Moreira Coelho Junior. 2020. "Microgeneration of Wind Energy for Micro and Small Businesses: Application of ANN in Sensitivity Analysis for Stochastic Economic Feasibility." IEEE Access 8, no. 99: 73931-73946.

Original article
Published: 13 February 2020 in Engineering with Computers
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During the multi-objective optimization process, numerous efficient solutions may be generated to form the Pareto frontier. Due to the complexity of formulating and solving mathematical problems, choosing the best point to be implemented becomes a non-trivial task. Thus, this paper introduces a weighting strategy named robust optimal point selection, based on ratio diversification/error, to choose the most preferred Pareto optimal point in multi-objective optimization problems using response surface methodology. Furthermore, this paper proposes to explore a theoretical gap—the prediction variance behavior related to the weighting. The ratios Shannon’s entropy/error and diversity/error and the unscaled prediction variance are experimentally modeled using mixture design and the optimal weights for the multi-objective optimization process are defined by the maximization of the proposed measures. The study could demonstrate that the weights used in the multi-objective optimization process influence the prediction variance. Furthermore, the use of diversification measures, such as entropy and diversity, associated with measures of error, such as mean absolute percent error, was determined to be useful in mapping regions of minimum variance within the Pareto optimal responses obtained in the optimization process.

ACS Style

Luiz Célio Souza Rocha; Paulo Rotela Junior; Giancarlo Aquila; Anderson Paulo De Paiva; Pedro Paulo Balestrassi. Toward a robust optimal point selection: a multiple-criteria decision-making process applied to multi-objective optimization using response surface methodology. Engineering with Computers 2020, 1 -27.

AMA Style

Luiz Célio Souza Rocha, Paulo Rotela Junior, Giancarlo Aquila, Anderson Paulo De Paiva, Pedro Paulo Balestrassi. Toward a robust optimal point selection: a multiple-criteria decision-making process applied to multi-objective optimization using response surface methodology. Engineering with Computers. 2020; ():1-27.

Chicago/Turabian Style

Luiz Célio Souza Rocha; Paulo Rotela Junior; Giancarlo Aquila; Anderson Paulo De Paiva; Pedro Paulo Balestrassi. 2020. "Toward a robust optimal point selection: a multiple-criteria decision-making process applied to multi-objective optimization using response surface methodology." Engineering with Computers , no. : 1-27.

Journal article
Published: 11 February 2020 in IEEE Access
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DMAIC (define, measure, analyze, improve and control) is one of the most utilized methods for guiding practitioners in the decision-making process of quality improvement projects. Industrial processes commonly deal with multiple critical-to-quality (CTQ) characteristics. When these characteristics are correlated, multivariate statistical techniques should be applied. This paper aims to propose a domainspecific Six Sigma method, the MDMAIC (multivariate DMAIC). The new stepwise procedure helps practitioners not only to reduce problem dimension but also to take account of the correlation structure among CTQs during the decision-making process. Principal component analysis has been applied for assessing the measurement system, analyzing process stability and capability, as well as modeling and optimizing multivariate manufacturing processes. A hardened steel turning case has been presented for proposal validation. The result analysis has shown that the MDMAIC was very successful in leading the practitioner during the steps and phases of the quality improvement project. The multivariate capability index of the enhanced process emphasized the substantial economic improvement.

ACS Style

Rogerio Santana Peruchi; Paulo Rotela Junior; Tarcisio G. Brito; Anderson P. Paiva; Pedro P. Balestrassi; Lavinia M. Mendes Araujo. Integrating Multivariate Statistical Analysis Into Six Sigma DMAIC Projects: A Case Study on AISI 52100 Hardened Steel Turning. IEEE Access 2020, 8, 34246 -34255.

AMA Style

Rogerio Santana Peruchi, Paulo Rotela Junior, Tarcisio G. Brito, Anderson P. Paiva, Pedro P. Balestrassi, Lavinia M. Mendes Araujo. Integrating Multivariate Statistical Analysis Into Six Sigma DMAIC Projects: A Case Study on AISI 52100 Hardened Steel Turning. IEEE Access. 2020; 8 (99):34246-34255.

Chicago/Turabian Style

Rogerio Santana Peruchi; Paulo Rotela Junior; Tarcisio G. Brito; Anderson P. Paiva; Pedro P. Balestrassi; Lavinia M. Mendes Araujo. 2020. "Integrating Multivariate Statistical Analysis Into Six Sigma DMAIC Projects: A Case Study on AISI 52100 Hardened Steel Turning." IEEE Access 8, no. 99: 34246-34255.

Journal article
Published: 14 June 2019 in Energies
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Wind power has grown popular in past recent years due to environmental issues and the search for alternative energy sources. Thus, the viability for wind power generation projects must be studied in order to attend to the environmental concerns and still be attractive and profitable. Therefore, this article aims to perform a sensitive analysis in order to identify the variables that influence most in the viability of a wind power investment for small size companies in the Brazilian northeast. For this, a stochastic analysis of viability through Monte Carlo Simulation (MCS) will be made and afterwards, Artificial Neural Networks (ANN) models will be applied for the most relevant variables identification. Through the sensitivity, it appears that the most relevant factors in the analysis are the speed of wind, energy tariff and the investment amount. Thus, the viability of the investment is straightly tied to the region where the wind turbine is installed, and the government incentives may allow decreasing in the investment amount for wind power. Based on this, incentives programs for the production of clean energy include cheaper purchase of wind turbines, lower taxing and financing rates, can make wind power more profitable and attractive.

ACS Style

Paulo Rotela Junior; Eugenio Fischetti; Victor G. Araújo; Rogério S. Peruchi; Giancarlo Aquila; Luiz Célio S. Rocha; Liviam S. Lacerda. Wind Power Economic Feasibility under Uncertainty and the Application of ANN in Sensitivity Analysis. Energies 2019, 12, 2281 .

AMA Style

Paulo Rotela Junior, Eugenio Fischetti, Victor G. Araújo, Rogério S. Peruchi, Giancarlo Aquila, Luiz Célio S. Rocha, Liviam S. Lacerda. Wind Power Economic Feasibility under Uncertainty and the Application of ANN in Sensitivity Analysis. Energies. 2019; 12 (12):2281.

Chicago/Turabian Style

Paulo Rotela Junior; Eugenio Fischetti; Victor G. Araújo; Rogério S. Peruchi; Giancarlo Aquila; Luiz Célio S. Rocha; Liviam S. Lacerda. 2019. "Wind Power Economic Feasibility under Uncertainty and the Application of ANN in Sensitivity Analysis." Energies 12, no. 12: 2281.

Journal article
Published: 10 April 2019 in Measurement
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Measurement system analysis has a pivotal role in assessing the measuring error when conducting empirical studies. Gage Repeatability and Reproducibility (GR&R) studies are classic methods applied to evaluate measurement system adequacy for a particular application. However, previous published studies are limited to determine the source of measuring error related to not only reproducibility but also repeatability. Hence, the objective of this research is to propose new indicators for measurement error detection due to both repeatability and reproducibility variation in GR&R studies. These indicators were calculated using standardized scores from the analysis of variance. The proposed procedure has been applied not only to literature data but also to a stainless steel cladding process on surfaces of carbon steel. While literature method has detected only reproducibility error, the proposed procedure were able to detect both reproducibility and repeatability sources of measuring error.

ACS Style

Lavínia Maria Mendes Araújo; Rafael Gomes Nobrega Paiva; Rogério Santana Peruchi; Paulo Rotela Junior; José Henrique De Freitas Gomes. New indicators for measurement error detection in GR&R studies. Measurement 2019, 140, 557 -564.

AMA Style

Lavínia Maria Mendes Araújo, Rafael Gomes Nobrega Paiva, Rogério Santana Peruchi, Paulo Rotela Junior, José Henrique De Freitas Gomes. New indicators for measurement error detection in GR&R studies. Measurement. 2019; 140 ():557-564.

Chicago/Turabian Style

Lavínia Maria Mendes Araújo; Rafael Gomes Nobrega Paiva; Rogério Santana Peruchi; Paulo Rotela Junior; José Henrique De Freitas Gomes. 2019. "New indicators for measurement error detection in GR&R studies." Measurement 140, no. : 557-564.

Proceedings article
Published: 15 November 2018
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ACS Style

Liviam Soares Lacerda; Paulo Rotela Junior; Giancarlo Aquila; Luiz Rocha. Geração de energia eólica: Uma análise estocástica da viabilidade econômica para empresas de pequeno porte em três diferentes estados brasileiros. 2018, 1 .

AMA Style

Liviam Soares Lacerda, Paulo Rotela Junior, Giancarlo Aquila, Luiz Rocha. Geração de energia eólica: Uma análise estocástica da viabilidade econômica para empresas de pequeno porte em três diferentes estados brasileiros. . 2018; ():1.

Chicago/Turabian Style

Liviam Soares Lacerda; Paulo Rotela Junior; Giancarlo Aquila; Luiz Rocha. 2018. "Geração de energia eólica: Uma análise estocástica da viabilidade econômica para empresas de pequeno porte em três diferentes estados brasileiros." , no. : 1.

Journal article
Published: 07 September 2018 in Renewable and Sustainable Energy Reviews
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Owing to the wind and photovoltaic (PV) potential in Brazil, the country has recently seen increased exploration into the construction of wind-PV hybrid plants. However, as specific criteria for contracting this type of project have not yet been developed, this paper presents a model to assist the government in contracting projects that maximize the socioeconomic well-being of the Brazilian electricity sector. For this, multiobjective programming is used to simultaneously handle two objective functions—maximally reducing emission density and minimizing the levelized cost of electricity (LCOE)—with the aid of the mixture arrangement technique. In this respect, the optimization method called normal boundary intersection (NBI) is applied to solve the multiobjective problem and construct the Pareto frontier. Additionally, a metric based on the ratio between entropy and the global percentage error (GPE) is used to identify the optimal Pareto solution. The model was applied to determine optimal configurations for wind-PV powerplants in twelve Brazilian cities, and the results obtained reveal the capacity of the model to indicate the optimum configuration according to the wind and PV potential of each city.

ACS Style

Giancarlo Aquila; Luiz Célio Souza Rocha; Edson De Oliveira Pamplona; Anderson Rodrigo de Queiroz; Paulo Rotela Junior; Pedro Paulo Balestrassi; Marcelo Nunes Fonseca. Proposed method for contracting of wind-photovoltaic projects connected to the Brazilian electric system using multiobjective programming. Renewable and Sustainable Energy Reviews 2018, 97, 377 -389.

AMA Style

Giancarlo Aquila, Luiz Célio Souza Rocha, Edson De Oliveira Pamplona, Anderson Rodrigo de Queiroz, Paulo Rotela Junior, Pedro Paulo Balestrassi, Marcelo Nunes Fonseca. Proposed method for contracting of wind-photovoltaic projects connected to the Brazilian electric system using multiobjective programming. Renewable and Sustainable Energy Reviews. 2018; 97 ():377-389.

Chicago/Turabian Style

Giancarlo Aquila; Luiz Célio Souza Rocha; Edson De Oliveira Pamplona; Anderson Rodrigo de Queiroz; Paulo Rotela Junior; Pedro Paulo Balestrassi; Marcelo Nunes Fonseca. 2018. "Proposed method for contracting of wind-photovoltaic projects connected to the Brazilian electric system using multiobjective programming." Renewable and Sustainable Energy Reviews 97, no. : 377-389.

Journal article
Published: 01 July 2018 in Renewable and Sustainable Energy Reviews
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ACS Style

Luiz Rocha; Giancarlo Aquila; Paulo Rotella Junior; Anderson Paulo de Paiva; Edson Pamplona; Pedro Paulo Balestrassi. A stochastic economic viability analysis of residential wind power generation in Brazil. Renewable and Sustainable Energy Reviews 2018, 90, 412 -419.

AMA Style

Luiz Rocha, Giancarlo Aquila, Paulo Rotella Junior, Anderson Paulo de Paiva, Edson Pamplona, Pedro Paulo Balestrassi. A stochastic economic viability analysis of residential wind power generation in Brazil. Renewable and Sustainable Energy Reviews. 2018; 90 ():412-419.

Chicago/Turabian Style

Luiz Rocha; Giancarlo Aquila; Paulo Rotella Junior; Anderson Paulo de Paiva; Edson Pamplona; Pedro Paulo Balestrassi. 2018. "A stochastic economic viability analysis of residential wind power generation in Brazil." Renewable and Sustainable Energy Reviews 90, no. : 412-419.