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Graduated in Economics at Pontificia Universidade Católica de Campinas (PUCCAMP) and Msc and Phd in Production Engineering at Federal Itajubá University (UNIFEI). He is currently a postdoctoral fellow in Economics in the Electro-Energy Sector at UNIFEI and works in consulting and R&D projects in energy economics and Regulatory Impact Analysis (RIA).
In 2018, A Regulatory Impact Analysis (RIA) was launched to review the Brazil's prosumer remuneration scheme in Brazil. Six policy alternatives that can impose different financial risks on photovoltaic prosumers, including whether or not there are complementary incentives, are considered. Policy implications are based on an analysis of the financial risk to prosumers in São Paulo state in terms of the Conditional Value at Risk of Net Present Value. The results reveal that additional financial incentives can mitigate the financial risk of some alternatives. Some alternatives impose financial risk that may discourage new prosumers in some of the São Paulo regions studied.
Eden de Oliveira Pinto Coelho; Giancarlo Aquila; Benedito Donizeti Bonatto; Pedro Paulo Balestrassi; Edson De Oliveira Pamplona; Wilson Toshiro Nakamura. Regulatory impact of photovoltaic prosumer policies in Brazil based on a financial risk analysis. Utilities Policy 2021, 70, 101214 .
AMA StyleEden de Oliveira Pinto Coelho, Giancarlo Aquila, Benedito Donizeti Bonatto, Pedro Paulo Balestrassi, Edson De Oliveira Pamplona, Wilson Toshiro Nakamura. Regulatory impact of photovoltaic prosumer policies in Brazil based on a financial risk analysis. Utilities Policy. 2021; 70 ():101214.
Chicago/Turabian StyleEden de Oliveira Pinto Coelho; Giancarlo Aquila; Benedito Donizeti Bonatto; Pedro Paulo Balestrassi; Edson De Oliveira Pamplona; Wilson Toshiro Nakamura. 2021. "Regulatory impact of photovoltaic prosumer policies in Brazil based on a financial risk analysis." Utilities Policy 70, no. : 101214.
This present study proposes to investigate whether the classification based on deterministic LCOE (Levelized Cost of Electricity) for PV microgeneration in twenty cities in Minas Gerais (Brazil) presents differences in relation to risk classification, based on a stochastic approach, namely CVaR-LCOE (Conditional Value at Risk – LCOE). In this stochastic approach, the Conditional Value at Risk (CVaR) is calculated with 99.9% confidence level for 5000 LCOE values for each city, generated by Monte Carlo Simulation. CVaR-LCOE results show a significant difference in ranking in relation to the deterministic approach. Diamantina city presented the best expected LCOE and the best CVaR-LCOE results. However, the cities located in Zona da Mata (Muriaé, Juiz de Fora and Manhuaçu) are the worst in the deterministic ranking, but in CVaR-LCOE approach, Juiz de Fora and Manhuaçu results are better than Ipatinga, Governador Valadares, and Poços de Caldas, this last one which presents the worst CVaR-LCOE. It is also clear that in the CVaR-LCOE ranking, the cities in different regions appear in more shuffle positions in the ranking, the opposite was observed in the deterministic ranking. Cities with the lowest LCOE standard deviation had the best classification changes among the two rankings.
Giancarlo Aquila; Eden de Oliveira Pinto Coelho; Benedito Donizeti Bonatto; Edson De Oliveira Pamplona; Wilson Toshiro Nakamura. Perspective of uncertainty and risk from the CVaR-LCOE approach: An analysis of the case of PV microgeneration in Minas Gerais, Brazil. Energy 2021, 226, 120327 .
AMA StyleGiancarlo Aquila, Eden de Oliveira Pinto Coelho, Benedito Donizeti Bonatto, Edson De Oliveira Pamplona, Wilson Toshiro Nakamura. Perspective of uncertainty and risk from the CVaR-LCOE approach: An analysis of the case of PV microgeneration in Minas Gerais, Brazil. Energy. 2021; 226 ():120327.
Chicago/Turabian StyleGiancarlo Aquila; Eden de Oliveira Pinto Coelho; Benedito Donizeti Bonatto; Edson De Oliveira Pamplona; Wilson Toshiro Nakamura. 2021. "Perspective of uncertainty and risk from the CVaR-LCOE approach: An analysis of the case of PV microgeneration in Minas Gerais, Brazil." Energy 226, no. : 120327.
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.
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 StyleGabriel 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 StyleGabriel 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.
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.
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 StyleLuiz 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 StyleLuiz 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.
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.
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 StyleGiancarlo 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 StyleGiancarlo 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.
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.
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 StyleRômulo 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 StyleRômulo 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.
This study proposes a Real Options approach to investigate the economic feasibility of a wind power plant investment with the option of abandoning along the project life cycle. This novel approach considers uncertainties representation concerning electricity sales revenue in the spot market, and the uncertainty represented by the settlements of energy trading differences. Our results show that when considering these uncertainties, the abandonment option adds 30.3% to the value of the project, and the chance of not abandoning it until the end of the useful life is equal to 70.9%.
G. Aquila; A.R. de Queiroz; P.P. Balestrassi; P. Rotella Junior; L.C.S. Rocha; E.O. Pamplona; W.T. Nakamura. Wind energy investments facing uncertainties in the Brazilian electricity spot market: A real options approach. Sustainable Energy Technologies and Assessments 2020, 42, 100876 .
AMA StyleG. Aquila, A.R. de Queiroz, P.P. Balestrassi, P. Rotella Junior, L.C.S. Rocha, E.O. Pamplona, W.T. Nakamura. Wind energy investments facing uncertainties in the Brazilian electricity spot market: A real options approach. Sustainable Energy Technologies and Assessments. 2020; 42 ():100876.
Chicago/Turabian StyleG. Aquila; A.R. de Queiroz; P.P. Balestrassi; P. Rotella Junior; L.C.S. Rocha; E.O. Pamplona; W.T. Nakamura. 2020. "Wind energy investments facing uncertainties in the Brazilian electricity spot market: A real options approach." Sustainable Energy Technologies and Assessments 42, no. : 100876.
This study proposes an approach to help the bidding processes of hiring wind-photovoltaic farms in long-term energy auctions. The proposed approach aims to define an optimal solution to configure wind-photovoltaic farms based on mixture design of experiments and the Lp method, as well as an efficiency metric designed to achieve diversification and to identify the Pareto dominant optimal portfolio. The proposed method is simple and flexible for practical applications. Moreover, its associated goals of choosing the Pareto dominant optimal solutions are aligned with the goals of the electricity regulators responsible to manage the hiring process for a new generation. To validate the method, wind-solar photovoltaic generation configurations in three Brazilian cities are analysed and the results are compared with other methods previously proposed in the literature. The results show that the proposed method has more intuitive criteria for the investor and regulator, without reducing the quality of the information provided to decision making.
Giancarlo Aquila; Anderson R. de Queiroz; Luana M.M. Lima; Pedro Paulo Balestrassi; J.W. Marangon Lima; Edson O. Pamplona. Modelling and design of wind‐solar hybrid generation projects in long‐term energy auctions: a multi‐objective optimisation approach. IET Renewable Power Generation 2020, 14, 2612 -2619.
AMA StyleGiancarlo Aquila, Anderson R. de Queiroz, Luana M.M. Lima, Pedro Paulo Balestrassi, J.W. Marangon Lima, Edson O. Pamplona. Modelling and design of wind‐solar hybrid generation projects in long‐term energy auctions: a multi‐objective optimisation approach. IET Renewable Power Generation. 2020; 14 (14):2612-2619.
Chicago/Turabian StyleGiancarlo Aquila; Anderson R. de Queiroz; Luana M.M. Lima; Pedro Paulo Balestrassi; J.W. Marangon Lima; Edson O. Pamplona. 2020. "Modelling and design of wind‐solar hybrid generation projects in long‐term energy auctions: a multi‐objective optimisation approach." IET Renewable Power Generation 14, no. 14: 2612-2619.
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.
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 StyleRômulo 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 StyleRômulo 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.
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.
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 StyleGiancarlo 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 StyleGiancarlo 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.
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.
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 StyleGiancarlo 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 StyleGiancarlo 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.
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.
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 StyleLiviam 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 StyleLiviam 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.
Recently, renewable energy projects, such as photovoltaic systems, have become interesting generation alternatives thanks to the incentive strategies developed by several countries. For the user of photovoltaic microgeneration, there is interest in the financial return of the investment, which is most often financed by public banks with a limited budget. Therefore, it is necessary to analyze variables related both to the point of view of the investor in microgeneration and to the public banks that subsidize them. However, defining the configuration of photovoltaic systems that guarantees the economic feasibility for those who invest without excessively burdening the public resource is a complex task and requires the analysis of different experts. To fill this gap, this paper proposes an innovative approach for evaluating photovoltaic projects based on Attribute Agreement Analysis. Experts on photovoltaic systems with different profiles and experience were asked about 16 scenarios, planned according to a factorial design with four factors: installed power capacity, PV cell type, debt ratio, and loan interest rate. The results demonstrated that the proposed approach fulfills the objective of simultaneously assessing the impact of investments in photovoltaic systems, considering the investors' and public banks’ viewpoints. In the case analyzed, although the evaluations are performed in a judicious way (Wwithin> 0.85), there is a low agreement between the experts (Woverall < 0.70). In addition, an expert bias was observed regarding loan interest for economic feasibility (W = 0.61), as well as a controversial perception of the maximization of social welfare (W = 0.2361). The Net Present Value profile, determined by the installed power capacity of the system, was used with these results to discuss the current Brazilian renewable energy financing policy. The results supported that experts tend to overestimate the impact of the financing interest rate on financial returns.
Lucas Guedes de Oliveira; Giancarlo Aquila; Pedro Paulo Balestrassi; Anderson Paulo de Paiva; Anderson Rodrigo de Queiroz; Edson De Oliveira Pamplona; Ulisses Pessin Camatta. Evaluating economic feasibility and maximization of social welfare of photovoltaic projects developed for the Brazilian northeastern coast: An attribute agreement analysis. Renewable and Sustainable Energy Reviews 2020, 123, 109786 .
AMA StyleLucas Guedes de Oliveira, Giancarlo Aquila, Pedro Paulo Balestrassi, Anderson Paulo de Paiva, Anderson Rodrigo de Queiroz, Edson De Oliveira Pamplona, Ulisses Pessin Camatta. Evaluating economic feasibility and maximization of social welfare of photovoltaic projects developed for the Brazilian northeastern coast: An attribute agreement analysis. Renewable and Sustainable Energy Reviews. 2020; 123 ():109786.
Chicago/Turabian StyleLucas Guedes de Oliveira; Giancarlo Aquila; Pedro Paulo Balestrassi; Anderson Paulo de Paiva; Anderson Rodrigo de Queiroz; Edson De Oliveira Pamplona; Ulisses Pessin Camatta. 2020. "Evaluating economic feasibility and maximization of social welfare of photovoltaic projects developed for the Brazilian northeastern coast: An attribute agreement analysis." Renewable and Sustainable Energy Reviews 123, no. : 109786.
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.
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 StyleLuiz 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 StyleLuiz 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.
This research considers the experience of Brazilian agencies with the application of complex Regulatory Impact Analysis (RIA) using based on quantitative methods of cost-benefit analysis. Public consultations with regulatory agencies were held to verify how the agencies have applied RIA. The collection of documents and information allows us to conclude that Brazilian agencies have little or no experience in conducting RIA with quantitative cost-benefit analysis.
Giancarlo Aquila; Edson De Oliveira Pamplona; José Alberto Ferreira Filho; Antônio Sergio Da Silva; João Victor De Azevedo Mataveli; João Ederson Correa; Mateus Sanches De Maria; Gustavo Cunha Garcia. Quantitative regulatory impact analysis: Experience of regulatory agencies in Brazil. Utilities Policy 2019, 59, 100931 .
AMA StyleGiancarlo Aquila, Edson De Oliveira Pamplona, José Alberto Ferreira Filho, Antônio Sergio Da Silva, João Victor De Azevedo Mataveli, João Ederson Correa, Mateus Sanches De Maria, Gustavo Cunha Garcia. Quantitative regulatory impact analysis: Experience of regulatory agencies in Brazil. Utilities Policy. 2019; 59 ():100931.
Chicago/Turabian StyleGiancarlo Aquila; Edson De Oliveira Pamplona; José Alberto Ferreira Filho; Antônio Sergio Da Silva; João Victor De Azevedo Mataveli; João Ederson Correa; Mateus Sanches De Maria; Gustavo Cunha Garcia. 2019. "Quantitative regulatory impact analysis: Experience of regulatory agencies in Brazil." Utilities Policy 59, no. : 100931.
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.
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 StylePaulo 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 StylePaulo 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.
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 StyleLiviam 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 StyleLiviam 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.
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.
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 StyleGiancarlo 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 StyleGiancarlo 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.
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 StyleLuiz 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 StyleLuiz 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.
The use of hybrid power generation systems is an attractive alternative to conventional fossil fuel generation since they may assist in mitigating the emission of gases that are harmful to the atmosphere when using clean and renewable sources of energy. However, finding the ideal configuration for the installation of a hybrid system composed of solar photovoltaic (PV)-diesel generation is a complex task. In this sense, the objective of this study is to develop an approach to select the optimal configuration of hybrid power generation systems for isolated regions by means of combining the techniques of Mixing Design of Experiments, Normal Boundary Intersection and analysis of super efficiency using Data Envelopment Analysis. The proposed approach is applied to a set of four isolated regions in the northern region of Brazil, more specifically in the state of Amazonas. The results show that for each region a different configuration is selected but with large shares of diesel generation at first. On the other hand, all these cases represent points in the Pareto frontier that are the most inefficient due to the high volume of CO2 emissions. From the application of the proposed approach, significant CO2 emission reductions are obtained by selecting the optimal configurations represented as the most efficient points in the Pareto frontier. Our results show that due to conflicting characteristics of the selected objectives, the installation of such hybrid power generation systems produces an increase in LCOE, mainly related to the high costs of the batteries, although less accentuated than the reductions in emissions.
Marcelo Nunes Fonseca; Edson De Oliveira Pamplona; Anderson Rodrigo de Queiroz; Victor Eduardo De Mello Valerio; Giancarlo Aquila; Saulo Ribeiro Silva. Multi-objective optimization applied for designing hybrid power generation systems in isolated networks. Solar Energy 2018, 161, 207 -219.
AMA StyleMarcelo Nunes Fonseca, Edson De Oliveira Pamplona, Anderson Rodrigo de Queiroz, Victor Eduardo De Mello Valerio, Giancarlo Aquila, Saulo Ribeiro Silva. Multi-objective optimization applied for designing hybrid power generation systems in isolated networks. Solar Energy. 2018; 161 ():207-219.
Chicago/Turabian StyleMarcelo Nunes Fonseca; Edson De Oliveira Pamplona; Anderson Rodrigo de Queiroz; Victor Eduardo De Mello Valerio; Giancarlo Aquila; Saulo Ribeiro Silva. 2018. "Multi-objective optimization applied for designing hybrid power generation systems in isolated networks." Solar Energy 161, no. : 207-219.