@article{nicoli_faria_queiroz_savoldi_2024, title={Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system}, volume={101}, ISSN={["2352-1538"]}, DOI={10.1016/j.est.2024.113814}, journal={JOURNAL OF ENERGY STORAGE}, author={Nicoli, Matteo and Faria, Victor Augusto Duraes and Queiroz, Anderson Rodrigo and Savoldi, Laura}, year={2024}, month={Nov} }
@misc{aquila_scianni morais_faria_marangon lima_marangon lima_queiroz_2023, title={An Overview of Short-Term Load Forecasting for Electricity Systems Operational Planning: Machine Learning Methods and the Brazilian Experience}, volume={16}, ISSN={["1996-1073"]}, url={https://publons.com/wos-op/publon/62637895/}, DOI={10.3390/en16217444}, abstractNote={The advent of smart grid technologies has facilitated the integration of new and intermittent renewable forms of electricity generation in power systems. Advancements are driving transformations in the context of energy planning and operations in many countries around the world, particularly impacting short-term horizons. Therefore, one of the primary challenges in this environment is to accurately provide forecasting of the short-term load demand. This is a critical task for creating supply strategies, system reliability decisions, and price formation in electricity power markets. In this context, nonlinear models, such as Neural Networks and Support Vector Machines, have gained popularity over the years due to advancements in mathematical techniques as well as improved computational capacity. The academic literature highlights various approaches to improve the accuracy of these machine learning models, including data segmentation by similar patterns, input variable selection, forecasting from hierarchical data, and net load forecasts. In Brazil, the national independent system operator improved the operation planning in the short term through the DESSEM model, which uses short-term load forecast models for planning the day-ahead operation of the system. Consequently, this study provides a comprehensive review of various methods used for short-term load forecasting, with a particular focus on those based on machine learning strategies, and discusses the Brazilian Experience.}, number={21}, journal={ENERGIES}, author={Aquila, Giancarlo and Scianni Morais, Lucas Barros and Faria, Victor Augusto and Marangon Lima, Jose Wanderley and Marangon Lima, Luana Medeiros and Queiroz, Anderson Rodrigo}, year={2023}, month={Nov} }
@article{faria_queiroz_decarolis_2023, title={Scenario generation and risk-averse stochastic portfolio optimization applied to offshore renewable energy technologies}, volume={270}, ISSN={["1873-6785"]}, url={https://publons.com/wos-op/publon/52521455/}, DOI={10.1016/J.ENERGY.2023.126946}, abstractNote={This work proposes an analytical decision-making framework considering scenario generation using artificial neural networks and risk-averse stochastic programming to define renewable offshore portfolios of wind, wave, and ocean current technologies. For the scenario generation, a generative adversarial neural network is developed to generate synthetic energy scenarios considering resources distributed over large geographic regions. These scenarios are then fed to a stochastic model, which objective to determine the optimal location and number of turbines for each technology. In the stochastic model formulation, a representation of the limits in the portfolio Levelized Cost of Energy and the maximization of the five percent lower energy generation conditions, also known as Conditional Value at Risk, is presented. The framework proposed here is tested considering data from a portion of the U.S. East coast, where the generative model was successful in creating energy scenarios statistically consistent with the historical data for wind, wave, and ocean current resources at more than 500 sites. Furthermore, the Conditional Value at Risk portfolio optimization model was used to construct efficient frontiers for a combination of different technologies, showing the significance of resource diversification as a tool to improve system security.}, journal={ENERGY}, publisher={Elsevier BV}, author={Faria, Victor A. D. and Queiroz, Anderson Rodrigo and DeCarolis, Joseph F.}, year={2023}, month={May} }
@article{morais_aquila_faria_lima_lima_queiroz_2023, title={Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system}, volume={348}, ISSN={["1872-9118"]}, url={https://publons.com/wos-op/publon/53188330/}, DOI={10.1016/j.apenergy.2023.121439}, abstractNote={This paper focuses on the development of shallow and deep neural networks in the form of multi-layer perceptron, long-short term memory, and gated recurrent unit to model the short-term load forecasting problem. Different model architectures are tested, and global climate model information is used as input to generate more accurate forecasts. A real study case is presented for the Brazilian interconnected power system and the results generated are compared with the forecasts from the Brazilian Independent System Operator model. In general terms, results show that the bidirectional versions of long-short term memory and gated recurrent unit produce better and more reliable predictions than the other models. From the obtained results, the recurrent neural networks reach Nash-Sutcliffe values up to 0.98, and mean absolute percentile error values of 1.18%, superior than the results obtained by the Independent System Operator models (0.94 and 2.01% respectively). The better performance of the neural network models is confirmed under the Diebold-Mariano pairwise comparison test.}, journal={APPLIED ENERGY}, author={Morais, Lucas Barros Scianni and Aquila, Giancarlo and Faria, Victor Augusto Duraes and Lima, Luana Medeiros Marangon and Lima, Jose Wanderley Marangon and Queiroz, Anderson Rodrigo}, year={2023}, month={Oct} }
@article{faria_queiroz_de carolis_2022, title={Optimizing offshore renewable portfolios under resource variability}, volume={326}, ISSN={["1872-9118"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85138794334&partnerID=MN8TOARS}, DOI={10.1016/j.apenergy.2022.120012}, abstractNote={The deployment of offshore wind, wave, and ocean current technologies can be coordinated to provide maximum economic benefit. We develop a model formulation based on Mean-Variance portfolio theory to identify the optimal site locations for a given number of wind, wave, and ocean current turbines subject to constraints on their energy collection system and the maximum number of turbines per site location. A model relaxation is also developed to improve the computational efficiency of the optimization process, allowing the inclusion of more than 5000 candidate generation sites. The model is tested using renewable resource estimates from the coast of North Carolina, along the eastern US coast. Different combinations of technology-specific offshore technologies are compared in terms of their levelized cost of electricity and energy variability. The optimal portfolio results are then included in a capacity expansion model to derive economic targets that make the offshore portfolios cost-competitive with other generating technologies. Results of this work indicate that the integration of different offshore technologies can help to decrease the energy variability associated with marine energy resources. Furthermore, this research shows that substantial cost reductions are still necessary to realize the deployment of these technologies in the region investigated.}, journal={APPLIED ENERGY}, publisher={Elsevier BV}, author={Faria, Victor A. D. and Queiroz, Anderson R. and De Carolis, Joseph F.}, year={2022}, month={Nov} }
@article{faria_queiroz_lima_lima_silva_2021, title={An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems}, volume={19}, ISSN={["1735-2630"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85111100097&partnerID=MN8TOARS}, DOI={10.1007/s13762-021-03565-y}, number={7}, journal={INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY}, publisher={Springer Science and Business Media LLC}, author={Faria, V. A. D. and Queiroz, A. R. and Lima, L. M. and Lima, J. W. M. and Silva, B. C.}, year={2021}, month={Jul} }
@article{faria_bernardes_bortoni_2020, title={Parameter estimation of synchronous machines considering field voltage variation during the sudden short-circuit test}, volume={114}, url={http://dx.doi.org/10.1016/j.ijepes.2019.105421}, DOI={10.1016/j.ijepes.2019.105421}, abstractNote={This work examines the influence of field voltage variation during a sudden short-circuit test and its direct impact on the parameter identification of synchronous machines. The test standards establish that field voltage must be kept constant during the short-circuit test. However, due to the presence of impedances in the voltage supply, control of the excitation system along with many other factors, field voltage may vary during this test. This work proposes a method to recover the machine parameters even when high amplitude field voltage variations are presented during the sudden short-circuit test. In addition, an algorithm capable of defining maximum field voltage variations along with its correspondent duration in order to respect a certain parameter estimation error is proposed. Finally, the models developed in this paper are investigated using data from a 140 MVA synchronous machine.}, journal={International Journal of Electrical Power & Energy Systems}, author={Faria, V.A.D. and Bernardes, J.V. and Bortoni, E.C.}, year={2020}, month={Jan} }
@article{energy system planning considering renewables and pumped-storage power plants_2019, url={https://publons.com/wos-op/publon/65805759/}, DOI={10.36040/IJSGSET.V1I2.206}, abstractNote={Renewables will play an important role in the generation for the next decades, but the great problem they face is the intermittency of the natural resource availability, mainly when considering solar and wind generation. In this context, the pumped-storage finds a great opportunity. Its operation consists of two mains mechanisms: to pump water to be stored in an upper reservoir when there is surplus of energy in the system, and to generate as a regular power plant, with the stored water, when there is a lack of energy in the system. This paper presents an introductory with a revision of the world consumption and capacity of 2030 considering the parcel of renewables, and a simulation of several possibilities of the energy mix in various Scenarios. The simulations consider mainly the contribution of pumped-storage hydro. The possible arrangements of construction pumped-storage hydro, costs, and a mathematical model of linear optimization using pumped-storage are analyzed and presented. The developed method is applied to several Scenarios and the conclusions are obtained from that.}, journal={International Journal of Smart Grid and Sustainable Energy Technologies}, year={2019} }
@inproceedings{faria_de queiroz_lima_lima_2018, title={Analysis of multiple solutions in the calculus of firm energy}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85050202742&partnerID=MN8TOARS}, DOI={10.1109/SBSE.2018.8395694}, abstractNote={This paper uses a linear optimization model to investigate the calculus of firm energy rights of hydro power plants in Brazil. The firm energy values influence directly in the remuneration of the Brazilian hydro plants, besides that, linear optimization models are widely used in the literature for studies of firm energy. In this work, the authors show that the linear optimization models used in the calculus of firm energy rights can present multiple optimal solutions, more specifically, that it is possible to solve the problem to optimality and find different individual firm energy values, this behavior is not desirable in the firm energy models since this parameter impacts directly in the remuneration of the hydro plants. Using data from the Brazilian Electrical System the authors could determine the intensity of these multiple optimal solutions in an example, the results show that the phenomenon is relevant, influencing significantly in the firm energy values.}, booktitle={SBSE 2018 - 7th Brazilian Electrical Systems Symposium}, author={Faria, V.A.D. and De Queiroz, A.R. and Lima, L.M.M. and Lima, J.W.M.}, year={2018}, pages={1–6} }
@article{faria_queiroz_lima_lima_2018, title={Cooperative game theory and last addition method in the allocation of firm energy rights}, volume={226}, ISSN={["1872-9118"]}, url={http://dx.doi.org/10.1016/j.apenergy.2018.06.065}, DOI={10.1016/j.apenergy.2018.06.065}, abstractNote={The firm energy rights of a hydro plant is a parameter used in some electricity markets to define the maximum amount of energy that a power plant can trade through contracts. In a centralized dispatch scheme, the coordinated operation of the hydro plants generates a synergetic gain in the system firm energy, in this setting, a question that often arises is how to fairly allocate this energy among each hydro plant. This work proposes a formulation to compute the firm energy rights of hydro plants using cooperative game theory and the last addition allocation method. The main goal is to integrate the interests of hydro agents with the needs of the regulatory agencies, searching in the core of the game for solutions that give the right incentives to the optimal system development. In order to make simulations of real instances possible, it is proposed a reformulation of the traditional mixed integer linear programming model that computes the core constraints, which induces a significant speed-up of the algorithm solution time. It is shown an application of the proposed methodology to a real instance representing the Brazilian electric power system.}, journal={APPLIED ENERGY}, author={Faria, Victor. A. D. and Queiroz, Anderson Rodrigo and Lima, Luana M. M. and Lima, Jose W. M.}, year={2018}, month={Sep}, pages={905–915} }
@article{bortoni_bernardes_silva_faria_vieira_2019, title={Evaluation of manufacturers strategies to obtain high-efficient induction motors}, volume={31}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85058820204&partnerID=MN8TOARS}, DOI={10.1016/j.seta.2018.12.022}, abstractNote={This paper presents a study on how manufacturers are working to comply with the minimum energy performance standards in three-phase squirrel-cage induction-motors. One of the possibilities is to reduce the stator and rotor resistances, and to increase the magnetizing branch resistance. A method to obtain the parameters of the equivalent circuit of the induction motor from the catalog data sheet is shown. A new method to separate the short-circuit reactance in stator and rotor components, based on start-up and breakdown torques, is presented. The variation in rotor parameters as a function of the slip is conveniently accounted for. The proposed methodology is applied to several motors from different manufacturers of significant influence in the European market. The main parameters that affect losses and energy efficiency of motors are compared, establishing an idea on how each of these manufacturers acts to meet energy efficiency requirements.}, journal={Sustainable Energy Technologies and Assessments}, author={Bortoni, E.C. and Bernardes, J.V. and Silva, P.V.V. and Faria, V.A.D. and Vieira, P.A.V.}, year={2019}, pages={221–227} }
@article{queiroz_faria_lima_lima_2019, title={Hydropower revenues under the threat of climate change in Brazil}, volume={133}, ISSN={["0960-1481"]}, url={http://dx.doi.org/10.1016/j.renene.2018.10.050}, DOI={10.1016/j.renene.2018.10.050}, abstractNote={This work analyzes the impacts of climate change in the revenues of hydropower plants. One important input for designing and evaluating investment opportunities in hydropower is the water inflows historical data. Unfortunately, the use of such information alone may not project well the future power generation due to the influence of climate change in the water inflow patterns. This paper introduces spatio-temporal information of the future climate into the operational planning of the Brazilian hydropower system. Global climate models from IPCC are considered along with downscaled regional climate models. Our results at the individual hydro plant level show the importance of taking into account climate change information when performing hydro generation planning studies.}, journal={RENEWABLE ENERGY}, publisher={Elsevier BV}, author={Queiroz, Anderson Rodrigo and Faria, Victor A. D. and Lima, Luana M. M. and Lima, Jose W. M.}, year={2019}, month={Apr}, pages={873–882} }