Journal Publications

Bayesian Modeling and Mechanical Simulations for Fragility Curve Estimation of the Mooring System of Marine Hydrokinetic Devices

de Faria, V.A.D., Jamaleddin, N., de Queiroz, A.R., & Gabr, M. (2024). Bayesian modeling and mechanical simulations for fragility curve estimation of the mooring system of marine hydrokinetic devices. Applied Ocean Research, 153, 104243.

This work uses Bayesian modeling and mechanical model simulations through the Ansys-AQWA software to construct fragility curve estimates for marine hydrokinetic devices, more specifically, their mooring system. The fragility curves proposed here associate wind speed levels with the risk of damage to the equipment and could be used to better understand the susceptibility of these devices to damage from hurricanes.

Modeling Energy Storage in Long-term Capacity Expansion Energy Planning: An Analysis of the Italian System

Nicoli, M., Faria, V. A. D., de Queiroz, A. R., & Savoldi, L. (2024). Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system. Journal of Energy Storage, 101, 113814.

This paper presents a framework to represent short-term operational phenomena associated with renewables capacity factors and final service demand distributions in a capacity-expansion and integrated energy system optimization model. The aim is to study the potential role of energy storage technologies coupled with renewable energy sources aiding the decarbonization of the overall energy system.

Diverse Decarbonization Pathways Under Near Cost-Optimal Futures

Sinha, A., Venkatesh, A., Jordan, K., Wade, C., Eshraghi, H., de Queiroz, A. R., Jaramillo, P., Johnson, J. X. (2024). Diverse decarbonization pathways under near cost-optimal futures. Nature Communications, 15(1), 8165.

This study uses modeling techniques to generate diverse near cost-optimal net-zero CO2 pathways for the United States’ energy system. Our findings reveal consistent trends across these pathways, including rapid expansion of solar and wind power generation, substantial petroleum use reductions, near elimination of coal combustion, and increased end-use electrification.

Refining Seasonal Precipitation Forecast in Brazil Using Simple Data-Driven Techniques and Climate Indices

Torres, F. L. R., Kuki, C. A. C., Reboita, M. S., Lima, L. M. M., Lima, J. W. M., & Queiroz, A. R. D. (2024). Refining Seasonal Precipitation Forecast in Brazil Using Simple Data-Driven Techniques and Climate Indices. Revista Brasileira de Meteorologia, 39, e39240052.

This study proposes and evaluates two approaches for refining seasonal precipitation forecasts in Brazil, using simple data-based models, such as multiple linear regression (MLR) and nonlinear support vector machine (SVM).

Integrating Hydrological and Machine Learning Models for Enhanced Streamflow Forecasting via Bayesian Model Averaging in a Hydro-Dominant Power System

Torres, F. L. R., Lima, L. M. M., Reboita, M. S., de Queiroz, A. R., & Lima, J. W. M. (2024). Integrating Hydrological and Machine Learning Models for Enhanced Streamflow Forecasting via Bayesian Model Averaging in a Hydro-Dominant Power System. Water, 16(4), 586.

This work proposes a framework that incorporates predictive uncertainty into the forecasting process, enhancing the robustness and reliability of predictions. Bayesian model averaging (BMA) statistically combines multiple models based on their posterior probability distributions, producing forecasts from the weighted averages of predictions.

Short-Term Load Forecasting in Electricity Power Systems: An Overview and the Brazilian Experience

Aquila, G., Scianni, L.AB., de Faria, V.A.D., Lima, J.W.M., Lima, L.M.M., de Queiroz, A.R., (2023) Short-Term Load Forecasting in Electricity Power Systems: An Overview and the Brazilian Experience, Energies, 16(21), 7444.

This work 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.

Energy Digital Twin Applications: A Review

Do Amaral, J. V. S., Dos Santos, C. H., Montevechi, J. A. B., & de Queiroz, A. R. (2023). Energy digital twin applications: A review. Renewable and Sustainable Energy Reviews, 188, 113891.

This work aims to evaluate relevant papers in this area considering their objectives, application fields, adopted techniques and tools, as well as to discuss the advantages and challenges of this approach. Though a Systematic Literature Review (SLR), the main scientific databases were explored, and relevant articles were selected for analysis based on search criteria. Some crucial findings were highlighted, including the state of the art of the theme and important discussions considering energy generation, storage, transmission, and consumption subsystems.

Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system

Morais, L. B. S., Aquila, G., de Faria, V. A. D., Lima, L. M. M., Lima, J. W. M., & de Queiroz, A. R. (2023). Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system. Applied Energy, 348, 121439.

This work 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.

Scenario Generation and Risk-averse Stochastic Portfolio Optimization Applied to Offshore Renewable Energy Technologies

de Faria, V.A.D., de Queiroz, A.R., DeCarolis, J.F., (2023) Scenario Generation and Risk-averse Stochastic Portfolio Optimization Applied to Offshore Renewable Energy Technologies, Energy, 325-120012.

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.

Optimizing Offshore Renewable Portfolios Under Resource Variability

de Faria, V.A.D., de Queiroz, A.R., DeCarolis, J.F., (2022) Optimizing Offshore Renewable Portfolios Under Resource Variability, Applied Energy, 325-120012

In this paper, 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. 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.

Using robust optimization to inform US deep decarbonization planning

Patankar, N., Eshraghi, H., de Queiroz, A. R., & DeCarolis, J. F. (2022). Using robust optimization to inform US deep decarbonization planning. Energy Strategy Reviews, 42, 100892

This work focuses on extending and applying robust optimization methods to TEMOA, an open source Energy System Optimization Model, to derive insights about low carbon pathways in the United States.

Co-Optimization of Reservoir and Power Systems (COREGS) for seasonal planning and operation

Ford, L., de Queiroz, A., DeCarolis, J., & Sankarasubramanian, A. (2022). Co-Optimization of Reservoir and Power Systems (COREGS) for seasonal planning and operation. Energy Reports, 8, 8061-8078

We present the Co-Optimization of Reservoir and Electricity Generation Systems (COREGS), a generalized, open-source, modeling framework that seeks to optimizes power generation costs using a multireservoir model (GRAPS) and an electricity system model (TEMOA). COREGS is then applied to Tennessee Valley Authority’s system in the United States.

Improving the Representation of Energy Efficiency in an Energy System Optimization Model

Patankar, N., Fell, H., DeCarolis, J., de Queiroz, A.R., Curtis, J., (2022) Improving the Representation of Energy Efficiency in an Energy System Optimization Model, Applied Energy, Vol 306(B): 118083

In this paper, the structure of an existing Energy System Optimization Model is adapted to include energy efficiency in way that is consistent with microeconomic theory. Therefore, the effectiveness of energy-efficient technologies in meeting energy service demands, and their potential to substitute electricity usage by conventional technologies is considered.

Promoting reproducibility and increased collaboration in electric sector capacity expansion models with community benchmarking and intercomparison efforts

Henry, C. L., Eshraghi, H., Lugovoy, O., Waite, M. B., DeCarolis, J. F., Farnham, D. J., Peer, R.A.M., Wu, Y., de Queiroz, A.R., Potashnikov, V., Modi, V., and Caldeira, K. (2021). Promoting reproducibility and increased collaboration in electric sector capacity expansion models with community benchmarking and intercomparison efforts, Applied Energy, 304, 117745

This paper presents a model benchmarking effort using highly simplified scenarios applied to four open-source models of the U.S. electric sector. We eliminate all parametric uncertainty through using a common dataset and leave only structural differences.

An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems

de Faria, V. A. D., de Queiroz, A. R., Lima, L. M., Lima, J. W. M., & da Silva, B. C. (2022). An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems. Int. Journal of Environmental Science and Technology, 19(7), 5819-5838.

This work analyzes the use of artificial neural networks in short-term streamflow forecasting for large interconnected hydropower systems. We present an algorithm to define the neural network inputs and apply it to create models for 55 major hydro plants in the Paraná Basin, which contribute to more than 30% of the total power generated in Brazil.

Energy-Storage Modeling: State-of-the-Art and Future Research Directions

Sioshansi, R., Denholm, P., Arteaga, J., Awara, S., Bhattacharjee, S., Botterud, A., Cole, W., Cortes, A., de Queiroz, A.R., DeCarolis, J.F., Ding, Z., Diorio, N., Dvorkin, Y., Helman, U., Johnson, J., Konstantelos, I., Mai, T., Pandzic, H., Sodano, D., Stephen, G., Svoboda, A., Zareipour, H., and Zhang, Z. (2021). Energy-Storage Modeling: State-of-the-Art and Future Research Directions, IEEE Transactions on Power Systems, 37(2): 860-875

This paper summarizes capabilities that operational, planning, and resource-adequacy models that include energy storage should have and surveys gaps in extant models.

Efficiency analysis for performance evaluation of electric distribution companies

Medeiros, G.O.S., Lima, L.M.M., de Queiroz, A.R., Lima, J.W.M., dos Santos, L.C.B., Barbosa, M.A., Alvares, J.E., (2021) Efficiency analysis for performance evaluation of electric distribution companies, International Journal of Electrical Power and Energy Systems, 134:107430

This paper evaluates weights restrictions influence on efficiencies results and to perform a sensitivity analysis of efficiency scores of Electricity Distribution Companies using different benchmarking techniques.

Transmission Towers Spotting in Power Systems Considering Engineering and Environmental Aspects: A Dynamic Programming Approach

Medeiros, G.O.S., de Queiroz, A.R., Lima, R.M., Pereira, C.R.S., Santos, A.H.M., Czank Jr, L., dos Santos, R.A., Carvalho Jr, E.L., (2021) Transmission Towers Spotting in Power Systems Considering Engineering and Environmental Aspects: A Dynamic Programming Approach, International Transactions on Electrical Energy Systems, 31(9): e13000

This paper proposes a dynamic programming model that seeks to obtain the optimal spotting of transmission towers considering environmental (type of land use, slope, and geotechnical class of the terrain) and engineering characteristics (minimum distance between the electric conductor and ground and tensions supported of each tower type) associated with the problem.

The Role of Temperature Variability on Seasonal Electricity Demand in the Southern US

Cawthorne, D., de Queiroz, A.R., Eshraghi, H., Sankarasubramanian, A., and DeCarolis, J.F., (2021) The Role of Temperature Variability on Seasonal Electricity Demand in the Southern US”, Frontiers in Sustainable Cities 3:644789

This paper shows that seasonal temperature forecasts from GCMs can potentially help in predicting season-ahead residential power demand forecasts for states in the Southern United States.

The Symbiotic Relationship of Solar Power and Energy Storage in Providing Capacity Value

Sodano, D., DeCarolis, J., de Queiroz, A.R., Johnson, J.X., (2021) The Symbiotic Relationship of Solar Power and Energy Storage in Providing Capacity Value, Renewable Energy, 177: 823-832

In this study, we use a loss of load probability model to estimate the capacity credit of solar photovoltaics and energy storage under increasing penetrations of both technologies, in isolation and in tandem, to offer new understanding on their potential synergistic effects.

Quantification of Climate-Induced Interannual Variability in Residential US Electricity Demand

Eshraghi, H., de Queiroz, A.R., Sankarasubramanian, A., DeCarolis, J.F., (2021) Quantification of Climate-Induced Interannual Variability in Residential US Electricity Demand, Energy, 236: 121273

We assess the sensitivity of residential electricity demand in 48 U S. states to seasonal climate variations and structural changes pertaining to state-level household electricity demand. The main objective is to quantify the effects of seasonal climate variability on residential electricity demand variability during the winter and summer seasons.

Leveraging open-source tools for collaborative macro-energy system modeling efforts

DeCarolis, J. F., Jaramillo, P., Johnson, J. X., McCollum, D. L., Trutnevyte, E., Daniels, D. C., Akın-Olçum, G., Bergerson, J., Joon-Choi, S., Craig, M.T., de Queiroz, A.R., et al. (2020). Leveraging open-source tools for collaborative macro-energy system modeling efforts. Joule, 4(12), 2523-2526

The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts.

Wind energy investments facing uncertainties in the Brazilian electricity spot market: A real options approach

Aquila, G., de Queiroz, A. R., Balestrassi, P. P., Junior, P. R., Rocha, L. C. S., Pamplona, E. O., & Nakamura, W. T. (2020). Wind energy investments facing uncertainties in the Brazilian electricity spot market: A real options approach. Sustainable Energy Technologies and Assessments, 42, 100876

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 in Brazil.

Performance Comparison of Equivalent Reservoir and Multi-Reservoir Models in forecasting hydropower potential for Linking Water and Power Systems

Mukhopadhyay, S., Arumugam, S., de Queiroz, A.R., (2020) Performance Comparison of Equivalent Reservoir and Multi-Reservoir Models in forecasting hydropower potential for Linking Water and Power Systems, Journal of Water Resources Planning and Management, 147(4): 04021005

This study systematically compares two equivalent reservoir models, an aggregated water balance and an energy balance representation, with a multireservoir cascade representation for a system of three reservoirs in series in Savannah, South Carolina, in terms of the total end-of-period release, hydropower and storage based on simulation, simulation optimization, and analytically over a 30-year period.

Contribution for bidding of wind-photovoltaic on grid farms based on NBI-EFA-SNR method

Aquila, G., de Queiroz, A. R., Junior, P. R., Rocha, L. C. S., de Oliveira Pamplona, E., & Balestrassi, P. P. (2020). Contribution for bidding of wind-photovoltaic on grid farms based on NBI-EFA-SNR method. Sustainable Energy Technologies and Assessments, 40, 100754

This study develops a novel model that can help bidding of Wind-photovoltaic 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.

Evaluating economic feasibility and maximization of social welfare of photovoltaic projects developed for the Brazilian northeastern coast: An attribute agreement analysis

de Oliveira, L. G., Aquila, G., Balestrassi, P. P., de Paiva, A. P., de Queiroz, A. R., de Oliveira Pamplona, E., & Camatta, U. P. (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: 109786

This paper proposes an innovative approach for evaluating solar photovoltaic projects based on Attribute Agreement Analysis.

Modeling and Design of Wind-Solar Hybrid Generation Projects in Long-term Energy Auctions: A Multi-objective Optimization Approach

Aquila, G., de Queiroz, A. R., Lima, L.M.M., Balestrassi, P.P., Lima, J.W.M., Pamplona, E.O., (2020) Modeling and Design of Wind-Solar Hybrid Generation Projects in Long-term Energy Auctions: A Multi-objective Optimization Approach, IET Renewable Power Generation, 14(14): 2612 – 2619

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.

Open Source Energy System Modeling Using Break-Even Costs to Inform State-Level Policy: A North Carolina Case Study

Li, B., Thomas, J., de Queiroz, A.R., DeCarolis, J.F., (2020) Open Source Energy System Modeling Using Break-Even Costs to Inform State-Level Policy: A North Carolina Case Study, Environmental Science & Technology, 54(2): 665-676

In this study, we utilize an open-source energy system optimization model and publicly available data sets to examine future electricity generation, CO2 emissions, and CO2 abatement costs for the North Carolina electric power sector through 2050. We illustrate how break-even costs can be used to inform the development of an extended renewable portfolio standard in the state.

Real-time Stochastic Optimization of Energy Storage Management using Deep Learning based Forecasts for Residential PV Applications

Hafiz, F., Awal, M.A., de Queiroz, A.R., Husain, I., (2020) Real-time Stochastic Optimization of Energy Storage Management using Deep Learning based Forecasts for Residential PV Applications, IEEE Transactions on Industry Applications, 56(3): 2216 – 2226

A computationally proficient real-time energy management method with stochastic optimization is presented for a residential photovoltaic (PV)-storage hybrid system comprised of a solar PV generation and a battery energy storage (BES). We propose an integrated energy management framework consisting of an offline optimization model concurrent with a real-time rule-based controller.

Repurposing an Energy System Optimization Model for Seasonal Power Generation Planning

de Queiroz, A.R., Mulcahy, D., DeCarolis, J.F., Sankarasubramanian, A., Mahinthakumar, K., Lu, N., (2019) Repurposing an Energy System Optimization Model for Seasonal Power Generation Planning, Energy, 181: 1321-1330

This paper develops and tests a computationally efficient model that can support seasonal planning while preserving key aspects of system operation over hourly and daily timeframes. To do so, an energy system optimization model is repurposed for seasonal planning using features drawn from a unit commitment model.

Coordinated Control of PEV and PV-based Storage System under Generation and Load Uncertainty

Hafiz, F., de Queiroz, A.R., Husain, I., (2019) Coordinated Control of PEV and PV-based Storage System under Generation and Load Uncertainty, IEEE Transactions on Industry Applications, 55(6): 5524-5532

In this paper, a method of coordinated optimal control between PV-based storage and PEV storage is proposed considering the stochastic nature of solar PV generation and load demand. The stochastic dual dynamic programming algorithm is employed to optimize the charge/discharge profiles of PV-based storage and PEV storage to minimize the daily household electricity purchase cost from the grid.

Optimizing Routing and Tower Spotting of Electricity Transmission Lines: An Integration of Geographical Data and Engineering Aspects into Decision-Making

Santos, A.H.M., de Lima, R.M., Pereira, C.R.S., Osis, R., Medeiros, G.O.S., de Queiroz, A.R., Flauzino, B.K., et al., (2019) Optimizing Routing and Tower Spotting of Electricity Transmission Lines: An Integration of Geographical Data and Engineering Aspects into Decision-Making, Electric Power Systems Research, 176: 105953

This paper presents a novel approach for the design of overhead Transmission Lines (TL), considering geographical, engineering and cost aspects into the decision-making process. The proposed methodology is focused on preliminary planning and decision-making for TL auctions, where the objective is to find design alternatives with the least cost.

Utilizing Demand Response for Distribution Service Restoration to Achieve Grid Resiliency against Natural Disasters

Hafiz, F., Chen, C., Chen, B., de Queiroz, A.R., Husain, I., (2019) Utilizing Demand Response for Distribution Service Restoration to Achieve Grid Resiliency against Natural Disasters, IET Generation, Transmission & Distribution, 13(14): 2942-2950

This paper demonstrates that effective distribution service restoration (DSR) can be significantly improved by leveraging the flexibility provided by the inclusion of demand response (DR). The authors propose a novel framework for this by considering integrated control of household-level flexible appliances to vary the load demand at the distribution-grid level to improve DSR.

Building Conflict Uncertainty into Electricity Planning: A South Sudan Case Study

Patankar, N., de Queiroz, A.R., DeCarolis, J.F., Bazilian, M., Chattopadhyay, D., (2019) Building Conflict Uncertainty into Electricity Planning: A South Sudan Case Study, Energy for Sustainable Development, 49: 53-64

This paper explores electricity planning strategies in South Sudan under future conflict uncertainty. A stochastic energy system optimization model that explicitly considers the possibility of armed conflict leading to electric power generator damage is presented.

Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach

Hafiz, F., de Queiroz, A.R., Fajri, P., Husain, I., (2019) Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach, Applied Energy, 236: 42-54

The aim of this paper is to propose a new energy management framework and storage sizing for a community composed of multiple houses and distributed solar generation. Uncertainties associated with solar generation and electricity demand are included to make the mathematical models more realistic, and as a result, provide more accurate control strategies to manage storage devices utilization.

Hydro Power Revenues Under the Threat of Climate Change in Brazil

de Queiroz, A.R., de Faria, V.A.D., Lima, L.M.M., Lima, J.W.M., (2019) Hydro Power Revenues Under the Threat of Climate Change in Brazil, Renewable Energy, 133: 873-882

We present a new framework to evaluate climate change impacts in hydropower plants. An interaction among regional climate, water inflows modeling, and optimization dispatch models is showed. This paper can help to support decision-making regarding investments in new hydro plants. This multidisciplinary research provides guidance for future planning of the generation system.

Solar Generation, Storage, and Electric Vehicles in Power Grids: Challenges and Solutions with Coordinated Control at the Residential Level

Hafiz, F., de Queiroz, A.R., Husain, (2018) Solar Generation, Storage, and Electric Vehicles in Power Grids: Challenges and Solutions with Coordinated Control at the Residential Level, IEEE Electrification Magazine, 6(4): 83-90

Solar energy is an abundant renewable energy source that is available all around the world every day. Wind energy is another important renewable resource available in large amounts every day. These two renewable energy sources are attracting significant investment as countries seek technology cost reductions to aid sustainability.

US Energy-Related Greenhouse Gas Emissions in the Absence of Federal Climate Policy

Eshraghi, H., de Queiroz, A.R., DeCarolis, J.F., (2018) US Energy-Related Greenhouse Gas Emissions in the Absence of Federal Climate Policy, Environmental Science & Technology, 52(17): 9595–9604

In this analysis, we utilize Tools for Energy Model Optimization and Analysis (Temoa), an open source, publicly available energy system optimization model (ESOM), to examine a large set of baseline US energy futures through 2040. Our objective is to rigorously explore the future decision landscape and quantify greenhouse gas (GHG) emissions in a future where energy system changes are driven by market forces rather than top-down federal policy.

Methodology for Electricity Transmission Lines Pole Spotting Based on Dynamic Programming

Medeiros, G.O.S., Lima, R.M., de Queiroz, A.R., et al., (2018) Methodology for Electricity Transmission Lines Pole Spotting Based on Dynamic Programming, Brazilian Energy Magazine, 24(3): 51-64 (in portuguese)

O presente trabalho propõe uma metodologia de locação otimizada das estruturas de transmissão por meio da modelagem de dados característicos do local de estudo, utilizando programação dinâmica, de maneira que o empreendimento proposto apresente o menor custo. Esse trabalho apresenta também um estudo de caso que compara os resultados obtidos pela metodologia proposta com a configuração do projeto real associado a LT Machadinho-Campos Novos.

Proposed Method for Contracting of Wind-Photovoltaic Connected Projects to the Brazilian Electric System using Multi-objective Programming

Aquila, G., Rocha, L.C.S., Pamplona, E.O., de Queiroz, A.R., Fonseca, M.N., (2018) Proposed Method for Contracting of Wind-Photovoltaic Connected Projects to the Brazilian Electric System using Multi-objective Programming, Renewable and Sustainable Energy Reviews, 97: 377-389

This paper presents a model to assist the government in contracting projects that maximize the socioeconomic well-being of the Brazilian electricity sector. 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.

Cooperative game theory and last addition method in the allocation of firm energy rights

Faria, V.A.D., de Queiroz, A.R., Lima, L.M.M., Lima, J.W.M., (2018) Cooperative game theory and last addition method in the allocation of firm energy rights, Applied Energy, 226: 905-915

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.

Demand-Side Management Via Photovoltaic Generation with Storage in The Context of the Brazilian Tariff Model

Rodrigues, L.F., do Carmo, B.K.S., Gomes, A.A.L., de Queiroz, A.R., Lima, J.W.M., Ribeiro, P.F., (2018) Demand-Side Management Via Photovoltaic Generation with Storage in The Context of the Brazilian Tariff Model, Hipótese, v. 4(2): 172-189 (in portuguese)

Com o avanço da geração de energia elétrica produzida junto ao consumo de carga, aliado com o cenário atual de tarifação de energia no Brasil, este trabalho apresenta o gerenciamento pelo lado da demanda (DSM) em uma microrrede, realizando estudos de comparação entre três modelos distintos aplicados no contexto da tarifa branca e no contexto da tarifa convencional. Observou-se uma economia considerável quando utilizada uma microrrede com DSM, sem provocar uma mudança de hábito do consumidor.

Analysis of the wind average speed in different Brazilian states using the nested GR&R measurement system

Aquila, G., Peruchi, R.S., Rotela Junior, P., Rocha, L.C.S., de Queiroz, A.R., Pamplona, E.O., Balestrassi, P.P. (2018) Analysis of the wind average speed in different Brazilian states using the nested GR&R measurement system, Measurement, 115: 217-222

This study aims to evaluate the behavior of wind average speed at the four major wind energy-producing states. The main contribution of this research is to use the Nested Gage Repeatability & Reproducibility (NGR&R) study, generally applied on manufacturing quality management.

Multi-objective Optimization Applied for Designing Hybrid Power Generation Systems in Isolated Networks

Fonseca, M.N., Pamplona, E.O., de Queiroz, A.R., et al., (2018) Multi-objective Optimization Applied for Designing Hybrid Power Generation Systems in Isolated Networks, Solar Energy, 161: 207-219

This proposes 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 Amazonas state located in the northern region of Brazil.

The Economics of Electricity Generation from Gulf Stream Currents

Li, B., de Queiroz, A.R., DeCarolis, J.F., Bane, J., He, R., Keeler, A.G., Neary, V.S., (2017) The Economics of Electricity Generation from Gulf Stream Currents, Energy, 134: 649-658

The economics of Gulf Stream energy off the North Carolina coast are assessed. A portfolio optimization model is developed to identify optimal generation sites. The optimal portfolio reduces the variance in monthly electricity generation tenfold.

Wind Power Feasibility Analysis under Uncertainty in the Brazilian Electricity Market

Aquila, G., Rotela Jr, P., Pamplona, E.O., de Queiroz, A.R., (2017) Wind Power Feasibility Analysis under Uncertainty in the Brazilian Electricity Market, Energy Economics, 65: 127-136

This paper proposes a framework for investment analysis capable of encompassing different uncertainties and possibilities for wind power generators in a regulated market, characterized by auctions. To reach the proposed objective we employ a simulation technique which allows to model cash flows considering uncertainties in variables related to project financial premises, electricity generation and producer exposure to the short-term market.

An Overview of Incentive Policies for the Expansion of Renewable Energy Generation in Electricity Power Systems and the Brazilian Experience

Aquila, G., Pamplona, E.O., de Queiroz, A.R., Rotela Jr, P., Fonseca, M.N., (2017) An Overview of Incentive Policies for the Expansion of Renewable Energy Generation in Electricity Power Systems and the Brazilian Experience, Renewable and Sustainable Energy Reviews, 70: 1090-1098

In this study, long-term policies that have been applied in several countries, such as feed-in tariffs, shares with commercialization of certificates, auctions, and net metering, are investigated and discussed. The main advantages and disadvantages of these incentive strategies are emphasized, focusing on applications.

Journal Publications

Anderson Rodrigo de Queiroz, Ph.D.