Article
Thermodynamics
Bo Ming, Jing Chen, Wei Fang, Pan Liu, Wei Zhang, Jianhua Jiang
Summary: By evaluating three different stochastic optimization models, the parameterization-simulation-optimization model was found to be capable of balancing economy, reliability, and robustness in the Longyangxia hydro-PV hybrid generation system in China under various climatic conditions. It is recommended for use in long-term operation modeling of hydro-based hybrid generation systems.
Article
Environmental Sciences
Anthony S. Kiem, George Kuczera, Pavel Kozarovski, Lanying Zhang, Garry Willgoose
Summary: This study presents an approach for stochastically generating future hydroclimatic conditions at multiple sites based on the relationship between temperature and rainfall in Australia, applied to catchments supplying Sydney. It found that future warming will lead to significant reductions in streamflow, impacting water security.
WATER RESOURCES RESEARCH
(2021)
Review
Energy & Fuels
Amirhossein Hashemi, Melis Sutman, Gabriela M. Medero
Summary: Energy geostructures are a cost-effective strategy for mitigating the adverse impact of climate change. This paper provides a comprehensive review of experimental data on the soil-structure interface, investigating the impact of matric suction and temperature on the shear strength of the interface, and discussing the role of stress history. Understanding the interface response is crucial for the analysis and design of energy geostructures.
GEOMECHANICS FOR ENERGY AND THE ENVIRONMENT
(2023)
Article
Green & Sustainable Science & Technology
Yue Yin, Chuan He, Tianqi Liu, Lei Wu
Summary: This paper proposes a risk-averse two-stage stochastic midterm scheduling model to address the impact of short-term uncertainties of renewable energy on power systems. The model effectively incorporates short-term operation constraints using a network-constrained clustered unit commitment (NC-CUC) model, improving solution accuracy and reducing computational burden. Case studies demonstrate the effectiveness of the model.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Energy & Fuels
Yachao Zhang, Xueli An, Chao Wang
Summary: This paper proposes a two-stage stochastic optimization model driven by data to solve the short-term hydro-thermal-wind coordination scheduling problem. By introducing a dynamic extreme scenario generation and reduction method, the relationship between hydropower output and practical constraints is combined, ultimately transformed into a mixed-integer linear programming problem for solution.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Environmental Sciences
Utsav Bhattarai, Laxmi Prasad Devkota, Suresh Marahatta, Dibesh Shrestha, Tek Maraseni
Summary: Despite its importance as a proven clean-energy technology, hydroelectricity is receiving less attention in global research. This study assesses the impact of climate change on hydro-energy generation in the Nepalese Himalaya and highlights the dependence of energy generation on reservoir operating rules. The study recommends considering a wide spectrum of climate change scenarios and implementing storage type projects with flexible operating rules to enhance climate resiliency.
ENVIRONMENTAL RESEARCH
(2022)
Article
Business, Finance
Falik Shear, Badar Nadeem Ashraf, Shazaib Butt
Summary: We investigate the impact of climate change vulnerability on foreign direct investment (FDI) inflows. Our study shows that multinational firms view countries with higher climate change vulnerability as less attractive for FDI. Using a dataset of 152 countries from 1996 to 2019 and panel pooled ordinary least square regressions, we find evidence that FDI inflows are lower in countries with greater climate change vulnerability. We also find that this relationship is only significant in high- and middle-income countries, where market size is less influential than climate-related risks.
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE
(2023)
Article
Thermodynamics
Qian Cheng, Pan Liu, Qian Xia, Lei Cheng, Bo Ming, Wei Zhang, Weifeng Xu, Yalian Zheng, Dongyang Han, Jun Xia
Summary: This study proposes an analytical method based on daily hydropower and PV power to evaluate the power curtailment rate of HPESs under future climate variability. The effectiveness of the method is verified through short-term and long-term operation models, and the accuracy of the PV curtailment function is validated through a case study. Results show that future hydropower and PV power will increase with substantial variances, while the PV curtailment rate exhibits an overall increase in the near future and a larger increase in the far future.
Article
Green & Sustainable Science & Technology
Chinmay Sharma, Van Lantz, Patrick Withey, Galen McMonagle, Thomas O. Ochuodho
Summary: Incoming federal regulations in Canada will require the phase-out of coal-fired electricity production. The study focuses on the economic impacts of this shift in New Brunswick and finds that phasing out coal would result in small reductions in GDP but significant reductions in CO2 emissions. Reinvesting in alternative energy sources would further reduce GDP, consumption, and investment. The most cost-effective approach would be reinvesting capital in nuclear and hydro power.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Electrical & Electronic
Atefeh Hassanpour, Emad Roghanian
Summary: This paper presents a two-stage stochastic programming formulation for yearly generation maintenance scheduling, considering the unreliability of power generators and the possibility of unit failures to maximize the net profit of generation companies. The decisions made in two stages, based on the Nash Equilibrium theory, involve independent generation amounts and load allocations.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Bining Zhao, Jesse Bukenberger, Mort Webster
Summary: A multi-stage and multi-scale stochastic generation expansion planning (GEP) model is proposed to represent uncertainties in load and renewable generation. The study finds that scenario partitioning methods are more effective in determining appropriate investment levels, while covariance-based approximations perform the best overall.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Energy & Fuels
Shuo Han, Mengjiao He, Ziwen Zhao, Diyi Chen, Beibei Xu, Jakub Jurasz, Fusheng Liu, Hongxi Zheng
Summary: A day-ahead scheduling model is proposed for a hydro-wind hybrid power generation system, considering the power regulation flexibility and frequency response flexibility. The study shows that utilizing the flexibility of hydropower can reduce frequency deviation, wind power curtailment, and load loss. Decision makers can use the flexibility supply capacity of the hydropower station to determine the connected wind power capacity and system load for comprehensive benefits.
Article
Environmental Sciences
Ashis Kumar Pradhan, Anshita Sachan, Udit Kumar Sahu, Vinita Mohindra
Summary: This study examines the impact of foreign direct investment on environmental degradation in BRICS nations, finding that FDI and GDP play significant roles in reducing CO2 emissions. It suggests the use of cleaner technology and promotion of environmental awareness, while also highlighting the importance of policies on climate change and effective enforcement of environmental protocols to reduce environmental degradation in these countries.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Studies
Uma S. Bhatt, Benjamin A. Carreras, Jose Miguel Reynolds Barredo, David E. Newman, Pere Collet, Damia Gomila
Summary: This study explores the impact of climate change on renewable energy supply and finds that this impact varies with location. It provides a framework to assess the optimal mix of renewables and changes in energy storage requirements, and demonstrates the effects on grid reliability and potential mitigation paths.
Article
Thermodynamics
T. Sukah, M. Saad, I. Mougharbel
Summary: This research establishes a long-term optimal scheduling model for a hybrid generation system, decomposing and solving the hydro-wind-thermal subproblems using the stochastic dynamic programming (SDP) technique to find the minimum cost trajectory under various constraints. The addition of a penalty factor reduces outflow variations. The results show that the cost decreases as demand increases.
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2023)
Article
Engineering, Civil
Sudarshana Mukhopadhyay, A. Sankarasubramanian, Anderson Rodrigo de Queiroz
Summary: This study compares the performance of two equivalent reservoir models, an aggregated water balance and an energy balance representation, with a multireservoir cascade representation in a system of three reservoirs. The findings show that equivalent reservoir models perform similarly to cascade models in systems with large storage-to-demand ratios, but poorly in systems with smaller ratios.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
(2021)
Article
Environmental Sciences
V. A. D. de Faria, A. R. de Queiroz, L. M. Lima, J. W. M. Lima, B. C. da Silva
Summary: This study examines the use of artificial neural networks in short-term streamflow forecasting for large hydropower systems, presenting a new algorithm for defining neural network inputs. Results show that neural network models provide more accurate forecasts than traditional hydrological models, and discuss the impact of historical rainfall information on streamflow prediction using neural networks.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Giulia O. S. Medeiros, Anderson Rodrigo de Queiroz, Rodolfo M. Lima, Camilo R. S. Pereira, Afonso H. M. Santos, Luiz Czank Junior, Renato A. Santos, L. C. Junior Eden
Summary: Electricity transmission systems planning has become a significant topic globally, with optimization techniques playing a crucial role in cost savings and decision-making support.
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2021)
Article
Energy & Fuels
Candise L. Henry, Hadi Eshraghi, Oleg Lugovoy, Michael B. Waite, Joseph F. DeCarolis, David J. Farnham, Tyler H. Ruggles, Rebecca A. M. Peer, Yuezi Wu, Anderson de Queiroz, Vladimir Potashnikov, Vijay Modi, Ken Caldeira
Summary: Capacity expansion models in the electric sector are commonly used for policy analysis and planning, but differences in parameters and structures lead to diverse results. Through a benchmarking effort using simplified scenarios and a common dataset, specific structural differences among models can be pinpointed, improving consistency and building confidence in models while identifying areas for further research and development. Introducing an open-source test dataset can promote collaboration among energy modelers and increase transparency for stakeholders such as policymakers.
Article
Thermodynamics
Hadi Eshraghi, Anderson Rodrigo de Queiroz, A. Sankarasubramanian, Joseph F. DeCarolis
Summary: By analyzing data from 48 U.S. states using a linear regression model from 2005 to 2017, it was found that the majority of states' summer and winter electricity demand variability is primarily driven by climate, indicating the need for new datasets to quantify unexplained variance in electricity demand.
Article
Engineering, Electrical & Electronic
Giulia O. S. Medeiros, Luana M. Marangon-Lima, Anderson R. de Queiroz, Jose W. Marangon-Lima, Lorena C. B. dos Santos, Maria A. Barbosa, Jairo E. Alvares
Summary: The study evaluates the impact of weight restrictions on efficiency results and conducts a sensitivity analysis of efficiency scores using additional benchmarking techniques. Results indicate that the diversity of concession areas significantly influences the stability of efficiency scores. By considering the proposed approach, an efficiency relationship among all distribution companies can be identified.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Daniel Sodano, Joseph F. DeCarolis, Anderson Rodrigo de Queiroz, Jeremiah X. Johnson
Summary: This study utilizes a loss of load probability model to estimate the capacity credit of solar photovoltaics and energy storage under high penetrations, finding that their synergistic effects can significantly improve system reliability by reducing daily peak demand hours and offering new insights into their potential benefits.
Article
Engineering, Electrical & Electronic
Ramteen Sioshansi, Paul Denholm, Juan Arteaga, Sarah Awara, Shubhrajit Bhattacharjee, Audun Botterud, Wesley Cole, Andres Cortes, Anderson de Queiroz, Joseph DeCarolis, Zhenhuan Ding, Nicholas DiOrio, Yury Dvorkin, Udi Helman, Jeremiah X. Johnson, Ioannis Konstantelos, Trieu Mai, Hrvoje Pandzic, Daniel Sodano, Gord Stephen, Alva Svoboda, Hamidreza Zareipour, Ziang Zhang
Summary: This paper summarizes the challenges of modeling energy storage and the gaps in existing models. Energy storage introduces new requirements for modeling methods and poses challenges in capturing chronology and system balance.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Energy & Fuels
Neha Patankar, Hadi Eshraghi, Anderson Rodrigo de Queiroz, Joseph F. DeCarolis
Summary: This study extends and applies robust optimization methods to the energy system optimization model in the United States to explore low carbon pathways. By considering future uncertainty, the robust strategy has shown significant cost savings and improved cost control.
ENERGY STRATEGY REVIEWS
(2022)
Article
Energy & Fuels
Victor A. D. de Faria, Anderson R. de Queiroz, Joseph F. De Carolis
Summary: This study develops a model based on Mean-Variance portfolio theory to optimize the deployment of offshore wind, wave, and ocean current technologies. The results show that integrating different offshore technologies can decrease energy variability, but significant cost reductions are still needed to realize their deployment in the investigated region.
Article
Energy & Fuels
Lucas Ford, Anderson de Queiroz, Joseph DeCarolis, A. Sankarasubramanian
Summary: This study develops a modeling framework called COREGS, which optimizes the allocation of water resources and reduces power generation costs through the co-optimization of reservoir and electricity generation systems. The findings suggest that co-optimization leads to more efficient water allocation decisions and better meets the needs of the power system compared to separate optimization.
Article
Thermodynamics
Victor A. D. Faria, Anderson Rodrigo de Queiroz, Joseph F. DeCarolis
Summary: This research proposes an analytical decision-making framework to define renewable offshore portfolios using artificial neural networks and risk-averse stochastic programming. Synthetic energy scenarios are generated using a generative adversarial neural network, considering distributed resources over large geographic regions. A stochastic model is then used to determine the optimal location and number of turbines for each technology. The framework is tested using data from the U.S. East coast, demonstrating the ability to create statistically consistent energy scenarios and the significance of resource diversification in improving system security.
Article
Energy & Fuels
Lucas Barros Scianni Morais, Giancarlo Aquila, Victor Augusto Duraes de Faria, Luana Medeiros Marangon Lima, Jose Wanderley Marangon Lima, Anderson Rodrigo de Queiroz
Summary: This paper investigates the application of shallow and deep neural networks in modeling short-term load forecasting problem. Different model architectures including multi-layer perceptron, long-short term memory, and gated recurrent unit are tested, and global climate model information is used as input for more accurate predictions. A case study for the Brazilian interconnected power system is presented and compared with forecasts from the Brazilian Independent System Operator model. The results show that bidirectional long-short term memory and gated recurrent unit outperform other models, achieving Nash-Sutcliffe values up to 0.98 and mean absolute percentile error values of 1.18%, superior to the results obtained by the Independent System Operator models (0.94 and 2.01% respectively). The better performance of neural network models is confirmed under the Diebold-Mariano pairwise comparison test.
Review
Energy & Fuels
Giancarlo Aquila, Lucas Barros Scianni Morais, Victor Augusto Duraes de Faria, Jose Wanderley Marangon Lima, Luana Medeiros Marangon Lima, Anderson Rodrigo de Queiroz
Summary: The development of smart grid technologies enables the integration of new and intermittent renewable energy sources into power systems. This requires accurate short-term load demand forecasting, which is crucial for supply strategies, system reliability decisions, and price formation. Machine learning models, such as Neural Networks and Support Vector Machines, have gained popularity due to advancements in mathematical techniques and computational capacity. The study reviews various methods used for short-term load forecasting, with a focus on machine learning strategies, and discusses the Brazilian experience.
Article
Green & Sustainable Science & Technology
Dylan Cawthorne, Anderson Rodrigo de Queiroz, Hadi Eshraghi, Arumugam Sankarasubramanian, Joseph F. DeCarolis
Summary: This study focuses on the impact of temperature variability on electricity consumption in the Southern United States, with results indicating that temperature significantly influences electricity demand at seasonal time scales. Climate forecasts are found to potentially aid in forecasting future electricity demand.
FRONTIERS IN SUSTAINABLE CITIES
(2021)
Article
Green & Sustainable Science & Technology
Cameron Bracken, Nathalie Voisin, Casey D. Burleyson, Allison M. Campbell, Z. Jason Hou, Daniel Broman
Summary: This study presents a methodology and dataset for examining compound wind and solar energy droughts, as well as the first standardized benchmark of energy droughts across the Continental United States (CONUS) for a 2020 infrastructure. The results show that compound wind and solar droughts have distinct spatial and temporal patterns across the CONUS, and the characteristics of energy droughts are regional. The study also finds that compound high load events occur more often during compound wind and solar droughts than expected.
Article
Green & Sustainable Science & Technology
Ning Zhang, Yanghao Yu, Jiawei Wu, Ershun Du, Shuming Zhang, Jinyu Xiao
Summary: This paper provides insights into the optimal configuration of CSP plants with different penetrations of wind power by proposing an unconstrained optimization model. The results suggest that large solar multiples and TES are preferred in order to maximize profit, especially when combined with high penetrations of wind and photovoltaic plants. Additionally, the study demonstrates the economy and feasibility of installing electric heaters (EH) in CSP plants, which show a linear correlation with the penetration of variable energy resources.
Article
Green & Sustainable Science & Technology
M. Szubel, K. Papis-Fraczek, S. Podlasek
Article
Green & Sustainable Science & Technology
J. Silva, J. C. Goncalves, C. Rocha, J. Vilaca, L. M. Madeira
Summary: This study investigated the methanation of CO2 in biogas and compared two different methanation reactors. The results showed that the cooled reactor without CO2 separation achieved a CO2 conversion rate of 91.8%, while the adiabatic reactors achieved conversion rates of 59.6% and 67.2%, resulting in an overall conversion rate of 93.0%. Economic analysis revealed negative net present worth values, indicating the need for government monetary incentives.
Article
Green & Sustainable Science & Technology
Yang Liu, Yonglan Xi, Xiaomei Ye, Yingpeng Zhang, Chengcheng Wang, Zhaoyan Jia, Chunhui Cao, Ting Han, Jing Du, Xiangping Kong, Zhongbing Chen
Summary: This study investigated the effect of using nanofiber membrane composites containing Prussian blue-like compound nanoparticles (PNPs) to relieve ammonia nitrogen inhibition of rural organic household waste during high-solid anaerobic digestion and increase methane production. The results showed that adding NMCs with 15% PNPs can lower the concentrations of volatile fatty acids and ammonia nitrogen, and increase methane yield.
Article
Green & Sustainable Science & Technology
Zhong Ge, Xiaodong Wang, Jian Li, Jian Xu, Jianbin Xie, Zhiyong Xie, Ruiqu Ma
Summary: This study evaluates the thermodynamic, exergy, and economic performance of a double-stage organic flash cycle (DOFC) using ten eco-friendly hydrofluoroolefins. The influences of key parameters on performance are analyzed, and the advantages of DOFC over single-stage type are quantified.
Article
Green & Sustainable Science & Technology
Nicolas Kirchner-Bossi, Fernando Porte-Agel
Summary: This study investigates the optimization of power density in wind farms and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced to optimize power density and turbine layout. The results show that the PDGA-driven solutions significantly reduce the levelized cost of energy (LCOE) compared to the default layout, and exhibit a convex relationship between area and LCOE or power density.
Article
Green & Sustainable Science & Technology
Chunxiao Zhang, Dongdong Li, Lin Wang, Qingpo Yang, Yutao Guo, Wei Zhang, Chao Shen, Jihong Pu
Summary: In this study, a novel reversible liquid-filled energy-saving window that effectively regulates indoor solar radiation heat gain is proposed. Experimental results show that this window can effectively reduce indoor temperature during both summer and winter seasons, while having minimal impact on indoor illuminance.
Article
Green & Sustainable Science & Technology
Alessandro L. Aguiar, Martinho Marta-Almeida, Mauro Cirano, Janini Pereira, Leticia Cotrim da Cunha
Summary: This study analyzed the Brazilian Equatorial Shelf using a high-resolution ocean model and found significant tidal variations in the area. Several hypothetical barrages were proposed with higher annual power generation than existing barrages. The study also evaluated the installation effort of these barrages.
Article
Green & Sustainable Science & Technology
Francesco Superchi, Nathan Giovannini, Antonis Moustakis, George Pechlivanoglou, Alessandro Bianchini
Summary: This study focuses on the optimization of a hybrid power station on the Tilos island in Greece, aiming to increase energy export and revenue by optimizing energy fluxes. Different scenarios are proposed to examine the impact of different agreements with the grid operator on the optimal solution.
Article
Green & Sustainable Science & Technology
Peimaneh Shirazi, Amirmohammad Behzadi, Pouria Ahmadi, Sasan Sadrizadeh
Summary: This research presents two novel energy production/storage/usage systems to reduce energy consumption and environmental effects in buildings. A biomass-fired model and a solar-driven system integrated with photovoltaic thermal (PVT) panels and a heat pump were designed and assessed. The results indicate that the solar-based system has an acceptable energy cost and the PVT-based system with a heat pump is environmentally superior. The biomass-fired system shows excellent efficiency.
Article
Green & Sustainable Science & Technology
Zihao Qi, Yingling Cai, Yunxiang Cui
Summary: This study aims to investigate the operational characteristics of the solar-ground source heat pump system (SGSHPS) in Shanghai under different operation modes. It concludes that tandem operation mode 1 is the optimal mode for winter operation in terms of energy efficiency.
Article
Green & Sustainable Science & Technology
L. Bartolucci, S. Cordiner, A. Di Carlo, A. Gallifuoco, P. Mele, V. Mulone
Summary: Spent coffee grounds are a valuable biogenic waste that can be used as a source of biofuels and valuable chemicals through pyrolysis and solvent extraction processes. The study found that heavy organic bio-oil derived from coffee grounds can be used as a carbon-rich biofuel, while solvent extraction can extract xantines and p-benzoquinone, which are important chemicals for various industries. The results highlight the promising potential of solvent extraction in improving the economic viability of coffee grounds pyrolysis-based biorefineries.
Article
Green & Sustainable Science & Technology
Luiza de Queiroz Correa, Diego Bagnis, Pedro Rabelo Melo Franco, Esly Ferreira da Costa Junior, Andrea Oliveira Souza da Costa
Summary: Building-integrated photovoltaics, especially organic solar technology, are important for reducing greenhouse gas emissions in the building sector. This study analyzed the performance of organic panels laminated in glass in a vertical installation in Latin America. Results showed that glass lamination and vertical orientation preserved the panels' performance and led to higher energy generation in winter.
Article
Green & Sustainable Science & Technology
Zhipei Hu, Shuo Jiang, Zhigao Sun, Jun Li
Summary: This study proposes innovative fin arrangements to enhance the thermal performance of latent heat storage units. Through optimization of fin distribution and prediction of transient melting behaviors, it is found that fin structures significantly influence heat transfer characteristics and melting behaviors.
