Article
Engineering, Electrical & Electronic
Mohammad Hossein Sadeghi, Ali Dastfan, Yaser Damchi
Summary: This paper investigates the protection and power quality issues of distributed generation resources and proposes a protection coordination optimization method and a new objective function. The simulation results show that the proposed approach can significantly reduce power losses and improve protection speed.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2022)
Review
Energy & Fuels
Swetalina Sarangi, Binod Kumar Sahu, Pravat Kumar Rout
Summary: This paper highlights the importance and challenges of protection in DC microgrids, as well as some loopholes in current research. By systematically and chronologically reviewing DC microgrid systems, some reliable improvements have been suggested.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Subhakanta Khatua, V. Mukherjee
Summary: In this paper, the integration of IMG into the EM-SBO power system of a 460 MWe NPP station is considered, focusing on the overcurrent protection coordination scheme. After load flow analysis and calculation of short circuit fault level, a combined fuse and numerical relays with digital logic-based adaptive overcurrent protection (AOP) scheme has been proposed.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Review
Energy & Fuels
Rene Prenc, Michele Rojnic, Dubravko Frankovic, Sasa Vlahinic
Summary: The goal of this review paper is to address complex optimization functions in overcurrent relay optimization and critically examine their application. It focuses on optimizing the discrimination time between primary and backup relays, considering the impact of distributed generation units. The paper also assesses meshed network operation and reviews the concept of adaptive distribution network protection.
Article
Energy & Fuels
Uma Uzubi Uma, Daniel Nmadu, Nnaemeka Ugwuanyi, Ogah Ekechi Ogah, Ngozi Eli-Chukwu, Marcellinus Eheduru, Arthur Ekwue
Summary: This paper proposes a novel adaptive protection coordination scheme using a neural network to automatically adjust the overcurrent relay settings in response to the adverse effects of distributed generators on conventional overcurrent protection relay coordination.
PROTECTION AND CONTROL OF MODERN POWER SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Daniel Alcala-Gonzalez, Eva M. Garcia del Toro, M. Isabel Mas-Lopez, Sara Garcia-Salgado, Santiago Pindado
Summary: This paper investigates the impact of distributed generation on protection devices in electric power distribution networks, and proposes an adjustment method for overcurrent relays based on linear programming techniques. The goal is to improve their response time to different faults.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Hui Li, Yifan Li, Shaofeng Huang, Peng Sun, Qi Gao
Summary: This article presents a comprehensive investigative analysis of the impact of phase sequence exchange (PSE) technology on protection performance. It is found that PSE can cause maloperation of current differential protection and zero-sequence current protection, and the circuit breaker needs to be re-matched. A solution is proposed to install the PSE device with independent protection between the transformer and the bus-bar.
IET POWER ELECTRONICS
(2023)
Article
Green & Sustainable Science & Technology
Feras Alasali, Naser El-Naily, Abdelaziz Salah Saidi, Awni Itradat, William Holderbaum, Faisal A. Mohamed
Summary: The high penetration of DGs has raised concerns about optimal overcurrent coordination for power protection. A new optimal OCR coordination scheme is developed in this study, using standard and non-standard tripping characteristics for phase and ground events. The Tug of War Optimization and Charged System Search algorithms are used to mitigate the effects of DGs on fault currents and locations. The findings show that the proposed multifunction OCR scheme reduces tripping time and increases relay sensitivity in islanding operation mode.
IET RENEWABLE POWER GENERATION
(2023)
Article
Engineering, Electrical & Electronic
G. P. Santos, A. Tsutsumi, J. C. M. Vieira
Summary: Microgrids integrate distributed energy resources and local loads into power distribution systems effectively, but face challenges in protection systems. Conventional overcurrent protection is not ideal for microgrids due to changes in fault current path and amplitude during islanded operation. Voltage-based relays have been researched as potential protection for AC microgrids. This paper reviews and improves the existing voltage-based protection technique to ensure reliability and selectivity among protection devices in different topologies of an AC microgrid.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Chemistry, Physical
Mikhail Andreev, Yuly Bay, Boris Malyuta
Summary: The integration of renewable energy sources and energy storage systems has significant impacts on electric power systems, especially during emergencies. The relay protection system may perform incorrectly due to the influence of these new technologies. In this paper, the authors conducted detailed research and mathematical modeling to adjust the relay protection system in renewable energy integrated power systems.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Review
Energy & Fuels
Swetalina Sarangi, Binod Kumar Sahu, Pravat Kumar Rout
Summary: This article discusses the rapid evolution of microgrid concept in the current power system scenario and the importance of protection for ensuring power quality and system resilience. The critical analysis of key issues and protection schemes for AC microgrid is emphasized, with a focus on the potential for future advancements in protection strategies.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Multidisciplinary Sciences
Mehdi Azari, Kazem Mazlumi, Mansour Ojaghi
Summary: This paper presents a novel methodology to apply PWLC for coordinating DOCRs in meshed power systems of any scale. By utilizing DIgSILENT software to obtain maximum short-circuit fault currents, each relay's PWLC is determined based on fault currents achieved, resulting in a more flexible and desirable approach for overcurrent protection coordination compared to NSCs. The proposed approach shows notable reduction in relay operating time and improved coordination in various power network scenarios.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Salman Rezaei
Summary: This study assesses the impact of ferroresonance on DFIG and the operation of directional overcurrent relays in wind farms using simulation software. An adaptive algorithm based on neural networks and signal analysis tools is developed to meet the protection strategy of smart grids and predict ferroresonance.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Review
Energy & Fuels
Feras Alasali, Saad M. Saad, Abdelaziz Salah Saidi, Awni Itradat, William Holderbaum, Naser El-Naily, Fatima F. Elkuwafi
Summary: This paper provides a comprehensive analysis of microgrid protection schemes, discussing their advantages, limitations, challenges, and opportunities for future research. Coordinating protective schemes to prevent overload and equipment damage is crucial for managing the complex power flow in microgrid systems.
Article
Engineering, Electrical & Electronic
Meng Yen Shih, Arturo Conde, Cesar Angeles-Camacho, Erika Fernandez, Zbigniew Leonowicz, Francisco Lezama, Jorge Chan
Summary: This paper presents a two-stage optimization approach for solving excessive network fault currents and resetting of overcurrent relays based on the Adaptive Protection Scheme (APS) concept. The optimization process effectively re-coordinated the DOCRs in consideration of the effects of FCLs and DGs, mitigating faults surpassing CB thermal limit, DOCR miscoordination and degraded performance caused by FCL over limitation.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Energy & Fuels
Keivan Shariatmadar, Adriano Arrigo, Francois Vallee, Hans Hallez, Lieven Vandevelde, David Moens
Summary: The current energy transition presents challenges to power systems due to the growth in variable and uncertain renewable-based energy generation. Classical probabilistic uncertainty models are widely used to enhance day-ahead decisions regarding renewable energy generation, but may not be valid for imprecise uncertainties. New non-probabilistic uncertainty models are proposed to address this issue and improve the reliability and cost-efficiency of power system operation.
Article
Energy & Fuels
Egnonnumi Lorraine Codjo, Bashir Bakhshideh Zad, Jean-Francois Toubeau, Bruno Francois, Francois Vallee
Summary: This study uses machine learning techniques combined with smart meter data to accurately identify and classify the degradation of low-voltage cables. The results show that logistic regression and decision tree algorithms perform better in prediction accuracy compared to the k-nearest neighbors algorithm.
Article
Management
Adriano Arrigo, Christos Ordoudis, Jalal Kazempour, Zacharie De Greve, Jean-Francois Toubeau, Francois Vallee
Summary: This paper presents a distributionally robust chance-constrained optimization with a Wasserstein ambiguity set for energy and reserve dispatch, refining the model by enforcing physical bounds on the uncertainty space to achieve a cost-optimal yet reliable trade-off between reserve procurement and load curtailment.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Multidisciplinary Sciences
Claire Liefferinckx, Zacharie De Greve, Jean-Francois Toubeau, Helene Peree, Eric Quertinmont, Vjola Tafciu, Charlotte Minsart, Souad Rahmouni, Michel Georges, Francois Vallee, Denis Franchimont
Summary: Research on immune-mediated inflammatory diseases is challenging due to variability in disease presentation. This study aimed to characterize global immune cell composition and influencing factors. Blood samples from healthy subjects were analyzed using complementary clustering methods to assess immune cell variability.
SCIENTIFIC REPORTS
(2021)
Article
Engineering, Electrical & Electronic
Jean-Francois Toubeau, Thomas Morstyn, Jeremie Bottieau, Kedi Zheng, Dimitra Apostolopoulou, Zacharie De Greve, Yi Wang, Francois Vallee
Summary: This study introduces a new spatio-temporal framework for day-ahead probabilistic forecasting of DLMPs using a recurrent neural network enriched with deep bidirectional architecture. The method is able to predict nodal DLMPs effectively, enabling cold-start forecasting and adaptation to topological changes. Experimental results demonstrate that relying on a compact model is crucial for enhancing model generalization capabilities, and the tool performs well in both temporal and spatial learning tasks.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Engineering, Electrical & Electronic
Martin Hupez, Jean-Francois Toubeau, Zacharie De Greve, Francois Vallee
Summary: This article presents an original collaborative framework for power exchanges inside a low voltage community, seeking to minimize total costs by scheduling resources of its members on a daily basis. Two different cost distributions are proposed based on the Shapley value and Nash equilibrium, both leading to significant savings for individual members.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Energy & Fuels
Bashir Bakhshideh Zad, Jean-Francois Toubeau, Francois Vallee
Summary: This paper proposes a chance-constrained framework to manage the voltage control problem of medium-voltage distribution systems in the presence of model uncertainty. By formulating the voltage control problem with joint chance constraints, the impact of model uncertainty can be accurately controlled.
Article
Thermodynamics
Jean-Francois Toubeau, Lorie Pardoen, Louis Hubert, Nicolas Marenne, Jonathan Sprooten, Zacharie De Greve, Francois Vallee
Summary: This study explores the use of machine learning models to predict the outcome of contingency analyses, with random forests consistently outperforming other benchmarks in identifying safe maintenance periods. Additionally, the expected rise in renewable generation will impact the maintainability of the future system.
Article
Engineering, Electrical & Electronic
Hooman Khaloie, Francois Vallee, Chun Sing Lai, Jean-Francois Toubeau, Nikos D. Hatziargyriou
Summary: This paper proposes a dispatch model for an Integrated Biomass-Concentrated Solar (IBCS) system, aiming to maximize profit by considering the synergies from the coupled operation of these two energy sources. The model incorporates Information Gap Decision Theory (IGDT) and Conditional Value-at-Risk (CVaR) to handle uncertainty and risk exposure, and uses a multi-objective optimization approach to derive the optimal dispatch pattern.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Jean-Francois Toubeau, Jeremie Bottieau, Yi Wang, Francois Vallee
Summary: This paper introduces a new neural network architecture for efficient processing of time-based information and generating interpretable forecasts. The model internalizes the selection of relevant variables, providing insights on the relative importance of individual inputs, and incorporates an attention mechanism to focus on relevant contextual information for better understanding of dynamics. Experimental results show that adding modules for explainable forecasts improves the model's performance.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Automation & Control Systems
Ashkan Pirooz, Yousef Firouz, Joeri Van Mierlo, Maitane Berecibar
Summary: This article presents a flexible controller algorithm for bidirectional modular cascaded H-bridge (CHB)-based battery storage systems that aims to maintain high-quality power and balanced battery voltages. The algorithm is based on a finite-set model-predictive current control technique and takes advantage of voltage vector redundancy to achieve balancing. The proposed modifications improve computational efficiency and minimize voltage differentials caused by nonideal semiconductors. The approach is efficient, easy to implement, and eliminates the need for additional control loops. Simulations and experiments confirm the feasibility and positive impact of the battery voltage balancing terms in battery storage applications.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Maxime Gobert, Jan Gmys, Jean-Francois Toubeau, Nouredine Melab, Daniel Tuyttens, Francois Vallee
Summary: Bayesian Optimization (BO) with Gaussian process regression is a popular framework for optimizing time-consuming cost functions. However, the integration of BO with parallel processing capabilities remains challenging. This study investigates five parallel BO algorithms for optimal scheduling and highlights their strengths and weaknesses.
Proceedings Paper
Green & Sustainable Science & Technology
Bashir Bakhshideh Zad, Behzad Vatandoust, Jean-Francois Toubeau, Zacharie De Greve, Francois Vallee
Summary: This paper focuses on the integration of interconnection capacities through Flow-Based domains in the adequacy assessments of the Central Western Europe electricity system. The study proposes advanced clustering techniques to improve partition of Flow-Based domains, with fuzzy clustering technique showing significant improvements in cluster results compared to traditional approaches.
2021 IEEE MADRID POWERTECH
(2021)
Proceedings Paper
Green & Sustainable Science & Technology
Adriano Arrigo, Jalal Kazempour, Zacharie De Greve, Jean-Francois Toubeau, Francois Vallee
Summary: This paper extends the current state of the art related to Wasserstein distributionally robust optimal power flow problems by incorporating dependence structure and support information. By focusing on space-time dependencies in stochastic renewable power generation uncertainty, a moment-metric-based distributionally robust optimization is applied with a constraint on the second-order moment of uncertainty. The proposed decision-making model is enhanced by adding support information to exclude unrealistic probability distributions, and the reformulated model is shown to perform satisfactorily in terms of operational results and computational time.
2021 IEEE MADRID POWERTECH
(2021)
Proceedings Paper
Green & Sustainable Science & Technology
Jeremie Bottieau, Adriano Arrigo, Zacharie De Greve, Francois Vallee, Jean-Francois Toubeau
Summary: This paper introduces a novel distributionally robust decision support tool based on a bi-level model for market actors providing passive balancing services. The proposed approach offers optimal passive balancing services in expectation over a worst-case imbalance price distribution, ensuring performance guarantees.
2021 IEEE MADRID POWERTECH
(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.
