Article
Energy & Fuels
Rishal Asri, Hirohisa Aki, Daisuke Kodaira
Summary: Solar photovoltaic generation and energy storage are increasingly important in supplying electricity to remote areas. However, private energy storage systems are burdensome for consumers in remote areas, and communal energy storage faces economic constraints. This study proposes a new model for shared energy storage using the Neighbor scenario, which can save costs and increase storage utilization rate compared to other scenarios. A sensitivity analysis demonstrates optimal operation in terms of economic and emission parameters.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Multidisciplinary Sciences
Masoud Dashtdar, Aymen Flah, Seyed Mohammad Sadegh Hosseinimoghadam, Attia El-Fergany
Summary: In this paper, a self-tuning PI-controller based on a combination of genetic algorithm and artificial neural network is proposed for frequency control in microgrids. The controller can automatically adjust and optimize its coefficients and avoid being stuck in local minimum points. Simulation results show that the proposed controller performs well.
SCIENTIFIC REPORTS
(2022)
Article
Energy & Fuels
Luoyi Li, Ying Han, Qi Li, Yuchen Pu, Cai Sun, Weirong Chen
Summary: This paper presents an event-triggered decentralized coordinated control method for an islanded electric-hydrogen hybrid DC microgrid. By analyzing the operation characteristics of the subsystem, a real-time efficient operating cost function is constructed, and an improved economic control strategy based on this function is designed to drive the electric-hydrogen hybrid energy storage system for economical and reliable operation. Experimental results from the RL-LAB platform demonstrate the economic benefits and effectiveness of the proposed decentralized method in ensuring reliability in various scenarios.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Green & Sustainable Science & Technology
Muhammad Maaruf, Khalid Khan, Muhammad Khalid
Summary: This paper proposes a robust sliding mode control strategy for hybrid renewable energy systems to achieve maximum power point tracking and stabilize energy management.
Article
Energy & Fuels
Mehrdad Bagheri-Sanjareh, Mohammad Hassan Nazari, Seyed Hossein Hosseinian
Summary: This paper proposes a novel frequency-based energy management scheme using lithium-ion batteries for primary frequency control and energy management, while dispatchable distributed generators supply the base load. Additionally, replacing thermal energy storage systems for controlling indoor temperatures can significantly reduce the demand for LIBESSs and the overall storage cost.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Alok Agrawal, Rajesh Gupta
Summary: This paper presents a new Energy Storage Device (ESD) charge controller for integrating multiple hybrid ESD stacks in DC microgrids. The controller effectively handles source-load and voltage fluctuations, while providing system redundancy. Unlike conventional controllers, this algorithm only requires one voltage sensor, simplifying control circuitry and hardware implementation. Simulation and experimental results demonstrate the viability and stability of the proposed controller.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Da Xu, Zhe-Li Yuan, Ziyi Bai, Zhibin Wu, Shuangyin Chen, Ming Zhou
Summary: This paper proposes a geothermal-solar-wind renewable energy hub framework for community multi-energy supplies. The framework explores the complementarities of geothermal-solar-wind hybrid renewable energy based on the electrolytic thermo-electrochemical effects of geothermal-to-hydrogen (GTH), integrated with multi-energy conversion and storage devices. A multi-energy coupling matrix is formulated to model the production, conversion, storage, and consumption of electricity, hydrogen, and heating energy within the hub. A multi-energy operation scheme is developed to dispatch the energy flows for cost-effective accommodation of community renewables. Case studies verify the effectiveness and superiority of the proposed methodology, showing improved solar-wind accommodation and lower system operating costs.
Article
Energy & Fuels
Ibrahim A. Bello, Malcolm D. McCulloch, Daniel J. Rogers
Summary: The paper presents a technique for compressing data in smart energy systems by substituting data points with linear regression coefficients. Experimental results demonstrate the effectiveness of the technique in compressing load profiles and household energy data with high compression performance and ratios.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Energy & Fuels
Yang Liu, Zhanpeng Jiang, Zuoxia Xing, Lichao Hao, Boyang Qu
Summary: This paper proposes a combined heat and power (CHP) microgrid model with renewable energy and calculates the optimal scheduling problem using an improved particle swarm algorithm, proposing an optimal scheduling strategy considering both economy and low carbon.
Article
Engineering, Electrical & Electronic
Sarthak Chopra, Gowtham Meda Vanaprasad, Gibran David Agundis Tinajero, Najmeh Bazmohammadi, Juan C. Vasquez, Josep M. Guerrero
Summary: This paper introduces a novel approach to optimize the operation of islanded AC microgrids, and validates the proposed energy management algorithm through two case studies, demonstrating its efficiency and reliability in optimal operation of microgrids with multiple renewable energy sources.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Nikola Simic, Luka Strezoski, Boris Dumnic
Summary: The fault currents in microgrids can fluctuate widely depending on whether they are operating in grid-connected mode or islanded mode. When in islanded mode, the fault current contribution from distributed energy resources (DERs) is significantly lower compared to grid-connected mode. Most DERs are inverter-based, contributing to lower overall fault currents in islanded mode. The differences in fault currents between the two operation modes can have a significant impact on relay protection systems in microgrids.
Article
Green & Sustainable Science & Technology
Yan Du, Di Wu
Summary: This paper proposes a novel two-stage learning framework for identifying an optimal restoration strategy in an islanded microgrid. The method utilizes deep deterministic policy gradient and expert demonstrations for pre-training, and employs action clipping, reward shaping, and expert demonstrations for online training to ensure safe exploration and accelerate the training process.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Energy & Fuels
Pinaki Dhar, Niladri Chakraborty
Summary: A novel scheme utilizing gravity energy storage system (GESS) and wind turbine (WT) has been proposed in this article for uninterrupted energy generation in areas with limited or no grid connectivity. The system is characterized by its simplicity, stable energy output, and low maintenance expenditure.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Md. Fatin Ishraque, Akhlaqur Rahman, Sk. A. Shezan, G. M. Shafiullah
Summary: This research examines the potential of a hybrid renewable energy microgrid with a dispatch strategy for a proposed location in Maldives, both in off-grid and on-grid conditions. The analysis includes technical, environmental, economic, and power system responses, and evaluates different strategies for the microgrid. The findings show the performance of various strategies and demonstrate the stable operation of the proposed system using dispatch techniques and voltage Q-droop and input mode P-Q controller.
Article
Green & Sustainable Science & Technology
Koksal Erenturk, Azeddine Draou, Abdulrahman AlKassem
Summary: In this paper, different types of synergetic controllers are designed and applied to an islanded DC microgrid. A generalized mathematical method is derived for all power electronics-based subsystems. A small-scale experimental system is designed and the performance of different controllers is verified through simulation and experiment tests.
Article
Engineering, Electrical & Electronic
Sami Ekici, Ferhat Ucar, Besir Dandil, Reza Arghandeh
Summary: Management of the electrical grid is crucial for the sustainability and reliability of the electrical energy supply. This article introduces a novel method for classifying power quality disturbances using deep learning and image processing, achieving a high accuracy of 99.8%.
ELECTRICAL ENGINEERING
(2021)
Article
Engineering, Civil
Mingyang Chen, Alican Karaer, Eren Erman Ozguven, Tarek Abichou, Reza Arghandeh, Jaap Nienhius
Summary: Hurricanes have devastating consequences on people and infrastructure, prompting the need for measures to alleviate their impacts. This paper proposes an integrated methodology using satellite images and GIS to study vegetation change and urban structure to identify areas most affected by hurricanes.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Construction & Building Technology
Behzad Najafi, Monica Depalo, Fabio Rinaldi, Reza Arghandeh
Summary: The study focuses on extracting influential features from smart meter data to improve machine learning-based classification of non-residential buildings. Through advanced feature selection methods and a custom approach, the number of features needed for classification is reduced while accuracy is increased. By selecting and utilizing fewer features, the methodology simplifies feature extraction procedures and enhances interpretation of important features' influence.
ENERGY AND BUILDINGS
(2021)
Article
Environmental Studies
Mahyar Ghorbanzadeh, Mohammadreza Koloushani, Eren Erman Ozguven, Arda Vanli, Reza Arghandeh
Summary: This study assessed the impacts of Hurricane Hermine on the transportation network of Tallahassee, Florida, by analyzing spatial patterns of roadway closures and power outages using GIS-based analysis, and developing a statistical model to understand the association between variables. The results indicated that power outages and power lines have strong relationships with roadway closures, and the city center experienced more disruptions than other areas. This knowledge can help city officials prepare better emergency policies for potential future hurricanes.
ENVIRONMENTAL HAZARDS-HUMAN AND POLICY DIMENSIONS
(2022)
Article
Engineering, Electrical & Electronic
Michele Gazzea, Michael Pacevicius, Dyre Oliver Dammann, Alla Sapronova, Torleif Markussen Lunde, Reza Arghandeh
Summary: This paper proposes an automated framework for monitoring vegetation along power lines using high-resolution satellite imagery and machine learning algorithms, aiming to reduce monitoring costs and time by replacing ground patrols and helicopter/drone inspections.
IEEE TRANSACTIONS ON POWER DELIVERY
(2022)
Article
Automation & Control Systems
Michele Gazzea, Alican Karaer, Mahyar Ghorbanzadeh, Nozhan Balafkan, Tarek Abichou, Eren Erman Ozguven, Reza Arghandeh
Summary: This article proposes a method to automatically identify fallen trees on roadways using high-resolution satellite imagery before and after hurricanes. The method employs a covoting strategy of three algorithms and tailored dissimilarity scores, making it more practical than existing approaches.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Editorial Material
Automation & Control Systems
Reza Arghandeh, Bahri Uzunoglo, Salvatore D'arco, Eren Ozguven
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Geosciences, Multidisciplinary
Alican Karaer, Mingyang Chen, Michele Gazzea, Mahyar Ghorbanzadeh, Tarek Abichou, Reza Arghandeh, Eren Erman Ozguven
Summary: Transportation systems are vulnerable to catastrophic storms and it is important to quickly evaluate the damage caused by these storms. This paper introduces a remote sensing-based approach that can analyze the damage caused by different strengths of storms and provide a comparative assessment. The results show that suburban and urban areas, as well as areas with higher roadway density, generate more debris compared to rural areas with lower roadway density.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Engineering, Electrical & Electronic
Mehmet Baran Ulak, Lalitha Madhavi Konila Sriram, Ayberk Kocatepe, Eren Erman Ozguven, Reza Arghandeh
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2022)
Article
Engineering, Civil
Michele Gazzea, Alican Karaer, Mahyar Ghorbanzadeh, Eren Erman Ozguven, Reza Arghandeh
Summary: This study uses remote sensing techniques and satellite images to detect road vulnerabilities to hurricanes and creates a vulnerability map by assigning vulnerability scores to each road. The findings can assist management teams and city responders in identifying the most vulnerable regions and organizing resources in advance.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Environmental Sciences
Oscar Sommervold, Michele Gazzea, Reza Arghandeh
Summary: After years of research, the problem of automatic SAR-optical registration remains unsolved. Combining SAR and optical satellites can improve remote sensing applications, but it is a challenging process due to the differences in imaging mechanisms and characteristics. Machine learning-based approaches show potential in bridging the information gap, but there are still challenges and no one-size-fits-all approach available.
Article
Multidisciplinary Sciences
Mojtaba Yousefi, Jinghao Wang, Oivind Fandrem Hoivik, Jayaprakash Rajasekharan, August Hubert Wierling, Hossein Farahmand, Reza Arghandeh
Summary: Climate change has significant impacts on river water regimes, which in turn affect hydropower generation and reservoir storage operation. Reliable and accurate short-term inflow forecasting is crucial for better understanding and addressing these climate effects. This paper proposes a Causal Variational Mode Decomposition (CVD) preprocessing framework for inflow forecasting, which can reduce computation time and improve forecasting accuracy by selecting the most relevant features.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Michele Gazzea, Adrian Solheim, Reza Arghandeh
Summary: This study explores the potential of high-resolution X-band synthetic aperture radar (SAR) and optical images for pixel-wise mapping of forest structure attributes, achieving promising results.
SCIENCE OF REMOTE SENSING
(2023)
Article
Engineering, Electrical & Electronic
Michele Gazzea, Oscar Sommervold, Reza Arghandeh
Summary: In this article, an end-to-end machine learning pipeline inspired by image segmentation is proposed for feature extraction from satellite images. The siamese multiscale attention-gated residual U-Net transforms heterogeneous images into a homogeneous feature space and computes cross-correlation using fast Fourier transform. Experimental results demonstrate that the proposed method achieves superior matching accuracy and precision compared to other state-of-the-art methods.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Michele Gazzea, Lars Michael Kristensen, Francesco Pirotti, Eren Erman Ozguven, Reza Arghandeh
Summary: This article introduces a weakly supervised method based on deep learning for estimating tree species using remote-sensing technology in multiple study areas, and validates the effectiveness of the method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
