Article
Engineering, Electrical & Electronic
Ogbonnaya Bassey, Chen Chen, Karen L. Butler-Purry
Summary: Linear power flow formulations are presented for three-phase islanded droop-controlled microgrids, derived from current injection method and three-phase DistFlow formulation. The approximations were verified through time-domain simulations with nodal voltage errors below 1%. These linear power flow formulations can be easily solved using non-iterative linear matrix operations, and their optimal power flow extensions are linearly constrained.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
M. Elgamal, Akram Elmitwally, J. M. Guerrero
Summary: This paper proposes a hierarchical distributed multi-agent control system for an islanded microgrid with hybrid-energy resources and a battery-storage bank. The system utilizes three layers of control to achieve frequency and voltage stability while minimizing operation costs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Ahmed M. Hussien, Jonghoon Kim, Abdulaziz Alkuhayli, Mohammed Alharbi, Hany M. Hasanien, Marcos Tostado-Veliz, Rania A. Turky, Francisco Jurado
Summary: This research proposes a new technique for the optimum operation of an isolated microgrid based on an enhanced block-sparse adaptive Bayesian algorithm. Extensive simulations are conducted to demonstrate the superiority of the proposed method in the system's transient reactions.
Review
Energy & Fuels
Mudhafar Al-Saadi, Maher Al-Greer, Michael Short
Summary: Intelligent energy management plays a crucial role in renewable-based power distribution applications, and the adoption of artificial intelligence can help overcome challenges and achieve benefits in this transition towards decentralization and digitalization.
Article
Engineering, Multidisciplinary
A. M. Hussien, Hany M. Hasanien, S. F. Mekhamer
Summary: This paper introduces a novel application of the SFO algorithm to optimize the performance of inverter-based microgrids by selecting PI controller parameters. The research utilizes the RSM method to establish a multi-objective function and conducts testing under various operating states. Results confirm the effectiveness and flexibility of the proposed SFO algorithm compared to PSO.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Computer Science, Information Systems
Ahmed M. Hussien, Hany M. Hasanien, Mohammed H. Qais, Saad Alghuwainem
Summary: This study introduces a new method, AWGC-DA, to achieve robust performance in an isolated microgrid (MG). The method allows for adjustable kernel width to reject misleading input from attackers, and can identify attackers using a simple rule. Three optimization algorithms are used to improve the technique's effectiveness. The proposed method outperforms other methods in terms of transient response.
Article
Thermodynamics
Didar Tukymbekov, Ahmet Saymbetov, Madiyar Nurgaliyev, Nurzhigit Kuttybay, Gulbakhar Dosymbetova, Yeldos Svanbayev
Summary: This paper discusses an autonomous street lighting system with adaptive energy consumption based on weather forecast, which is completely powered by solar panels and can improve the energy efficiency of the street lighting system. By adjusting the brightness levels of lamps and forecasting energy generation by solar panels, the system shows stable and sustainable performance in simulations under random weather conditions for 1000 days.
Letter
Automation & Control Systems
Yalei Yu, Chen Guo, Tieshan Li
Summary: This letter addresses the path following of underactuated autonomous surface vessels (ASV) under surge velocity constraint, asymmetric saturation, and unknown dynamics. An adaptive finite-time sliding mode control scheme (AFTSM) is designed to cope with these constraints. The ASV's constraints are addressed by a novel rate and magnitude velocity guidance, projection-based finite-time auxiliary system, and parametric finite-time robust observer in this scheme. The effectiveness of the presented scheme is demonstrated through simulations and comparisons.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Article
Engineering, Civil
Shiyao Zhang, Christos Markos, James J. Q. Yu
Summary: The research team designed an autonomous vehicle intelligent system that provides joint ride-sharing and parcel delivery services under realistic constraints, using mixed-integer linear programming and Lagrangian dual decomposition method to ensure scalability. Experimental results show that the system can effectively provide services and meet the demands of transportation networks of various scales.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Sudha Anbalagan, Gunasekaran Raja, Sugeerthi Gurumoorthy, R. Deepak Suresh, Kapal Dev
Summary: Connected and Autonomous Vehicles (CAVs) enable various capabilities and functionalities in the real-time environment, but they also render potential vulnerabilities in the Internet of Vehicles (IoV) environment, making it susceptible to cyberattacks. This paper proposes an Intelligent IDS (IIDS) that uses a modified Convolutional Neural Network (CNN) with hyperparameter optimization approaches to enhance intrusion detection and categorize malicious AVs in IoV systems. The experimental results show that the proposed IIDS achieves 98% accuracy in detecting attacks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Thermodynamics
Junjie Zhong, Yijia Cao, Yong Li, Yi Tan, Yanjian Peng, Lihua Cao, Zilong Zeng
Summary: A distributed synergistic model with min max-min robust optimization is proposed for a 3-block integrated energy system, which effectively handles multiple uncertainties and accelerates the solution process with the developed C&CG-AOP algorithm. The simulation results show that the constructed uncertainty set considering spatial-temporal correlation and symmetry can reduce operating costs.
Article
Energy & Fuels
Bishwajit Dey, Srikant Misra, Fausto Pedro Garcia Marquez
Summary: The primary goal of this paper is to provide a demand-response (DR) model that maximizes the benefits of energy retailers, specifically microgrid customers. The model takes into account the different behaviors of customers during peak and valley periods and uses an exhaustive optimization process to calculate the optimal incentive value. The results show that the use of a DR-based energy management microgrid system significantly reduces overall generating costs and pollutants released, while also lowering the peak demand.
Article
Construction & Building Technology
Mansour Selseleh Jonban, Luis Romeral, Adel Akbarimajd, Zunaib Ali, Seyedeh Samaneh Ghazimirsaeid, Mousa Marzband, Ghanim Putrus
Summary: This paper presents a smart control and energy management system for a DC microgrid that distributes demand among several generators. An energy management system (EMS) based on multi-agent system (MAS) controller is developed to manage energy, control voltage, and maintain balance between supply and demand in the system to support reliability. The proposed approach includes a self-healing hierarchical algorithm to control agent interaction and ensure system reliability under faults, providing a robust and stable control of the microgrid.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Engineering, Civil
Juan Casavilca Silva, Muhammad Saadi, Lunchakorn Wuttisittikulkij, Davi Ribeiro Militani, Renata Lopes Rosa, Demostenes Zegarra Rodriguez, Sattam Al Otaibi
Summary: A learning-based framework for directly simulating the LF distribution is proposed to address the surface errors of MLA and limited pixel count issues in LF cameras. Experimental results demonstrate that the method outperforms existing approaches in LF image reconstruction, showing effective learning of LF distribution and generation of high-quality LF images.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Pedram Asef, Rahim Taheri, Mohammad Shojafar, Iosif Mporas, Rahim Tafazolli
Summary: This article investigates the performance of hybrid microgrids under cyber-physical security adversarial attacks and proposes defense algorithms to increase the robustness of the models.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Khamisi Kalegele, Kazuto Sasai, Hideyuki Takahashi, Gen Kitagata, Tetsuo Kinoshita
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2015)
Article
Chemistry, Analytical
Tetsuo Kinoshita
Article
Chemistry, Multidisciplinary
Yusuke Tanimura, Kazuto Sasai, Gen Kitagata, Tetsuo Kinoshita
APPLIED SCIENCES-BASEL
(2017)
Article
Chemistry, Analytical
Kazuto Sasai, Ryota Fukutani, Gen Kitagata, Tetsuo Kinoshita
Summary: This study proposes a multiagent-based data presentation mechanism for heuristic inference in network management tasks. The results indicate that multifaceted presentation of data can better support administrators compared to selected single-faceted optimal presentation.
Proceedings Paper
Computer Science, Artificial Intelligence
Kento Watanabe, Takahiro Uchiya, Ichi Takumi, Tetsuo Kinoshita
COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS, CISIS-2017
(2018)
Proceedings Paper
Mathematics, Applied
Kazuto Sasai, Yukio-Pegio Gunji, Tetsuo Kinoshita
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2016 (ICNAAM-2016)
(2017)
Article
Mathematics, Interdisciplinary Applications
Kazuto Sasai, Yukio-Pegio Gunji, Tetsuo Kinoshita
ADVANCES IN COMPLEX SYSTEMS
(2017)
Article
Robotics
Kazuto Sasai, Yukio-Pegio Gunji, Tetsuo Kinoshita
ARTIFICIAL LIFE AND ROBOTICS
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Yoshitaka Kato, Takahiro Uchiya, Ichi Takumi, Tetsuo Kinoshita
PROCEEDINGS OF 2016 10TH INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS (CISIS)
(2016)
Proceedings Paper
Computer Science, Artificial Intelligence
Kazuto Sasai, Hideyuki Takahashi, Gen Kitagata, Tetsuo Kinoshita
TRENDS IN APPLIED KNOWLEDGE-BASED SYSTEMS AND DATA SCIENCE
(2016)
Proceedings Paper
Computer Science, Theory & Methods
Takahiro Uchiya, Motohiro Shibakawa, Ichi Takumi, Tetsuo Kinoshita
2015 IEEE/ACIS 14TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS)
(2015)
Proceedings Paper
Computer Science, Software Engineering
Takumi Kato, Ryo Chiba, Hideyuki Takahashi, Tetsuo Kinoshita
IEEE 39TH ANNUAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE WORKSHOPS (COMPSAC 2015), VOL 3
(2015)
Proceedings Paper
Computer Science, Hardware & Architecture
Masato Hibino, Takahiro Uchiya, Ichi Takumi, Tetsuo Kinoshita
PROCEEDINGS 2015 18TH INTERNATIONAL CONFERENCE ON NETWORK-BASED INFORMATION SYSTEMS (NBIS 2015)
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
Kazuto Sasai, Hideyuki Takahashi, Gen Kitagata, Tetsuo Kinoshita
2014 IEEE 13TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI-CC)
(2014)
Proceedings Paper
Computer Science, Artificial Intelligence
Akiko Takahashi, Makoto Oide, Mitsuru Abe, Tetsuo Kinoshita
2014 IEEE 13TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI-CC)
(2014)
