Article
Automation & Control Systems
Yoan Martinez-Lopez, Ansel Y. Rodriguez-Gonzalez, Julio Madera, Miguel Bethencourt Mayedo, Fernando Lezama
Summary: The Energy Resource Management problem can be modeled as a Mixed-Integer Non-Linear Problem, where uncertainties need to be considered during optimization. In this context, evolutionary algorithms can provide effective near-optimal solutions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Information Systems
Alexandre B. Nassif, Sean Ericson, Chad Abbey, Robert Jeffers, Eliza Hotchkiss, Shay Bahramirad
Summary: Extreme climate events have increased the need for resilient electrical infrastructure, especially in areas prone to hurricanes, floods, and wildfires. Microgrids and advanced controls are a promising solution to improve grid resilience. This paper presents a technoeconomic analysis approach to evaluate the economic benefits of grid resilience investments, using Vieques and Culebra islands in Puerto Rico as a case study.
Article
Computer Science, Information Systems
Georgios Tsaousoglou, Polyzois Soumplis, Nikolaos Efthymiopoulos, Konstantinos Steriotis, Aristotelis Kretsis, Prodromos Makris, Panagiotis Kokkinos, Emmanouel Varvarigos
Summary: The uncertain and non-dispatchable nature of renewable energy sources makes Demand Response (DR) an essential component of modern electricity distribution systems. This article presents a distributed DR market clearing algorithm based on Lagrangian decomposition, combined with an optimal cloud resource allocation algorithm. Simulations demonstrate the near-optimal performance of this algorithm and its ability to meet the demands of multiple DR requests.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Construction & Building Technology
Zhanwei He, Javad Khazaei, Faegheh Moazeni, James D. Freihaut
Summary: The proposed approach in this paper utilizes a simplified neural network to detect false data injection (FDI) attacks targeting transmission lines in smart grids. The innovation lies in its ability to detect stealthy attacks that not only bypass state-estimation, but also result in congestion of transmission lines. Numerical results demonstrate the high accuracy of the method in detecting cyber-physical attacks, and case studies are included to test its resilience in various scenarios.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Engineering, Electrical & Electronic
Wenqu Li, Zhi-Wei Liu, Wei Yao, Yaowen Yu
Summary: Line outage detection is crucial for preventing and recovering from power system black-outs. In this study, compressive sensing theory is applied to address the issue of detecting multiple line outages in power systems, given the sparsity of such outages in the early stages. A binary matching pursuit algorithm is proposed to solve the problem, and a dice coefficient and an atom exclusion strategy are introduced to enhance detection accuracy. The complexity of the algorithm is also analyzed. Simulation results demonstrate that the proposed algorithm is more resilient to noise, less sensitive to data sampling size, and has lower computational burden with higher detection efficiency.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Computer Science, Information Systems
Hao Liu, Yunliang Chen, Ningning Cui, Dazhao Xu, Jianxin Li
Summary: This article presents a novel data fusion model, KNN-XGBoost, for predicting missing values. Experimental results demonstrate that the proposed model improves accuracy compared to other methods.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Chemical
Matej Vrtal, Jan Benedikt, Radek Fujdiak, David Topolanek, Petr Toman, Jiri Misurec
Summary: This paper describes the design of a simulation platform that provides simulations of interconnected data networks and power grids through a virtual user interface. By developing complex models and using multiple open-source tools for virtualization, important outputs for analyzing critical infrastructures at the level of urban networks can be obtained.
Article
Engineering, Multidisciplinary
Mehmet Gucyetmez, Husham Sakeen Farhan
Summary: The traditional electricity grid needs to be transformed into a smart grid infrastructure to address the increasing electricity demand and energy prices. Smart meters play a vital role in this transformation by enabling consumers to track their energy consumption and receive warnings. The developed Internet of Things (IoT) based smart meter has features like high data rate, bidirectional data transmission, and integration with fuzzy system and mobile application software.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Review
Green & Sustainable Science & Technology
Sara Barja-Martinez, Monica Aragues-Penalba, Ingrid Munne-Collado, Pau Lloret-Gallego, Eduard Bullich-Massague, Roberto Villafafila-Robles
Summary: This paper provides a comprehensive analysis of artificial intelligence applications in distribution power systems, covering various aspects such as operation, monitoring, maintenance, and planning. It identifies potential AI techniques for power system applications and needed data sources. The study also examines data-driven services for distribution networks, highlighting interdependencies between different services and the importance of enhanced sensorization for better service outcomes.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Energy & Fuels
Yizheng Liao, Yang Weng, Chin-Woo Tan, Ram Rajagopal
Summary: This paper proposes a data-driven outage monitoring approach based on stochastic time series analysis to identify line outages in distribution grids. The method only requires voltage magnitude data and achieves high accuracy in outage identification, making it suitable for distribution grids with large-scale DER penetration.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Marco Pau, Zid Tamim
Summary: This article presents a novel state estimation (SE) solution based on the backward-forward sweep (BFS) method, which is tailored to the monitoring of radially operated distribution grids. The designed algorithm allows integrating redundant measurements for SE purposes while offering the typical benefits of the BFS approach. The proposed formulation achieves the same accuracy performance of classical Weighted Least Squares estimators.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Review
Chemistry, Multidisciplinary
Maria Fotopoulou, Stefanos Petridis, Ioannis Karachalios, Dimitrios Rakopoulos
Summary: This paper reviews the algorithms for Distribution System State Estimation (DSSE), focusing on their specific requirements, mathematical formulation, existing model-based and data-driven approaches, and recommended solutions. The paper also highlights DSSE applications and future trends, emphasizing the business-related aspects.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Qin Shu, Yu Fan, Fangwei Xu, Chang Wang, Jinyan He
Summary: This paper proposes a new method for utility side harmonic impedance estimation based on the Burg algorithm and AR model, which considers the timing correlation to estimate the harmonic impedance accurately. The proposed method is robust and has small error in estimation results, and is not limited by some traditional assumptions.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Li Ding, Shihao Nie, Wenqu Li, Ping Hu, Feng Liu
Summary: This article investigates the problem of multiple line outage detection through sparse representation and an accumulation-based method, introducing an adaptive threshold selection rule and an event-triggered mechanism to improve performance and reduce computational burden. Numerical experiments are conducted to illustrate the effectiveness of the proposed method based on the IEEE Standard Test Bus System.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Automation & Control Systems
Maman Ahmad Khan, Barry Hayes
Summary: This article presents a two-layer state estimation technique based on smart meters for integrated monitoring of medium-voltage and low-voltage power distribution networks. The technique improves the accuracy and stability of distribution system state estimation through topology reduction and linear estimation methods.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Umair Fakhar, Humayun Zubair Khan, Zarrar Tariq, Mudassar Ali, Ahmad Naeem Akhtar, Muhammad Naeem, Abdul Wakeel
Summary: This paper investigates the issues of admission control, user association, and power distribution in Satellite-Terrestrial Integrated Networks (STIN) to improve energy efficiency and ensure fairness in user association and spectrum resource allocation.
Article
Energy & Fuels
Saad Salman Khan, Sadiq Ahmad, Muhammad Naeem
Summary: This study proposes a robust optimization technique to solve the uncertainty problem in the energy management and trading framework of smart power systems. The model takes into account practical constraints such as human factors, load shedding patterns, peak clipping, and consumer preferences to achieve lower cost energy utilization.
Article
Telecommunications
Mushtaq Ahmad, Muhammad Awais, Muhammad Naeem, Muhammad Altaf, Muhammad Iqbal, Muhammad Abrar
Summary: This paper proposes an effective resource management approach for D2D networks, which maximizes both overall throughput and the number of admitted users. The approach solves the NP-complete problem using the BPSO algorithm and achieves better performance compared to other solutions.
TELECOMMUNICATION SYSTEMS
(2023)
Article
Medicine, General & Internal
Riaz Ahmad, Muhammad Awais, Nabeela Kausar, Tallha Akram
Summary: This paper presents an improved hybrid approach for efficient white blood cell (WBC) subtype classification. It uses transfer learning on pre-trained deep neural networks to extract optimum deep features from enhanced and segmented WBC images, and then filters the feature vector using an entropy-controlled marine predator algorithm. The proposed method achieves an overall average accuracy of 99.9% with more than 95% reduction in the size of the feature vector.
Article
Computer Science, Information Systems
Muhammad Ahsan, Ashfaq Ahmed, Arafat Al-Dweik, Arsalan Ahmad
Summary: This article proposes an optimal BBU placement using a mixed functional split scheme to address the challenge of fronthaul latency and reduce network cost.
IEEE SYSTEMS JOURNAL
(2023)
Article
Computer Science, Information Systems
Glaucio H. S. Carvalho, Isaac Woungang, Alagan Anpalagan, Issa Traore
Summary: This article proposes an optimal admission and placement stochastic controller that ensures the security and latency compliance of an edge-cloud system under 5G deployment. By analyzing the structure of the optimal policy and numerical results, the implementation friendliness of the controller and the potential for cost optimization are demonstrated.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Peter He, Alagan Anpalagan, Waleed Ejaz
Summary: In this paper, an Iterative Water-Filling algorithm named IWF-EE-MIMO is proposed for the Energy-Efficiency maximization problem of the Multi-User Multiple-Input Multiple-Output Multiple-Access-Channel (MU-MIMO-MAC) system. The algorithm consists of two levels of operations: the inner level computes the solution for each user while the outer level determines when to accept a good solution based on the inner level results. The considered problem is of non-linear fractional semi-definite optimization in complex-valued matrix optimization variables, and the optimality condition needs to be created.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Telecommunications
Alishba Azam, Muhammad Imran, Mudassar Ali, Humayun Zubair Khan, Abdul Wakeel, Muhammad Naeem
Summary: Current 5G networks must be upgraded to 6G networks as data rate demands increase. The emerging technology of re-configurable intelligent surfaces (RISs) can optimize wireless environments and improve network throughput. This paper investigates the joint user and throughput maximization problem in RIS-assisted B5G/6G wireless networks, considering power transmission, quality of service, and phase shift constraints. A mesh adaptive direct search (MADS) algorithm is proposed to efficiently solve the non-convex problem. Extensive simulations demonstrate that incorporating RIS in a network can increase throughput and maximize admitted users, and the proposed MADS algorithm outperforms existing algorithms with low computational complexity.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2023)
Article
Oncology
Riaz Ahmad, Muhammad Awais, Nabeela Kausar, Usman Tariq, Jae-Hyuk Cha, Jamel Balili
Summary: Leukocytes, or white blood cells (WBCs), are essential for the immune system, but abnormal proliferation can lead to leukemia. Using deep convolutional neural networks for automated WBC classification shows promising accuracy, but is computationally expensive. This study proposes an improved pipeline that uses deep neural networks for feature extraction, quantum-inspired evolutionary algorithm for feature selection, and multiple baseline classifiers for final classification. The results demonstrate a 99% classification accuracy with a 90% reduction in feature vector size.
Article
Medicine, General & Internal
Shairyar Malik, Tallha Akram, Muhammad Awais, Muhammad Attique Khan, Myriam Hadjouni, Hela Elmannai, Areej Alasiry, Mehrez Marzougui, Usman Tariq
Summary: The demand for accurate and timely identification of melanoma is increasing. Many studies have been done on skin cancer classification and segmentation techniques, but there is still room for new research. This research proposes a hybrid metaheuristic preprocessor, BA-ABC, to improve image quality and validates its efficacy using publicly available datasets.
Article
Engineering, Electrical & Electronic
Muhammad Ahsan, Ashfaq Ahmed, Huma Fida, Arafat Al-Dweik, Umair Sajid Hashmi, Arsalan Ahmad
Summary: Network slicing in 5G RAN allows for efficient allocation of network resources to meet different service quality requirements. This paper proposes a novel cloud fog RAN architecture that divides RAN functions into layers to improve BBU centralization and request handling performance.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Zaiba Shah, Umer Javed, Muhammad Naeem, Sherali Zeadally, Waleed Ejaz
Summary: This paper investigates the problem of maximizing the utility function in disaster scenarios by jointly optimizing the computing power, user associations, performance, duration, and location of user equipments (UEs) in UAV-assisted MEC networks. A multi-stage offloading algorithm based on a learning algorithm and an interior-point method is proposed to obtain a viable solution. The simulation results demonstrate the effectiveness of the proposed algorithm compared to existing schemes.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Hamad Yahya, Ashfaq Ahmed, Emad Alsusa, Arafat Al-Dweik, Zhiguo Ding
Summary: Non-orthogonal multiple access (NOMA) is a potential technique for improving the spectral efficiency of wireless networks, with recent focus shifting to error rate analysis of different NOMA configurations. This paper serves as a survey on NOMA error rate analysis, providing key insights for readers to understand the progress in this area. In addition to summarizing the principles of NOMA error rate analysis, it aims to minimize redundancy, identify research gaps, and outline future research directions.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
Article
Computer Science, Information Systems
Rizwana Shahzadi, Mudassar Ali, Muhammad Naeem
Summary: The advancements in technology have influenced our daily lives and transformed the way we interact and share information. The rise of social media platforms has changed the way people communicate. Unmanned aerial vehicles (UAVs) have potential in heterogeneous networks (HetNets) due to their advantages in providing additional coverage and capacity in crowded or disaster-hit areas. This study proposes an optimized resource allocation problem and a novel algorithm to solve it in UAV-assisted HetNets, with simulation results demonstrating its outperformance compared to conventional methods.
Article
Computer Science, Information Systems
Ashfaq Ahmed, Abdulhadi Shoufan, Kais Belwafi
Summary: The semiconductor supply chain is susceptible to various security attacks, including hardware Trojan injection, intellectual property theft, and overproduction. The concept of zero-trust (ZT) provides a promising opportunity for chip security by authenticating integrated circuits (ICs) during their connection to critical computing systems. This paper proposes the use of secure protocol and data model (SPDM) for chip-to-chip (C2C) zero-trust communications. Formal models are presented and verified using state-of-the-art formal verification tools, demonstrating that SPDM meets the requirements of the ZT architecture and can serve as a foundation for secure C2C interconnection.
Article
Computer Science, Artificial Intelligence
Guiliang Gong, Jiuqiang Tang, Dan Huang, Qiang Luo, Kaikai Zhu, Ningtao Peng
Summary: This paper proposes a flexible job shop scheduling problem with discrete operation sequence flexibility and designs an improved memetic algorithm to solve it. Experimental results show that the algorithm outperforms other algorithms in terms of performance. The proposed model and algorithm can help production managers obtain optimal scheduling schemes considering operations with or without sequence constraints.
SWARM AND EVOLUTIONARY COMPUTATION
(2024)
Article
Computer Science, Artificial Intelligence
Daniel Molina-Perez, Efren Mezura-Montes, Edgar Alfredo Portilla-Flores, Eduardo Vega-Alvarado, Barbara Calva-Yanez
Summary: This paper presents a new proposal based on two fundamental strategies to improve the performance of the differential evolution algorithm when solving MINLP problems. The proposal considers a set of good fitness-infeasible solutions to explore promising regions and introduces a composite trial vector generation method to enhance combinatorial exploration and convergence capacity.
SWARM AND EVOLUTIONARY COMPUTATION
(2024)
