Article
Engineering, Electrical & Electronic
Ahmad M. Alshamrani
Summary: This research focuses on developing a mathematical methodology for joint transmission network and wind power investment problem under a centralized approach. The objective function is defined as the ratio of total cost to total wind power generation, allowing the operator to minimize overall cost while maximizing wind power output.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Computer Science, Software Engineering
Niels van der Laan, Ward Romeijnders
Summary: The study introduces a new class of convex approximations, generalized alpha-approximations, which are more suitable for efficient computations than existing methods. By constructing a loose Benders decomposition algorithm, large problem instances can be solved in reasonable time.
MATHEMATICAL PROGRAMMING
(2021)
Article
Mathematics
Francisco Fernandez-Navarro, Luisa Martinez-Nieto, Mariano Carbonero-Ruz, Teresa Montero-Romero
Summary: This paper introduces the mean-variance (MV) portfolio and mean squared variance (MSV) portfolio methods, and proposes a mixed-integer linear programming (MILP) reformation for the non-convex QP problem, as well as a data-driven method for determining the optimal value of the hyper-parameter. Empirical tests show that the MSV portfolio exhibits competitive performance in most problems.
Article
Computer Science, Software Engineering
Ilias Zadik, Miles Lubin, Juan Pablo Vielma
Summary: We investigate the structural geometric properties of mixed-integer convex representable (MICP-R) sets and compare them with the class of mixed-integer linear representable (MILP-R) sets. We provide examples of MICP-R sets that are countably infinite unions of convex sets with countably infinitely many different recession cones, and countably infinite unions of polytopes with different shapes. These examples highlight the differences between MICP-R sets and MILP-R sets.
MATHEMATICAL PROGRAMMING
(2023)
Article
Computer Science, Information Systems
Baha Alzalg, Hadjer Alioui
Summary: This paper discusses five applications that lead to stochastic mixed-integer second-order cone programming problems, presents solution algorithms for solving these problems, and explores how bringing applications to the surface can detect tractable special cases.
Article
Economics
Juyoung Wang, Mucahit Cevik, Saman Hassanzadeh Amin, Amir Ali Parsaee
Summary: The study focuses on a reverse logistics network for household hazardous wastes, utilizing multiobjective mixed-integer deterministic and stochastic mathematical models to optimize transportation costs, reduce risks, maximize convenience, and enhance participation. By proposing an optimization framework and using a testbed, the analysis aims to address waste management challenges.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Operations Research & Management Science
Saravanan Venkatachalam, Lewis Ntaimo
Summary: This paper develops the theory of integer set reduction for solving two-stage stochastic mixed-integer programs with general integer variables in the second-stage. The goal is to generate a valid inequality by using the smallest possible subset of the subproblem feasible integer set, similar to Fenchel decomposition cuts, in order to reduce computation time. An algorithm is devised to obtain such a subset based on the solution of the subproblem linear programming relaxation and incorporated into a decomposition method for SMIP. A computational study based on randomly generated knapsack test instances demonstrates the effectiveness of the new integer set reduction methodology in speeding up cut generation and obtaining better bounds compared to using a direct solver in solving SMIPs with pure integer recourse.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2023)
Article
Computer Science, Software Engineering
Xian Yu, Siqian Shen
Summary: In this study, we investigate multistage distributionally robust mixed-integer programs with endogenous uncertainty. We propose two ambiguity sets based on decision-dependent bounds and empirical moments. We show that the subproblems in each stage can be formulated as mixed-integer linear programs. Additionally, we extend the moment-based ambiguity set and derive mixed-integer semidefinite programming reformulations. We develop methods to approximate the optimal objective value and solve the problem using the Stochastic Dual Dynamic integer Programming (SDDiP) method. Numerical experiments demonstrate the effectiveness of the proposed approach in solving multistage facility-location problems with decision-dependent distributional ambiguity.
MATHEMATICAL PROGRAMMING
(2022)
Article
Mathematics, Applied
Kurt M. Anstreicher
Summary: This method utilizes the computational power of modern MILP solvers to test if a given matrix is copositive by solving a single mixed-integer linear programming problem. Numerical experiments demonstrate that the method is robust and efficient.
LINEAR ALGEBRA AND ITS APPLICATIONS
(2021)
Article
Automation & Control Systems
Andrea Camisa, Giuseppe Notarstefano
Summary: This article discusses the distributed control of microgrids, taking into account the unpredictability of renewable energy sources. A distributed methodology based on neighboring communication is proposed and its effectiveness is verified through numerical experiments.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Computer Science, Software Engineering
Fengqiao Luo, Sanjay Mehrotra
Summary: The paper introduces a decomposition algorithm for distributionally-robust two-stage stochastic mixed-integer convex conic programs, ensuring finite convergence by solving second-stage problems to optimality and identifying worst-case probability distribution. The algorithm can be used with a branch and cut algorithm or a parametric cuts based algorithm for solving second stage problems. An example illustration of the decomposition algorithm shows significant improvements in solution time, making solutions possible for previously intractable models. Computational results also indicate similar optimality gaps between distributionally robust instances and their stochastic programming counterparts.
MATHEMATICAL PROGRAMMING
(2022)
Article
Computer Science, Interdisciplinary Applications
Bernard Knueven, James Ostrowski, Anya Castillo, Jean-Paul Watson
Summary: In electricity markets, convex hull pricing offers a solution to the challenges posed by non-convex production offers, providing uniform prices while minimizing side payments. The computation of convex hull prices can be achieved through solving large-scale linear programs or the Lagrangian dual of non-convex scheduling problems, with the Benders decomposition approach offering a more efficient solution.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Management
Niels van der Laan, Ward Romeijnders
Summary: We propose a new solution method for two-stage mixed-integer recourse models that can handle general mixed-integer variables in both stages. Our method is based on Benders' decomposition, where we iteratively construct tighter approximations of the expected second stage cost function using a new family of optimality cuts derived from extended formulations of the second stage problems. We show convergence of our method by proving that the optimality cuts recover the convex envelope of the expected second stage cost function. Finally, we demonstrate the potential of our approach through numerical experiments on investment planning and capacity expansion problems.
OPERATIONS RESEARCH
(2023)
Article
Automation & Control Systems
Rubens J. M. Afonso, Roberto K. H. Galvao
Summary: This note addresses the problem of crossing a target set between sample instants under the influence of bounded unknown disturbances. The proposed solution utilizes mixed-integer linear programming and is less conservative compared to the standard approach of imposing pointwise-in-time constraints at the sample instants.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Thermodynamics
Karl Vilen, Erik O. Ahlgren
Summary: Most computer models used in energy systems optimization modeling studies are constructed using linear equations. However, linear equations may not adequately reflect real-world conditions and are less suitable for representing individual-scale technologies in local system studies. This study investigates the differences in heating solutions and model solution times for a local expanding heating system. The results show that the use of district heating is higher for cost structures that use mixed integer linear programming. On the other hand, the solution time is significantly shorter for linear formulations compared to mixed integer linear formulations.
Article
Automation & Control Systems
Dinh Ba Pham, Xuan Quang Duong, Duc Sang Nguyen, Manh Cuong Hoang, Duong Phan, Ehsan Asadi, Hamid Khayyam
Summary: This article presents a synchronization control method for Ballbot robots, which stabilizes the body and controls the ball transfer through synchronization and coupling errors. The study demonstrates superior stabilization accuracy of the proposed method.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Green & Sustainable Science & Technology
M. Ahmadi, O. Zabihi, H. A. Nazarloo, K. Shirvanimoghaddam, X. Duan, P. Adetunji, B. Egan, M. Naebe
Summary: This research evaluates the potential of a homogenization and dechlorination algorithm to improve the homogeneity of mixed plastic waste. The results show that the physical, thermal, and rheological behavior of the waste improved significantly after extrusions. The inclusion of a clay catalyst reduced the activation energy and degradation temperature, and increased the amount of low carbon atom and aromatic products.
MATERIALS TODAY SUSTAINABILITY
(2023)
Article
Chemistry, Multidisciplinary
Jaworski C. C. Capricho, Tzu-Ying Liao, Boon Xian Chai, Ahmed Al-Qatatsheh, Jitraporn (Pimm) Vongsvivut, Peter Kingshott, Saulius Juodkazis, Bronwyn Louise Fox, Nishar Hameed
Summary: This study demonstrates the potential of macroradical epoxies as surface coating materials, with the use of magnets during polymerization. The magnetically oriented and stable radicals in the polymer backbone render the coatings antimicrobial.
CHEMISTRY-AN ASIAN JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Mirhamed Mola, Ali Moradi Amani, Mahdi Jalili, Hamid Khayyam
Summary: This paper investigates the predictive data-driven control of Continuously Variable Transmission (CVT) systems in order to improve the energy efficiency of autonomous vehicles (AVs). The proposed Data Driven Control (DDC) framework can learn the optimum pattern from archived real data and adapt itself to any drive cycle. The control framework shows a satisfactory performance and reduces energy consumption by 1-5% compared to pre-defined mappings in HWFET and NEDC drive cycles.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Green & Sustainable Science & Technology
Mojgan Fayyazi, Paramjotsingh Sardar, Sumit Infent Thomas, Roonak Daghigh, Ali Jamali, Thomas Esch, Hans Kemper, Reza Langari, Hamid Khayyam
Summary: Environmental concerns have driven advancements in conventional vehicles, with hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles being the preferred choices due to their minimal greenhouse gas emissions. However, energy management in these vehicles poses a major challenge, requiring appropriate control strategies. Recent progress in artificial intelligence and machine learning has allowed for the development of state-of-the-art energy management technologies based on data-driven intelligent controllers.
Article
Chemistry, Multidisciplinary
Ken Aldren S. Usman, Ya Yao, Christine Jurene O. Bacal, Jizhen Zhang, Karyn L. Jarvis, Peter A. Lynch, Pablo Mota-Santiago, Si Qin, Minoo Naebe, Luke C. Henderson, Dylan Y. Hegh, Benjamin J. Allardyce, Joselito M. Razal
Summary: It has been found that using silk fibroin biopolymer as an additive for MXene fiber production improves durability, conductivity, and volumetric capacitance. These fibers also show no cytotoxicity towards THP-1 monocytic cells, making them suitable for flexible electronics and biomedical applications.
ADVANCED MATERIALS INTERFACES
(2023)
Article
Chemistry, Multidisciplinary
Jigar Patadiya, Xungai Wang, Ganapati Joshi, Balasubramanian Kandasubramanian, Minoo Naebe
Summary: Nacreous architecture with a combination of toughness and modulus can be imitated through 3D printing at the micron to submicron level, meeting the demand in various applications. This study investigates the fabrication of two nacre structures (columnar and sheet) and a pristine structure using fused deposition modeling, exploring their superior mechanical properties, failure mechanism, crack propagation, and energy dissipation. The examination reveals that nacre structure has significant mechanical properties compared to a neat sample, with the sheet structure showing better impact resistance, elastic modulus, and flexural modulus than the columnar arrangement.
Article
Computer Science, Artificial Intelligence
Mojgan Fayyazi, Monireh Abdoos, Duong Phan, Mohsen Golafrouz, Mahdi Jalili, Reza N. Jazar, Reza Langari, Hamid Khayyam
Summary: This paper presents an intelligent energy management system based on reinforcement learning for conventional autonomous vehicles, aiming to reduce emissions and energy consumption. A new exploration strategy is proposed to replace the traditional epsilon-greedy strategy in the Q-learning algorithm. The Q-learning and SAQ-learning controllers are shown to generate the desired engine torque and control the air/fuel ratio efficiently in real-time, improving operational time compared to standard Q-learning.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Civil
Nida Ishtiaq, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar, Reza Hoseinnezhad
Summary: Tracking multiple objects is crucial in intelligent transportation systems. However, most existing methods neglect the interactions between objects. This paper proposes a novel approach to explicitly incorporate target interactions in the prediction step of a multi-target filter. The method is tested and shows significant performance improvement over other methods in terms of selected metrics.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad, David Suter, Alireza Bab-Hadiashar
Summary: Deep convolutional neural networks for dense prediction tasks are commonly optimized using synthetic data, but they do not generalize well to real-world environments. We propose an Information-Theoretic Shortcut Avoidance (ITSA) approach to mitigate the issue of poor synthetic to real generalization. The proposed method effectively improves S2R generalization in multiple distinct dense prediction tasks and enhances the robustness of synthetically trained networks for challenging out-of-domain applications.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Chemistry, Multidisciplinary
Milad Laghaei, Chao Liu, Quanxiang Li, Minoo Naebe, Lingxue Kong
Summary: Chemical etching of carbon cloths (CCs) with potassium hydroxide (KOH) has been used to enhance their specific surface area (SSA). Different weight ratios (WRs) of CCs to KOH were investigated to understand pore development mechanism. The activated CCs with a WR of 0.01 wt%/wt% showed more than 15-fold increase in SSA compared to neat CCs, primarily due to outside-in pore deepening and metallic potassium intercalation. The introduction of KOH also affected defective sites and surface energy.
NEW JOURNAL OF CHEMISTRY
(2023)
Review
Computer Science, Information Systems
Steven Korevaar, Ruwan Tennakoon, Alireza Bab-Hadiashar
Summary: One prominent issue in deep learning is the difficulty of generalizing to data outside the training distribution. Though many methods have been proposed to address this, previous research has shown that most algorithms perform similarly under the same conditions. This study analyzes eight domain generalization algorithms on medical imaging and natural image classification datasets to understand their differences in different contexts.
Article
Materials Science, Characterization & Testing
Papangkorn Jessadatavornwong, Ruwan Tennakoon, Alireza Bab-Hadiashar, Raj Das, Adrian P. Mouritz, Mark A. Easton
Summary: One challenge of using X-ray computed tomography (CT) is the detection limit of the smallest feature. This challenge can be addressed by generating defined size notches on the surface and investigating different X-ray CT parameters. The results show that the voxel size and scan duration are significant factors for defect detection and measurement accuracy.
NDT & E INTERNATIONAL
(2023)
Article
Chemistry, Multidisciplinary
Jaehoon Choi, Omid Zabihi, Mojtaba Ahmadi, Minoo Naebe
Summary: This study presents a promising approach for fabricating high-performance structural batteries with enhanced energy storage and structural capabilities.
Review
Computer Science, Information Systems
Sundaram Muthu, Ruwan Tennakoon, Reza Hoseinnezhad, Alireza Bab-Hadiashar
Summary: In this paper, a review of recent learning-based scene flow estimation papers is conducted, focusing on the problem formulation, challenges, applications, existing datasets and performance metrics. The shift from traditional variational methods to learning-based methods is discussed. CNN-based scene flow estimation methods are categorized based on supervision level, data availability, and number of steps involved. The performance of different methods on well-known datasets is compared, and their advantages and limitations are analyzed. Future trends and open problems, particularly in the area of self-supervised methods, are discussed.
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.