Article
Computer Science, Interdisciplinary Applications
Philippe Olivier, Andrea Lodi, Gilles Pesant
Summary: The quadratic multiknapsack problem involves packing items of various weights into knapsacks with limited capacities and assigning profits to pairs of items in the same knapsack. Various heuristics and an exact method have been used to solve this problem. A generalized version of the problem has been introduced, incorporating pairwise conflicts and balance constraints, and constraint programming and integer programming approaches have been compared for solving it.
INFORMS JOURNAL ON COMPUTING
(2021)
Article
Operations Research & Management Science
Nacera Maachou, Mustapha Moulai
Summary: This article proposes a new algorithm for solving the integer indefinite quadratic bilevel problem, using branch and bound method with cuts to determine the set of efficient solutions, and checking the integer optimal solution found for optimality of the main problem by solving the lower level problem.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Biochemical Research Methods
Ziying Yang, Guoxian Yu, Maozu Guo, Jiantao Yu, Xiangliang Zhang, Jun Wang
Summary: The study introduces a new approach called CDPath to discover cooperative driver pathways, which can identify driver genes and pathways related to target cancer, involved in carcinogenesis and key biological processes. CDPath can uncover more potential biological associations and cooperative driver pathways compared to competitive approaches.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Xiaojin Zheng, Xueting Cui
Summary: This paper investigates quadratic convex reformulations for the portfolio selection problem with Value-atRisk (VaR) constraint. By introducing semicontinuous variables and exploiting their special properties, a class of quadratic convex reformulations with tight continuous relaxation bounds is proposed, which are shown to be effective through computational experiments.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Energy & Fuels
Chao Charles Liu, Hongkun Chen, Jing Shi, Lei Chen
Summary: Driven by cost reduction and sustainable policies, the penetration of distributed photovoltaic (PV) systems has deepened in recent years. This paper proposes a self-supervised learning method to train supervised estimation models from unlabeled data. The method synthesizes pseudo labels for unlabeled net load measurements using PV generation measurements and utilizes an end-to-end network architecture for improved estimation performance.
Article
Mathematics, Applied
Prerna, Vikas Sharma
Summary: This paper presents a novel method for optimizing a quadratic function over the efficient set of a multi-objective integer linear programming problem. The method obtains a globally optimal solution by ranking and efficiency testing, and demonstrates high computational efficiency.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2024)
Article
Computer Science, Software Engineering
Alberto Del Pia, Mingchen Ma
Summary: The research examines the upper bound of proximity of optimal solutions in Integer Linear Programming and convex function minimization, as well as the limitations in the case of nonconvex problems and approximate solutions.
MATHEMATICAL PROGRAMMING
(2022)
Article
Engineering, Electrical & Electronic
Zhao Wu, Chao Wang, Huaiqing Zhang, Wenxiong Peng, Weihua Liu
Summary: This paper introduces the application of Hidden Markov Model (HMM) and its variations in Non-Intrusive Load Monitoring (NILM). By proposing a time-efficient Factorial Hidden Semi-Markov Model (TE-FHSMM), the paper achieves a reduction in time consumption while maintaining performance when dealing with datasets with different numbers of appliances. Additionally, experiments show that TE-FHSMM outperforms six state-of-the-art algorithms in terms of Accuracy and F1 score in real-world scenarios and publicly available datasets.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Zhen Wang, Shan-Shan Wang, Lan Bai, Wen-Si Wang, Yuan-Hai Shao
Summary: This article proposes a semisupervised fuzzy clustering method with fuzzy pairwise constraints, which can represent more complex relationships between samples and avoid eliminating fuzzy characteristics. The method solves a nonconvex optimization problem using a modified expectation-maximization algorithm and diagonal block coordinate descent algorithm, and is extended to different metric spaces. Experimental results demonstrate the superior performance of this method.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Hardware & Architecture
Kiyo Ishii, Shu Namiki
Summary: This study developed an optical path computation prototype based on a functional block-based disaggregation approach, supporting various optical node structures and computationally intensive flexible grid mechanism. By employing integer linear programming as a generic computational method, universal path computation applicable to any node structure was achieved, and the computation time was evaluated and optimized.
JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING
(2022)
Article
Management
Stephen J. Maher
Summary: Benders' decomposition is a popular algorithm for mathematical and constraint programming, but traditionally viewed as problem specific. This paper introduces a general purpose algorithm capable of handling various types of problems and providing flexibility. A branch-and-cut approach for Benders' decomposition was implemented in the SCIP solver, allowing for extensions and customisations. The effectiveness of the algorithm and enhancement techniques was assessed through comprehensive computational study.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Feiping Nie, Chaodie Liu, Rong Wang, Zhen Wang, Xuelong Li
Summary: Researchers propose a fast fuzzy clustering algorithm based on anchor graph (FFCAG), which utilizes prior knowledge of anchors to improve clustering performance and reduces computational time.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Operations Research & Management Science
Philippe Olivier, Andrea Lodi, Gilles Pesant
Summary: This paper examines three cases where balance integration is deficient, analyzes the causes, and provides general guidelines for choosing measures of balance.
4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Yu Du, Gary Kochenberger, Fred Glover, Haibo Wang, Mark Lewis, Weihong Xie, Takeshi Tsuyuguchi
Summary: Finding good solutions to clique partitioning problems is computationally challenging. The choice of modeling structure has a significant impact on obtaining practical solutions from exact solvers. Commercial solvers like CPLEX, GUROBI, and XPRESS combined with the right model can greatly improve solution computation for modest-sized problems. This paper explores and compares the use of three commercial solvers on clique partitioning problems and finds that the quadratic model outperforms the classic linear model as problem size increases.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Review
Engineering, Electrical & Electronic
Pascal A. Schirmer, Iosif Mporas
Summary: The rapid development of technology in the electrical energy sector has led to increased electric power needs. This has resulted in the adoption of smart-meters and smart-grids, as well as the rise of Load Monitoring (LM) using Non-Intrusive Load Monitoring (NILM) for appliance-specific energy monitoring. The article provides a review of NILM approaches, groups previously published results, and includes a software implementation of the described NILM approaches.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Automation & Control Systems
Weiye Zheng, David J. Hill
Summary: In this article, a distributed method for real-time IEHS dispatch is proposed, ensuring feasibility and system security through techniques such as network reduction and feasibility cut generation.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Lipeng Zhu, David J. Hill
Summary: This paper proposes a networked time series shapelet learning approach for interpretable transient stability assessment (TSA). By introducing a network impedance-based adjacency matrix to characterize spatial networked correlations, and incorporating it as spatial constraints, the method learns critical sequential features, i.e., networked shapelets, from time series trajectories acquired from multiple buses. The obtained data-driven TSA model performs highly reliable and interpretable online TSA, as demonstrated by numerical test results on real-world power systems.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Computer Science, Information Systems
Lipeng Zhu, David J. Hill, Chao Lu
Summary: This article presents an intelligent data-driven approach for performing PMU data anomaly identification in IoT-enabled power grids. By utilizing the spatial-temporal correlations in PMU measurements, the proposed approach effectively identifies and labels abnormal data, leading to improved reliability and accuracy in power grid monitoring.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Lipeng Zhu, David J. Hill, Chao Lu
Summary: This paper proposes a semi-supervised ensemble learning framework for accelerating the computation process of stability knowledge base generation. By performing detailed simulations for a minority of cases and fast simulations for the majority ones, the total computation time is reduced. Two concise feature descriptors are introduced to extract transient features from multiplex system trajectories, and a series of semi-supervised support vector machines are trained to derive an enhanced SSEL model.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Jun Lin, Jin Ma, Jianguo Zhu
Summary: Understanding residential household characteristics is crucial for retailers to provide personalized services. This paper proposes a federated learning-based deep learning model for identifying household characteristics in a decentralized manner, using a hybrid model that combines convolutional neural networks and long short-term neural networks. Comprehensive experiments are conducted to verify the effectiveness of the proposed method.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Multidisciplinary
Yinyan Liu, Jing Qiu, Junda Lu, Wei Wang, Jin Ma
Summary: Non-intrusive load monitoring (NILM) is an important feature in smart grids for identifying users' energy consumption behavior. This paper proposes an energy disaggregation network (EDNet) that achieves latency-free NILM with a deep encoder-decoder architecture.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Lipeng Zhu, David J. Hill
Summary: This article proposes a novel data/model jointly driven framework to generate high-quality cases for power system DSA applications. By utilizing model-driven numerical simulations and CycleGAN learning, refined cases highly resembling actual historical ones can be produced. With the combination of LSTM-based semisupervised learning scheme, all refined cases can be reliably labeled to mitigate the small sample size and class-imbalance problems.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Energy & Fuels
Yinyan Liu, Jin Ma, Xinjie Xing, Xinglu Liu, Wei Wang
Summary: This paper proposes an advanced Home Energy Management System (HEMS) that incorporates uncertainty-aware user preference and characterizes energy consumption user behavior in a data-driven way. Extensive experiments demonstrate the effectiveness and superiority of the proposed algorithm in reducing energy costs, maintaining user preference level, and encouraging user participation in demand response.
Article
Computer Science, Information Systems
William Infante, Jin Ma
Summary: This paper proposes a multi-stakeholder planning and operational strategy involving cooperation between BSS owners, EV drivers, and DisCo operators using a multi-objective optimization approach. Case studies have shown that this collaboration is feasible and can improve flexible load and power generation responses.
IEEE SYSTEMS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Han Wang, Jin Ma, Jianguo Zhu
Summary: This paper proposes a novel non-intrusive load monitoring (NILM) method based on Weighted Power Recurrence Graphs (WPRG) to accurately identify the EV models connected to the power grid, regardless of brand and state of charge. The WPRG method considers the relationship between voltages and currents, increasing the variance of original electrical current values. Experimental results demonstrate that the proposed WPRG method outperforms two weighted-based methods in identifying EV models and other household appliances, achieving an overall macro F1-score of 94.3%.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Tong Han, David J. Hill
Summary: This paper proposes a learning-based solution approach for optimal transmission switching (OTS) and distribution network reconfiguration (DNR) in power network transitions. The proposed approach utilizes a parameterized function designed with gated graph neural network and multilayer perceptrons, replacing the original hand-crafted and short-sighted evaluation function. A learning algorithm combining the double deep Q-network algorithm and multi-step learning is designed to learn the parameterized function without training labels. Numerical studies demonstrate the superiority of the learning-based heuristic algorithm in both solution optimality and computational efficiency.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Automation & Control Systems
Yue Song, David J. Hill, Tao Liu, Xinran Zhang
Summary: This article investigates the concept of the impasse surface in the differential-algebraic equation model of power systems. It establishes a necessary condition for a system trajectory hitting the impasse surface and identifies a class of static load parameters that prevent power systems from collapsing. The obtained results have important implications for early indicators of voltage collapse and inductive compensation in power networks.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Si Phu Me, Mohammad Hasan Ravanji, Bruno Leonardi, Deepak Ramasubramanian, Jin Ma, Sasan Zabihi, Behrooz Bahrani
Summary: In this letter, a transient stability analysis of VSGs equipped with quadrature-prioritized CL is performed. The study shows that in addition to the instability caused by the positive feedback of the primary controller, a VSG could become unstable after large disturbances due to the failure of the inner voltage controller. A stability criterion is provided for the voltage control loop in this study.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Tong Han, Yue Song, David J. J. Hill
Summary: This paper proposes a novel methodology to address the topology transition problem of transmission networks. The methodology utilizes various eligible control resources in transmission networks to cooperate with the optimization of line-switching sequence, aiming at achieving a bumpless topology transition regarding both static and dynamic performance. The effectiveness and superiority of the proposed methodology to achieve bumpless topology transition is demonstrated through numerical studies.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Tong Han, David J. Hill, Yue Song
Summary: Network topology has a significant impact on the operational performance of power systems. The problem of transitioning from an initial topology to the desired optimal topology requires study. To address this problem, the concept of optimal topology transition (OTT) is proposed, aiming to find the transition trajectory that optimizes transition performance and satisfies operational constraints. The OTT problem is further formulated as a mixed-integer program, and an efficient problem-specific solution algorithm is developed.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
