Article
Engineering, Electrical & Electronic
Thiago R. Fernandes, Bala Venkatesh, Madson C. de Almeida
Summary: A common assumption in distribution system state estimation is that the system's topology is perfectly known. However, it is difficult to ensure the accuracy of available topology information due to unmonitored network equipment settings and unreported topology changes. This paper proposes an efficient Weighted Least Absolute Value State Estimator (WLAV-SE) for Topology Identification (TI) in distribution systems. The proposed method combines linear programming and mixed-integer linear programming to solve the state estimation problem with excellent performance demonstrated in various case studies and comparisons.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Wei Qian, Di Lu, Simeng Guo, Yunji Zhao
Summary: The article establishes a new multichannel random attack model for mixed delays system and proves the effectiveness of the designed algorithm.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Davide Gotti, Hortensia Amaris, Pablo Ledesma
Summary: This paper presents a network topology identification method based on deep neural networks for online applications. The proposed method utilizes measurements for state estimation to predict the actual network topology with low computational times and high accuracy across various testing scenarios. Simulation results on the IEEE 14-bus and 39-bus test systems demonstrate the effectiveness and efficiency of the proposed methodology.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Automation & Control Systems
Xia Jiang, Xianlin Zeng, Jian Sun, Jie Chen
Summary: This article studies the distributed nonconvex optimization problem with nonsmooth regularization, which has wide applications in decentralized learning, estimation, and control. A distributed proximal gradient algorithm is presented for the nonsmooth nonconvex optimization problem. The algorithm updates local variable estimates with a constant step-size at the cost of multiple consensus steps, achieving consensus and convergence to the set of critical points.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Hazhar Sufi Karimi, Balasubramaniam Natarajan
Summary: The paper proposes a compressive sensing framework to jointly estimate system states and network topology, addressing the challenging problem of topology identification. By investigating two reformulations of the original MINLP problems, the efficiency and accuracy of the solutions are improved. Simulation results illustrate the effectiveness and scalability of the proposed approaches in both state estimation and topology identification, even with limited data available.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Automation & Control Systems
Guitao Yang, Hamed Rezaee, Angelo Alessandri, Thomas Parisini
Summary: This paper focuses on the state estimation of linear time-invariant (LTI) systems using a network of distributed observers. The observability of the system is guaranteed by the ensemble of all measurements in the network, even though each observer has access to only a local measurement. The main contribution is the proposal of a distributed approach that ensures convergence of the estimated state vector of each observer to the state vector of the system, even when the communication links may fail and rebuild over time. The paper also considers the scenario of external disturbances and measurement noise, providing conditions for desired performance in attenuating their effects on estimation errors.
Article
Automation & Control Systems
An -Yang Lu, Guang-Hong Yang
Summary: This paper addresses the problem of distributed secure state estimation in cyber-physical systems monitored by a multi-agent network with malicious agents. A novel strategy is proposed using a sort and filter approach to mitigate the impact of malicious agents. Sufficient conditions for tolerating a bounded number of malicious agents are given. Simulation results demonstrate the effectiveness of the proposed algorithms in generating correct state estimates and efficiently updating them.
Article
Engineering, Electrical & Electronic
Ankur Srivastava, Saikat Chakrabarti, Joao Soares, Sri Niwas Singh
Summary: The paper presents an optimization-based method for detecting topology errors in power systems. The method utilizes residual analysis and minimization of normalized measurement residual in state estimation, with the application of matrix inverse lemma. The proposed method is computationally efficient and produces accurate results, with robust performance in the presence of measurement uncertainties and bad data.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Automation & Control Systems
An-Yang Lu, Guang-Hong Yang
Summary: This article investigates the distributed secure state estimation problem in distributed systems, proposes a DSGD algorithm, and illustrates its effectiveness through a numerical example.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(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
Automation & Control Systems
Bosen Lian, Yan Wan, Ya Zhang, Mushuang Liu, Frank L. Lewis, Tianyou Chai
Summary: In this article, we propose a novel distributed Kalman consensus filter (DKCF) with an information-weighted consensus structure for random mobile target estimation. We address the issues of low convergence speed and limited sensing range and target mobility in existing Kalman filters. Our simulations and comparative studies demonstrate the effectiveness and superiority of the proposed DKCF.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Yacun Guan, Bin Jiang, Yun Chen
Summary: This study investigates PDE-based fault-tolerant control for a swarm system with a dynamic graph, where all agents are deployed along desired planar curves to maintain communication connectivity and avoid collisions in the presence of actuator faults.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Engineering, Electrical & Electronic
Adnan Anwar, Abdun Naser Mahmood, Zahir Tari, Akhtar Kalam
Summary: This study highlights the importance of smart grid cyber-security and the construction of sparse False Data Injection attacks using data-driven methods. By revealing grid topology through measurement signals and utilizing the ADMM method to solve the complex problem, the accuracy of revealing grid topology is evaluated using graph-theoretic measures. The research findings demonstrate that manipulating a few sensor devices can construct sparse attacks, significantly impacting operational performance.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Robotics
Amirhossein Tamjidi, Reza Oftadeh, Mohamed Naveed Gul Mohamed, Dan Yu, Suman Chakravorty, Dylan Shell
Summary: This article introduces and studies a recursive information consensus filter for decentralized dynamic state estimation in unreliable communication networks. The hybrid method achieves consensus over priors and new information, producing unbiased conservative estimates that outperform traditional methods.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Article
Automation & Control Systems
Yifan Su, Zhaojian Wang, Ming Cao, Mengshuo Jia, Feng Liu
Summary: This article analyzes the convergence of the dual decomposition algorithm in distributed optimization when both communication asynchrony and subproblem solution inexactness exist. The interaction between asynchrony and inexactness slows down the convergence rate from O(1/k) to O(1/v/k). With a constant step size, the objective function value converges to a neighborhood of the optimal value, and the solution converges to a neighborhood of the optimal solution. The violation of constraints diminishes in O(1/ k). Numerical simulations validate the theoretical results.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Jiangkai Peng, Bo Fan, Wenxin Liu
Summary: This paper presents a distributed optimal control scheme for DC microgrid aiming to achieve generation cost minimization and individual bus voltage regulation simultaneously. By formulating an optimal control problem and deriving necessary optimality conditions, the proposed controller dynamically drives the system to operate at optimal conditions. The performance of the controller is validated through simulations based on a switch-level microgrid model, ensuring convergence to optimal operating points while maintaining individual bus voltages within bounds.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Computer Science, Information Systems
Jiangkai Peng, Bo Fan, Qinmin Yang, Wenxin Liu
Summary: The article introduces a distributed event-triggered control algorithm for load current sharing and voltage regulation in a dc microgrid. Controllers only communicate with neighboring controllers when certain conditions are met, reducing communication and computation requirements for improved efficiency. Lyapunov synthesis confirms that reduced communication does not compromise control performance.
IEEE SYSTEMS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Javad Khazaei, Zhenghong Tu, Arash Asrari, Wenxin Liu
Summary: This paper investigates the design and analysis of a robust nonlinear controller for voltage source converters connected to weak AC grids. The control inputs are developed using feedback linearization method to regulate the active power and output voltage of the grid-connected converter, based on the frequency-domain model of an LCL filter in dq-frame. The proposed controller is not negatively affected by PLL gains and demonstrates a broader range of operation, while also maintaining robustness against sudden active power commands and fault ride through when the AC grid is weak.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Computer Science, Information Systems
Zhen Fan, Bo Fan, Jiangkai Peng, Wenxin Liu
Summary: DC microgrids are gaining popularity for their simplicity and energy efficiency, but traditional hierarchical optimization schemes face challenges in terms of energy efficiency and real-time optimization. This article presents a distributed optimal control algorithm to minimize operation loss in real time and ensure all bus voltages stay within predefined ranges. Simulation studies demonstrate the benefits of the proposed controller through a detailed switch-level model.
IEEE SYSTEMS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Zhenghong Tu, Bo Fan, Wei Zhang, Jiangkai Peng, Wenxin Liu
Summary: This article presents an optimal control solution based on barrier-Lyapunov-function for online PPL accommodation. By introducing the state-constrained technique, it realizes multiple control objectives including safe charging, high-quality regulation, and dynamic cost minimization.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Electrical & Electronic
Zhen Fan, Bo Fan, Wenxin Liu
Summary: DC microgrids are gaining popularity for their simplicity and high energy efficiency, with a distributed discrete-time control scheme being proposed to optimize coordination between conventional generators and renewable generators. The control algorithm minimizes generation costs, maximizes energy utilization, and improves stability and dynamic performance. By avoiding possible instability from digital implementation, the algorithm maintains bus voltages in safe ranges and simulation results show its advantages.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Computer Science, Information Systems
Jiangkai Peng, Bo Fan, Qinmin Yan, Wenxin Liu
Summary: This article presents a novel distributed DT control scheme for load current sharing and bus voltage regulation in dc microgrids. A sparse communication network is utilized to achieve proportional load current sharing, and a distributed voltage observer is designed to estimate and regulate the weighted average bus voltage. The control gains are constrained to alleviate the destabilizing effect induced by DT sampling, and a sufficient condition on CPLs is proposed to counteract their negative impact on stability. Simulation studies validate the control scheme's effectiveness and robustness.
IEEE SYSTEMS JOURNAL
(2022)
Article
Automation & Control Systems
Huaizhi Wang, Xichang Wen, Yinliang Xu, Bin Zhou, Jianchun Peng, Wenxin Liu
Summary: This article proposes a new operating state reconstruction scheme for the smart grid, which can automatically filter out possible cyberattacks and correct erroneous states, mitigating the impact of attacks on the grid.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Jiangkai Peng, Bo Fan, Zhenghong Tu, Wei Zhang, Wenxin Liu
Summary: This article presents a distributed periodic event-triggered optimal control scheme for generation cost minimization and average bus voltage regulation in DC microgrids. The proposed scheme utilizes a virtual incremental cost and a distributed event-triggered mechanism to improve system performance.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Engineering, Electrical & Electronic
Jiangkai Peng, Bo Fan, Wenxin Liu
Summary: This article proposes an optimal controller for DC microgrids that achieves real-time minimization of operating losses and regulation of line currents and DG output currents. By converting the optimization problem to an optimal control problem using a penalty function, a distributed controller tracks the optimal operating point dynamically. Simulations validate the performance of the proposed control solution.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2022)
Article
Automation & Control Systems
Bo Fan, Jiangkai Peng, Qinmin Yang, Wenxin Liu
Summary: This article presents a distributed consensus-based controller for dc microgrids to achieve proportional current sharing and weighted average voltage regulation in the presence of ZIP loads. The proposed algorithm allows the regulation of the global weighted average voltage in a distributed manner and relaxes the precondition on initial bus voltages. The study investigates the negative conductance introduced by constant power loads and obtains a sufficient stability condition with improved adaptability for ZIP loads.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Zhenghong Tu, Bo Fan, Javad Khazaei, Wei Zhang, Wenxin Liu
Summary: This paper presents a novel load frequency control (LFC) method based on an optimal reset control (ORC) scheme for isolated ac microgrids with multiple controllable distributed energy resources (DERs). The ORC consists of a baseline linear controller and resetting elements to reduce the overshoot in frequency regulation and shorten the settling time. By coordinating the reset controllers of all controllable DERs, the overall frequency control performance is further improved.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Engineering, Electrical & Electronic
Zhenghong Tu, Wei Zhang, Wenxin Liu
Summary: This paper addresses the challenging power system optimal control problem in the dc shipboard power system by using a model-free optimal control method based on deep reinforcement learning (DRL). A DRL control framework based on the improved twin-delayed deep deterministic policy gradient (TD3) algorithm is developed to solve the dc shipboard power system optimal control problem with three control objectives and input constraints, which includes the fast ESS charge, the dc bus voltage regulation, and the proportional load current sharing. The proposed method effectively links the DRL framework with optimal control.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Automation & Control Systems
Wei Zhang, Zhenghong Tu, Wenxin Liu
Summary: In this article, the charging control of the energy storage system for pulse power load accommodation in a shipboard integrated power system is studied. An improved twin-delayed deep deterministic policy gradient algorithm is proposed to solve this control problem. The proposed method addresses issues such as reward function design and constraint handling for control variables.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Zhenghong Tu, Wei Zhang, Wenxin Liu
Summary: In this paper, a deep reinforcement learning (DRL) optimal control method is proposed to address the online deployment problem of pulsed power load (PPL) in DC shipboard integrated power systems (SIPSs). The method adopts a stack-based state observation technique to enhance learning and control performance, and employs a multi-objective reward function design. The performance of the proposed DRL control is validated by case studies considering different load conditions.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
