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Your search keyword '"Wen, Fushuan"' showing total 105 results
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105 results on '"Wen, Fushuan"'

1. Applying Large Language Models to Power Systems: Potential Security Threats

Author

Ruan, Jiaqi, Liang, Gaoqi, Zhao, Huan, Liu, Guolong, Sun, Xianzhuo, Qiu, Jing, Xu, Zhao, Wen, Fushuan, and Dong, Zhao Yang

Subjects
Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Systems and Control
Abstract

Applying large language models (LLMs) to modern power systems presents a promising avenue for enhancing decision-making and operational efficiency. However, this action may also incur potential security threats, which have not been fully recognized so far. To this end, this article analyzes potential threats incurred by applying LLMs to power systems, emphasizing the need for urgent research and development of countermeasures.

Published
2023

2. Cyber-physical interdependent restoration scheduling for active distribution network via ad hoc wireless communication

Author

Wang, Chongyu, Yan, Mingyu, Pang, Kaiyuan, Wen, Fushuan, and Teng, Fei

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper proposes a post-disaster cyber-physical interdependent restoration scheduling (CPIRS) framework for active distribution networks (ADN) where the simultaneous damages on cyber and physical networks are considered. The ad hoc wireless device-to-device (D2D) communication is leveraged, for the first time, to establish cyber networks instantly after the disaster to support ADN restoration. The repair and operation crew dispatching, the remote-controlled network reconfiguration and the system operation with DERs can be effectively coordinated under the cyber-physical interactions. The uncertain outputs of renewable energy resources (RESs) are represented by budget-constrained polyhedral uncertainty sets. Through implementing linearization techniques on disjunctive expressions, a monolithic mixed-integer linear programming (MILP) based two-stage robust optimization model is formulated and subsequently solved by a customized column-and-constraint generation (C&CG) algorithm. Numerical results on the IEEE 123-node distribution system demonstrate the effectiveness and superiorities of the proposed CPIRS method for ADN.

Published
2022

16. Optimized low carbon scheduling strategy of integrated energy sources considering load aggregators.

Author

Wang, Xiu Li, Guo, Huanyu, Wen, Fushuan, and Wang, Kai

Subjects
CARBON offsetting, PARTICLE swarm optimization, PRODUCTION scheduling, SIMULATED annealing, CARBON emissions, HIERARCHICAL clustering (Cluster analysis)
Abstract

In the context of the global low-carbon energy development strategy, the massive influx of renewable energy leads to the instability of the power system, so it is necessary to carry out effective scheduling strategy and management mechanism for energy. On this basis, the Integrated Energy System including Electricity/Heat/Storage (EHSIES) is discussed in this paper. First, an ordered clustering method using a combination of simulated annealing and improved profile coefficients for load evolution number approximation is proposed. Second, a hybrid load clustering algorithm based on hierarchical clustering algorithm and K-means++ is presented and four types of load scenarios are obtained. Third, an Improved Harris Hawk Optimization (IHHO) algorithm based on the hybrid strategy is proposed and solved to the model of EHSIES. Finally, under the premise of the dynamic carbon trading mechanism considering historical compliance and load aggregator management, the scheduling strategies of flexible electric loads and thermal loads participating in EHSIES are discussed and solved by CPLEX. The results show that the solution time of IHHO is 50% and 33.3% lower than that of particle swarm optimization (PSO) and Harris hawk optimization (HHO), and the number of iterations is 76.6% and 56.25% lower than that of PSO and HHO, respectively. In addition, considering a flexible load aggregator and a compliance-based dynamic carbon trading mechanism in EHSIES scheduling can effectively reduce the actual operating cost by 27.37%, the source-side energy spill rate by 68.75%, and the carbon emission by 51.92% and improve the operating efficiency and economic benefits of EHSIES. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Synchrophasor-Based Real-Time Detection for Power System Events With Fast and Slow Dynamics via Dual Windowed Recurrence Quantification Analysis Algorithm

Author

Tan, Weitao, Zhang, Tianhan, Liu, Shengyuan, Ma, Yuanqian, Lin, Zhenzhi, and Wen, Fushuan

Abstract

Accurate event detection is critical for power system operators to take appropriate control strategies so as to ensure the system stability under disturbances. Whereas, most existing event detection techniques are conducted under a single analytical window and criterion, which leads to the misdetection for events of different dynamics. Given this background, a synchrophasor-based real-time event detection method using dual windowed recurrence quantification analysis (DWRQA) algorithm is proposed in this article. First, the recurrence quantification analysis algorithm for synchrophasor data is employed to analyze the nonstationary state of power systems, and a recurrence rate-based power system event indicator is presented to reveal the occurrence of power system events. Then, a real-time event detection scheme based on the dual window structure is proposed to monitor both fast and slow dynamic events of power systems. Finally, case studies on the Western Electricity Coordinating Council (WECC) 179-bus power system and the actual Guangdong power system (GDPS) are performed to demonstrate the effectiveness of the proposed method. Simulation results show that the proposed method can detect both fast and slow dynamic events without misdetections and false alarms, and short time delays for detecting events also make it suitable for real-time applications in actual power systems.

Published
2024
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24. Adaptive Weighted Combination Approach for Wind Power Forecast Based on Deep Deterministic Policy Gradient Method

Author

Li, Menglin, Yang, Ming, Yu, Yixiao, Shahidehpour, Mohammad, and Wen, Fushuan

Abstract

Accurate wind power forecast (WPF) is critical for ensuring secure and economic operation of a power system, and combination forecasting approaches for WPF have been proved effective on attaining accurate forecasting results. However, the weights in a combination forecasting model are usually predetermined based on the global performance on the training set, limiting the adaptability of the model to different scenarios. To further enhance the accuracy and effectiveness of the combination forecasting approaches, this article proposes an adaptive weighted combination forecasting approach based on the deep deterministic policy gradient (DDPG) so as to consider the local behavior accompanied by the change of external environment. Three sub-models are first selected considering the equal-likelihood and dispersion indices to construct a combination model. Then, the DDPG agent is trained to act as a weight generator by interacting with the environment and to maximize the reward. Thus, the DDPG agent can perceive the environmental changes online and dynamically weight the sub-models to attain accurate forecasting results. Case studies demonstrate that the forecasting accuracy of the proposed approach is better than that of all sub-models and several benchmark combination forecasting approaches.

Published
2024
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25. Dynamic Restoration of Active Distribution Networks by Coordinated Repair Crew Dispatch and Cold Load Pickup

Author

Pang, Kaiyuan, Wang, Chongyu, Hatziargyriou, Nikos D., and Wen, Fushuan

Abstract

This article presents a dynamic restoration strategy for active distribution networks (ADNs) by coordinating repair crew dispatch and frequency-constrained cold load pickup. To incorporate the stochastic repair time, the repair crew dispatch is formulated as “event-driven” with the implementation of model predictive control (MPC). The stochastic repair time is estimated, convexified, and updated dynamically with each MPC execution. The finish of a repair task triggers the subsequent cold load pickup model, where the frequency dynamics are computed and linearly constrained with the help of a uniform frequency response model for low-inertia systems. Next, a co-optimization framework of the two models is developed to coordinate the repair crew dispatch and cold load pickup under a unified time scale. Numerical results on a modified IEEE 33-node test feeder and a real-world 136-node distribution system have verified the effectiveness of the proposed model.

Published
2024
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26. Formulation of Radiality Constraints for Optimal Microgrid Formation

Author

Pang, Kaiyuan, Wang, Chongyu, Hatziargyriou, Nikos D., Wen, Fushuan, and Xue, Yusheng

Abstract

Forming microgrids (MG) in distribution systems (DSs) is an operational measure proposed to enhance power system flexibility. The computational performance of the applied optimization techniques varies greatly according to the constraints ensuring network radiality. Formulations of radiality constraints differ from each other by model complexity and the search space of the relaxed linear programming (LP) problem. In this paper, widely used formulations of radiality constraints are first revisited and flexibly enhanced to address the complex operating environment of modern DSs. To incorporate various radiality constraints and provide an optimization basis for comparison, a flexible MG formation problem is proposed with the ability to automatically allocate distributed generators (DGs) into multiple MGs. Combined formulations with parent-child (PC) constraints are then developed to shrink the LP feasible region. Moreover, to accelerate the branching process by applying the branch-and-cut (B&C) algorithm, an efficient formulation of radiality constraints is proposed by adding extra constraints that exclude fundamental loops into the single-commodity flow formulation. To further accelerate the branching process, a dynamic constraint generation algorithm is developed without substantially increasing the complexity of the LP problem. DSs of various complexities and sizes are employed to verify the computational efficiency of the proposed formulations. The paper concludes by suggesting the most efficient formulations of radiality constraints according to the scale of the targeted DS.

Published
2023
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48. Electric Vehicles Charging Infrastructure Demand and Deployment: Challenges and Solutions.

Author

Singh, Praveen Prakash, Wen, Fushuan, Palu, Ivo, Sachan, Sulabh, and Deb, Sanchari

Subjects
*INFRASTRUCTURE (Economics), *ELECTRIC charge, *SCHEDULING, *ELECTRIC vehicles, *AUTOMOTIVE transportation
Abstract

Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and future scope of EV charging infrastructure are also highlighted in this paper. [ABSTRACT FROM AUTHOR]

Published
2023
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