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Minimizing Age of Information in UAV-Assisted Edge Computing System with Multiple Transmission Modes

清华大学学报自然科学版（英文版） 2025年第3期30卷 1060-1078页

作者： Yanhua Pei Yunzhi Zhao Fen Hou State Key Laboratory of IoT for Smart City and Department of Electrical and Computer Engineering University of MacauMacau 999078China

With the advance of 5G technologies and the development of space-air-ground-sea applications,the fast and efficient collection and processing of the explosive growth of sensing data have become significant and *** this paper,considering the Age of Information(AoI),the limited coverage of Base Stations(BS),and the constrained computation capability of Unmanned Aerial Vehicle(UAV),we propose a hybrid communication framework that utilizes UAVs as relays to optimize the collection of sensing *** aim to minimize the average AoI of the data among all sensor nodes while considering the energy consumption constraints of sensor nodes,which is formulated as a Mixed Integer NonLinear Programming(MINLP).To address this problem,we decompose it into communication resource allocation and computation resource ***,the average AoI of the whole system is minimized and the average energy consumption constraint of sensor nodes is *** simulation results show that our proposed method can achieve significant performance *** specific,our proposed method can reduce the average AoI by 20％,11％,and 43％compared to the three counterparts,Data Transmission Directly Algorithm(DTDA),Max Weight Algorithm(MWA),and matching algorithm,respectively.

关键词： edge computing hybrid relay Unmanned Aerial Vehicle(UAV)assisted Age of Information(AoI)

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Distributionally Robust Chance-Constrained Optimization for Soft Open Points Operation in Active Distribution Networks

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CSEE Journal of Power and Energy Systems 2025年第2期11卷 637-648页

作者： Qilin Hou Ge Chen Ningyi Dai Hongcai Zhang Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart CityUniversity of MacaoMacao 999078China

The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across various regions. Moreover, due to the intermittent and stochastic characteristics, DG also introduces uncertain forecasting errors, which further increase difficulties for power dispatch. To overcome these challenges, an emerging flexible interconnection device, soft open point (SOP), is introduced. A distributionally robust chance-constrained optimization (DRCCO) model is also proposed to effectively exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust, stochastic and chance-constrained models, the DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. More-over, unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g, bus voltage and branch current limitations), joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid redundant conservativeness. Based on numerical experiments, we validate that SOPs' employment can significantly enhance the energy efficiency of ADNs by alleviating DG curtailment and load shedding problems. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability while reducing the conservativeness of conventional DRCCO methods.

关键词： Active distribution networks distributionally robust chance-constrained optimization soft open points

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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua Song Ge Chen Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow

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Dynamic Performance of Non-Minimum-Phase Zeros-Dominated Power-Synchronization Control

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IEEE Transactions on Power Systems 2025年第2期40卷 1985-1988页

作者： Jin, Xin Dai, Ningyi State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering University of Macau 999078 China

In this letter, it is found that non-minimum-phase zeros of power-synchronization control (PSC), induced by q-axis current injection, only dominate the system in weak grids, with one exception of low converter voltage magnitude. Using Bode's gain/phase relation, a trade-off analytical condition between the bandwidth and phase margin is proposed considering the locations of right-half-plant (RHP) zeros. System dynamic performance is improved compared to the design ignoring the effect of RHP zeros. © 1969-2012 IEEE.

关键词： Bandwidth Transfer functions Power system stability Impedance System dynamics Stability criteria Reactive power Power system dynamics Grid forming Tuning

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A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 953-962页

作者： Kunjie Tang Shufeng Dong Yonghua Song College of Electrical Engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao SARChina IEEE

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first *** that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is *** with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are ***,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power *** experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark ***,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional ***,in some cases,where conventional methods diverge,these LSI methods can still converge.

关键词： Fixed-point theory integrated transmission and distribution networks least-squares-based iterative method master-slave-splitting method optimal power flow power flow

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Frequency-constrained Unit Commitment Considering Typhoon-induced Wind Farm Cutoff and Grid Islanding Events

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Journal of Modern Power Systems and Clean Energy 2024年第6期12卷 1760-1772页

作者： Yanqi Liu Dunjian Xie Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacaoChina Institute of Catastrophe Risk Management Nanyang Technological UniversitySingapore

In coastal regions of China,offshore wind farm ex-pansion has spurred extensive research to reduce operational costs in power systems with high penetration of wind ***,frequent extreme weather conditions such as typhoons pose substantial challenges to system stability and ***-vious research has intensively examined the steady-state opera-tions arising from typhoon-induced faults,with a limited em-phasis on the transient frequency dynamics inherent to such *** address this challenge,this paper proposes a frequen-cy-constrained unit commitment model that can promote ener-gy utilization and improve *** proposed model ana-lyzes uncertainties stemming from transmission line failures and offshore wind generation through typhoon *** types of power disturbances resulting from typhoon-in-duced wind farm cutoff and grid islanding events are *** addition,new frequency constraints are defined considering the changes in the topology of the power ***,the complex frequency nadir constraints are incorporated into a two-stage stochastic unit commitment model using the piece-wise ***,the proposed model is verified by nu-merical experiments,and the results demonstrate that the pro-posed model can effectively enhance system resilience under ty-phoons and improve frequency dynamic characteristics following fault disturbances.

关键词： Frequency constraint offshore wind farm typhoon uncertainty unit commitment

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Stochastic Unit Commitment with High-Penetration Offshore Wind Power Generation in Typhoon Scenarios

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 535-546页

作者： Yanqi Liu Dundun Liu Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China University of Macao Zhuhai UM Science and Technology Research Institute ZhuhaiChina

To tackle the energy crisis and climate change,wind farms are being heavily invested in across the *** China's coastal areas,there are abundant wind resources and numerous offshore wind farms are being *** secure operation of these wind farms may suffer from typhoons,and researchers have studied power system operation and resilience enhancement in typhoon ***,the intricate movement of a typhoon makes it challenging to evaluate its spatial-temporal *** published papers only consider predefined typhoon trajectories neglecting *** address this challenge,this study proposes a stochastic unit commitment model that incorporates high-penetration offshore wind power generation in typhoon *** adopts a data-driven method to describe the uncertainties of typhoon trajectories and considers the realistic anti-typhoon mode in offshore wind farms.A two-stage stochastic unit commitment model is designed to enhance power system resilience in typhoon *** formulate the model into a mixed-integer linear programming problem and then solve it based on the computationally-efficient progressive hedging algorithm(PHA).Finally,numerical experiments validate the effectiveness of the proposed method.

关键词： Unit commitment two-stage stochastic programming offshore wind farm typhoon

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Time-efficient Strategic Power Dispatch for District Cooling Systems Considering Evolution of Cooling Load Uncertainties

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CSEE Journal of Power and Energy Systems 2022年第5期8卷 1457-1467页

作者： Ge Chen Biao Yan Hongcai Zhang Dongdong Zhang Yonghua Song State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China

District cooling system(DCS)provides centralized chilled water to multiple buildings for air conditioning with high energy-efficiency and operational *** is one of the most popular cooling systems for large buildings in modern cities and an important demand response source for power *** order to enhance its energy efficiency and utilize its flexibility,strategic operation is ***,finding an optimal policy for DCS operation is a challenging task because of the high inter-connectivity among *** evolution of cooling load uncertainties further increases the *** paper addresses the aforementioned challenges by proposing a novel optimal power dispatch model for *** proposed model optimizes water temperature and mass flow rates simultaneously to improve the energy efficiency as much as *** also explicitly describes the uncertainty accumulation and ***-constrained programming is employed to guarantee the cooling service *** further propose a more timeefficient formulation to overcome the computational intractability caused by the non-smooth and non-convex *** experiments based on a real DCS confirm that a time-efficient formulation can save about half of solution time with negligible cost increase.

关键词： District cooling system HVAC cooling power dispatch demand-side flexibility chance-constrained programming

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DEEP-iot: Downlink-Enhanced Efficient-Power Internet of Things

DEEP-IoT: Downlink-Enhanced Efficient-Power Internet of Thin...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Shao, Yulin University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350351255

At the heart of the Internet of Things (iot) - a domain witnessing explosive growth - the imperative for energy efficiency and the extension of device lifespans has never been more pressing. This paper presents DEEP-iot, a novel communication paradigm poised to redefine how iot devices communicate. Through a pioneering "listen more, transmit less"strategy, DEEP-iot challenges and transforms the traditional transmitter (iot devices)-centric communication model to one where the receiver (the access point) play a pivotal role, thereby cutting down energy use and boosting device longevity. We not only conceptualize DEEP-iot but also actualize it by integrating deep learning-enhanced feedback channel codes within a narrow-band system. Simulation results show a significant enhancement in the operational lifespan of iot cells - surpassing traditional systems using Turbo and Polar codes by up to 52.71%. This leap signifies a paradigm shift in iot communications, setting the stage for a future where iot devices boast unprecedented efficiency and durability. © 2024 IEEE.

关键词： Energy utilization

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Optimal Operation and Economic Analysis of Ice Thermal Energy Storage in District Cooling System

Optimal Operation and Economic Analysis of Ice Thermal Energ...

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2024 IEEE Power and Energy Society General Meeting, PESGM 2024

作者： Wei, Xiangyu Zhang, Hongcai Wong, Chi Kong University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering 999078 China

Ice thermal energy storage (ITES) is a type of cooling thermal energy storage. It can shift the daytime peak cooling load to nighttime, thereby enhancing the economic benefit of the cooling system and enabling peak load shifting in the power grid. Although ITES has been widely utilized in district cooling systems (DCSs), the economic assessment of its implementation in DCS remains inadequate due to the thermal dynamics and operation strategy. This paper first presents an ITES-equipped DCS optimal operation model integrated with the time of use electricity price and demand charge. The proposed model can provide the economically optimal operation scheme considering the ITES dynamic charging/discharging process, and the change of the chiller's coefficient of performance, which depends on the ambient temperature and partial load rates. Then the economy of the ITES in a real DCS is assessed based on the proposed operation model. A comprehensive case study is employed to evaluate its benefit in comparison with the DCS equipped with battery energy storage. The case study indicates that the DCS with ITES outperforms in the economy, whereas DCS with battery energy storage surpasses in reducing demand charge. © 2024 IEEE.

关键词： Battery storage

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