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IoT Empowered Early Warning of Transmission Line Galloping Based on Integrated Optical Fiber Sensing and Weather Forecast Time Series Data

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Computers, Materials & Continua 2025年第1期82卷 1171-1192页

作者： Zhe Li Yun Liang Jinyu Wang Yang Gao state grid Henan electric power company electric power Scientific Research Institute State Grid Henan Electric Power CompanyZhengzhou450052China

Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power *** early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false *** address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather ***,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused ***,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network ***,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this ***,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.

关键词： Optical fiber sensing multi-source data fusion early warning of galloping time series data IoT adaptive weighted learning irregular time series perception closed-loop attention mechanism

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Coordinated Control Strategy of New Energy power Generation System with Hybrid Energy Storage Unit

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Energy Engineering 2025年第1期122卷 167-184页

作者： Yun Zhang ZifenHan Biao Tian Ning Chen Yi Fan School of Mechano-Electronic Engineering Xidian UniversityXi’an710071China electric power Control Center State Grid Gansu Electric Power CompanyLanzhou730030China electric power Control Center State Grid Gansu Electric Power Company Zhangye Power Supply BranchZhangye734000China

The new energy power generation is becoming increasingly important in the power *** as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power *** solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage ***,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage ***,the fuzzy control algorithm is introduced to balance the power between energy *** this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current *** is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.

关键词： Photovoltaic power suppression hybrid energy storage unit variationalmodal decomposition fuzzy control power distribution control

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A Verifiable Trust-Based CP-ABE Access Control Scheme for Cloud-Assisted Renewable Energy Systems

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Computers, Materials & Continua 2025年第1期82卷 1211-1232页

作者： Jiyu Zhang Kehe Wu Ruomeng Yan Zheng Tian Yizhen Sun Yuxi Wu Yaogong Guo Department of Control and Computer Engineering North China Electric Power UniversityBeijing102206China state grid Information&Communication company of Hunan electric power Corporation Changsha410118China state grid Hunan electric power Corporation Chenzhou power Supply Branch Chenzhou423000China

Renewable Energy Systems(RES)provide a sustainable solution to climate warming and environmental pollution by enhancing stability and reliability through status acquisition and analysis on cloud platforms and intelligent processing on edge servers(ES).However,securely distributing encrypted data stored in the cloud to terminals that meet decryption requirements has become a prominent research ***,managing attributes,including addition,deletion,and modification,is a crucial issue in the access control scheme for *** address these security concerns,a trust-based ciphertext-policy attribute-based encryption(CP-ABE)device access control scheme is proposed for RES(TB-CP-ABE).This scheme effectivelymanages the distribution and control of encrypted data on the cloud through robust attribute key *** introducing trust management mechanisms and outsourced decryption technology,the ES system can effectively assess and manage the trust worthiness of terminal devices,ensuring that only trusted devices can participate in data exchange and access sensitive ***,the ES system dynamically evaluates trust scores to set decryption trust thresholds,thereby regulating device data access permissions and enhancing the system’s *** validate the security of the proposed TB-CP-ABE against chosen plaintext attacks,a comprehensive formal security analysis is conducted using the widely accepted random oraclemodel under the decisional q-Bilinear Diffie-Hellman Exponent(q-BDHE)***,comparative analysis with other schemes demonstrates that the TB-CP-ABE scheme cuts energy/communication costs by 43%,and scaleswell with rising terminals,maintaining average latency below 50ms,ensuring real-time service *** proposed scheme not only provides newinsights for the secure management of RES but also lays a foundation for future secure energy solutions.

关键词： Access control renewable energy systems(RES) ciphertext-policy attribute-based encryption(CP-ABE) security

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Experimental Study on Energy Storage Characteristics of Sintered Ore Particle Packed Beds

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Journal of Thermal Science 2025年第1期34卷 242-253页

作者： LAI Zhenya DING Liwei LYU Hongkun HOU Chenglong CHEN Jiaying GUO Xutao HAN Gaoyan ZHANG Kang state grid Zhejiang electric power Research Institute state Key Laboratory of Clean Energy Utilization Zhejiang University

The particle packed bed energy storage system has advantages such as low costs and wide temperature ranges,which can be combined with solar thermal power generation systems to solve the inherent volatility and discontinuity of renewable *** new materials with low costs and excellent storage performances is one of the eternal research hotspots in the field of energy *** paper innovatively uses sintered ore particles as energy storage material and studies the effect of particle size on the airflow resistance characteristics,energy storage characteristics,and thermocline evolution characteristics of the packed bed through thermal energy storage *** results indicate that for the particles in the macro scale,the smaller the particle,the lower the absolute permeability of the bed and the greater the airflow *** packed bed with smaller particles has a larger specific surface area,larger bulk mass,and smaller bed ***,the packed beds with smaller particles have better thermocline characteristics,less irreversible loss,and can achieve higher thermal efficiency and higher exergy efficiency in the heat storage *** cycle thermal efficiency in packed beds with 25-40 mm,16-25 mm,and 10-16 mm particles is 53.58%,56.27%,and 57.60%,respectively,and the cycle exergy efficiency is 61.81%,69.25%,and 74.13%,***,this paper also studies the effect of discharging airflow rates on thermal storage *** experimental results indicate that suitable discharging strategies should be selected based on different heat demands.

关键词： airflow resistance particle packed bed thermal energy storage thermocline evolution

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Multi-Stage Voltage Control Optimization Strategy for Distribution Networks Considering Active-Reactive Co-Regulation of electric Vehicles

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Energy Engineering 2025年第1期122卷 221-242页

作者： Shukang Lyu Fei Zeng Huachun Han HuiyuMiao Yi Pan Xiaodong Yuan electric power Research Institute State Grid Jiangsu Electric Power Co.Ltd.Nanjing211103China

The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the existing research has not deeply explored the EV active-reactive synergistic regulating characteristics,and failed to realize themulti-timescale synergistic control with other regulatingmeans,For this reason,this paper proposes amultilevel linkage coordinated optimization strategy to reduce the voltage deviation of the distribution ***,a capacitor bank reactive power compensation voltage control model and a distributed photovoltaic(PV)activereactive power regulationmodel are ***,an external characteristicmodel of EVactive-reactive power regulation is developed considering the four-quadrant operational characteristics of the *** optimization model of the distribution network is then constructed considering the time-series coupling constraints of multiple types of voltage regulators.A multi-timescale control strategy is proposed by considering the impact of voltage regulators on active-reactive EV energy consumption and PV energy ***,a four-stage voltage control optimization strategy is proposed for various types of voltage regulators with multiple time ***-objective optimization is solved with the improvedDrosophila algorithmto realize the power fluctuation control of the distribution network and themulti-stage voltage control *** results validate that the proposed voltage control optimization strategy achieves the coordinated control of decentralized voltage control resources in the distribution *** effectively reduces the voltage deviation of the distribution network while ensuring the energy demand of EV users and enhancing the stability and economic efficiency of the distribution network.

关键词： electric vehicle(EV) distribution network multi-stage optimization active-reactive power regulation voltage control

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Anomaly Detection of Controllable electric Vehicles through Node Equation against Aggregation Attack

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Computers, Materials & Continua 2025年第1期82卷 427-442页

作者： Jing Guo Ziying Wang Yajuan Guo Haitao Jiang state grid Jiangsu electric power Co. Ltd.Research InstituteState Grid Corporation of ChinaNanjing211100China

The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids *** study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation *** approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation *** employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter *** xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging *** results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging ***,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 *** research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.

关键词： Anomaly detection electric vehicle aggregation attack deep cross-network

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Dispatchable Capability of Aggregated electric Vehicle Charging in Distribution Systems

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Energy Engineering 2025年第1期122卷 129-152页

作者： ShiqianWang Bo Liu Yuanpeng Hua Qiuyan Li Binhua Tang Jianshu Zhou Yue Xiang Economic and Technology Research Institute State Grid Henan Electric Power CompanyZhengzhou450052China College of electrical Engineering Sichuan UniversityChengdu610065China

This paper introduces a method for modeling the entire aggregated electric vehicle(EV)charging process and analyzing its dispatchable *** methodology involves developing a model for aggregated EV charging at the charging station level,estimating its physical dispatchable capability,determining its economic dispatchable capability under economic incentives,modeling its participation in the grid,and investigating the effects of different scenarios and EV penetration on the aggregated load dispatch and dispatchable *** results indicate that using economic dispatchable capability reduces charging prices by 9.7%compared to physical dispatchable capability and 9.3%compared to disorderly ***,the peak-to-valley difference is reduced by 64.6%when applying economic dispatchable capability with 20%EV penetration and residential base load,compared to disorderly charging.

关键词： Aggregated charging dispatchable capability peak shaving and valley filling the economics of charging demand response

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A coordinated planning strategy of energy storage allocation and line upgrading to increase photovoltaic consumption with lowest planning cost

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Science China Technological Sciences 2025年

作者： Bo ZHANG Yuqi JI Lu ZHANG Wei TANG Xiaohui ZHANG Liang WANG Haoran DING Hanchen MAO College of Information and electrical Engineering China Agricultural University state grid Heilongjiang electric power Research Institute State Grid Heilongjiang Electric Power Company Limited School of electrical and Information Engineering Zhengzhou University of Light Industry

Random integration of massive distributed photovoltaic (PV) generation poses serious challenges to distribution networks. Voltage violations, line overloads, increased peak–valley differences, and power-flow reversals can occur at different locations, times, and severities. Traditional planning methods such as energy storage (ES) allocation and upgrading of lines may result in poor economics and low equipment utilization. This study proposes a distribution-network planning strategy that coordinates three planning mechanisms:ES allocation to substations and to feeders, and line upgrading. The proposed strategy achieved the lowest annual cost, considering the distribution network problems at different locations, times, and severities. A net load curve description method was first proposed considering economic planning and the uncertain distribution of loads and PVs. Second, a multistage optimization model for ES allocation and line upgrading was established based on the net load curves. Finally, an improved IEEE33 node system was used in the case study. The planning results show that the proposed coordinated planning strategy can address the problems caused by the random integration of massive distributed PVs, improve equipment utilization, and obtain the lowest total annual planning cost.

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Short-term Photovoltaic power Prediction Based on Feature Optimization and Hybrid Improved Grey Wolf Algorithm-optimized BiLSTM Network

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Dianwang Jishu/power System Technology 2025年第1期49卷 209-222页

作者： Zhao, Ruyi Wang, Xiaohui Zheng, Bihuang Li, Daoxing Gao, Yi Guo, Pengtian China electric power Research Institute Haidian District Beijing 100192 China Economic and Technological Research Institute State Grid Tianjin Electric Power Company Hedong District Tianjin 300171 China

To address the challenges posed by strong noise interference in photovoltaic (PV) sequences and the issues of low accuracy and poor generalization of a single model in PV power prediction, we propose a short-term PV power prediction method. This method uses feature optimization and a hybrid improved Grey Wolf algorithm to optimize the BiLSTM network. Firstly, the mutual information algorithm is employed for variable selection in input data to eliminate redundant variables. Subsequently, the Complementary Ensemble Empirical Mode Decomposition and an improved wavelet threshold algorithm are applied to the selected data for feature reconstruction to reduce noise interference in the data and optimize input variable features. Finally, the standard Grey Wolf Optimizer algorithm underwent hybrid optimization by integrating improved Tent chaotic mapping, nonlinear decreasing factors, dynamic weight strategies, and the differential evolution algorithm. This process aimed to ascertain the optimal hyperparameter combination for the BiLSTM network. The attention mechanism was also employed to extract key temporal information from the data, developing a novel short-term photovoltaic power prediction model. Simulation experiments demonstrate that, compared to the least squares support vector machine, long short-term memory network, and bidirectional long short-term memory neural network, the proposed model achieves an average reduction of 12.45%, 7.95%, and 5.37% in root mean square error under various weather conditions such as sunny, cloudy, overcast, and rainy, showcasing excellent predictive performance, good generalization ability, and promising engineering application value. © 2025 power System Technology Press. All rights reserved.

关键词： Mean square error

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Construction Concept and Innovative Practices of Virtual power Plants in Megacities Under electricity Market Environment

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Dianwang Jishu/power System Technology 2025年第1期49卷 103-112页

作者： Tang, Jun Gao, Hongchao Yu, Tao Kang, Chongqing state grid Shanghai Municipal electric power company Pudong New Area Shanghai 200122 China National Key Laboratory of New power System Operation and Control [Tsinghua University Haidian District Beijing 100084 China

With the accelerated construction of new power systems, the Virtual power Plant (VPP), a key component of the new energy framework, provides critical support for safe supply, energy conservation, and emission reduction for power systems. However, the increasingly diverse technological forms and application scenarios of VPPs present challenges for standardization in large-scale development. A timely summary and generalization of VPP development principles, construction pathways, and technical practices can promote technical synergy and drive industry growth. This paper takes the VPP in a megacity as a typical use case. It thoroughly discusses the top-level design of the VPP by reviewing and analyzing four perspectives of form, policy, market, and standards. Secondly, this paper examines a multi-spatiotemporal regulation technology system for VPPs from three dimensions precise response, regional coordination, and fast regulation, which supports the normalized operation of Shanghai’s VPP. Then, this paper introduces the large-scale demonstration outcomes of Shanghai’s VPP, offering a valuable reference for development constructions and innovative practices of VPPs at the megacity scale. Finally, by analyzing the construction and operational outlook of Shanghai's VPP, this paper distills a clear pathway for its future development. © 2025 power System Technology Press. All rights reserved.

关键词： Virtual power Plants

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