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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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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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Multi-objective interval prediction of wind power based on conditional copula function

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Journal of Modern power Systems and Clean Energy 2019年第4期7卷 802-812页

作者： Gang ZHANG Zhixuan LI Kaoshe ZHANG Lei ZHANG Xia HUA Yongqing WANG Institute of Water Resources and Hydro-electric Engineering Xi’an University of TechnologyXi’an 710048China state grid shaanxi baoji electric power company Baoji 721000China state grid Gansu electric power company Gansu Electric Power Research InstituteLanzhou 730050China state grid shaanxi electric power company Shaanxi Electric Power Research InstituteXi’an 710054China

Interval prediction of wind power,which features the upper and lower limits of wind power at a given confidence level,plays a significant role in accurate prediction and stability of the power grid integrated with wind ***,the conventional methods of interval prediction are commonly based on a hypothetic probability distribution function,which neglects the correlations among various variables,leading to the decrease of prediction ***,we improve the multi-objective interval prediction based on the conditional copula function,through which we can fully utilize the correlations among variables to improve prediction accuracy without an assumed probability distribution *** use the multi-objective optimization method of nondominated sorting genetic algorithm-II(NSGA-II)to obtain the optimal solution *** particular best solution is weighted by the prediction interval average width(PIAW)and prediction interval coverage probability(PICP)to pick the optimized solution in practical ***,we apply the proposed method to three wind power plants in different cities in China as examples forvalidation and obtain higher prediction accuracy compared with other methods,i.e.,relevance vector machine(RVM),artificial neural network(ANN),and particle swarm optimization kernel extreme learning machine(PSO-KELM).These results demonstrate the superiority and practicability of this method in interval prediction of wind power.

关键词： Wind power prediction Interval prediction Conditional copula function Empirical distribution function Multi-objective optimization algorithm

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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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A grid Cell Based Distribution Network Planning Method Adapting to the Increasing Permeability of Distributed Resources

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Dianwang Jishu/power System Technology 2025年第1期49卷 306-315页

作者： Zhou, Yang Wang, Zhuding Zhang, Man Yang, Jie Shu, Dongsheng state Key Laboratory of power Transmission Equipment & System Security and New Technology Chongqing University Shapingba District Chongqing 400044 China Chongqing electric Energy Star Inc Jiulongpo District Chongqing 400039 China Economic Research Institute of state grid Hubei electric power company Hubei Province Wuhan 430000 China

Based upon the existing research findings of distribution network planning，and based on the optimization division of power areas (or grid cells), a heuristic method of distribution network planning, i.e., the grid cell based distribution network planning method, is proposed to adapt to the gradual increase in the penetration rate of distributed resources, wherein the power balancing method involves differential approaches of different space-time-resources and two typical operating modes. The optimization division of grid cells is carried out by the principles of nearby use for distributed power resources and "nearby backup supply", resulting in the regional grid cell, substation grid cell, medium-voltage and low-voltage grid cell in terms of space, and also the energy output type, energy input type and balance type in terms of resources. The real planning example shows that the proposed method has relatively strong operability. © 2025 power System Technology Press. All rights reserved.

关键词： power distribution planning

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Research on Resilience Assessment and Improvement Methods of New Energy Bases Under Strong Sandstorm

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Dianwang Jishu/power System Technology 2025年第1期49卷 124-135页

作者： Wang, Jinyan Ding, Kun Sun, Yalu Wang, Xiang Dong, Haiying College of New Energy and power Engineering Lanzhou Jiaotong University Gansu Province Lanzhou 730070 China state grid Gansu electric power company Gansu Province Lanzhou 730000 China Tsinghua Sichuan Energy Internet Research Institute Sichuan Province Chengdu 610213 China

The natural endowments of wind and solar resources in the desert and Gobi Desert areas of our country, as well as the reverse distribution of energy and load, make it of great significance to develop large-scale new energy bases and large-scale transmission of AC/DC hybrid power grids in the desert and Gobi Desert areas. The frequent occurrence of extreme sandstorms in the desert and Gobi Desert areas has seriously affected the centralized development and long-distance safe and stable transmission of new energy power generation bases. This article first quantifies the impact of two disaster-causing factors of sandstorms on new energy bases, establishes a mathematical model that reflects the relationship between sandstorms and new energy output, strong winds, and line failure rates, uses Monte Carlo sampling combined with system information entropy to select typical fault scenarios and construct a recovery model, obtains the system elasticity curve based on operating conditions, considers the entire process of system disaster, and adopts the Analytic Hierarchy Process (AHP) method Establish elasticity evaluation indicators;Secondly, a flexible improvement method is proposed from a planning perspective, to minimize the equivalent annual investment cost of the line and energy storage and the system's loss of load cost. A joint planning model for line expansion and energy storage configuration for flexible improvement is established, which is transformed into a mixed integer linear programming (MILP) problem, and the expansion plan of the new energy baseline and the optimal configuration of energy storage are solved. Finally, taking the improved IEEE36 node system as an example for simulation analysis, the elasticity indicators before and after adopting improvement measures are compared to verify the effectiveness and accuracy of the proposed elasticity evaluation and improvement methods. © 2025 power System Technology Press. All rights reserved.

关键词： Charge storage

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