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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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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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Optimal Operation of Multi Alkaline Electrolyzers Considering Flexible electrical and Hydrogen Load

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Dianwang Jishu/power System Technology 2025年第1期49卷 84-92页

作者： Tian, Xueqin Feng, Yajie Yuan, Tiejiang Yang, Fuyuan Ge, Yangyang School of electrical Engineering Dalian University of Technology Liaoning Province Dalian 116024 China Sate Grid Economic and Technological Research Institute Co. Ltd. Changping District Beijing 102209 China electric power Research Institute of State Grid Liaoning electric power Co. Ltd. Liaoning Province Shenyang 110006 China

Hydrogen production from renewable energy is one of the effective ways to reduce the high waste electricity of new energy and increase the proportion of green hydrogen. The multi-alkaline electrolyzers optimization operation strategy is proposed considering flexible electric loads and hydrogen loads in response to the optimization operation of large-scale new energy hydrogen production systems and high abandonment of electricity. Firstly, after considering the demand for electricity and hydrogen loads on the user side, transferable electric loads and hydrogen load models are established based on the transferable characteristics of electricity and hydrogen. Secondly, the multi-stack electrolyzer optimization operation strategy is proposed, considering the operating characteristics of a single electrolytic cell and electrolytic efficiency. Satisfying system operation constraints and optimizing the operating model to minimize economic cost is established and solved using the Yalmip toolbox and Cplex. The calculation results show that the participation of transferable loads can promote wind power consumption, reduce system electricity consumption, and improve the system economy. Compared with the multi-stack electrolyzer rotation strategy, the strategy proposed in this article effectively reduces the start and stop times of the electrolyzer, stabilizes the standard deviation of electrolysis cell power fluctuation within 0.27, improves the service life of electrolyzer arrays and increases the overall electrolysis efficiency to about 57%. © 2025 power System Technology press. All rights reserved.

关键词： Wind power

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Optimization of Convolutional Neural Network Based on Improved Sparrow Algorithm for Flywheel Energy Storage System Loss in Small Sample

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Dianwang Jishu/power System Technology 2025年第1期49卷 366-372页

作者： Wei, Le Li, Chenglin Fang, Fang Liu, Yubin School of Control and Computer Engineering North China Electric Power University Changping District Beijing 102206 China

Flywheel energy storage systems have standby losses and are unsuitable for long-term energy storage. Aiming at the economic index of flywheel loss, based on the small sample data of the operation of the flywheel energy storage system, a flywheel loss calculation model combining a Logistic chaotic sparrow optimization algorithm and a convolutional neural network was proposed. Firstly, the causes of flywheel loss were analyzed. Next, the flywheel operation data of Ningxia Lingwu power Plant was preprocessed, and the adversarial generation network was used for small-sample enrichment. Then, the loss model is established based on the convolutional neural network, the improved sparrow algorithm is used to optimize the hyperparameters of the model, and the superiority of the model is verified by comparison. Finally, simulation experiments show that the model can optimize the output of the flywheel energy storage system and reduce the flywheel loss. © 2025 power System Technology press. All rights reserved.

关键词： Flywheels

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Daily Intra Day Collaborative Rolling Optimization Strategy for Solar Energy Storage power Stations Participating in Multiple Application Scenarios

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Dianwang Jishu/power System Technology 2025年第1期49卷 198-208页

作者： Liu, Zifa Li, Kunyang Zheng, Siqi School of electrical and Electronic Engineering North China Electric Power University Changping District Beijing 102206 China

The joint operation of photovoltaic power stations and energy storage systems can reduce the uncertainty of power output from the power supply side and improve the stability of the power grid. The current application scenarios for solar energy storage power stations are relatively single, making it difficult to simultaneously consider primary and secondary frequency regulation and joint electricity sales. In response to this issue, this paper proposes a multi-scenario compatible day-ahead rolling optimization operation strategy that considers the electricity market and primary and secondary frequency regulation services. Firstly, the characteristics of primary and secondary frequency modulation signals will be analyzed, and a collaborative optimization strategy framework for hybrid energy storage in photovoltaic power plants will be proposed under multi-application scenario scheduling resolution. Then, to maximize the joint revenue of the station, a daily optimization model is established that considers the secondary frequency regulation capacity of energy storage. In the intraday stage, the actual output priority of each scenario is considered, and a rolling optimization solution is obtained to obtain the operation plan of the energy storage system. Using actual data from a photovoltaic power station in Daqing, Heilongjiang Province, simulation verification was conducted, and sensitivity analysis was conducted on the model. The example shows that the optimization strategy proposed in this paper can unleash the scheduling potential of different energy storage resources, effectively improve the accuracy of power station reporting and frequency regulation ability. © 2025 power System Technology press. All rights reserved.

关键词： Sensitivity analysis

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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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Optimization Model for Inter-regional Emergency power Dispatch Considering Transmission Rights Allocation

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Dianwang Jishu/power System Technology 2025年第1期49卷 223-231页

作者： Guan, Jinyu Liang, Zhifeng Chang, Li Cao, Rongzhang Li, Lili NARI Group Corporation State Grid Electric Power Research Institute Jiangsu Province Nanjing 211106 China NARI Technology Co. Ltd. Jiangsu Province Nanjing 211106 China Department of electrical Engineering Tsinghua University Haidian District Beijing 100084 China National power Dispatch and Control Centre Xicheng District Beijing 100031 China

Inter-regional emergency power dispatch refers to the mandatory fallback guarantee measures for ensuring supply or absorption of emergency demands within provincial grids when market-based approaches have been exhausted from the perspective of mutual assistance in electricity surplus and shortage across provinces and regions. When it is impossible to rely on market declarations directly, how to allocate emergency demands and inter-provincial/regional support capacities and distribute the limited available transfer capacity reasonably among market entities is one of the key issues urgently needing to be addressed in current emergency dispatch. This paper proposes an optimization model for inter-provincial and inter-regional emergency power dispatch considering transmission rights. Inspired by china's current mechanism for allocating transmission channel revenue rights, based on local prioritization and the urgency of emergency demands, a method for determining the priority of emergency transactions considering transmission rights allocation is proposed. This method transforms transmission rights into priority transaction rights, addressing the lack of a reasonable basis for transmission capacity allocation in the emergency dispatch phase. Considering constraints such as available transfer capacity, transaction flow balance, and transaction point power balance constraints, to maximize adjusted social welfare, a clearing model for emergency dispatch optimization considering transaction path priority is constructed. Comparative analysis of the optimization results of three 1e clearing modes, price-based sequential clearing, scenario-based separation, and clearing with transaction path priority, validates the effectiveness and superiority of the proposed optimization clearing model and analyzes the impact of related parameter settings on the clearing results. © 2025 power System Technology press. All rights reserved.

关键词： Commerce

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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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Strategy for Enhancing the Available Capacity of Distribution Networks Considering electric Vehicle Charging Modes

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Dianwang Jishu/power System Technology 2025年第1期49卷 177-186页

作者： Chen, Peng Liu, Youbo Yuan, Chuan Tang, Donglai Xiang, Yue Liu, Junyong College of electrical Engineering Sichuan University Sichuan Province Chengdu 610065 China State Grid Sichuan electric power Company Sichuan Province Chengdu 610041 China Aostar Information Technology Co. Ltd. Sichuan Province Chengdu 610067 China

The available capacity of distribution networks represents the maximum load capacity that can be accommodated under the existing conditions of the distribution network. It is an essential indicator for evaluating distribution networks' planning and operational effectiveness. This paper proposes a grid transformation method for distribution networks considering electric vehicle charging modes to address the significant decrease in available capacity caused by the large-scale disorderly charging of electric vehicles. By optimizing the grid topology and the optimal number, location, and type of line expansion and energy storage investment within the limited investment., the optimal enhancement of available capacity is achieved. Firstly, the Monte Carlo method is employed to generate scenarios of disorderly charging of electric vehicles, and an orderly electric vehicle charging model based on optimizing charging schedules is constructed. Secondly, a transformation model for enhancing the available capacity of distribution networks is developed based on the coordination of network reconfiguration, line expansion, and energy storage investment. Then, the complexity of the model is reduced using the Benders decomposition algorithm, and a commercial solver is employed for the solution. Finally, a case study based on a city's actual distribution network grid is conducted to validate the effectiveness of the proposed strategies for enhancing the available capacity. © 2025 power System Technology press. All rights reserved.

关键词： Monte Carlo methods

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