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Cloud-Edge Collaborative Federated GAN Based Data Processing for IoT-Empowered Multi-Flow Integrated Energy Aggregation Dispatch

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Computers, Materials & Continua 2024年第7期80卷 973-994页

作者： Zhan Shi Electric power dispatching control center Guangdong Power Grid Co.Ltd.Guangzhou510030China

The convergence of Internet of Things(IoT),5G,and cloud collaboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data *** generative adversarial networks(GANs)are instrumental in resource scheduling,their application in this domain is impeded by challenges such as convergence speed,inferior optimality searching capability,and the inability to learn from failed decision making ***,a cloud-edge collaborative federated GAN-based communication and computing resource scheduling algorithm with long-term constraint violation sensitiveness is proposed to address these *** proposed algorithm facilitates real-time,energy-efficient data processing by optimizing transmission power control,data migration,and computing resource *** employs federated learning for global parameter aggregation to enhance GAN parameter updating and dynamically adjusts GAN learning rates and global aggregation weights based on energy consumption constraint *** results indicate that the proposed algorithm effectively reduces data processing latency,energy consumption,and convergence time.

关键词： IoT federated learning generative adversarial network data processing multi-flowintegration energy aggregation dispatch

Research on Regulation Method of Energy Storage System Based on Multi-Stage Robust Optimization

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Energy Engineering 2024年第3期121卷 807-820页

作者： Zaihe Yang Shuling Wang Runhang Zhu Jiao Cui Ji Su Liling Chen Electrical dispatching and control center Yunnan Power GridKunming650011China Kunming power Supply Bureau Yunnan Power Grid Co.Ltd.Kunming650011China Yuxi power Supply Bureau Yunnan Power Grid Co.Ltd.Yuxi653100China

To address the scheduling problem involving energy storage systems and uncertain energy,we propose a method based on multi-stage robust *** approach aims to regulate the energy storage system by using a multi-stage robust optimal control method,which helps overcome the limitations of traditional methods in terms of time *** goal is to effectively utilize the energy storage power station system to address issues caused by unpredictable variations in environmental energy and fluctuating load throughout the *** achieve this,a mathematical model is constructed to represent uncertain energy sources such as photovoltaic and wind *** generalized Benders Decomposition method is then employed to solve the multi-stage objective optimization *** decomposing the problem into a series of sub-objectives,the system scale is effectively reduced,and the algorithm’s convergence ability is *** with other algorithms,the multi-stage robust optimization model has better economy and convergence ability and can be used to guide the power dispatching of uncertain energy and energy storage systems.

关键词： Multi-stage robust optimization energy storage system regulation methods output uncertainty

Distribution Line Longitudinal ProtectionMethod Based on Virtual Measurement Current Restraint

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Energy Engineering 2024年第2期121卷 315-337页

作者： WeiWang Yang Yu Simin Luo Wenlin Liu Wei Tang Yuanbo Ye power dispatching control center State Grid Anhui Electric Power Co.Ltd.Hefei230022China School of Electrical Engineering Beijing Jiaotong UniversityBeijing100044China

As an effective approach to achieve the“dual-carbon”goal,the grid-connected capacity of renewable energy increases *** are the most widely used renewable energy sources and have been applied on various ***,the inherent randomness,intermittency,and weak support of grid-connected equipment not only cause changes in the original flow characteristics of the grid but also result in complex fault *** overcurrent and differential protection methods cannot respond accurately due to the effects of unknown renewable energy ***,a longitudinal protection method based on virtual measurement of current restraint is proposed in this *** positive sequence current data and the network parameters are used to calculate the virtual measurement current which compensates for the output current of photovoltaic(PV).The waveform difference between the virtual measured current and the terminal current for internal and external faults is used to construct the protection *** improved edit distance algorithm is proposed to measure the similarity between virtual measurement current and terminal measurement ***,the feasibility of the protection method is verified through PSCAD simulation.

关键词： Photovoltaic interconnection distribution network longitudinal protection method edit distance algorithm

Modeling of Large-Scale Hydrogen Storage System Considering Capacity Attenuation and Analysis of Its Efficiency Characteristics

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Energy Engineering 2024年第2期121卷 291-313页

作者： Junhui Li Haotian Zhang Cuiping Li Xingxu Zhu Ruitong Liu Fangwei Duan Yongming Peng Key Laboratory of Modern power System Simulation and control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Ministry of Science and Technology Electric Power Research Institute of State Grid Liaoning Electric Power Co.Ltd.Shenyang110006China Northeast Electric power dispatching control center Northeast Branch of State Grid Corporation of ChinaShenyang110180China

In the existing power system with a large-scale hydrogen storage system,there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage *** order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation,and speed up the process of electric-hydrogen-electricity *** article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit,and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen storage *** models are of great significance for studying and optimizing gas storage *** these models,the performance of gas storage units can be better understood and *** studies are very helpful for improving energy storage efficiency and sustainable *** factors affecting the charge-discharge efficiency of hydrogen storage units are *** integrating the models of each unit and considering the capacity degradation of the hydrogen storage system,we can construct an efficiency model for a large hydrogen storage system and power conversion *** addition,the simulation models of the hydrogen production system and hydrogen consumption system were established in MATLAB/*** accuracy and effectiveness of the simulation model were proved by comparing the output voltage variation curve of the simulation with the polarization curve of the typical hydrogen production system and hydrogen consumption *** results show that the charge-discharge efficiency of the hydrogen storage unit increases with the increase of operating temperature,and H2 and O2 partial voltage have little influence on the charge-discharge *** the process of power conversion system converter rectification operation,its efficiency decreases wi

关键词： Hydrogen storage system simulation modeling electrolyzer fuel cell capacity loss

A comprehensive review on the development of data-driven methods for wind power prediction and AGC performance evaluation in wind–thermal bundled power systems

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Energy and AI 2024年第2期16卷 450-463页

作者： Shuai Wang Bin Li Guanzheng Li Botong Li Hongbo Li Kui Jiao Chengshan Wang National Industry-Education Platform for Energy Storage Tianjin UniversityTianjin300350China Key Laboratory of Smart grid of Ministry of Education Tianjin UniversityTianjin300072China power dispatching and control center Inner Mongolia Power(Group)Co.LtdHohhot010020China

The wind–thermal bundled power system achieves energy complementarity and optimized scheduling, which is an important way to build a new type of energy system. For the safe and stable operation of the wind–thermal bundled power system, accurate data-driven analysis is necessary to maintain real-time balance between electricity supply and demand. By summarizing the development and characteristics of wind–thermal bundled power system in china and different countries, current research in this field can be clearly defined in two aspects: short-term wind power prediction for wind farms and performance evaluation of automatic generation control (AGC) for thermal power generation units. For short-term wind power prediction, it is recommended to focus on historical data preprocessing and artificial intelligence methods. The technical characteristics of different data-driven wind power prediction methods have been compared in detail. For performance evaluation of AGC units, a comprehensive analysis was conducted on current evaluation methods, including the “permitted-band” and “regulation mileage” methods, as well as the issue of evaluation failure in traditional evaluation methods in practical engineering. Finally, the relative optimal dynamic performance of AGC units was discussed and the future trend of data-driven research in wind–thermal bundled power system was summarized.

关键词： Wind power prediction Automatic generation control Performance evaluation Data-driven Feature analysis

Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs

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Journal of Modern power Systems and Clean Energy 2024年第3期12卷 767-781页

作者： Dan Xu Zhi Cai Qian Cheng Guodong Huang Jingyang Zhou Junjie Tang Beijing Key Laboratory of Research and System Evaluation of power dispatching Automation Technology China Electric Power Research InstituteBeijing 100192China State Key Laboratory of power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqing 400044China

With the large-scale integration of renewable energy,the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy ***,in a market-oriented operation mode,the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power ***,a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed *** model is built on double-layer optimization framework,where the upper-layer model is used for maintenance and generation planning,and the lowerlayer model is primarily used to address the operational security risk arising from the random prediction error and N-1 transmission ***,a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution *** cost is determined using long-term security-constrained unit commitment,and the operational risk cost is obtained using a double-layer N-1 risk assessment *** electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously,thereby improving model convergence *** IEEE 118-bus system is used as a test case for illustration,and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.

关键词： Transmission maintenance security-constrained unit commitment iterative algorithm cost feedback N−1 risk assessment

Privacy-Preserving Consensus-Based Distributed Economic Dispatch of Smart grids via State Decomposition

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1250-1261页

作者： Wei Chen Guo-Ping Liu The authors are with the center for control Science and Technology Southern University of Science and TechnologyShenzhen 518055China

This paper studies the privacy-preserving distributed economic dispatch(DED)problem of smart *** autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both the islanded mode and the grid-connected mode of smart *** prevent power-sensitive information from being disclosed,a privacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts,where only partial data is *** objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical constraints while preventing sensitive information from being *** this end,a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation *** particular,the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected ***,rigorous analysis is given to show privacy-preserving performance against internal and external ***,case studies illustrate the feasibility and validity of the developed algorithm.

关键词： preserving autonomous mode

Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework

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CSEE Journal of power and Energy Systems 2024年第1期10卷 66-75页

作者： Lingkang Zeng Wei Yao Ze Hu Hang Shuai Zhouping Li Jinyu Wen Shijie Cheng State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronics EngineeringHuazhong University of Science and TechnologyWuhan 430074China dispatching and control center Central China Branch of State Grid Corporation of ChinaWuhan 430077China. Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN 37996USA

Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power *** improve efficiency of predetermination,this paper proposes a framework of knowledge fusion-based deep reinforcement learning(KF-DRL)for intelligent predetermination of ***,the Markov Decision Process(MDP)for GTS problem is formulated based on transient instability ***,linear action space is developed to reduce dimensionality of action space for multiple controllable ***,KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making *** can enhance the efficiency and learning ***,the graph convolutional network(GCN)is introduced to the policy network for enhanced learning *** simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.

关键词： Deep reinforcement learning generator tripping scheme graph convolutional network invalid action masking knowledgefusion

Embedded Scenario Clustering for Wind and Photovoltaic power,and Load Based on Multi-head Self-attention

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Protection and control of Modern power Systems 2024年第1期9卷 122-132页

作者： Lijun Liu Xin Hu Junsheng Chen Ruixing Wu Feixiong Chen School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108China State grid Fuzhou power Supply Company Fujian Smart Electrical Engineering Technology Research center

The source and load uncertainties arising from increased applications of renewable energy sources such as wind and photovoltaic energy in the power system have had adverse effects on optimal planning and *** for generating typical renewable energy and load scenarios are constructed to reduce such effects and improve the applicability of a planning and optimal dispatching model of power systems with a high proportion of renewable *** traditional clustering-based model for representing such scenarios cannot handle high-dimensional time-series data and consequently the feature-related information obtained cannot fully reflect the characteristics of the ***,a deep convolutional embedded clustering model based on multi-head self-attention is ***,a variational mode decomposition model is optimized to reduce the influence of noise-related signals on the feature *** deep features are then extracted from the data using an improved convolutional autoencoder,and the appropriate number of clusters is determined using the elbow *** this,the network parameters are optimized based on the sum of losses during reconstruction and ***,typical scenarios are then generated based on the optimized network ***,the proposed method is evaluated based on data visualization and evaluation *** is shown that the quality of features and the accuracy of clustering can be effectively improved by the proposed scenario generation method.

关键词： handle Embedded network