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Research on Asymmetric Fault Location of Wind Farm Collection system Based on Compressed Sensing

energy Engineering 2023年第9期120卷 2029-2057页

作者： Huanan Yu Gang Han Hansong Luo He Wang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Qinhuangdao Power Supply Company State Grid Jibei Electric Power Co.Ltd.Qinhuangdao066099China

Aiming at the problem that most of the cables in the power collection systemof offshore wind farms are buried deep in the seabed,whichmakes it difficult to detect faults,this paper proposes a two-step fault location method based on compressed sensing and ranging *** first step is to determine the fault zone through compressed sensing,and improve the datameasurement,dictionary design and algorithmreconstruction:Firstly,the phase-locked loop trigonometric functionmethod is used to suppress the spike phenomenon when extracting the fault voltage,so that the extracted voltage valuewillnot have a large error due to the voltage ***,theλ-NIM dictionary is designed by using the node impedancematrix and the fault location coefficient to further reduce the influence of pseudo-fault ***,the CoSaMP algorithmis improved with the generalized Jaccard coefficient to improve the reconstruction *** second step is to use the ranging equation to accurately locate the asymmetric fault of the wind farm collection system on the basis of determining the fault *** simulation results show that the proposedmethod ismore accurate than the compressedsensingmethod andimpedancemethod in fault section location and fault location accuracy,the relative error is reduced from 0.75%to 0.4%,and has a certain anti-noise ability.

关键词： Offshore wind farm convergence system compression sensing ranging equation fault location

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Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

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energy Engineering 2024年第9期121卷 2655-2680页

作者： Jiaxin Qiao Yuchen Hao Yingqi Liao Fang Liang Jing Bian Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control&Renewable Energy TechnologyMinistry of EducationJilin132011China State Grid Jiangsu Electric Power Co. Ltd.Power Dispatch Control CenterNanjing210017China State Grid Jiangsu Electric Power Co. Ltd.Nanjing Power Supply BranchPower Dispatch Control CenterNanjing210019China

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution *** accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response ***,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation *** this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation ***,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within ***,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of *** model can provide scientific guidance for the economic dispatch of the distribution station ***,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of th

关键词： Distributed photovoltaic distribution station area assessment of adjustment capacity line transmission capacity economic optimization

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Dynamic Economic Scheduling with Self-Adaptive Uncertainty in Distribution Network Based on Deep Reinforcement Learning

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energy Engineering 2024年第6期121卷 1671-1695页

作者： Guanfu Wang Yudie Sun Jinling Li Yu Jiang Chunhui Li Huanan Yu He Wang Shiqiang Li State Grid Liaoning Electric Power Co. Ltd.Liaoyang Power Supply CompanyLiaoyang111000China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Jilin Northeast Electric Power University Science and Technology Development Co. Ltd.Jilin132012China

Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network ***, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.

关键词： Self-adaptive the uncertainty of sources and load deep reinforcement learning dynamic economic scheduling

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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

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Multi-Timescale Optimization Scheduling of Distribution Networks Based on the Uncertainty Intervals in Source-Load Forecasting

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energy Engineering: Journal of the Association of energy Engineering 2025年第6期122卷 2417-2448页

作者： Yu, Huanan Ye, Chunhe Li, Shiqiang Wang, He Bian, Jing Li, Jinling Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 China

With the increasing integration of large-scale distributed energy resources into the grid, traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load. Accounting for these issues, this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks. First, the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts, based on which, the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed. Subsequently, a multi-timescale optimization framework was constructed, incorporating the generation and load forecast uncertainties. This framework included optimization models for dayahead scheduling, intra-day optimization, and real-time adjustments, aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid. Furthermore, an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability. Utilizing a centralized training and decentralized execution framework, a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents. Finally, the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system. © 2025 The Authors. Published by Tech Science Press.

关键词： distribution networks flexible scheduling optimization model renewable energy soft actor-critic algorithm source-load uncertainty interval

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Short-Term Prediction of Wind Farm Cluster power Based on Load Risk Scenarios and Improved Weighted Loss During Peak and Valley Load Periods 7

Short-Term Prediction of Wind Farm Cluster Power Based on Lo...

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7th IEEE Conference on energy Internet and energy system Integration, EI2 2023

作者： Yang, Mao Guo, Yunfeng Wang, Bo Wang, Zhao Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China China Electric Power Research Institute National Key Laboratory of Renewable Energy Grid-Integration Beijing100192 China

ISBN: (纸本)9798350345094

Load peak and valley periods as the key scheduling scenarios, the effectiveness of wind power prediction becomes extremely important, in order to minimize the impact of wind power on the power system due to prediction errors, a short-term prediction method of wind farm cluster power considering risk scenarios and improved loss function is proposed. Firstly, the coupled correlation mechanism between meteorological type and load demand is explored, and the load risk scenario and meteorological correlation are derived. Second, according to the risk scenarios of load demand, the traditional loss function is improved and used to train the power prediction model under the risk scenarios. Then, a dynamic division strategy of wind farm clusters considering the meteorological similarity of the previous day is proposed to obtain the sub-clusters of similar output. Finally, the model with improved weighted loss function is used to predict the wind power for different regional sub-clusters and extended to wind farm clusters. The above method is validated using the wind farm clusters in West Inner Mongolia, China. and the results show that in the low-risk load scenario, the accuracy of the model with improved loss is higher, and the accuracy decreases with the increase of the load risk level, but the overall risk indexes are significantly lower than the method with traditional loss function, which proves the validity of the proposed method. © 2023 IEEE.

关键词： Risk assessment

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Optimal Scheduling of Integrated energy systems in Low-Carbon Communities Considering Flexibility of Resources and Segmental control of Solid Oxide Fuel Cells

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Journal of modern power systems and Clean energy 2025年第3期13卷 915-927页

作者： Yang, Mao Wang, Yuxin Wang, Jinxin Liu, Dongxu Xu, Weihang Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Jilin132012 China

To address the strong thermoelectric coupling of the combined heat and power (CHP) units, the low utilization rate of energy storage, and the underexploitation of load-side resource flexibility in integrated energy systems (lESs)., this paper proposes an optimal scheduling model of an IES in low-carbon communities considering flexibility of resources and the segmental control of solid oxide fuel cells (SOFCs). Firstly., by replacing the gas turbine (GT) in the CHP unit with an SOFC array to reduce carbon emissions and simultaneously weakening the thermoelectric coupling of the CHP unit, the segmental control method is used to control the SOFC array to improve the overall efficiency of the CHP unit. Secondly, coupled interactions among different types of energy storage equipments are mobilized through the integrated energy storage system to make full use of the remaining space in the heat and natural gas storage tanks. Finally, load-side flexible resources are utilized by considering transferable, substitutable, and heat loads, taking into account the thermal inertia of the building and categorizing rooms based on floors, orientations, and room area. Additionally., different user characteristics are characterized, and the flexible resources of building heating periods in northern cities in China are tapped in depth according to the actual factors. Compared with the traditional model, the optimal scheduling model proposed in this paper can reduce the wind abandonment rate and the carbon emission of community-integrated energy system (CIES) by 4.54% and 70.63%, respectively, and increase the utilization rate of heat and natural gas storage tanks by 12.34 % and 30.52%., respectively, and lower the total cost by ¥2183.6 under the premise of ensuring user comfort during energy consumption, which promotes the economic and low-carbon operation of the CIES. © 2013 State Grid Electric power Research Institute.

关键词： energy utilization

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Optimal Scheduling of Pumped Storage power Station with Double-Fed Variable Speed Unit Based on Reservoir Regional Operation Strategy 4

Optimal Scheduling of Pumped Storage Power Station with Doub...

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4th Asia-Pacific Conference on Communications technology and Computer Science, ACCTCS 2024

作者： Ma, Yuhan An, Yining Ge, Xiaohui Zhao, Bo State Grid Zhejiang Electric Power Co. Ltd. Research Institute Zhejiang Hangzhou China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin Jilin China

ISBN: (纸本)9798350359985

The conventional pumping unit lacks the ability to continuously adjust input power during pumping operations, and exhibits poor adaptability when integrating new energy sources into the grid. In this study, we propose a novel 'domain operation' strategy that allocates resources based on real-time reservoir conditions across all levels of hydropower stations, while optimizing operations through the implementation of doubly fed units. © 2024 IEEE.

关键词： Hydroelectric power

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Real-time Optimal energy Management of Combined Cooling, Heating and power systems Based on Knowledge conlusion 6

Real-time Optimal Energy Management of Combined Cooling, Hea...

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6th IEEE International Electrical and energy Conference, CIEEC 2023

作者： He, Chunjiang Wang, Yijian Xu, Yang Cui, Yang China Electric Power Research Institute State Key Laboratory of Power Grid Security and Energy Conservation Beijing China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9798350346671

Combined Cooling, Heating and power(CCHP) system is an important way to improve the efficiency of energy utilization and wind power consumption. In this case, increasing the operational flexibility of CCHP systems can help increase renewable energy consumption and reduce carbon emissions. So, it is necessary to provide real-time optimal energy management(OEM) for CCHP systems. In this paper. Firstly, a new training method is proposed for the LightGBM to improve the accuracy of real-time wind power prediction. In addition, to solve the nonlinear OEM of CCHP in real-time, a novel deep reinforcement learning algorithm-Soft Actor-Critic, is used in this paper. By combining the mechanism of CCHP with the reward function through knowledge fusion, the non-convex models can be translated into Markov Decision Processes(MDP), and then according to the Bellman optimal equation, the real-time optimized operation of the CCHP system is realized. Finally, the effectiveness of the proposed policy is verified by the actual operation data of a CCHP system in Northwest China. © 2023 IEEE.

关键词： Reinforcement learning

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A Disturbance Localization Method for power system Based on Group Sparse Representation and Entropy Weight Method

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energy Engineering 2024年第8期121卷 2275-2291页

作者： Zeyi Wang Mingxi Jiao Daliang Wang Minxu Liu Minglei Jiang He Wang Shiqiang Li Changchun Power Supply Company State Grid Jilin Electric Power Co.Ltd.Changchun130021China Economic and Technical Research Institute State Grid Jilin Electric Power Co.Ltd.Changchun130022China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Northeast Electric Power UniversityJilin132012China

This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight *** different electrical quantities are selected as observations in the compressed sensing *** entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance ***,by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,an improved Joint Generalized Orthogonal Matching Pursuit(J-GOMP)algorithm is utilized for *** reconstructed sparse vectors are divided into three *** at least two parts have consistent node identifiers,the node is identified as the disturbance *** the node identifiers in all three parts are inconsistent,further analysis is conducted considering the weights to determine the disturbance *** results based on the IEEE 39-bus system model demonstrate that the proposed method,utilizing electrical quantity information from only 8 measurement points,effectively locates disturbance positions and is applicable to various disturbance types with strong noise resistance.

关键词： Disturbance location compressed sensing group sparse representation entropy power method GOMP algorithm

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