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4th International Conference on intelligent Power and Systems, ICIPS 2024

作者： Zhu, Yuanzhen Wei, Xinyu Li, Tianshu Chen, Yiheng Zhou, Ning Fang, Qiao Zhao, Kang Sun, Runjia State Grid Shandong Electric Power Company Electric Power Science Research Institute Shandong Smart Grid Technology Innovation Center Jinan China Key Laboratory of Power System Intelligent Dispatch and Control The Ministry of Education Jinan China

ISBN: (纸本)9798331532765

Energy storage station (ESS) and wind farm (WF) have the potential to serve as a black-start sources to accelerate the power system restoration after blackout. However, the voltage security problem when start the auxiliary machines of power plants limit their reliability as black-start sources. A voltage control method is proposed for ESS and WF combined black-start sources to improve the voltage security during black-start. Firstly, the black-start process based on grid-forming ESS and WF is presented, and the voltage control framework is established. Then, a predictive control method considering the impact of active power on voltage variations is proposed, in which different optimization modes are established to obtain the active and reactive control sequences for WF and ESS. Finally, black-start simulation with Matlab/Simulink demonstrate the proposed method can improve the voltage security level when starting auxiliary machines of power plants. © 2024 IEEE.

关键词： Predictive control systems

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Resilience Assessment of Distributed Distribution Networks Taking into Account Sudden Natural Conditions 25

Resilience Assessment of Distributed Distribution Networks T...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Song, Huayu Kong, Xiangyu Liu, Jiancun Song, Xudong Yang, Wenlong Liu, Hongbin Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin China Tianjin Universityy Key Laboratory of Smart Grid Ministry of Education Tianjin China Electric Power Scientific Research Institute of Guangdong Power Grid Co. Guangzhou China

ISBN: (纸本)9798350366600

Understanding and improving the reliability of distribution grids under extreme weather conditions in the context of global climate change is important for ensuring stable socio-economic operation and improving the quality of life of the public. The current global assessment of distribution grid reliability under extreme weather conditions faces challenges such as insufficient data, modeling limitations, insufficient consideration of multidimensional impacts, technical resource constraints, and global change uncertainty. Through this paper, we hope to provide new perspectives and ideas for power system researchers and practitioners to jointly explore effective strategies for distribution network reliability and resilience under extreme weather. This study enhances the resilience assessment of distribution networks. It takes into account the generation and consumption dynamics of the network, the unpredictability of power supply and demand, as well as the impact of network topology and equipment on its reliability, and utilizes the Markov process to perform comprehensive reliability analysis of the network. In terms of assessment techniques, the Monte Carlo simulation method simulates the stochastic nature of severe weather, including its severity, timing, and duration, while quantifying its impact on the network through fault modeling. In terms of assessment metrics, the network is divided into two phases in order to establish a precise and clear system of network resilience assessment metrics. Through literature review, modeling analysis, and actual case studies, the current status of distributed generation application in extreme weather is explored, its impact on distribution network reliability is assessed, and future research directions and practical suggestions are proposed. © 2024 IEEE.

关键词： Power distribution networks

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Virtual Power Plant Optimization Scheduling Considering Large-Scale New Energy Connected to the grid 25

Virtual Power Plant Optimization Scheduling Considering Larg...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Zhao, Zhiyuan Kong, Xiangyu Zhang, Delong Zhang, Peirong Zhu, Jingkai Zheng, Qingrong Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin China Tianjin University Key Laboratory of Smart Grid of Ministry of Education Tianjin China Shanghai Municipal Electric Power Company Shanghai China

ISBN: (纸本)9798350366600

In the context of the current 'dual-carbon' strategy, large-scale acquisition of new energy sources will greatly impact the actual power grid due to the intermittent and uncertain nature of wind and solar energy. This paper proposed a virtual power plant (VPP) optimization scheduling considering large-scale new energy connected to the power grid. Firstly, an optimal scheduling scheme for real-time balancing of VPP is established. Then, considering the power deviation compensation mechanism with the objective function of maximizing the expected net profit of the VPPs, an optimal scheduling method is obtained, which deals with the uncertainties brought by new energy and reduces the cost of deviation penalties. The proposed method reduces the bidding deviation penalties by considering the compensation mechanism for the intra-day deviation. The example results show that the model proposed in this paper improves the expected profit of the virtual power plant to a certain extent. © 2024 IEEE.

关键词： new energy sources optimal scheduling virtual power plant

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Load Flexibility Evaluation Method for Industrial Parks Based on SPA and TOPSIS 25

Load Flexibility Evaluation Method for Industrial Parks Base...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Wang, Yubo Kong, Xiangyu Wang, Yang Zhang, Haixuan Wu, Shunyu Luo, Shuai Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin China Tianjin University Key Laboratory of Smart Grid Tianjin China State Grid Tianjin Electric Power Company Tianjin China Economic and Technological Research Institute State Grid Tianjin Electric Power Company Tianjin China

ISBN: (纸本)9798350366600

With the requirement for an increased share of renewable energy, park load flexibility is needed to balance fluctuations between supply and demand. The factors affecting the load flexibility of the park are analyzed from four dimensions: high quality, high efficiency, security, and low carbon. The index system for evaluating the load flexibility of the park is constructed. Given the relevance of the load flexibility assessment indexes of the park, the grey entropy algorithm is improved, and the combined assignment method is proposed to enhance the assignment of the indexes' weights. The quantitative assessment method of park flexibility is proposed based on the coupling of SPA (Set Pair Analysis) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The simulation shows that this method can solve the shortcomings of traditional TOPSIS well and make the quantitative assessment results of park load flexibility more accurate, which can be a guide for evaluating the flexibility of other urban industrial parks. © 2024 IEEE.

关键词： evaluation indicators grey correlation analysis park load TOPSIS

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Day ahead load forecasting of integrated energy system based on multi-model combination

Day ahead load forecasting of integrated energy system based...

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2021 International Conference on Computer Application and Information Security, ICCAIS 2021

作者： Ye, Jianhua Luo, Fengzhang Cao, Jing Yang, Li Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education Tianjin300222 China Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin300072 China State Grid Tianjin Electric Power Company Tianjin300010 China State Grid Chongqing Yongchuan Power Supply Company Chongqing402160 China

ISBN: (纸本)9781510655218

The load of user level integrated energy system changes rapidly and it is difficult to predict accurately. Therefore, a day ahead load forecasting method of integrated energy system based on multi-model combination was proposed. Firstly, the long short-term memory (LSTM) network model, convolutional neural network (CNN) model and harmony search (HS) optimized light gradient boosting machine (LightGBM) model were established. Then, the inverse root mean square error method (IRMSE) was used to combine the forecasting results of the three models to obtain the final forecasting value. The effectiveness of the proposed method was verified by the actual data of an integrated energy system. The results show that the proposed method is superior to the single prediction model and the simple average combination model, and has the best prediction accuracy for electric, cooling and heat loads. © The Authors.

关键词： Long short-term memory

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Electricity and Heat Load Forecasting for Integrated Energy System Based on Variational Modal Decomposition and Deep Neural Networks 4

Electricity and Heat Load Forecasting for Integrated Energy ...

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4th International Conference on Electrical Engineering and control Science, IC2ECS 2024

作者： Hu, Shuibin Kong, Xiangyu Zhang, Delong Li, Dahua Huo, Xianxu Pang, Chao Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin China Tianjin University Key Laboratory of Smart Grid of Ministry of Education Tianjin China Electric Power Research Institute Tianjin Electric Power Company Tianjin China

ISBN: (纸本)9798331510107

Load forecasting is crucial for the optimal scheduling of integrated energy systems(IES). With the increasing complexity of system load due to demand diversification and load coupling, this paper proposes a method for electricity and heat load forecasting based on Variational Mode Decomposition(VMD) and Deep Neural Networks. First, VMD decomposes the loads into components with different central frequencies, providing more stable load eigenmode functions. Then, a hybrid model combining Convolutional Neural Networks(CNN) and Long Short-Term Memory networks(LSTM) is used to extract time-series features, with parameter optimization performed using the Salp Swarm Algorithm(SSA). A case study of a real IES demonstrates the model's superior predictive performance. © 2024 IEEE.

关键词： Variational mode decomposition

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Advanced control strategy of SVC based on artificial immune algorithm

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Journal of Computational Information Systems 2015年第6期11卷 1965-1972页

作者： Chen, Saisai Li, Kejun Jing, Ping Zha, Guoliang Tian, Xin Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Smart Grid Research Institute of State-Grid Changping District Beijing China

For the conventional Static Var Compensator (SVC), there is a contradiction between the response time and system stability. An advanced control strategy is proposed in this paper. Improved Proportional Integral (PI) controller and Artificial Immune Algorithm are adopted in SVC control system, with the response speed of SVC as objective function of optimization. Meanwhile, a non-linear link is added to ensure the stability of the system. The non-linear link is proved that it can significantly improve the stability of the nonlinear system. Simulation results show that the new SVC control strategy can not only track the set voltage value of SVC quickly, but also comprehensively compensate for reactive power and three-phase imbalance. Copyright © 2015 Binary Information Press.

关键词： Static Var compensators

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Effect of long-term fluorination on surface electrical performance of ethylene propylene rubber

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High Voltage 2019年第4期4卷 339-344页

作者： Rujia Men Zhipeng Lei Tao Han Davide Fabiani Chuanyang Li Simone Vincenzo Suraci Jian Wang Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control College of Electrical and Power EngineeringTaiyuan University of TechnologyTaiyuan 030024People's Republic of China Department of Electrical Electronicand Information Engineering‘Guglielmo Marconi’University of BolognaViale Risorgimento 2Bologna 40136Italy Key Laboratory of Smart Grid of Education Ministry School of Electrical and Information Engineering Tianjin UniversityTianjin 300072People's Republic of China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityChangping DistrictBeijing 102206People's Republic of China

To investigate the effect of fluorination on surface electrical performance of ethylene propylene rubber(EPR),four pieces of EPR specimens are prepared and fluorinated for different duration ranging from 120 min to 480 *** surface morphology and element compositions of experimental specimens are *** surface potential decay and complex permittivity are *** tracking discharge property and the erosion properties after tracking test are *** surface charge transport and electrical property tailoring mechanism are *** results show that when the fluorination duration is from 120 min to 360 min,the surface morphology gradually becomes flat and compact with time,and the surface resistance to electrical tracking is *** an excessive fluorination with the duration of 480 min leads to a significant increase in surface conductivity and a weakening in the resistance to electrical tracking,which is mainly due to a change in surface *** recommended fluorination duration for an optimised surface property is between 240 and 360 min for EPR specimen.

关键词： electrical propylene rubber

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Voltage control Method for Offshore Floating Photovoltaic Storage Hydrogen Production DC System

Voltage Control Method for Offshore Floating Photovoltaic St...

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System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Hongbin Liu Xiangyu Kong Delong Zhang Chunjie Wang Hui Jin Yangping Shao Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin China Key Laboratory of Smart Grid Tianjin University Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

To address the problems of high PV output volatility and unstable DC system voltage control caused by environmental influences on offshore floating photovoltaic hydrogen production systems, this paper proposes a voltage control method based on voltage stabilization for the DC system model of PV storage hydrogen production. Aiming to improve PV power generation quality and enhance system stability, this control method includes maximum power point tracking (MPPT) control for the floating PV system and adaptive coordinated control for the hydrogen storage system. These controls enable the optimal utilization of light resources while ensuring stable bus voltage. Finally, the effectiveness of the control method was verified by simulation.

关键词： Photovoltaic systems Maximum power point trackers Adaptation models Hydrogen storage Adaptive systems Hydrogen control systems Stability analysis Systems simulation Voltage control

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Optimal Scheduling of Provincial local Coordinated Based on Source-grid-load-storage Interactions

Optimal Scheduling of Provincial local Coordinated Based on ...

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System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Haixuan Zhang Xiangyu Kong Delong Zhang Jiancun Liu Xuesong Zhou Mao Liu Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin China Key Laboratory of Smart Grid Tianjin University Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

Considering the characteristics of coordination among source-network-load-storage, a provincial local coordinated scheduling method based on the interaction of sourcenetwork-load-storage is proposed. Firstly, the interaction mechanism of source-grid-load-storage is refined. Secondly, according to the spatial characteristics of the scheduling of provincial local coordinated, a multi-objective optimal scheduling model is established with the objectives of economy and new energy consumption. Thirdly, a genetic algorithm is used to solve the problem. Finally, by analyzing the examples, it is proved that the proposed method can reduce the system cost and improve the utilization rate of new energy.

关键词： Energy consumption Costs Optimal scheduling Systems simulation Genetic algorithms

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