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

作者： Zhang, Shan Han, Xiaoqing Li, Tingjun Yin, Zehua Taiyuan University of Technology Shanxi Key Laboratory of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350345094

Aiming at the problems that the traditional centralized operation mode cannot meet the demands of individual interests in the interconnected electric heating system, and the randomness and volatility of new energy bring uncertainty to the operation of the interconnected electric heating system, a distributed and coordinated operation mechanism of the interconnected electric heating system based on multi-agent P2P transactions is proposed. Firstly, in order to deal with the uncertainty of new energy, a robust day-ahead scheduling model considering unexpected constraints is established in the day-ahead stage. In the real-time stage, a real-time scheduling model based on P2P transactions is proposed, and distributed algorithms are adopted to solve the proposed model. Finally, an interconnected system composed of 3 electric heating systems is used for testing and analysis. The results show that the proposed operation model based on P2P transaction can reduce the total operation cost of the interconnected electric heating system. © 2023 IEEE.

关键词： Multi agent systems

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A data selection method for matrix effects and uncertainty reduction for laser-induced breakdown spectroscopy

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Plasma Science and Technology 2023年第7期25卷 82-89页

作者：龙杰宋惟然侯宗余王哲 State Key Laboratory of Power System Operation and Control Systems International Joint Laboratory on Low Carbon Clean Energy InnovationDepartment of Energy and Power EngineeringTsinghua UniversityBeijing 100084People’s Republic of China Shanxi Research Institute for Clean Energy Tsinghua UniversityTaiyuan 030032People’s Republic of China

Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal *** selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification *** applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,*** results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.

关键词： laser-induced breakdown spectroscopy(LIBS) quantification uncertainty univariate/multivariate analysis matrix effects temperature matching

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Pathway Planning of Nuclear power Development Incorporating Assessment of Nuclear Event Risk

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Journal of Modern power systems and Clean Energy 2024年第2期12卷 500-513页

作者： Xinxin Yang Yusheng Xue Bin Cai School of Electrical Engineering Southeast UniversityNanjingChinaand they are also with State Grid Electric Power Research Institute(NARI Group Corporation)NanjingChina State Key Laboratory of Smart Grid Protection and Operation Control NanjingChina State Grid Electric Power Research Institute(NARI Group Corporation) NanjingChina

The nuclear event risk(NER)is an important and disputed factor that should be reasonably considered when planning the pathway of nuclear power development(NPD)to assess the benefits and risks of developing nuclear power more *** paper aims to explore the impact of nuclear events on NPD pathway *** influence of nuclear events is quantified as a monetary risk component,and an optimization model that incorporates the NER in the objective function is *** optimize the pathway of NPD in the lowcarbon transition course of power supply structure evolution,a simulation model is built to deduce alternative NPD pathways and corresponding power supply evolution scenarios under the constraint of an exogenously assigned carbon emission pathway(CEP);moreover,a method is proposed to describe the CEP by superimposing the maximum carbon emission space and each carbon emission reduction(CER)component,and various CER components are clustered considering the emission reduction characteristics and resource endowments of different power generation technologies.A case study is conducted to explore the impact of NER and its risk valuation uncertainty on NPD pathway *** method presented in this paper allows the impact of nuclear events on NPD pathway planning to be quantified and improves the level of coordinated optimization of benefits and risks.

关键词： Low-carbon transition power supply structure evolution nuclear power development(NPD) quantitative analysis nuclear event risk evaluation

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operation Strategy of Rail Transit Green Energy system Considering Uncertainty Risk of Photovoltaic power Output

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Journal of Modern power systems and Clean Energy 2024年第6期12卷 1859-1868页

作者： Yanbo Chen Haoxin Tian Guodong Zheng Yuxiang Liu Maja Grbic State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBejing 102206China School of Engineering Qinghai University of TechnologyXining 810016China New Energy(Photovoltaic)Industry Research Center and the Key Laboratory for Smart Operation of New Energy Power System of the Ministry of Education Qinghai UniversityXining 810016China Nikola Tesla Electrical Engineering Institute University of BelgradeBelgrade 11000Serbia

The integration of photovoltaic power generation is a new development into the traction power supply system(TPSS). However, traditional research on the TPSS operation strategy has not fully considered the risk of uncertainty in photovoltaic power output. To this end, we propose an operation strategy for the rail transit green energy system that considers the uncertainty risk of photovoltaic power output. First, we establish a regenerative braking energy utilization model that considers the impact of time-of-use(TOU) electricity price on the utilization efficiency and economic profit of regenerative braking energy and compensates for non-traction load. Then, we propose an operation strategy based on the balance of power supply and demand that uses an improved light robust(ILR) model to minimize the total cost of the rail transit green energy system, considering the risk of uncertainty in photovoltaic power output. The model incorporates the two-step load check on the second-level time scale to correct the operational results, solve the issue of different time resolutions between photovoltaic power and traction load, and achieve the coordinated optimization of risk cost and operation cost after photovoltaic integration. Case studies demonstrate that the proposed model can effectively consider the impact of the uncertainty in photovoltaic power output on the operation strategy, significantly improving the efficiency and economy of the system operation.

关键词： Rail transit green energy system improved light robust(ILR)optimization two-step load check time resolution operation strategy

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Numerical Simulation of Streamer Discharge in Transformer Oil Under Various Ionization Energies 19th

Numerical Simulation of Streamer Discharge in Transformer Oi...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Bao, Yanyan Liang, Shaobin Wang, Feng Zhang, Guangdong Chen, Jianning Zhou, Yuanxiang State Grid Gansu Electric Power Research Institute Lanzhou730070 China State Key Laboratory of Power System Operation and Control Beijing100084 China Department of Electrical Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9789819613786

Discharge in transformer oil is one of the primary causes of transformer failures. The physical mechanisms of oil discharges are not yet fully understood. Scholars have simulated the discharge process with electrodynamics model, but there is limited research on how the ionization energy, which changes due to various factors such as components and temperature of transformer oil, affect the streamer discharge characteristic. To improve the mechanism of discharge in transformer oil, this paper adopts an electrohydrodynamic model to study the impact of different ionization energies on the streamer discharge characteristics of transformer oil, including initiation voltage, discharge voltage, development speed, and electric field strength. When the ionization energy is between 6.1 eV and 8.1 eV, the initiation voltage and discharge voltage increase linearly with the ionization energy. Within the range of 7.1 eV to 8.1 eV, the time in the streamer accumulation phase increases exponentially with the ionization energy, while the streamer development speed decreases. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electrohydrodynamics

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Feasibility study of renewable e-methanol production:A substitution pathway from blue to green

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iEnergy 2024年第2期3卷 108-114页

作者： Peiyang Li Jin Lin Zhipeng Yu Yingtian Chi Kai Zhao State Key Laboratory of Power System Operation and Control Department of Electrical EngineeringTsinghua UniversityBeijing 100087China Tsinghua-Sichuan Energy Internet Research Institute Chengdu 610213China Beijing Representative Office of Methanol Institute Beijing 100020China

Producing renewable e-methanol from e-hydrogen and diverse carbon sources is an essential way for clean methanol *** this,the technical and economic feasibility of different e-methanols has yet to be thoroughly compared,leaving the most promising pathway to achieve commercialization yet *** paper reports a preliminary analysis of the lifecycle greenhouse gas(GHG)emissions and costs of four renewable e-methanols with different carbon sources:bio-carbon,direct air capture(DAC),fossil fuel carbon capture(FFCC),and *** results indicate that renewable e-methanol costs(4167−10250 CNY/tonne)2−4 times the market rate of grey ***,with the carbon tax and the projected decline in e-H2 costs,blue e-methanol may initially replace diesel in inland navigation,followed by a shift from heavy fuel oil(HFO)to green e-methanol in ocean ***,the e-H2 cost and the availability of green carbon are vital factors affecting cost-effectiveness.A reduction in e-H2 cost from 2.1 CNY/Nm3 to 1.1 CNY/Nm3 resulting from a transition from an annual to a daily scheduling period,could lower e-methanol costs by 1200 to 2100 *** paper also provides an in-depth discussion on the challenges and opportunities associated with the various green carbon sources.

关键词： Renewable energy e-methanol e-hydrogen green carbon source chemical process flexibility

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Improved Proximal Policy Optimization Algorithm for Sequential Security-constrained Optimal power Flow Based on Expert Knowledge and Safety Layer

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Journal of Modern power systems and Clean Energy 2024年第3期12卷 742-753页

作者： Yanbo Chen Qintao Du Honghai Liu Liangcheng Cheng Muhammad Shahzad Younis State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources and School of Electrical&Electronic Engineering North China Electric Power UniversityBeijing 102206China School of Engineering Xining UniversityXining 810008Chinaand Key Laboratory of Smart Operation of New Energy Power SystemMinistry of EducationQinghai UniversityXining 810016China China Electric Power Research Institute Nanjing 210003China National University of Sciences and Technology Islamabad44000Pakistan

In recent years,reinforcement learning(RL)has emerged as a solution for model-free dynamic programming problem that cannot be effectively solved by traditional optimization *** has gradually been applied in the fields such as economic dispatch of power systems due to its strong selflearning and self-optimizing ***,existing economic scheduling methods based on RL ignore security risks that the agent may bring during exploration,which poses a risk of issuing instructions that threaten the safe operation of power ***,we propose an improved proximal policy optimization algorithm for sequential security-constrained optimal power flow(SCOPF)based on expert knowledge and safety layer to determine active power dispatch strategy,voltage optimization scheme of the units,and charging/discharging dispatch of energy storage *** expert experience is introduced to improve the ability to enforce constraints such as power balance in training process while guiding agent to effectively improve the utilization rate of renewable ***,to avoid line overload,we add a safety layer at the end of the policy network by introducing transmission constraints to avoid dangerous actions and tackle sequential SCOPF *** results on an improved IEEE 118-bus system verify the effectiveness of the proposed algorithm.

关键词： Sequential security-constrained optimal power flow(SCOPF) expert experience safety layer renewable energy safe reinforcement learning

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Numerical study of a trapezoidal bypass dual throat nozzle

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Chinese Journal of Aeronautics 2023年第3期36卷 42-62页

作者： Shuai HUANG Jinglei XU Kaikai YU Yangsheng WANG Ruifeng PAN Kuangshi CHEN Yuqi ZHANG State Key Laboratory of Mechanics and Control of Aeronautics and Astronautics Structures Nanjing 210016China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Jiangsu Province Key Laboratory of Aerospace Power System Nanjing 210016China

Bypass Dual Throat Nozzle(BDTN)is a novel type of fluidic thrust vectoring *** improve the infrared stealth performance of BDTN,a nozzle based on BDTN is proposed and numerically *** cross-section along the x-axis of the novel nozzle becomes a trapezoid,which is named“BDTN-TRA.”The main numerical simulation results show that BDTN-TRA can produce a thrust vectoring angle when the upper or lower bypass valve is *** angle difference between the two conditions mentioned above is usually approximately 1°-2°.Even if the two bypasses are closed,BDTN-TRA can produce a small thrust vectoring angle at around 3°-5°.When the sidewall angle increases from 60°to 90°,the thrust coefficient and thrust vectoring angle under each work condition usually decrease.A larger aspect ratio indicates better *** the aspect ratio increases over 7.2,the performance of BDTN-TRA is quite close to that of BDTN with rectangular cross-sections at the same aspect *** features will benefit the control and trimming for future aircraft design,especially for the flying wing layout *** but not least,BDTN-TRA has a more extraordinary mixing performance compared with *** distributions of static temperature and axial velocity along the x-axis of BDTN-TRA with sidewall angle of 60°decrease faster than those of *** the total temperature of the inlet equals 1600 K,the static temperature difference between BDTN-TRA with sidewall angles of 60°and 90°is over 360 K at twice the length of the nozzle downstream of the nozzle exit,which is the reflection for excellent infrared stealth for the fighter.

关键词： Bypass dual throat nozzle Infrared stealth performance Mixing performance Trapezoidal cross-sections Thrust vectoring

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Effect of Photoionization Mechanism on Numerical Simulation of Transformer Oil Streamer Discharge 19th

Effect of Photoionization Mechanism on Numerical Simulation ...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Liang, Shaobin Zhou, Yuanxiang Chen, Jianning He, Zhiyang Li, Yuhang School of Electrical Engineering Xinjiang University Urumqi China State Key Laboratory of Power System Operation and Control Beijing China Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9789819613861

Discharge in transformer oil is one of the primary causes of transformer failures. The physical mechanisms of oil discharges are not yet fully understood. However, the prevailing electrohydrodynamics models primarily adopt field ionization and collision ionization, neglecting photoionization, which could potentially affect the discharge of liquid dielectric streamers. To reveal the discharge characteristics of transformer oil, this paper improves the field ionization term in electrohydrodynamics model, establishes a function of the ionization energy of transformer oil in relation to the recombination strength of carriers, and proposes a simulation model of streamer discharge in oil considering photoionization. The effects of photoionization on the characteristics of streamer discharge in transformer oil are studied, by examining the morphology and propagation velocity of streamers. The results show that the introduction of the photoionization mechanism promotes the formation of streamer branches and makes the energy in the streamer channel more concentrated. Moreover, photoionization facilitates the rapid propagation of streamers, which is key to the formation of the third mode of streamers. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electrohydrodynamics

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Preventive control Methods for power systems Based on Improved Deep Reinforcement Learning 6

Preventive Control Methods for Power Systems Based on Improv...

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6th International Conference on power and Energy Technology, ICPET 2024

作者： Zhang, Jie Zhu, Yihua Liang, Zhuohang Zhang, Qingqing Ma, Qinfeng Liu, Mingshun An, Su Dai, Jiang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd Guiyang China

ISBN: (纸本)9798350375855

Convergence speed, accuracy, generalization and decision transparency are very important indices for transient stability preventive control generation methods based on AI. This paper proposes a transient stability preventive control generation method based on graph deep reinforcement learning and its interpretation method using mutual information optimization. Firstly, a transient stability preventive control generation model is built based on the framework of deep reinforcement learning algorithm. The grid domain buses are mapped to the graph domain nodes and the grid graph data samples are generated. The graph convolutional neural network via initial residual and identity mapping (GCNII) is used to build the action network and the evaluation network. Secondly, based on the GCNII network, a transient stability assessment model is built and pre-trained, and graph data samples containing varies of topological structures and power flow states are applied to train the model. Then the interpretation method based on mutual information optimization is used to analyze the decision-making basis of the transient stability assessment model. The dominant factor affecting the transient instability of power system is extracted and its contribution degree is quantified, and the abduction analysis of transient stability is realized. Finally, the pre-trained transient stability assessment model is embedded in the deep reinforcement learning framework as a guide, and the power flow adjustment method is used to preferentially correct the weak factors and their influencing factors so that the transient stability prevention control strategies are obtained. The feasibility and effectiveness of the proposed method are verified in the IEEE-39 node test system. © 2024 IEEE.

关键词： Transient stability

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