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Insight into the role of ethylene glycol on thermodynamics and nucleation kinetics of dimethyl terephthalate in mixed solvent system

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Particuology 2024年第2期85卷 1-12页

作者： Yujin zhang Chunyan Shi Jing Tang Li Liu dongxia Yan Qing Zhou Xingmei Lu Songyan Jia College of Chemical Engineering Shenyang University of Chemical TechnologyShenyang110142China Bejing Key Laboratoryoflonic Liquids Clean Process CAS Key LaboratoryofGreen Process and EngineeringState Key Laboratoryof Multiphase Complex SystemsInstitute of Process EngineeringChinese Academy of SciencesBeijing100190China School of Chemistry and Chemical Engineering Qingdao UniversityQingdao266071China Henan Institute of Advanced Technology Zhengzhou UniversityZhengzhou450001China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China

Dissolution and nucleation are two essential processes for industrial crystallization.This paper in-vestigates the effect of ethylene glycol addition on the crystallization behavior of dimethyl terephthalate(DMT)in solution.The DMT solubility in mixed solvent system(methanol-ethylene glycol)was deter-mined by isothermal satiation approach,and the solubility was associated using seven models.The model fitting results were consistent with the experimental values.Based on the results,the metastable zone width(MSZW)of DMT was detected by the polythermal approach;the modified Sangwal's theory was used to investigate the nucleation behavior,which can provide a new way of thought for better analysis of the crystallization behavior.The results demonstrated that MSZW was associated with various elements,such as cooling rate,saturation temperature and mass fraction of ethylene glycol.The addition of ethylene glycol slowed down the nucleation rate as shown by the broadening of MSZW.We derive the solid-liquid interface energy,the nucleation driving force,the critical nucleation size and the critical Gibbs free energy according to the classical nucleation theory.It is demonstrated that the nucleation driving force and the solid-liquid interface energy are dependent and jointly influence the MSZW.

关键词： Dissolution Nucleation Solubility Apparent thermodynamic parameters Metastable zone width Solid-liquid interface energy

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Hierarchical Multi-objective Planning for Integrated Energy Systems in Smart Parks Considering Operational Characteristics

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CSEE Journal of Power and Energy Systems 2022年第6期8卷 1760-1771页

作者： Weijie Dong Limei zhang dongxia zhang Quansheng Cui Beijing Information Science&Technology University Beijing 100044China Hebei Agricultural University Hebei 071001China China Electric Power Research Institute Beijing 100192China TBEA Technology&Investment Co. Ltd.Tianjin 301700China

An integrated energy system(IES)is considered to be an important supporting technology for emission reduction because it can effectively improve the efficiency of energy utilization and promote its sustainable development.Considering the uncertainties and operational conditions,this paper establishes a bilevel multi-objective optimization model for IES for the Smart Park from the standpoint of economy,technology and environment.The upper level with one objective reflects the economic cost composed of investment,operating and maintenance,etc.The lower level constructs three objectives,including pollution emission,operation costs and renewable energy utilization.Simultaneously,various equality and inequality constraints are addressed to satisfy the technical requirements.In addition,an improved MOEA/D-MC-DC algorithm(Multi Objective Evolutionary Algorithm through Decomposition Based on Monte Carlo and Decoupled Coding,MOEA/D-MC-DC)is presented for handling the complex and nonlinear bilevel multi-objective optimization problems with constraints.A genetic algorithm(GA)is used to solve the upper single objective,while MOEA is employed to cope with the multi-objectives of the lower level.Using three typical IESs in the Smart Park as examples,several simulations are carried out to verify the efficiency,applicability and universality of the proposed model and optimization algorithm.The results show that the proposed method can effectively optimize the configuration of an IES in various Smart Parks.

关键词： Integrated energy system bilevel multiobjective optimization configuration MOEA/D-CA-DC Smart Park

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Seismogenic Structure of the 1605 Qiongshan M7½ Earthquake and Its Holocene Activity History in Northern Hainan Island, China: Evidence from Cross-Section Drilling and Shallow Seismic Profile

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Journal of Earth Science 2024年第3期35卷 905-917页

作者： Chaoqun Wang Liyun Jia Daogong Hu Shibiao Bai Zhengwang Hu dongxia Sun Xiaoxiao Yang Lei zhang Xiumin Ma Institute of Geomechanics Chinese Academy of Geological SciencesBeijing 100081China Key Laboratory of Active Tectonics and Geological Safety Ministry of Natural ResourcesBeijing 100081China Key Laboratory of Geohazard Prevention of Hilly Mountains Ministry of Land and Resources(Fujian Key Laboratory of Geohazard Prevention)Fuzhou 350002China Observation and Research Station of Crustal Stress and Strain in Beijing Ministry of Natural ResourcesBeijing 100081China College of Marine Science and Engineering Nanjing Normal UniversityNanjing 210023China Hubei Subsurface Multi-Scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhan 430074China

The 1605 M7½ Earthquake is the only earthquake in the history of China that has caused large-scale land subsidence into the sea,with the total area of land subsidence exceeding 100 km2.The disaster has led to the sinking of 72 villages.There is still no clear understanding of the source seismogenic fault of this earthquake.In this work,we conducted a detailed study of the middle segment of the Maniao-Puqian fault(MPF),which is the epicenter area,through geomorphological survey,data collection,shallow seismic exploration,cross-section drilling,and chronological dating.The results showed that the middle segment of the MPF zone is composed of three nearly parallel normal faults with a dextral strike-slip:“Macun-Luodou fault(F2-1),Haixiu-Dongyuan fault(F2-2),and ChangliuZhuxihe fault(F2-3)”.And F2-2 is composed of two secondary faults,namely F2-2′and F2-2″,with a flower-shaped structure buried under the ground.It is distributed nearly east-west,dipping to the north and has experienced at least five stages of activities since the Miocene.The vertical activity rates of F2-2′and F2-2″are~2.32 and~2.5 mm/a,since the Holocene,respectively.There were eight cycles of transgression and regression since the Miocene.The fault activity resulted in the thickening of the Holocene strata with a slight dip to the south,on the hanging wall,showing V-shaped characteristics.The MPF is likely the source seismogenic fault of the M7½ earthquake that hit Qiongshan in 1605.

关键词： seismogenic structure earthquakes Maniao-Puqian fault fault activity history geomorphology.

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Circulating Current Suppression Method with Adaptive Virtual Impedance for Multi-bidirectional Power Converters Under Unbalanced Conditions

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 77-87页

作者： Baifu zhang Xiaoqing Han Chunguang Ren dongxia zhang Lei Wang Tianhao Song Taiyuan University of Technology Taiyuan030024 CHN

Multi-paralleled bidirectional power converters(BPCs)are commonly used to improve the power capacity and reliability in an AC/DC hybrid microgrid.However,circulating current through multi-BPCs has been one of the challenges and it can be aggravated in the presence of non-ideal operating conditions,such as unbalanced AC voltages,and the mismatch of hardware parameters.In order to suppress the circulating current,this paper proposes a distributed method based on adaptive virtual impedance,which also employs positive sequence power droop control and voltage deviation compensation control.The traditional positive sequence power droop control is adopted to only regulate the positive components of the BPCs output voltage.The negative sequence power term is fed to an adaptive virtual impedance generator to modify the damping characteristics of the BPCs.Also,an adaptive virtual impedance-based voltage deviation compensation method is proposed to recover the fluctuated output voltage of the BPCs due to droop action and the power fluctuations.The fully distributed regulation of adaptive virtual impedance enables the load power to be shared accurately among BPC modules and thus the circulating current can be effectively suppressed.The proposed control strategy does not require an additional communication system and the precise parameters of hardware equipment and line impedance.Furthermore,the effectiveness of the proposed method is verified by the experimental results.

关键词： Adaptive virtual impedance bidirectional power converters(BPCs) hybrid microgrid unbalance operation Circulating current

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Data-driven Decision-making Strategies for Electricity Retailers:A Deep Reinforcement Learning Approach

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CSEE Journal of Power and Energy Systems 2021年第2期7卷 358-367页

作者： Yuankun Liu dongxia zhang Hoay Beng Gooi Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Electric Power Research Institute Beijing 100192China Nanyang Technological University Nanyang AvenueSingapore 639798Singapore

With the continuous development of the electricity market,the electricity retailers,as the intermediaries between producers and consumers,have emerged in some of the liberalized electricity markets.Meanwhile,the electricity retailer faces many increasingly significant challenges from the complexities and uncertainties in both the supply and consumption sides.This paper applies a data-driven decision-making strategy via Advantage Actor-Critic(A2C)and Deep Q-Learning(DQN)for the electricity retailers.The retailers’profits and consumers’costs are both taken into account.This study verifies that the applied data-driven methods can handle the decision-making problem as well as promote the profitability of retailers in the electricity market.Furthermore,A2C is more appropriate than DQN in our simulation.The effectiveness of the applied data-driven methods is validated by using real-world data.

关键词： Artificial intelligence electricity market demand response smart grid

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Preventive Control for Power System Transient Security Based on XGBoost and DCOPF with Consideration of Model Interpretability

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CSEE Journal of Power and Energy Systems 2021年第2期7卷 279-294页

作者： Songtao zhang dongxia zhang Ji Qiao Xinying Wang Zhijian zhang China Electric Power Research Institute Beijing 100192China State Grid Beijing Electric Power Dispatching and Control Center Beijing 100031China

This paper proposes a new approach for online power system transient security assessment(TSA)and preventive control based on XGBoost and DC optimal power flow(DCOPF).The novelty of this proposal is that it applies the XGBoost and data selection method based on the 1-norm distance in local feature importance evaluation which can provide a certain model interpretability.The method of SMOTE+ENN is adopted for data rebalancing.The contingency-oriented XGBoost model is trained with databases generated by time domain simulations to represent the transient security constraint in the DCOPF model,which has a relatively fast speed of calculation.The transient security constrained generation rescheduling is implemented with the differential evolution algorithm,which is utilized to optimize the rescheduled generation in the preventive control.Feasibility and effectiveness of the proposed approach are demonstrated on an IEEE 39-bus test system and a 500-bus operational model for South Carolina,USA.

关键词： DC optimal power flow(DCOPF) model interpretability preventive control transient security assessment(TSA) XGBoost

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Deep Reinforcement Learning for Power System Applications: An Overview

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CSEE Journal of Power and Energy Systems 2020年第1期6卷 213-225页

作者： Zidong zhang dongxia zhang Robert C.Qiu Research Center For Big Data Engineering And Technologies Shanghai Jiao Tong UniversityShanghai 200240China Department of Electrical and Computer Engineering Tennessee Technological UniversityCookevilleTN 38505USA China Electric Power Research Institute Beijing 100192China

Due to increasing complexity, uncertainty and data dimensions in power systems, conventional methods often meet bottlenecks when attempting to solve decision and control prob- lems. Therefore, data-driven methods toward solving such prob- lems are being extensively studied. Deep reinforcement learning (DRL) is one of these data-driven methods and is regarded as real artificial intelligence (AI). DRL is a combination of deep learning (DL) and reinforcement learning (RL). This field of research has been applied to solve a wide range of complex sequential decision-making problems, including those in power systems. This paper firstly reviews the basic ideas, models, algorithms and techniques of DRL. Applications in power systems such as energy management, demand response, electricity market, operational control, and others are then considered. In addition, recent advances in DRL including the combination of RL with other classical methods, and the prospect and challenges of applications in power systems are also discussed.

关键词： Artificial intelligence deep reinforcement learning machine learning power system smart grids

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Optimization Strategy Based on Deep Reinforcement Learning for Home Energy Management

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CSEE Journal of Power and Energy Systems 2020年第3期6卷 572-582页

作者： Yuankun Liu dongxia zhang Hoay Beng Gooi China Electric Power Research Institute Beijing 100192China Nanyang Technological University Nanyang AvenueSingapore 639798Singapore

With the development of a smart grid and smart home,massive amounts of data can be made available,providing the basis for algorithm training in artificial intelligence applications.These continuous improving conditions are expected to enable the home energy management system(HEMS)to cope with the increasing complexities and uncertainties in the enduser side of the power grid system.In this paper,a home energy management optimization strategy is proposed based on deep Q-learning(DQN)and double deep Q-learning(DDQN)to perform scheduling of home energy appliances.The applied algorithms are model-free and can help the customers reduce electricity consumption by taking a series of actions in response to a dynamic environment.In the test,the DDQN is more appropriate for minimizing the cost in a HEMS compared to DQN.In the process of method implementation,the generalization and reward setting of the algorithms are discussed and analyzed in detail.The results of this method are compared with those of Particle Swarm Optimization(PSO)to validate the performance of the proposed algorithm.The effectiveness of applied data-driven methods is validated by using a real-world database combined with the household energy storage model.

关键词： Deep reinforcement learning demand response home energy management system smart grid

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基于改进长短期记忆网络的电力系统暂态稳定评估方法研究

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电网技术 2024年第3期48卷 998-1007页

作者：解治军张东霞韩肖清胡伟电力系统运行与控制山西省重点实验室(太原理工大学) 山西省太原市030024 中国电力科学研究院有限公司北京市海淀区100192 电力系统及发电设备控制和仿真国家重点实验室(清华大学电机工程与应用电子技术系) 北京市海淀区100084

现代电力系统海量量测数据为电力系统暂态稳定评估提供可靠的数据基础,与此同时,数据信息挖掘成为研究焦点,暂态稳定分析中不平衡故障样本以及多特征电气量时间序列数据中所蕴藏的信息仍有待深入挖掘。为此,该文提出一种结合注意力机制... 详细信息

现代电力系统海量量测数据为电力系统暂态稳定评估提供可靠的数据基础,与此同时,数据信息挖掘成为研究焦点,暂态稳定分析中不平衡故障样本以及多特征电气量时间序列数据中所蕴藏的信息仍有待深入挖掘。为此,该文提出一种结合注意力机制的长短期记忆网络(long short term memory network with attention,LSTMA)方法,用以深入挖掘暂态稳定评估样本中所蕴藏的信息。在离线训练环节,以长短期记忆网络为基础分类器,引入Attention注意力机制引导模型学习样本中关键特征,并对损失函数进行改进,以此强化对不平衡样本的学习能力;在线应用环节,在目标域小样本条件下采用迁移学习方法更新成型的离线LSTMA模型,并对比不同迁移学习策略对模型性能影响,经过迁移学习建立的新运行点下的改进LSTMA模型评估精度有效提高,训练时间大幅减少,所得出的迁移学习策略确定方法有利于实际应用环节快速决策。研究在IEEE39节点和IEEE300节点系统上进行实验,验证了所提方法的有效性。

关键词：暂态稳定评估长短期记忆网络注意力机制迁移学习不平衡样本

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Dynamic Capture Method for Out-of-step Center of Power Grid Based on Measurement Information

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CSEE Journal of Power and Energy Systems 2021年第6期7卷 1256-1266页

作者： Zonghan Li dongxia zhang Daowei Liu Shaobo Yang Gaoshang Zhao China Electric Power Research Institute Beijing 100192China the School of Electrical Engineering Northeast Electric Power UniversityJilin Province 132012China

This paper dynamically captures the out-of-step center for a bulk power system based on measurement information.First,the position characteristics of the out-of-step center are discussed from the perspective of triangular geometry under different potential and uniform impedance distributions based on a two-machine system.The correlation between the out-of-step center and the oscillation center is analyzed.Second,combined with analytical geometry,it is inferred that the distribution characteristics of the out-of-step center voltage vector ends are a circle or a straight line,and the position of the out-of-step center corresponds to the intersection between the voltage drop of the line and the distribution characteristics;then,the accurate location of the out-of-step center and the determination of the appearance moment is realized.Finally,a dynamic equivalence method for a power grid is proposed based on the electrical parameters of the transmission line,and an alternative iterative correction of equivalent parameters is carried out by trajectory sensitivity,which provides a new way for capturing the out-ofstep center dynamically in a multimachine system.The proposed method is validated using a three-machine system,the IEEE-39 system and the Northwest China Power Grid,and shows potential for online applications.

关键词： Dynamic equivalence geometric characteristics accurate location out-of-step center

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