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Deep Reinforcement Learning Based Real-time AC Optimal Power Flow Considering Uncertainties

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Journal of Modern Power Systems and Clean Energy 2022年第5期10卷 1098-1109页

作者： Yuhao Zhou wei-jen lee Ruisheng Diao Di Shi IEEE Energy Systems Research Center in the Electrical Engineering Department University of Texasat ArlingtonArlington TX76019USA AI&System Analytics Groupat GEIRINA San JoseCA95134USA

Modern power systems are experiencing larger fluctuations and more uncertainties caused by increased penetration of renewable energy sources(RESs) and power electronics equipment. Therefore, fast and accurate corrective control actions in real time are needed to ensure the system security and economics. This paper presents a novel method to derive realtime alternating current(AC) optimal power flow(OPF) solutions considering the uncertainties including varying renewable energy and topology changes by using state-of-the-art deep reinforcement learning(DRL) algorithm, which can effectively assist grid operators in making rapid and effective real-time decisions. The presented DRL-based approach first adopts a supervised-learning method from deep learning to generate good initial weights for neural networks, and then the proximal policy optimization(PPO) algorithm is applied to train and test the artificial intelligence(AI) agents for stable and robust performance. An ancillary classifier is designed to identify the feasibility of the AC OPF problem. Case studies conducted on the Illinois 200-bus system with wind generation variation and N-1 topology changes validate the effectiveness of the proposed method and demonstrate its great potential in promoting sustainable energy integration into the power system.

关键词： Alternating current(AC)optimal power flow(OPF) deep learning deep reinforcement learning(DRL) renewable integration proximal policy optimization

An efficient stochastic algorithm for mid-term scheduling of cascaded hydro systems

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Journal of Modern Power Systems and Clean Energy 2019年第1期7卷 163-173页

作者： Xiaolin GE Shu XIA wei-jen lee Electric Power College Shanghai University of Electric Power Shibei Electricity Supply Company of State Grid Shanghai Municipal Electric Power Company Energy Systems Research Center University of Texas at Arlington

Due to the stochastic and correlated attributes of natural inflows, the mid-term generation scheduling problem for cascaded hydro systems is a very challenging *** paper proposes a novel stochastic optimization algorithm using Latin hypercube sampling and Cholesky decomposition combined with scenario bundling and sensitivity analysis(LC-SB-SA) to address this *** deal with the uncertainty of natural inflows, Latin hypercube sampling is implemented to provide an adequate number of sampling scenarios efficiently, and Cholesky decomposition is introduced to describe the correlated natural inflows among cascaded *** addition, to overcome the difficulties in solving the objectives of all the scenarios, scenario bundling and sensitivity analysis algorithms are developed to improve the computational *** results from both two-station and tenstation systems indicate that the proposed method has the merits in accuracy as well as calculation speed for the midterm cascaded hydro generation *** consideration of natural inflow correlation makes the formulated problem more realistic.

关键词： Cascaded hydro systems Mid-term scheduling Stochastic optimization algorithm Correlation Sensitivity

Multi-timescale robust dispatching for coordinated automatic generation control and energy storage

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Global Energy Interconnection 2020年第4期3卷 355-364页

作者： Yiran Ma Xueshan Han Ming Yang wei-jen lee School of Electrical Engineering Shandong UniversityNo.17923 Jingshi RoadJinan 250061P.R.China The University of Texas at Arlington 701 S.Nedderman Drive Arlington TX 76019

The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy *** dispatch decision-making methods often ignore the intermittent effects of renewable *** paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC *** model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the *** an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.

关键词： Automatic generation control Energy storage Intermittency Coordinated dispatching Robust optimization

Market-oriented Optimal Dispatching Strategy for a Wind Farm with a Multiple Stage Hybrid Energy Storage System

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CSEE Journal of Power and Energy Systems 2018年第4期4卷 417-424页

作者： Zhenyuan Zhang Yun Zhang Qi Huang wei-jen lee University of Electronic Science and Technology of China Chengdu 611731China University of Texas at Arlington ArlingtonTX 76019USA

With the increased promotion of integrated energy power systems(IEPS),renewable energy and energy storage systems(ESS)play a more important ***,the fluctuation and intermittent nature of wind not only results in substantial reliability and stability defects,but it also weakens the competitiveness of wind generation in the electric power ***,the way to further enhance the system reliability effectively improving market profits of wind farms is one of the most important aspects of Wind-ESS joint operational *** this paper,a market-oriented optimized dispatching strategy for a wind farm with a multiple stage hybrid ESS is *** first stage ESS is designed to improve the profits of wind generation through day-ahead market operations,the real-time marketbased second stage ESS is focused on day-ahead forecasting error elimination and wind power fluctuation smoothing,while the backup stage ESS is associated with them to provide the ancillary *** interval forecasting method is adopted to help to ensure reliable forecast results of day-ahead wind power,electricity prices and *** this hybrid ESS design,supply reliability and market profits are simultaneously achieved for wind farms.

关键词： Dispatching optimization energy storage integrated energy power systems interval forecasting power market p2g wind power generation

A Data-driven Method for Fast AC Optimal Power Flow Solutions via Deep Reinforcement Learning

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Journal of Modern Power Systems and Clean Energy 2020年第6期8卷 1128-1139页

作者： Yuhao Zhou Bei Zhang Chunlei Xu Tu Lan Ruisheng Diao Di Shi Zhiwei Wang wei-jen lee IEEE the Electrical Engineering Department University of Texas at ArlingtonTX 76019USA GEIRI North America San JoseCA 95134USA State Grid Jiangsu Electric Power Company NanjingChina

With the increasing penetration of renewable energy,power grid operators are observing both fast and large fluctuations in power and voltage profiles on a daily *** and accurate control actions derived in real time are vital to ensure system security and *** this end,solving alternating current(AC)optimal power flow(OPF)with operational constraints remains an important yet challenging optimization problem for secure and economic operation of the power *** paper adopts a novel method to derive fast OPF solutions using state-of-the-art deep reinforcement learning(DRL)algorithm,which can greatly assist power grid operators in making rapid and effective *** presented method adopts imitation learning to generate initial weights for the neural network(NN),and a proximal policy optimization algorithm to train and test stable and robust artificial intelligence(AI)*** and testing procedures are conducted on the IEEE 14-bus and the Illinois 200-bus *** results show the effectiveness of the method with significant potential for assisting power grid operators in real-time operations.

关键词： Alternating current(AC)optimal power flow(OPF) deep reinforcement learning(DRL) imitation learning proximal policy optimization

考虑区域无功平衡的主导节点选择和无功分区的优化方法

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电网技术 2017年第1期41卷 164-170页

作者：崔惟颜伟 wei-jen lee 赵霞输配电装备及系统安全与新技术国家重点实验室(重庆大学) 重庆市沙坪坝区400044 德州大学阿灵顿分校美国76019

针对区域无功需满足多负荷水平下的平衡要求,以及二级电压控制以主导节点为控制中心的特点,提出了考虑区域无功平衡的主导节点选择和无功分区的优化方法。该优化方法以电源对主导节点的可控性最强,主导节点对本区域负荷节点的可控性最... 详细信息

针对区域无功需满足多负荷水平下的平衡要求,以及二级电压控制以主导节点为控制中心的特点,提出了考虑区域无功平衡的主导节点选择和无功分区的优化方法。该优化方法以电源对主导节点的可控性最强,主导节点对本区域负荷节点的可控性最强以及主导节点对其他区域负荷节点的影响最小为目标,以多负荷水平下区域静态无功平衡为约束,采用基于目标相对占优的遗传算法进行求解。其中,为表征主导节点对负荷节点的可控性,提出了主导节点的控制空间。该控制空间以主导节点对负荷节点的电压控制灵敏度为基础,通过逐次递归的方法进行构造。IEEE 39和IEEE 118节点系统的仿真结果论证了该方法的有效性。

关键词：主导节点分区算法控制空间控制中心

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

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Advances in Atmospheric Sciences 2024年第5期41卷 817-829页

作者： Heng LYU wei WANG Keer ZHANG Chang CAO wei XIAO Xuhui lee Key Laboratory of Meteorological Disaster Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Key Laboratory of Ecosystem Carbon Source and SinkChina Meteorological Administration(ECSS-CMA)/Jiangsu Key Laboratory of Agricultural MeteorologyNanjing University of Information Science&TechnologyNanjing 210044China Key Laboratory of Urban Meteorology China Meteorological AdministrationBeijing 100089China School of the Environment Yale UniversityNew HavenCT 06511USA

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling *** this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were *** performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its *** results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday *** urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate *** release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate *** rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

关键词： air temperature urban heat island spatial variations biophysical drivers Chinese cities climate model

Magnetic resonance imaging findings of radiation-induced breast angiosarcoma:A case report

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World Journal of Clinical Cases 2024年第13期12卷 2237-2242页

作者： Wen-Pei Wu Chih-wei lee Department of Medical Imaging Changhua Christian HospitalChanghua 50006Taiwan Department of Radiology Changhua Christian Medical Foundation Changhua Christian HospitalChanghua 50006Taiwan

BACKGROUND Breast conservation surgery(BCS)with adjuvant radiotherapy has become a gold standard in the treatment of early-stage breast cancer,significantly reducing the risk of tumor ***,this treatment is associated with adverse effects,including the rare but aggressive radiation-induced angiosarcoma(RIAS).Despite its rarity and nonspecific initial presentation,RIAS presents a challenging diagnosis,emphasizing the importance of imaging techniques for early detection and accurate *** SUMMARY We present a case of a 48-year-old post-menopausal woman who developed skin ecchymosis on the right breast seven years after receiving BCS and adjuvant radiotherapy for breast *** mammography and ultrasound were inconclusive,showing post-treatment changes but failing to identify the underlying ***-enhanced breast magnetic resonance imaging(MRI)revealed diffuse skin thickening and nodularity with distinctive enhan-cement kinetics,leading to the diagnosis of *** case highlights the crucial role of MRI in diagnosing and determining the extent of RIAS,facilitating timely and appropriate surgical *** Breast MRI is crucial for detecting RIAS,especially when mammography and ultrasound are inconclusive.

关键词： Radiation-induced angiosarcoma Radiotherapy Breast conserving surgery Breast cancer Magnetic resonance imaging Case report

Guest Editorial: Special Section on Forecasting in Modern Power Systems

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Journal of Modern Power Systems and Clean Energy 2018年第2期6卷 189-190页

作者： Tao HONG wei-jen lee Department of Systems Engineering and Engineering Management University of North Carolina at Charlotte University of Texas at Arlington

Power systems have been evolving during the past century. The electric grid is getting more and more sophisticated due to modern technologies and business requirements, such as implementation of smart grid technologies, deployment of utra-high voltage transmission systems, and integration of ultra-high levels of renewable resources. All of these factors are challenging today’s energy forecasting practice.

关键词： In Special Section on Forecasting in Modern Power Systems Guest Editorial PV