DOCSLIB.ORG

Buy Hollysys Automation

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Buy Hollysys Automation Deutsche Bank Markets Research Rating Company Date 11 July 2016 Buy Hollysys Initiation of Coverage Asia Automation China Reuters Bloomberg Exchange Ticker Price at 8 Jul 2016 (USD) 17.63 Industrials HOLI.OQ HOLI US NAS HOLI Price target - 12mth (USD) 25.80 Manufacturing 52-week range (USD) 22.80 - 15.21 NASDAQ 100 4,528 HOLIstic solutions; initiating with Buy Sky Hong, CFA Nick Zheng, CFA Research Analyst Research Analyst (+852 ) 2203 6131 (+852 ) 2203 6198 A temporary slowdown is in the price but two emerging growth drivers are not [email protected] [email protected] Hollysys (HOLI), a leading industrial automation solution provider in China, has underperformed the NASDAQ100 by 22% in the past year. With valuations hitting three-year troughs, we believe that the market has overly priced in a Price/price relative slowdown in existing operations, but overlooked rising after-sales service and 28 new product launches. On the back of potential positive earnings surprise (DBe 24 13% EPS CAGR over FY16-18E vs. consensus’ 5%) and the start of a regular dividend, we initiate with Buy and a TP of US$25.8, with 49% upside potential. 20 16 Rising after-sales to cushion slowdown in new sales 12 As the installed base of DCS and rail signalling systems continues to grow, we 7/14 1/15 7/15 1/16 expect lucrative after-sales service revenue to build momentum. For DCS, the Hollysys Automation maintenance/repair cost makes up of c.80% of the total cost of ownership over NASDAQ 100 (Rebased) its lifespan. For rail signalling systems, we expect more high-speed trains to be Performance (%) 1m 3m 12m due for heavy maintenance in the coming years. We expect HOLI’s after-sales revenue to account for 15% of the total by FY18 vs. 9% in FY15. Margins for Absolute 0.6 -12.1 -17.6 after-sales service can typically reach 50-70% vs. 30-40% for initial sales. NASDAQ 100 0.2 1.2 4.1 Source: Deutsche Bank Horizontal expansion gaining traction; watch out for new product launches We highlighted in our sector report that “know your products” and “know your customers” are two winning strategies in industrial automation. HOLI’s success in TCM dispensers is a perfect example as its core control technology is combined with in-depth knowledge of sector verticals. This success, in our This report accompanies our FITT view, is easily replicable in other niche verticals, as customers are increasingly research report – China Industrial looking for customised automation solutions. For rail, similarly leveraging its Automation: Dawn of the Machines core technology and existing customers, new products, such as track circuit and subway signalling systems, should be launched successfully, in our view. Valuations at multi-year lows; key risks At 8x/7x FY17E/FY18E P/E, the stock is trading at 1SD below its long-term average, which looks too pessimistic. Our TP of US$25.8 is derived based on a DCF valuation (WACC: 11.2%, TGR: 0%), corresponding to a non-GAAP P/E of 11.9x/10.2x on FY17E/FY18E, in line with its mid-cycle levels in the past five years. The possibility of a regular dividend ahead also bodes well for the stock. Key risks: an unexpected slowdown in automation capex/railway investment. Forecasts And Ratios Year End Jun 30 2014A 2015A 2016E 2017E 2018E Sales (USDm) 521.3 531.4 536.0 566.1 613.0 EBITDA (USDm) 105.5 139.4 136.7 154.0 176.1 Reported NPAT (USDm) 69.6 96.5 107.6 119.3 139.5 Reported EPS FD(USD) 1.19 1.61 1.84 2.04 2.39 DB EPS FD(USD) 1.49 1.72 1.96 2.17 2.52 DB EPS growth (%) 45.7 15.5 14.3 10.5 16.2 PER (x) 11.6 13.2 9.0 8.1 7.0 Source: Deutsche Bank estimates, company data 1 DB EPS is fully diluted and excludes non-recurring items 2 Multiples and yields calculations use average historical prices for past years and spot prices for current and future years, except P/B which uses the year end close ________________________________________________________________________________________________________________ Deutsche Bank AG/Hong Kong Distributed on: 07/11/2016 15:04:19GMT Deutsche Bank does and seeks to do business with companies covered in its research reports. Thus, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision. DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1. MCI (P) 057/04/2016. 11 July 2016 Manufacturing Hollysys Automation Model updated:07 July 2016 Fiscal year end 30-Jun 2013 2014 2015 2016E 2017E 2018E Running the numbers Financial Summary Asia DB EPS (USD) 1.02 1.49 1.72 1.96 2.17 2.52 Reported EPS (USD) 0.92 1.19 1.61 1.84 2.04 2.39 China DPS (USD) 0.00 0.00 0.40 0.00 0.00 0.00 BVPS (USD) 7.2 8.5 9.9 11.4 13.4 15.8 Manufacturing Weighted average shares (m) 56 58 59 58 58 58 Hollysys Automation Technol Average market cap (USDm) 602 1,004 1,333 1,029 1,029 1,029 Enterprise value (USDm) 487 825 1,116 731 643 543 Reuters: HOLI.OQ Bloomberg: HOLI US Valuation Metrics P/E (DB) (x) 10.5 11.6 13.2 9.0 8.1 7.0 Buy P/E (Reported) (x) 11.6 14.5 14.2 9.6 8.6 7.4 Price (8 Jul 16) USD 17.63 P/BV (x) 1.69 2.83 2.42 1.55 1.31 1.12 Target Price USD 25.80 FCF Yield (%) 3.6 7.5 6.0 9.8 8.9 10.1 Dividend Yield (%) 0.0 0.0 1.8 0.0 0.0 0.0 52 Week range USD 15.21 - 22.80 EV/Sales (x) 1.4 1.6 2.1 1.4 1.1 0.9 Market Cap (m) EURm 932 EV/EBITDA (x) 7.1 7.8 8.0 5.3 4.2 3.1 EV/EBIT (x) 8.2 8.9 8.8 5.9 4.6 3.4 USDm 1,029 Income Statement (USDm) Company Profile Sales revenue 349 521 531 536 566 613 Founded in 1993 and headquartered in Beijing, HollySys Gross profit 124 176 214 204 224 248 Automation (HOLI) specializes in process automation, EBITDA 69 105 139 137 154 176 factory automation, rail automation and mechanical & Depreciation 6 7 9 9 9 10 engineering solutions. Hollysys has established itself as Amortisation 3 6 5 5 5 5 the local leading automation and IT solutions provider in EBIT 59 93 126 123 140 161 China and Southeast Asia. HollySys listed its common Net interest income(expense) 1 1 2 3 5 7 stock on NASDAQ in 2008. Associates/affiliates 0 -3 -3 6 0 0 Exceptionals/extraordinaries 0 0 0 0 0 0 Other pre-tax income/(expense) 0 0 0 0 0 0 Profit before tax 61 91 125 132 145 169 Price Performance Income tax expense 8 20 26 22 22 25 Minorities 1 2 3 3 3 4 28 Other post-tax income/(expense) 0 0 0 0 0 0 Net profit 52 70 97 108 119 139 24 DB adjustments (including dilution) 6 17 7 7 7 8 20 DB Net profit 58 87 103 115 127 147 16 Cash Flow (USDm) 12 Jul 14 Oct 14Jan 15Apr 15 Jul 15 Oct 15Jan 16Apr 16 Cash flow from operations 31 83 84 121 113 128 Net Capex -9 -7 -4 -20 -22 -24 Hollysys Automation Technol Free cash flow 22 76 80 101 91 104 NASDAQ 100 (Rebased) Equity raised/(bought back) 1 0 1 0 0 0 Margin Trends Dividends paid 0 0 -23 -23 0 0 Net inc/(dec) in borrowings -5 -8 24 -30 0 -20 32 Other investing/financing cash flows -2 -18 -36 0 0 0 28 Net cash flow 16 50 46 47 91 84 Change in working capital -37 -21 -58 3 -23 -30 24 Balance Sheet (USDm) 20 Cash and other liquid assets 112 162 208 255 346 430 16 Tangible fixed assets 92 95 92 98 105 114 13 14 15 16E 17E 18E Goodwill/intangible assets 78 73 62 62 63 63 EBITDA Margin EBIT Margin Associates/investments 41 48 67 73 73 73 Other assets 422 549 556 565 597 646 Growth & Profitability Total assets 745 927 984 1,053 1,183 1,326 Interest bearing debt 36 28 51 21 20 0 60 20 Other liabilities 293 407 347 360 368 387 50 15 Total liabilities 329 435 398 380 388 387 40 Shareholders' equity 414 488 579 663 783 922 30 10 Minorities 2 4 6 9 13 16 20 5 Total shareholders' equity 415 492 585 673 795 939 10 Net debt -76 -134 -157 -234 -326 -430 0 0 13 14 15 16E 17E 18E Key Company Metrics Sales growth (%) nm 49.4 1.9 0.9 5.6 8.3 Sales growth (LHS) ROE (RHS) DB EPS growth (%) na 45.7 15.5 14.3 10.5 16.2 Solvency EBITDA Margin (%) 19.7 20.2 26.2 25.5 27.2 28.7 EBIT Margin (%) 17.0 17.8 23.8 23.0 24.7 26.3 0 Payout ratio (%) 0.0 0.0 24.3 0.0 0.0 0.0 -10 ROE (%) 12.6 15.4 18.1 17.3 16.5 16.4 Capex/sales (%) 2.6 1.6 0.9 3.7 3.9 3.9 -20 Capex/depreciation (x) 1.0 0.7 0.3 1.5 1.6 1.6 -30 Net debt/equity (%) -18.3 -27.3 -26.8 -34.9 -41.0 -45.8 -40 Net interest cover (x) nm nm nm nm nm nm -50 Source: Company data, Deutsche Bank estimates 13 14 15 16E 17E 18E Net debt/equity (LHS) Net interest cover (RHS) Sky Hong, CFA +852 2203 6131 [email protected] Page 2 Deutsche Bank AG/Hong Kong 11 July 2016 Manufacturing Hollysys Automation Table of contents Investment thesis ...............................................................
Load more

Recommended publications
  • Ambitious Roadmap for City's South
    4 nation MONDAY, MARCH 11, 2013 CHINA DAILY PLAN FOR BEIJING’S SOUTHERN AREA SOUND BITES I lived with my grandma during my childhood in an old community in the former Xuanwu district. When I was a kid we used to buy hun- dreds of coal briquettes to heat the room in the winter. In addition to the inconvenience of carry- ing those briquettes in the freezing winter, the rooms were sometimes choked with smoke when we lit the stove. In 2010, the government replaced the traditional coal-burning stoves with electric radiators in the community where grand- ma has spent most of her life. We also receive a JIAO HONGTAO / FOR CHINA DAILY A bullet train passes on the Yongding River Railway Bridge, which goes across Beijing’s Shijingshan, Fengtai and Fangshan districts and Zhuozhou in Hebei province. special price for electricity — half price in the morn- ing. Th is makes the cost of heating in the winter Ambitious roadmap for city’s south even less. Liang Wenchao, 30, a Beijing resident who works in the media industry Three-year plan has turned area structed in the past three years. In addition to the subway, six SOUTH BEIJING into a thriving commercial hub roads, spanning 167 km, are I love camping, especially also being built to connect the First phase of “South Beijing Three-year Plan” (2010-12) in summer and autumn. By ZHENG XIN product of the Fengtai, Daxing southern area with downtown, The “New South Beijing Three-year Plan” (2013-15) [email protected] We usually drive through and Fangshan districts is only including Jingliang Road and Achievements of the Plan for the next three 15 percent of the city’s total.
    [Show full text]
  • Beijing Subway Map
    Beijing Subway Map Ming Tombs North Changping Line Changping Xishankou 十三陵景区 昌平西山口 Changping Beishaowa 昌平 北邵洼 Changping Dongguan 昌平东关 Nanshao南邵 Daoxianghulu Yongfeng Shahe University Park Line 5 稻香湖路 永丰 沙河高教园 Bei'anhe Tiantongyuan North Nanfaxin Shimen Shunyi Line 16 北安河 Tundian Shahe沙河 天通苑北 南法信 石门 顺义 Wenyanglu Yongfeng South Fengbo 温阳路 屯佃 俸伯 Line 15 永丰南 Gonghuacheng Line 8 巩华城 Houshayu后沙峪 Xibeiwang西北旺 Yuzhilu Pingxifu Tiantongyuan 育知路 平西府 天通苑 Zhuxinzhuang Hualikan花梨坎 马连洼 朱辛庄 Malianwa Huilongguan Dongdajie Tiantongyuan South Life Science Park 回龙观东大街 China International Exhibition Center Huilongguan 天通苑南 Nongda'nanlu农大南路 生命科学园 Longze Line 13 Line 14 国展 龙泽 回龙观 Lishuiqiao Sunhe Huoying霍营 立水桥 Shan’gezhuang Terminal 2 Terminal 3 Xi’erqi西二旗 善各庄 孙河 T2航站楼 T3航站楼 Anheqiao North Line 4 Yuxin育新 Lishuiqiao South 安河桥北 Qinghe 立水桥南 Maquanying Beigongmen Yuanmingyuan Park Beiyuan Xiyuan 清河 Xixiaokou西小口 Beiyuanlu North 马泉营 北宫门 西苑 圆明园 South Gate of 北苑 Laiguangying来广营 Zhiwuyuan Shangdi Yongtaizhuang永泰庄 Forest Park 北苑路北 Cuigezhuang 植物园 上地 Lincuiqiao林萃桥 森林公园南门 Datunlu East Xiangshan East Gate of Peking University Qinghuadongluxikou Wangjing West Donghuqu东湖渠 崔各庄 香山 北京大学东门 清华东路西口 Anlilu安立路 大屯路东 Chapeng 望京西 Wan’an 茶棚 Western Suburban Line 万安 Zhongguancun Wudaokou Liudaokou Beishatan Olympic Green Guanzhuang Wangjing Wangjing East 中关村 五道口 六道口 北沙滩 奥林匹克公园 关庄 望京 望京东 Yiheyuanximen Line 15 Huixinxijie Beikou Olympic Sports Center 惠新西街北口 Futong阜通 颐和园西门 Haidian Huangzhuang Zhichunlu 奥体中心 Huixinxijie Nankou Shaoyaoju 海淀黄庄 知春路 惠新西街南口 芍药居 Beitucheng Wangjing South望京南 北土城
    [Show full text]
  • EUROPEAN COMMISSION DG RESEARCH STADIUM D2.1 State
    EUROPEAN COMMISSION DG RESEARCH SEVENTH FRAMEWORK PROGRAMME Theme 7 - Transport Collaborative Project – Grant Agreement Number 234127 STADIUM Smart Transport Applications Designed for large events with Impacts on Urban Mobility D2.1 State-of-the-Art Report Project Start Date and Duration 01 May 2009, 48 months Deliverable no. D2.1 Dissemination level PU Planned submission date 30-November 2009 Actual submission date 30 May 2011 Responsible organization TfL with assistance from IMPACTS WP2-SOTA Report May 2011 1 Document Title: State of the Art Report WP number: 2 Document Version Comments Date Authorized History by Version 0.1 Revised SOTA 23/05/11 IJ Version 0.2 Version 0.3 Number of pages: 81 Number of annexes: 9 Responsible Organization: Principal Author(s): IMPACTS Europe Ian Johnson Contributing Organization(s): Contributing Author(s): Transport for London Tony Haynes Hal Evans Peer Rewiew Partner Date Version 0.1 ISIS 27/05/11 Approval for delivery ISIS Date Version 0.1 Coordination 30/05/11 WP2-SOTA Report May 2011 2 Table of Contents 1.TU UT ReferenceTU DocumentsUT ...................................................................................................... 8 2.TU UT AnnexesTU UT ............................................................................................................................. 9 3.TU UT ExecutiveTU SummaryUT ....................................................................................................... 10 3.1.TU UT ContextTU UT ........................................................................................................................
    [Show full text]
  • Can Light Rail Benefit Job-Housing Relationships and Land Use-Transp Ortation Integration in New Town? ——Case Study of Yizhuang in Beijing
    Can Light Rail Benefit Job-Housing Relationships and Land Use-Transp ortation Integration in New Town? ——case study of Yizhuang in Beijing Chun Zhang USC Nov 10, 2016 BJTU Beijing Jiaotong University 1.The Research Background 1.1 Beijing Urban Rail Transit bursty expansion • After 2002 ,the Beijing urban metro construction suddenly accelerated, and firstly the northern part of Beijing which is more developed than southern part formed the urban metro network. urban metro network 2000 urban metro network 2010 urban metro network 2015 The study on synergy development of urban metro and urban space Beijing Jiaotong University 1.The Research Background 1.2 Spatial differentiation of urban functions • With the expansion of the population and scale of city , the function and division of urban land are more clear than ever, the phenomenon of urban spatial differentiation is more obvious. • The city of Beijing is divided into 4 different functional areas. Different urban functions require organic connection, and mutual complement among urban functions can help city work effectively. The study on synergy development of urban metro and urban space Beijing Jiaotong University 2.The Research methods 2.1 The research target • Yizhuang line is the suburb line of Beijing urban metro network, the line starts with the Songjiazhuang station in the Fengtai District and end with Yizhuang railway station. • Yizhuang line makes the urban metro network cover the southeast part of Beijing, connects the center part and Yizhuang Economic Development Zone. The study
    [Show full text]
  • Job-Worker Spatial Dynamics in Beijing: Insights from Smart Card Data
    Published as: Huang, Jie, Levinson, D., Wang, Jiaoe, Jin, Haitao (2019) Job-worker spatial dynamics in Beijing: Insights from Smart Card Data. Cities 86, 89-93 https://doi.org/10.1016/j.cities.2018.11.021 1 Job-worker spatial dynamics in Beijing: insights from Smart 2 Card Data 3 Abstract: 4 As a megacity, Beijing has experienced traffic congestion, unaffordable housing 5 issues and jobs-housing imbalance. Recent decades have seen policies and projects 6 aiming at decentralizing urban structure and job-worker patterns, such as subway 7 network expansion, the suburbanization of housing and firms. But it is unclear 8 whether these changes produced a more balanced spatial configuration of jobs and 9 workers. To answer this question, this paper evaluated the ratio of jobs to workers 10 from Smart Card Data at the transit station level and offered a longitudinal study for 11 regular transit commuters. The method identifies the most preferred station around 12 each commuter’s workpalce and home location from individual smart datasets 13 according to their travel regularity, then the amounts of jobs and workers around each 14 station are estimated. A year-to-year evolution of job to worker ratios at the station 15 level is conducted. We classify general cases of steepening and flattening job-worker 16 dynamics, and they can be used in the study of other cities. The paper finds that (1) 17 only temporary balance appears around a few stations; (2) job-worker ratios tend to be 18 steepening rather than flattening, influencing commute patterns; (3) the polycentric 19 configuration of Beijing can be seen from the spatial pattern of job centers identified.
    [Show full text]
  • Smart Train Operation Algorithms Based on Expert Knowledge and Ensemble Cart for the Electric Locomotive,” Knowledge-Based Systems, Vol
    PREPRINT VERSION. PUBLISHED IN IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS - https://ieeexplore.ieee.org/abstract/document/9144488. Smart Train Operation Algorithms based on Expert Knowledge and Reinforcement Learning Kaichen Zhou, Student Member, IEEE, Shiji Song, Member, IEEE, Anke Xue, Member, IEEE Keyou You, Member, IEEE and Hui Wu, Student Member, IEEE Abstract—During recent decades, the automatic train operation on the train’s trajectory. And improving the performance of the (ATO) system has been gradually adopted in many subway systems ATO system has become a focus in the field of the transportation for its low-cost and intelligence. This paper proposes two smart system. In most cases, research on the urban subway system train operation algorithms by integrating the expert knowledge with reinforcement learning algorithms. Compared with previous works, can be divided into two parts: the energy-efficient train operation the proposed algorithms can realize the control of continuous action committed to designing an off-line optimized train trajectory, and for the subway system and optimize multiple critical objectives the automatic train tracking method to track the real-time train without using an offline speed profile. Firstly, through learning speed-distance profile. historical data of experienced subway drivers, we extract the expert knowledge rules and build inference methods to guarantee the riding During recent years, lot of studies are devoted to designing comfort, the punctuality, and the safety of the subway system. Then an off-line optimized train trajectory to improve the energy we develop two algorithms for optimizing the energy efficiency of efficiency. For example, Albrecht et al.
    [Show full text]
  • China Clean Energy Study Tour for Urban Infrastructure Development
    China Clean Energy Study Tour for Urban Infrastructure Development BUSINESS ROUNDTABLE Tuesday, August 13, 2019 Hyatt Centric Fisherman’s Wharf Hotel • San Francisco, CA CONNECT WITH USTDA AGENDA China Urban Infrastructure Development Business Roundtable for U.S. Industry Hosted by the U.S. Trade and Development Agency (USTDA) Tuesday, August 13, 2019 ____________________________________________________________________ 9:30 - 10:00 a.m. Registration - Banquet AB 9:55 - 10:00 a.m. Administrative Remarks – KEA 10:00 - 10:10 a.m. Welcome and USTDA Overview by Ms. Alissa Lee - Country Manager for East Asia and the Indo-Pacific - USTDA 10:10 - 10:20 a.m. Comments by Mr. Douglas Wallace - Director, U.S. Department of Commerce Export Assistance Center, San Francisco 10:20 - 10:30 a.m. Introduction of U.S.-China Energy Cooperation Program (ECP) Ms. Lucinda Liu - Senior Program Manager, ECP Beijing 10:30 a.m. - 11:45 a.m. Delegate Presentations 10:30 - 10:45 a.m. Presentation by Professor ZHAO Gang - Director, Chinese Academy of Science and Technology for Development 10:45 - 11:00 a.m. Presentation by Mr. YAN Zhe - General Manager, Beijing Public Transport Tram Corporation 11:00 - 11:15 a.m. Presentation by Mr. LI Zhongwen - Head of Safety Department, Shenzhen Metro 11:15 - 11:30 a.m. Tea/Coffee Break 11:30 - 11:45 a.m. Presentation by Ms. WANG Jianxin - Deputy General Manager, Tianjin Metro Operation Corporation 11:45 a.m. - 12:00 p.m. Presentation by Mr. WANG Changyu - Director of General Engineer's Office, Wuhan Metro Group 12:00 - 12:15 p.m.
    [Show full text]
  • Exploration in the Curriculum and Teaching Based Cultivation of Innovation Capabilities for Graduate Students
    2016 2nd International Conference on Modern Education and Social Science (MESS 2016) ISBN: 978-1-60595-346-5 Research on Beijing Urban Rail Transit Network Based on Traffic Efficiency Shu-Lan ZHANGa,*, Hao WUb and Wen SUNc Beijing Jiaotong University, School of Economics and Management, China [email protected], [email protected], [email protected] *Corresponding author Keywords: Urban rail transit, Network density, Transfer station, Transport efficiency. Abstract. The coordination between urban rail transit network and city spatial functional distribution plays an important role in the process of urbanization. This paper, based on an empirical analysis, studies the characteristics of the Beijing urban rail transit network from the perspective of time and space. Then, according to statistical analysis, a series of reasonable evaluating indicators and comparison among the typical cities in the world, we summarize the obvious problems existing in the network. At last, we draw the conclusions that the network needs improvement and we put forward six suggestions aiming to increase the transport efficiency and optimize the network layout. Introduction Beijing is in the stage of adjusting its city spatial layout to “two-axis, two-belt and multiple centers” according to The General Plan of Beijing (2004-2020). The non-capital core functional industries will be moved to suburban regions and the core-functional industries will be strengthened, aiming to achieve balanced development. With the adjustment of Beijing population and industrial distribution, the demand for transport shows new features. The key method to solve the traffic problem is to build urban transport system coordinated with the overall development plan of the city.
    [Show full text]
  • Multi-Train Energy Saving for Maximum Usage of Regenerative Energy by Dwell Time Optimization in Urban Rail Transit Using Genetic Algorithm
    energies Article Multi-Train Energy Saving for Maximum Usage of Regenerative Energy by Dwell Time Optimization in Urban Rail Transit Using Genetic Algorithm Fei Lin *, Shihui Liu, Zhihong Yang, Yingying Zhao, Zhongping Yang and Hu Sun School of Electrical Engineering, Beijing Jiaotong University, No. 3 Shangyuancun, Beijing 100044, China; [email protected] (S.L.); [email protected] (Z.Y.); [email protected] (Y.Z.); [email protected] (Z.Y.); [email protected] (H.S.) * Correspondence: fl[email protected]; Tel.: +86-136-4139-8863 Academic Editor: William Holderbaum Received: 2 February 2016; Accepted: 10 March 2016; Published: 17 March 2016 Abstract: With its large capacity, the total urban rail transit energy consumption is very high; thus, energy saving operations are quite meaningful. The effective use of regenerative braking energy is the mainstream method for improving the efficiency of energy saving. This paper examines the optimization of train dwell time and builds a multiple train operation model for energy conservation of a power supply system. By changing the dwell time, the braking energy can be absorbed and utilized by other traction trains as efficiently as possible. The application of genetic algorithms is proposed for the optimization, based on the current schedule. Next, to validate the correctness and effectiveness of the optimization, a real case is studied. Actual data from the Beijing subway Yizhuang Line are employed to perform the simulation, and the results indicate that the optimization method of the dwell time is effective. Keywords: genetic algorithm; dwell time; energy saving; braking energy; multi-train; urban rail transit 1.
    [Show full text]
  • Flood Risk Assessment of Subway Systems in Metropolitan Areas Under Land Subsidence Scenario: a Case Study of Beijing
    remote sensing Article Flood Risk Assessment of Subway Systems in Metropolitan Areas under Land Subsidence Scenario: A Case Study of Beijing Guangpeng Wang 1,2,3 , Yong Liu 1,2,3, Ziying Hu 1,2,3, Guoming Zhang 1,2,3, Jifu Liu 1,2,3, Yanli Lyu 1,2,3, Yu Gu 1,2,3, Xichen Huang 1,2,3, Qingyan Zhang 1,2,3 and Lianyou Liu 1,2,3,* 1 Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China; [email protected] (G.W.); [email protected] (Y.L.); [email protected] (Z.H.); [email protected] (G.Z.); [email protected] (J.L.); [email protected] (Y.L.); [email protected] (Y.G.); [email protected] (X.H.); [email protected] (Q.Z.) 2 Engineering Research Center of Desertification and Blown-sand Control, Ministry of Education, Beijing Normal University, Beijing 100875, China 3 Faculty of Geographical Science, Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China * Correspondence: [email protected]; Tel.: +86-10-58802600 Abstract: Flooding is one of the most destructive natural events that severely damage the ground and inundate underground infrastructure. Subway systems in metropolitan areas are susceptible to flooding, which may be exacerbated when land subsidence occurs. However, previous studies have focused on flood risk evaluation on regional/watershed-scales and land subsidence monitoring in plains, instead of on subway flood risk evaluation and how land subsidence aggravates the flood risk in subway systems.
    [Show full text]
  • Assessing Survivability of the Beijing Subway System
    University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Masters Theses Graduate School 8-2014 Assessing Survivability of the Beijing Subway System Yan Li University of Tennessee - Knoxville, [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes Part of the Geographic Information Sciences Commons Recommended Citation Li, Yan, "Assessing Survivability of the Beijing Subway System. " Master's Thesis, University of Tennessee, 2014. https://trace.tennessee.edu/utk_gradthes/2872 This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a thesis written by Yan Li entitled "Assessing Survivability of the Beijing Subway System." I have examined the final electronic copy of this thesis for form and content and recommend that it be accepted in partial fulfillment of the equirr ements for the degree of Master of Science, with a major in Geography. Hyun Kim, Major Professor We have read this thesis and recommend its acceptance: Shih-Lung Shaw, Dali Wang Accepted for the Council: Carolyn R. Hodges Vice Provost and Dean of the Graduate School (Original signatures are on file with official studentecor r ds.) Assessing Survivability of the Beijing Subway System A Thesis Presented for the Master of Science Degree The University of Tennessee, Knoxville Yan Li August 2014 Copyright © 2014 by Yan Li All rights reserved.
    [Show full text]
  • Coordinated Train Control in a Fully Automatic Operation System for Reducing Energy Consumption
    Computers in Railways XIII 3 Coordinated train control in a fully automatic operation system for reducing energy consumption J. Xun1, X. Yang1, B. Ning1, T. Tang1 & W. Wang2 1The State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 2National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing Abstract Energy efficient train operation includes four levels for energy saving: energy efficient driving, real-time multi-train coordination and rescheduling, energy- saving timetabling, and energy-saving planning. For a fully automatic operation system, it provides a flexible way to coordinate trains. The coordination of trains can improve some system performances, such as the efficient use of regenerative energy. The efficient use of energy regenerated by other trains which are during braking phase can contribute to reducing energy consumption. In general, the approaches of coordinated train control for using regenerative energy can be divided into two types: train dwell time control and train running time control. This paper proposes an approach for coordinating trains in fully automatic operation system by modifying running time between adjacent stations. Simulation studies are performed and the usage of regenerative energy and average passenger waiting time is analysed by using the proposed method. It is shown that improvements in the usage of regenerative energy can be achieved by using the proposed method. Keywords: coordinated train control, energy-saving, fully automatic operation, running time control. WIT Transactions on The Built Environment, Vol 127, © 2012 WIT Press www.witpress.com, ISSN 1743-3509 (on-line) doi:10.2495/CR120011 4 Computers in Railways XIII 1 Introduction Reduction of energy consumption has drawn more and more attractions in railway industry.
    [Show full text]