发电技术 ›› 2022, Vol. 43 ›› Issue (2): 287-304.DOI: 10.12096/j.2096-4528.pgt.22058
黄超1,2, 卜思齐1,2, 陈麒宇3, 李晓虹2
收稿日期:
2022-03-16
出版日期:
2022-04-30
发布日期:
2022-05-13
作者简介:
基金资助:
Chao HUANG1,2, Siqi BU1,2, Qiyu CHEN3, Hiu Hung LEE2
Received:
2022-03-16
Published:
2022-04-30
Online:
2022-05-13
Supported by:
摘要:
元宇宙是数字化革命的新进程,它将宇宙打造成一个由多种技术支撑的具有强交互性和超时空性的生态系统。将元宇宙应用到电力系统能进一步提升电力系统的信息化和智能化程度,成为新一代智能电网。定义引入元宇宙的电力系统为元电力,元电力的多技术性促进了电力系统运行的灵活性、安全性和智能性,元电力的强交互性提高了电力系统监测和维护的便利性和沉浸性,元电力的超时空性突破了电力系统运行的时空局限性,有利于未来能源发展战略的评估推演。
中图分类号:
黄超, 卜思齐, 陈麒宇, 李晓虹. 元电力:新一代智能电网[J]. 发电技术, 2022, 43(2): 287-304.
Chao HUANG, Siqi BU, Qiyu CHEN, Hiu Hung LEE. Meta-Power: Next-Generation Smart Grid[J]. Power Generation Technology, 2022, 43(2): 287-304.
1 | 申洪,周勤勇,刘耀,等 .碳中和背景下全球能源互联网构建的关键技术及展望[J].发电技术,2021,42(1):8-19. doi:10.12096/j.2096-4528.pgt.20113 |
SHEN H, ZHOU Q Y, LIU Y,et al .Key technologies and prospects for the construction of global energy internet under the background of carbon neutral[J].Power Generation Technology,2021,42(1):8-19. doi:10.12096/j.2096-4528.pgt.20113 | |
2 | 童光毅 .基于双碳目标的智慧能源体系构建[J].智慧电力,2021,49(5):1-6. doi:10.3969/j.issn.1673-7598.2021.05.002 |
TONG G Y .Construction of smart energy system based on dual carbon goal[J].Smart Power,2021,49(5):1-6. doi:10.3969/j.issn.1673-7598.2021.05.002 | |
3 | SILBERMAN S .The energy web[EB/OL].(2001-07-01)[2022-02-21].. |
4 | 张瑶,王傲寒,张宏 .中国智能电网发展综述[J].电力系统保护与控制,2021,49(5):180-187. |
ZHANG Y, WANG A H, ZHANG H .Overview of smart grid development in China[J].Power System Protection and Control,2021,49(5):180-187. | |
5 | 谢清玉,张耀坤,李经纬 .面向智能电网的电力大数据关键技术应用[J].电网与清洁能源,2021,37(12):39-46. doi:10.3969/j.issn.1674-3814.2021.12.006 |
XIE Q Y, ZHANG Y K, LI J W .Application of key technologies of power big data in smart grids[J].Power System and Clean Energy,2021,37(12):39-46. doi:10.3969/j.issn.1674-3814.2021.12.006 | |
6 | SMART J, CASCIO J, PAFFENDORF J .Metaverse roadmap:pathway to the 3D web[R].Metaverse:A Cross-Industry Public Foresight Project,2007. |
7 | NING H, WANG H, LIN Y,et al .A survey on metaverse:the state-of-the-art,technologies,applications,and challenges[EB/OL].(2021-11-18)[2022-02-21]. . |
8 | LEE L H, BRAUD T, ZHOU P,et al .All one needs to know about metaverse:a complete survey on technological singularity,virtual ecosystem,and research agenda[EB/OL].(2021-11-18)[2022-02-21]. . |
9 | SIYAEV A, JO G S .Towards aircraft maintenance metaverse using speech interactions with virtual objects in mixed reality[J].Sensors,2021,21(6):2066. doi:10.3390/s21062066 |
10 | NINAGAWA C .Virtual power plant integration technology[M].Singapore:Springer Press,2022. doi:10.1007/978-981-16-6148-8 |
11 | 米阳,王鹏,邓锦,等 .孤岛交直流混合微电网群分层协调控制[J].电力系统保护与控制,2021,49(20):1-8. |
MI Y, WANG P, DENG J,et al .Hierarchical coordinated control of island AC/DC hybrid microgrids[J].Power System Protection and Control,2021,49(20):1-8. | |
12 | KHODAEI A, BAHRAMIRAD A, SHAHIDEHPOUR M .Microgrid planning under uncertainty[J].IEEE Transactions on Power Systems,2015,30(5):2417-2425. doi:10.1109/tpwrs.2014.2361094 |
13 | FLUHR J, AHLERT K H, WEINHARDT C .A stochastic model for simulating the availability of electric vehicles for services to the power grid[C]//2010 43rd Hawaii International Conderence on System Sciences.2010:1-10. doi:10.1109/hicss.2010.33 |
14 | Gartner .Gartner identifies the top 10 strategic technology trends for 2018[R].U S:Gartner,2018. doi:10.1049/et.2018.1021 |
15 | RODIC B .Industry 4.0 and the new simulation modelling paradigm[J].Organizacija,2017,50(3):193-207. doi:10.1515/orga-2017-0017 |
16 | HARGREAVES P A, MECROW B C, HALL R . Calculation of iron loss in electrical generators using finite-element analysis[J].IEEE Transactions on Industry Applications,2012,48(5):1460-1466. doi:10.1109/tia.2012.2209851 |
17 | SANTOS H F DOS, SADOWSKI N, BATISTELA N J,et al .Synchronous generator fault investigation by experimental and finite-element procedures[J].IEEE Transactions on Magnetics,2016,52(3):1-4. doi:10.1109/tmag.2015.2480546 |
18 | RAMAYANTI S, BUDIANTORO P .Design analysis of solar panel structure LAPAN-constellation satellite using finite element analysis[J].IOP Conference Series:Materials Science and Engineering,2021,1041(1):12020. doi:10.1088/1757-899x/1041/1/012020 |
19 | TAO F, ZHANG M, LIU Y,et al .Digital twin driven prognostics and health management for complex equipment[J].CIRP Annals,2018,67(1):169-172. doi:10.1016/j.cirp.2018.04.055 |
20 | HUSSAIN M R, REFAAT S S .Improvement in three-dimension al finite element modeling for high voltage power transformer in time domain[C]//2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC).2021:460-466. doi:10.1109/pemc48073.2021.9432566 |
21 | QU J, WANG Q, ZHANG J,et al .3-D transient finite-element analysis and experimental investigation of short-circuit dynamic stability for air circuit breaker[J].IEEE Transactions on Components,Packaging and Manufacturing Technology,2015,5(11):1610-1617. doi:10.1109/tcpmt.2015.2475300 |
22 | WANG Z, LIU Y, KONG X,et al .Galloping characteristics of 10 kV overhead transmission line using finite element analysis method[C]//2021 International Conference on Electrical Materials and Power Equipment (ICEMPE).Chingqing,China:IEEE,2021:1-4. doi:10.1109/icempe51623.2021.9509102 |
23 | CONTI S, DILETTOSO E, RIZZO S A . Electromagnetic and thermal analysis of high voltage three-phase underground cables using finite element method[C]//2018 International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe).2018:1-6. doi:10.1109/eeeic.2018.8525354 |
24 | YAMAZAKI K, MATSUMOTO M .3-D finite element meshing for skewed rotor induction motors[J].IEEE Transactions on Magnetics,2015,51(3):1-4. doi:10.1109/tmag.2014.2348568 |
25 | TSAO B, CHMIEL B, DEVILLIER A,et al .Transient finite element simulation of a Lithium-ion battery pack thermal management system based on latent heat system materials[J].ECS Transactions,2021,104(1):61-71. doi:10.1149/10401.0061ecst |
26 | CANIZARES C, FERNANDES T, GERALDI E,et al .Benchmark models for the analysis and control of small-signal oscillatory dynamics in power systems[J].IEEE Transactions on Power Systems,2017,32(1):715-722. doi:10.1109/tpwrs.2016.2561263 |
27 | LATRECHE Y, BOUCHEKARA H R E H, NAIDU K,et al .Comprehensive review of radial distribution test systems[EB/OL].(2020-06-20)[2022-02-21].. doi:10.36227/techrxiv.12578648 |
28 | HE X, AI Q, QIU R C,et al .Preliminary exploration on digital twin for power systems:challenges,framework,and applications[EB/OL].(2019-09-16)[2022-02-21]. . |
29 | AGHAMOLKI H G, MIAO Z, FAN L .A hardware-in-the-loop SCADA testbed[C]//2015 North American Power Symposium (NAPS),Charlotte,USA:IEEE,2015:1-6. doi:10.1109/naps.2015.7335093 |
30 | YANG Y, JIANG H T, MCLAUGHLIN K,et al .Cybersecurity test-bed for IEC 61850 based smart substations[C]//2015 IEEE Power & Energy Society General Meeting.Denver,USA:IEEE,2015:1-5. doi:10.1109/pesgm.2015.7286357 |
31 | CINTUGLU M H, MOHAMMED O A, AKKAYA K,et al .A survey on smart grid cyber-physical system testbeds[J].IEEE Communications Surveys & Tutorials,2017,19(1):446-464. doi:10.1109/comst.2016.2627399 |
32 | SONG X, JIANG T, SCHLEGEL S,et al .Investigation of inventive tuning algorithm for the realization of digital twins of inverter model in inverter-dominated power distribution grid[C]//2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe).Bucharest,Romania:IEEE,2019:1-6. doi:10.1109/isgteurope.2019.8905551 |
33 | SAAD A, FADDEL S, MOHAMMED O .IoT-based digital twin for energy cyber-physical systems:design and implementation[J].Energies,2020,13(18):4762. doi:10.3390/en13184762 |
34 | LE F C, TAO Y .Intelligent energy dispatching robot and its knowledge automation:information,physics and social integration:frame-work,technology and challenges[J].Procedia CSEE,2018,38(1):25-40. |
35 | 杨挺,翟峰,赵英杰,等 .泛在电力物联网释义与研究展望[J].电力系统自动化,2019,43(13):9-20. doi:10.7500/AEPS20190418015 |
YANG T, ZHAI F, ZHAO Y J,et al .Interpretation and research prospects of ubiquitous power internet of things[J].Automation of Electric Power Systems,2019,43(13):9-20. doi:10.7500/AEPS20190418015 | |
36 | GALLI S, SCAGLIONE A, WANG Z .For the grid and through the grid:the role of power line communications in the smart grid[J].Proceedings of the IEEE,2011,99(6):998-1027. doi:10.1109/jproc.2011.2109670 |
37 | ANCILLOTTI E, BRUNO R, CONTI M .The role of communication systems in smart grids:architectures,technical solutions and research challenges[J].Computer Communications,2013,36(17/18):1665-1697. doi:10.1016/j.comcom.2013.09.004 |
38 | YANG B, YAMAZAKI J, SAITO N,et al .Big data analytic empowered grid applications:is PMU a big data issue[C]//2015 12th International Conference on the European Energy Market (EEM).Lisbon,Potugal:IEEE,2015:1-4. doi:10.1109/eem.2015.7216718 |
39 | THOLOMIER D, Kang H, CVOROVIC B .Phasor measurement units:functionality and applications[C]//2009 Power Systems Conference.Clemson,USA:IEEE,2009:1-12. doi:10.1109/psamp.2009.5262468 |
40 | MAHMOOD A, AAMIR M, ANIS M I .Design and implementation of AMR smart grid system[C]//2008 IEEE Canada Electric Power Conference.Karachi,Pakistan:IEEE,2008:1-6. doi:10.1109/epc.2008.4763340 |
41 | LEWIS R P, IGICT P, ZHOU Z .Assessment of communication methods for smart electricity metering in the UK[C]//2009 IEEE PES/IAS Conference on Sustainable Alternative Energy (SAE).Valencia,Spain:IEEE,2009:1-4. doi:10.1109/sae.2009.5534884 |
42 | ZHANG D, SUN B, FAN H .Remote online power system monitoring system based on multiinformation acquisition technology[C]//2004 International Conference on Power System Technology.Singapore:IEEE,2004:1147-1151. |
43 | SYED D, ZAINAB A, GHRAYEB A,et al .Smart grid big data analytics:survey of technologies,techniques,and applications[J].IEEE Access,2020,9:59564-59585. doi:10.1109/access.2020.3041178 |
44 | 魏梦飒,陆增洁,徐建清,等 .基于大数据模型的电网风电场群总功率预测[J].电子设计工程,2019,27(23):64-67. |
WEI M S, LU Z J, XU J Q,et al .Prediction of total power of grid-connected wind farm based on big data model[J].Electronic Design Engineering,2019,27(23):64-67. | |
45 | 赵川,孙华利,王国平,等 .基于大数据的电力信息系统网络安全分析[J].电子设计工程,2019,27(23):148-152. |
ZHAO C, SUN H L, WANG G P,et al .Network security analysis of power information system based on big data[J].Electronic Design Engineering,2019,27(23):148-152. | |
46 | 赵俊华,文福拴,薛禹胜,等 .云计算:构建未来电力系统的核心计算平台[J].电力系统自动化,2010,34(48):1-8. |
ZHAO J H, WEN F S, XUE Y S,et al .Cloud computing:the core computing platform for building future power systems[J].Automation of Electric Power Systems,2010,34(48):1-8. | |
47 | TONG J, WU H, LIN Y,et al .Fog-computing-based short-circuit diagnosis scheme[J].IEEE Transactions on Smart Grid,2020,11(4):3359-3371. doi:10.1109/tsg.2020.2964805 |
48 | PENG N, LIANG R, WANG G,et al .Edge computing based fault location in distribution networks by using asynchronous transient amplitudes at limited nodes[J].IEEE Transactions on Smart Grid,2021,12(1):574-588. doi:10.1109/tsg.2020.3009005 |
49 | LIU Y, YANG C, JIANG L,et al .Intelligent edge computing for IoT-based energy management in smart cities[J].IEEE Network,2019,33(2):111-117. doi:10.1109/mnet.2019.1800254 |
50 | IBRAHIM M S, DONG W, YANG Q .Machine learning driven smart electric power systems:current trends and new perspectives[J].Applied Energy,2020,272:115237. doi:10.1016/j.apenergy.2020.115237 |
51 | OGUZ K .Big data applications in the energy sector[M].Portugal:Instituto Superior Tecnico,2017. doi:10.23919/ropaces.2017.7916057 |
52 | JIAO R, HUANG X, MA X,et al .A model combining stacked auto encoder and back propagation algorithm for short-term wind power forecasting[J].IEEE Access,2018,6:17851-17858. doi:10.1109/access.2018.2818108 |
53 | ONETO L, LAURERI F, ROBBA M,et al .Data-driven photovoltaic power production nowcasting and forecasting for polygeneration microgrids[J].IEEE Systems Journal,2017,12(3):2842-2853. doi:10.1109/jsyst.2017.2688359 |
54 | KONG W, DONG Z Y, JIA Y,et al . Short-term residential load forecasting based on LSTM recurrent neural network[J].IEEE Transactions on Smart Grid,2017,10(1):841-851. |
55 | WANG S, WANG X, WANG S,et al .Bi-directional long short-term memory method based on attention mechanism and rolling update for short-term load forecasting[J].International Journal of Electrical Power & Energy Systems,2019,109:470-479. doi:10.1016/j.ijepes.2019.02.022 |
56 | RAFIEI M, NIKNAM T, AGHAEI J,et al .Probabilistic load forecasting using an improved wavelet neural network trained by generalized extreme learning machine[J].IEEE Transactions on Smart Grid,2018,9(6):6961-6971. doi:10.1109/tsg.2018.2807845 |
57 | YIN L, GAO Q, ZHAO L,et al .Expandable deep learning for real-time economic generation dispatch and control of three-state energies based future smart grids[J].Energy,2020,191:116561. doi:10.1016/j.energy.2019.116561 |
58 | ZHANG X S, LI Q, YU T,et al .Consensus transfer Q-learning for decentralized generation command dispatch based on virtual generation tribe[J].IEEE Transactions on Smart Grid,2016,9(3):2152-2165. doi:10.1109/tsg.2016.2607801 |
59 | ISLAM M, LEE G, HETTIWATTE S N,et al .Calculating a health index for power transformers using a subsystem-based GRNN approach[J].IEEE Transactions on Power Delivery,2017,33(4):1903-1912. doi:10.1109/tpwrd.2017.2770166 |
60 | PENG X, YANG F, WANG G,et al .A convolutional neural network-based deep learning methodology for recognition of partial discharge patterns from high-voltage cables[J].IEEE Transactions on Power Delivery,2019,34(4):1460-1469. doi:10.1109/tpwrd.2019.2906086 |
61 | YAO S, KANG Q, ZHOU M,et al .Intelligent and data-driven fault detection of photovoltaic plants[J].Processes,2021,9(10):1711. doi:10.3390/pr9101711 |
62 | ABDELGAYED T S, MORSI W G, SIDHU T S .A new approach for fault classification in microgrids using optimal wavelet functions matching pursuit[J].IEEE Transactions on Smart Grid,2017,9(5):4838-4846. doi:10.1109/tsg.2017.2672881 |
63 | LIVANI H, EVRENOSOGLU C Y .A machine learning and wavelet-based fault location method for hybrid transmission lines[J].IEEE Transactions on Smart Grid,2013,5(1):51-59. doi:10.1109/tsg.2013.2260421 |
64 | LAAKI H, MICHE Y, TAMMI K .Prototyping a digital twin for real time remote control over mobile networks:application of remote surgery[J].IEEE Access,2019,7:20325-20336. doi:10.1109/access.2019.2897018 |
65 | GOMES Jr D L, DE PAIVA A C, SILVA A C,et al .Augmented visualization using homomorphic filtering and Haar-based natural markers for power systems substations[J].Computers in Industry,2018,97:67-75. doi:10.1016/j.compind.2018.01.010 |
66 | GORSKI F, GRAJEWSKI D,BUN P,et al .Study of interaction methods in virtual electrician training[J].IEEE Access,2021,9:118242-118252. doi:10.1109/access.2021.3106826 |
67 | 宋慧娟 .基于混合现实的人工智能在电力巡检中的应用[J].电网与清洁能源,2020,36(2):75-79. |
SONG H J .Application of artificial intelligence based on mixed reality in power inspection[J].Power System and Clean Energy,2020,36(2):75-79. | |
68 | 肖东裕,谢旭琛,王慧豪,等 .基于虚拟成像技术的变电站运维系统设计[J].通信电源技术,2019,36(8):46-47. |
XIAO D Y, XIE X C, WANG H H,et al .Design of substation operation and maintenance system based on virtual imaging technology[J].Telecom Power Technology,2019,36(8):46-47. | |
69 | ZHANG P, LI F, BHATT N .Next-generation monitoring,analysis,and control for the future smart control center[J].IEEE Transactions on Smart Grid,2010,1(2):186-192. doi:10.1109/tsg.2010.2053855 |
70 | CHAE C H, JUNG N J, KO K H .Mobile power facilities maintenance system using augmented reality[J].Journal of Electrical Engineering & Technology,2021:1-13. doi:10.1007/s42835-021-00942-y |
71 | DAVIDSON E M, MCARTHUR S D J, MCDONALD J R,et al .Applying multi-agent system technology in practice:automated management and analysis of SCADA and digital fault recorder data[J].IEEE Transactions on Power Systems,2006,21(2):559-567. doi:10.1109/tpwrs.2006.873109 |
72 | TU C, HE X, SHUAI Z,et al .Big data issues in smart grid:a review[J].Renewable and Sustainable Energy Reviews,2017,79:1099-1107. doi:10.1016/j.rser.2017.05.134 |
73 | BAZMOHAMMADI N, MADARY A, VASQUEZ J C,et al .Microgrid digital twins:concepts,applications,and future trends[J].IEEE Access,2021,10:2284-2302. doi:10.1109/access.2021.3138990 |
74 | 周博文,奚超,李广地,等 .元宇宙在电力系统中的应用[J].发电技术,2022,43(1):1-9. doi:10.12096/j.2096-4528.pgt.21144 |
ZHOU B W, XI C, LI G D,et al .Metaverse application in power systems[J].Power Generation Technology,2022,43(1):1-9. doi:10.12096/j.2096-4528.pgt.21144 | |
75 | SAAD A, FADDEL S, YOUSSEF T,et al .On the implementation of IoT-based digital twin for networked microgrids resiliency against cyber attacks[J].IEEE Transactions on Smart Grid,2020,11(6):5138-5150. doi:10.1109/tsg.2020.3000958 |
76 | JAIN P, POON J, SINGH J P,et al .A digital twin approach for fault diagnosis in distributed photovoltaic systems[J].IEEE Transactions on Power Electronics,2019,35(1):940-956. doi:10.1109/tpel.2019.2911594 |
77 | BRANDTSTAEDTER H, LUDWIG C, HUBNER L,et al .Digital twins for large electric drive trains[C]//2018 Petroleum and Chemical Industry Conference Europe (PCIC Europe).2018:1-5. doi:10.23919/pciceurope.2018.8491413 |
78 | NOWOCIN J K .Microgrid risk reduction for design and validation testing using controller hardware in the loop[D].Massachusetts:Massachusetts Institute of Technology,2017. |
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