IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v177y2023ics1364032123000850.html
   My bibliography  Save this article

IntelliSense technology in the new power systems

Author

Listed:
  • Xie, Haonan
  • Jiang, Meihui
  • Zhang, Dongdong
  • Goh, Hui Hwang
  • Ahmad, Tanveer
  • Liu, Hui
  • Liu, Tianhao
  • Wang, Shuyao
  • Wu, Thomas

Abstract

The energy and climate crises have accelerated the decarbonization of electric power systems. An important part of this decarbonization process, along with the incorporation of renewable and alternative energies, is the emergence of Carbon-neutral, intelligent systems technologies, coupled with digital transformation. These have brought new dynamics to the electric power systems transformation. Significant amounts of renewable energy, massive power electronics, changes in market planning, policy influence, demand response, and emerging technologies all become the essential components of new power systems, bringing remarkable changes to this new power systems' enabling technologies: IntelliSense. A novel IntelliSense framework driven by new power system requirements is proposed. The development status, classification characteristics, the application of intelligent sensors, intelligent sensor flexible charging, and multisource plus multidimensional big data processing are all discussed in detail. They are interspersed with discussions of critical features of new power systems, the uncertainties inherent in big data about power, wireless power transfer technologies, edge-fog-cloud collaborative computing, intelligent algorithms, and other core elements of IntelliSense. Finally, ten core IntelliSense technology challenges and five major future opportunities are summarized and are expected to serve as a reference and spark new ideas for low-carbon power system development.

Suggested Citation

  • Xie, Haonan & Jiang, Meihui & Zhang, Dongdong & Goh, Hui Hwang & Ahmad, Tanveer & Liu, Hui & Liu, Tianhao & Wang, Shuyao & Wu, Thomas, 2023. "IntelliSense technology in the new power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
  • Handle: RePEc:eee:rensus:v:177:y:2023:i:c:s1364032123000850
    DOI: 10.1016/j.rser.2023.113229
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032123000850
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2023.113229?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Qi, Nanjian & Yin, Yajiang & Dai, Keren & Wu, Chengjun & Wang, Xiaofeng & You, Zheng, 2021. "Comprehensive optimized hybrid energy storage system for long-life solar-powered wireless sensor network nodes," Applied Energy, Elsevier, vol. 290(C).
    2. Li, Yang & Zhang, Meng & Chen, Chen, 2022. "A Deep-Learning intelligent system incorporating data augmentation for Short-Term voltage stability assessment of power systems," Applied Energy, Elsevier, vol. 308(C).
    3. Maciej Chojowski & Aleksander Dziadecki & Marcin Baszyński & Roman Dudek & Andrzej Stobiecki & Józef Skotniczny, 2021. "Wide Bandwidth and Inexpensive Current Sensor for Power Electronics—An Augmented LEM Current Sensor," Energies, MDPI, vol. 14(14), pages 1-14, July.
    4. Yucekaya, A., 2022. "Electricity trading for coal-fired power plants in Turkish power market considering uncertainty in spot, derivatives and bilateral contract market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    5. Guerrero-Lemus, R. & Cañadillas-Ramallo, D. & Reindl, T. & Valle-Feijóo, J.M., 2019. "A simple big data methodology and analysis of the specific yield of all PV power plants in a power system over a long time period," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 123-132.
    6. Ashraf Virk, Mati-ur-Rasool & Mysorewala, Muhammad Faizan & Cheded, Lahouari & Aliyu, AbdulRahman, 2022. "Review of energy harvesting techniques in wireless sensor-based pipeline monitoring networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    7. Shafie, S.M. & Mahlia, T.M.I. & Masjuki, H.H. & Andriyana, A., 2011. "Current energy usage and sustainable energy in Malaysia: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4370-4377.
    8. Marszal-Pomianowska, Anna & Widén, Joakim & Le Dréau, Jérôme & Heiselberg, Per & Bak-Jensen, Birgitte & de Cerio Mendaza, Iker Diaz, 2020. "Operation of power distribution networks with new and flexible loads: A case of existing residential low voltage network," Energy, Elsevier, vol. 202(C).
    9. Song, Yingjie & Ji, Qiang & Du, Ya-Juan & Geng, Jiang-Bo, 2019. "The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets," Energy Economics, Elsevier, vol. 84(C).
    10. Yanine, Franco F. & Sauma, Enzo E., 2013. "Review of grid-tie micro-generation systems without energy storage: Towards a new approach to sustainable hybrid energy systems linked to energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 60-95.
    11. Yanine, Franco Fernando & Caballero, Federico I. & Sauma, Enzo E. & Córdova, Felisa M., 2014. "Building sustainable energy systems: Homeostatic control of grid-connected microgrids, as a means to reconcile power supply and energy demand response management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 1168-1191.
    12. Skea, Jim & van Diemen, Renée & Portugal-Pereira, Joana & Khourdajie, Alaa Al, 2021. "Outlooks, explorations and normative scenarios: Approaches to global energy futures compared," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    13. Yanine, Franco Fernando & Caballero, Federico I. & Sauma, Enzo E. & Córdova, Felisa M., 2014. "Homeostatic control, smart metering and efficient energy supply and consumption criteria: A means to building more sustainable hybrid micro-generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 235-258.
    14. Edmonds, Lawryn & Derby, Melanie & Hill, Mary & Wu, Hongyu, 2021. "Coordinated operation of water and electricity distribution networks with variable renewable energy and distribution locational marginal pricing," Renewable Energy, Elsevier, vol. 177(C), pages 1438-1450.
    15. Hafeez, Ghulam & Khan, Imran & Jan, Sadaqat & Shah, Ibrar Ali & Khan, Farrukh Aslam & Derhab, Abdelouahid, 2021. "A novel hybrid load forecasting framework with intelligent feature engineering and optimization algorithm in smart grid," Applied Energy, Elsevier, vol. 299(C).
    16. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    17. Fei Lu & Hua Zhang & Chris Mi, 2017. "A Review on the Recent Development of Capacitive Wireless Power Transfer Technology," Energies, MDPI, vol. 10(11), pages 1-30, November.
    18. Li, Fuxiang & Wu, Wei, 2022. "Coupled electrical-thermal performance estimation of photovoltaic devices: A transient multiphysics framework with robust parameter extraction and 3-D thermal analysis," Applied Energy, Elsevier, vol. 319(C).
    19. Yanine, Fernando & Sanchez-Squella, Antonio & Barrueto, Aldo & Tosso, Joshua & Cordova, Felisa M. & Rother, Hans C., 2018. "Reviewing homeostasis of sustainable energy systems: How reactive and predictive homeostasis can enable electric utilities to operate distributed generation as part of their power supply services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2879-2892.
    20. Li, Shuijia & Gong, Wenyin & Gu, Qiong, 2021. "A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    21. Gjorgiev, Blazhe & Sansavini, Giovanni, 2022. "Identifying and assessing power system vulnerabilities to transmission asset outages via cascading failure analysis," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    22. Yu, Songyuan & Fang, Fang & Liu, Yajuan & Liu, Jizhen, 2019. "Uncertainties of virtual power plant: Problems and countermeasures," Applied Energy, Elsevier, vol. 239(C), pages 454-470.
    23. Andrzej Wetula & Andrzej Bień & Mrunal Parekh, 2021. "New Sensor for Medium- and High-Voltage Measurement," Energies, MDPI, vol. 14(15), pages 1-12, July.
    24. Chhawchharia, Saransch & Sahoo, Sarat Kumar & Balamurugan, M. & Sukchai, Sukruedee & Yanine, Fernando, 2018. "Investigation of wireless power transfer applications with a focus on renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 888-902.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mukhopadhyay, Bineeta & Das, Debapriya, 2020. "Multi-objective dynamic and static reconfiguration with optimized allocation of PV-DG and battery energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    2. Roslan, M.F. & Hannan, M.A. & Ker, Pin Jern & Uddin, M.N., 2019. "Microgrid control methods toward achieving sustainable energy management," Applied Energy, Elsevier, vol. 240(C), pages 583-607.
    3. Yanine, Fernando & Sanchez-Squella, Antonio & Barrueto, Aldo & Tosso, Joshua & Cordova, Felisa M. & Rother, Hans C., 2018. "Reviewing homeostasis of sustainable energy systems: How reactive and predictive homeostasis can enable electric utilities to operate distributed generation as part of their power supply services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2879-2892.
    4. Zia, Muhammad Fahad & Elbouchikhi, Elhoussin & Benbouzid, Mohamed, 2018. "Microgrids energy management systems: A critical review on methods, solutions, and prospects," Applied Energy, Elsevier, vol. 222(C), pages 1033-1055.
    5. Antonio Parejo & Antonio Sanchez-Squella & Rodrigo Barraza & Fernando Yanine & Aldo Barrueto-Guzman & Carlos Leon, 2019. "Design and Simulation of an Energy Homeostaticity System for Electric and Thermal Power Management in a Building with Smart Microgrid," Energies, MDPI, vol. 12(9), pages 1-19, May.
    6. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao & Tang, Bowen, 2017. "Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system," Applied Energy, Elsevier, vol. 190(C), pages 1126-1137.
    7. Yanine, Franco Fernando & Caballero, Federico I. & Sauma, Enzo E. & Córdova, Felisa M., 2014. "Building sustainable energy systems: Homeostatic control of grid-connected microgrids, as a means to reconcile power supply and energy demand response management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 1168-1191.
    8. Qiao, Sen & Guo, Zi Xin & Tao, Zhang & Ren, Zheng Yu, 2023. "Analyzing the network structure of risk transmission among renewable, non-renewable energy and carbon markets," Renewable Energy, Elsevier, vol. 209(C), pages 206-217.
    9. Muhammad Kashif & Thomas Leirvik, 2022. "The MAX Effect in an Oil Exporting Country: The Case of Norway," JRFM, MDPI, vol. 15(4), pages 1-16, March.
    10. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    11. Shen, Yiran & Liu, Chang & Sun, Xiaolei & Guo, Kun, 2023. "Investor sentiment and the Chinese new energy stock market: A risk–return perspective," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 395-408.
    12. Ruikun Mai & Youyuan Zhang & Ruimin Dai & Yang Chen & Zhengyou He, 2018. "A Three-Coil Inductively Power Transfer System with Constant Voltage Output," Energies, MDPI, vol. 11(3), pages 1-13, March.
    13. Jing, Ong Li & Bashir, Mohammed J.K. & Kao, Jehng-Jung, 2015. "Solar radiation based benefit and cost evaluation for solar water heater expansion in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 328-335.
    14. Zhijie Sasha Dong & Lingyu Meng & Lauren Christenson & Lawrence Fulton, 2021. "Social media information sharing for natural disaster response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2077-2104, July.
    15. Song, Huiling & Wang, Chang & Lei, Xiaojie & Zhang, Hongwei, 2022. "Dynamic dependence between main-byproduct metals and the role of clean energy market," Energy Economics, Elsevier, vol. 108(C).
    16. Svetlana Drobyazko & Suparna Wijaya & Pavel Blecharz & Sergii Bogachov & Milyausha Pinskaya, 2021. "Modeling of Prospects for the Development of Regional Renewable Energy," Energies, MDPI, vol. 14(8), pages 1-17, April.
    17. Nasrin Aghamohammadi & Stacy Simai Reginald & Ahmad Shamiri & Ali Akbar Zinatizadeh & Li Ping Wong & Nik Meriam Binti Nik Sulaiman, 2016. "An Investigation of Sustainable Power Generation from Oil Palm Biomass: A Case Study in Sarawak," Sustainability, MDPI, vol. 8(5), pages 1-19, April.
    18. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    19. Wu, Han & Liang, Yan & Heng, Jiani, 2023. "Pulse-diagnosis-inspired multi-feature extraction deep network for short-term electricity load forecasting," Applied Energy, Elsevier, vol. 339(C).
    20. Nor, Khalid Mohamed & Shaaban, Mohamed & Abdul Rahman, Hasimah, 2014. "Feasibility assessment of wind energy resources in Malaysia based on NWP models," Renewable Energy, Elsevier, vol. 62(C), pages 147-154.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:177:y:2023:i:c:s1364032123000850. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.