IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i17p6292-d900474.html
   My bibliography  Save this article

Multivariate Empirical Mode Decomposition and Recurrence Quantification for the Multiscale, Spatiotemporal Analysis of Electricity Demand—A Case Study of Japan

Author

Listed:
  • Rémi Delage

    (Department of Management Science and Technology, Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan)

  • Toshihiko Nakata

    (Department of Management Science and Technology, Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan)

Abstract

In the new energy systems’ modeling paradigm with high temporal and spatial resolutions, the complexity of renewable resources and demand dynamics is a major obstacle for the scenario analysis of future energy systems and the design of sustainable solutions. Most advanced models are indeed currently restricted by past temporal energy demand data, improper for the analysis of future systems and often insufficient in terms of quantity or spatial resolution. A deeper understanding on energy demand dynamics is thus necessary to improve energy system models and expand their possibilities. The present study introduces noise-assisted multivariate empirical mode decomposition and recurrence quantification analysis for the study of this problematic variable with a case study of Japan’s electricity demand data per region. These tools are adapted to nonlinear, complex systems’ data and are already applied in a wide range of scientific fields including climate studies. The decomposition of electricity demand as well as the detection of irregularities in its dynamics allow to identify relations with temperature variations, demand sector shares, life style and local culture at different temporal scales.

Suggested Citation

  • Rémi Delage & Toshihiko Nakata, 2022. "Multivariate Empirical Mode Decomposition and Recurrence Quantification for the Multiscale, Spatiotemporal Analysis of Electricity Demand—A Case Study of Japan," Energies, MDPI, vol. 15(17), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6292-:d:900474
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/17/6292/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/17/6292/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Calikus, Ece & Nowaczyk, Sławomir & Sant'Anna, Anita & Gadd, Henrik & Werner, Sven, 2019. "A data-driven approach for discovering heat load patterns in district heating," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    2. Karsten Neuhoff & Stefan Bach & Jochen Diekmann & Martin Beznoska & Tarik El-Laboudy, 2013. "Distributional Effects of Energy Transition: Impacts of Renewable Electricity Support in Germany," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    3. Rodríguez, Rolando A. & Becker, Sarah & Andresen, Gorm B. & Heide, Dominik & Greiner, Martin, 2014. "Transmission needs across a fully renewable European power system," Renewable Energy, Elsevier, vol. 63(C), pages 467-476.
    4. Zhou, Yue & Wu, Jianzhong & Long, Chao, 2018. "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework," Applied Energy, Elsevier, vol. 222(C), pages 993-1022.
    5. Varun Rai & Adam Douglas Henry, 2016. "Agent-based modelling of consumer energy choices," Nature Climate Change, Nature, vol. 6(6), pages 556-562, June.
    6. Amir Mosavi & Mohsen Salimi & Sina Faizollahzadeh Ardabili & Timon Rabczuk & Shahaboddin Shamshirband & Annamaria R. Varkonyi-Koczy, 2019. "State of the Art of Machine Learning Models in Energy Systems, a Systematic Review," Energies, MDPI, vol. 12(7), pages 1-42, April.
    7. Marc Deissenroth & Martin Klein & Kristina Nienhaus & Matthias Reeg, 2017. "Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration," Complexity, Hindawi, vol. 2017, pages 1-24, December.
    8. Rémi Delage & Taichi Matsuoka & Toshihiko Nakata, 2021. "Spatial–Temporal Estimation and Analysis of Japan Onshore and Offshore Wind Energy Potential," Energies, MDPI, vol. 14(8), pages 1-12, April.
    9. Charakopoulos, Avraam & Karakasidis, Theodoros & Sarris, loannis, 2019. "Pattern identification for wind power forecasting via complex network and recurrence plot time series analysis," Energy Policy, Elsevier, vol. 133(C).
    10. Martin Robinius & Alexander Otto & Philipp Heuser & Lara Welder & Konstantinos Syranidis & David S. Ryberg & Thomas Grube & Peter Markewitz & Ralf Peters & Detlef Stolten, 2017. "Linking the Power and Transport Sectors—Part 1: The Principle of Sector Coupling," Energies, MDPI, vol. 10(7), pages 1-22, July.
    11. Thomas Morstyn & Niall Farrell & Sarah J. Darby & Malcolm D. McCulloch, 2018. "Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants," Nature Energy, Nature, vol. 3(2), pages 94-101, February.
    12. Brown, T. & Schlachtberger, D. & Kies, A. & Schramm, S. & Greiner, M., 2018. "Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system," Energy, Elsevier, vol. 160(C), pages 720-739.
    13. Bale, Catherine S.E. & Varga, Liz & Foxon, Timothy J., 2015. "Energy and complexity: New ways forward," Applied Energy, Elsevier, vol. 138(C), pages 150-159.
    Full references (including those not matched with items on IDEAS)

    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. Rémi Delage & Taichi Matsuoka & Toshihiko Nakata, 2021. "Spatial–Temporal Estimation and Analysis of Japan Onshore and Offshore Wind Energy Potential," Energies, MDPI, vol. 14(8), pages 1-12, April.
    2. Fridgen, Gilbert & Keller, Robert & Körner, Marc-Fabian & Schöpf, Michael, 2020. "A holistic view on sector coupling," Energy Policy, Elsevier, vol. 147(C).
    3. Kobashi, Takuro & Yoshida, Takahiro & Yamagata, Yoshiki & Naito, Katsuhiko & Pfenninger, Stefan & Say, Kelvin & Takeda, Yasuhiro & Ahl, Amanda & Yarime, Masaru & Hara, Keishiro, 2020. "On the potential of “Photovoltaics + Electric vehicles” for deep decarbonization of Kyoto’s power systems: Techno-economic-social considerations," Applied Energy, Elsevier, vol. 275(C).
    4. Amir Ali Safaei Pirooz & Mohammad J. Sanjari & Young-Jin Kim & Stuart Moore & Richard Turner & Wayne W. Weaver & Dipti Srinivasan & Josep M. Guerrero & Mohammad Shahidehpour, 2023. "Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation," Energies, MDPI, vol. 16(8), pages 1-16, April.
    5. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    6. Maruf, Md. Nasimul Islam, 2021. "Open model-based analysis of a 100% renewable and sector-coupled energy system–The case of Germany in 2050," Applied Energy, Elsevier, vol. 288(C).
    7. Min-Hwi Kim & Dong-Won Lee & Deuk-Won Kim & Young-Sub An & Jae-Ho Yun, 2021. "Energy Performance Investigation of Bi-Directional Convergence Energy Prosumers for an Energy Sharing Community," Energies, MDPI, vol. 14(17), pages 1-17, September.
    8. Stefan Arens & Sunke Schlüters & Benedikt Hanke & Karsten von Maydell & Carsten Agert, 2020. "Sustainable Residential Energy Supply: A Literature Review-Based Morphological Analysis," Energies, MDPI, vol. 13(2), pages 1-28, January.
    9. Ma, Li & Wang, Lingfeng & Liu, Zhaoxi, 2021. "Multi-level trading community formation and hybrid trading network construction in local energy market," Applied Energy, Elsevier, vol. 285(C).
    10. Els van der Roest & Stijn Beernink & Niels Hartog & Jan Peter van der Hoek & Martin Bloemendal, 2021. "Towards Sustainable Heat Supply with Decentralized Multi-Energy Systems by Integration of Subsurface Seasonal Heat Storage," Energies, MDPI, vol. 14(23), pages 1-31, November.
    11. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    12. Ahl, A. & Yarime, M. & Goto, M. & Chopra, Shauhrat S. & Kumar, Nallapaneni Manoj. & Tanaka, K. & Sagawa, D., 2020. "Exploring blockchain for the energy transition: Opportunities and challenges based on a case study in Japan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    13. Stöckl, Fabian & Schill, Wolf-Peter & Zerrahn, Alexander, 2021. "Optimal supply chains and power sector benefits of green hydrogen," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11.
    14. Els van der Roest & Theo Fens & Martin Bloemendal & Stijn Beernink & Jan Peter van der Hoek & Ad J. M. van Wijk, 2021. "The Impact of System Integration on System Costs of a Neighborhood Energy and Water System," Energies, MDPI, vol. 14(9), pages 1-33, May.
    15. Yuki Matsuda & Yuto Yamazaki & Hiromu Oki & Yasuhiro Takeda & Daishi Sagawa & Kenji Tanaka, 2021. "Demonstration of Blockchain Based Peer to Peer Energy Trading System with Real-Life Used PHEV and HEMS Charge Control," Energies, MDPI, vol. 14(22), pages 1-12, November.
    16. Jasmine Ramsebner & Reinhard Haas & Amela Ajanovic & Martin Wietschel, 2021. "The sector coupling concept: A critical review," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(4), July.
    17. Child, Michael & Kemfert, Claudia & Bogdanov, Dmitrii & Breyer, Christian, 2019. "Flexible electricity generation, grid exchange and storage for the transition to a 100% renewable energy system in Europe," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 139, pages 80-101.
    18. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    19. Milad Afzalan & Farrokh Jazizadeh, 2021. "Quantification of Demand-Supply Balancing Capacity among Prosumers and Consumers: Community Self-Sufficiency Assessment for Energy Trading," Energies, MDPI, vol. 14(14), pages 1-21, July.
    20. Georg Holtz & Christian Schnülle & Malcolm Yadack & Jonas Friege & Thorben Jensen & Pablo Thier & Peter Viebahn & Émile J. L. Chappin, 2020. "Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies," Energies, MDPI, vol. 13(22), pages 1-26, November.

    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:gam:jeners:v:15:y:2022:i:17:p:6292-:d:900474. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.