IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i3p690-d727468.html
   My bibliography  Save this article

Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

Author

Listed:
  • Jiming Chen

    (College of New Energy, China University of Petroleum (East China), Qingdao 266580, China)

  • Ke Ning

    (College of New Energy, China University of Petroleum (East China), Qingdao 266580, China)

  • Xingzhi Xin

    (Electric Power Branch Company of Shengli Oilfield, SINOPEC, Dongying 257001, China)

  • Fuhao Shi

    (Public Service Center of Shengli Oilfield, SINOPEC, Dongying 257001, China)

  • Qing Zhang

    (Qingdao Ruinengda Electrical Technology Limited Company, Qingdao 266580, China)

  • Chaolin Li

    (Qingdao Ruinengda Electrical Technology Limited Company, Qingdao 266580, China)

Abstract

The interdependency of electric and natural gas systems is becoming stronger. The challenge of how to meet various energy demands in an integrated energy system (IES) with minimal cost has drawn considerable attention. The optimal scheduling of IESs is an ideal method to solve this problem. In this study, a day-ahead optimal scheduling model for IES that included an electrical system, a natural gas system, and an energy hub (EH), was established. The proposed EH contained detailed models of the fuel cell (FC) and power to gas (P2G) system. Considering that the optimal scheduling of an IES is a non-convex complex optimal problem, a piecewise self-adaptive particle swarm optimization (PCAPSO) algorithm based on multistage chaotic mapping was proposed to solve it. The objective was to minimize the operating cost of the IES. Three operation scenarios were designed to analyze the operation characteristics of the system under different coupling conditions. The simulation results showed that the PCAPSO algorithm improved the convergence rate and stability compared to the original PSO. An analysis of the results demonstrated the economics of an IES with the proposed EHs and the advantage of cooperation between the FC and P2G system.

Suggested Citation

  • Jiming Chen & Ke Ning & Xingzhi Xin & Fuhao Shi & Qing Zhang & Chaolin Li, 2022. "Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 15(3), pages 1-18, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:690-:d:727468
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/3/690/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/3/690/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hoseinzadeh, Siamak & Ghasemi, Mohammad Hadi & Heyns, Stephan, 2020. "Application of hybrid systems in solution of low power generation at hot seasons for micro hydro systems," Renewable Energy, Elsevier, vol. 160(C), pages 323-332.
    2. Tomin, Nikita & Shakirov, Vladislav & Kozlov, Aleksander & Sidorov, Denis & Kurbatsky, Victor & Rehtanz, Christian & Lora, Electo E.S., 2022. "Design and optimal energy management of community microgrids with flexible renewable energy sources," Renewable Energy, Elsevier, vol. 183(C), pages 903-921.
    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. Christoforos Menos-Aikateriniadis & Ilias Lamprinos & Pavlos S. Georgilakis, 2022. "Particle Swarm Optimization in Residential Demand-Side Management: A Review on Scheduling and Control Algorithms for Demand Response Provision," Energies, MDPI, vol. 15(6), pages 1-26, March.
    2. Tingling Wang & Tianyu Huo & Huihang Li, 2024. "Bi-Layer Planning of Integrated Energy System by Incorporating Power-to-Gas and Ground Source Heat Pump for Curtailed Wind Power and Economic Cost Reduction," Energies, MDPI, vol. 17(6), pages 1-22, March.

    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. Sulman Shahzad & Muhammad Abbas Abbasi & Hassan Ali & Muhammad Iqbal & Rania Munir & Heybet Kilic, 2023. "Possibilities, Challenges, and Future Opportunities of Microgrids: A Review," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    2. Sima, Catalina Alexandra & Popescu, Claudia Laurenta & Popescu, Mihai Octavian & Roscia, Mariacristina & Seritan, George & Panait, Cornel, 2022. "Techno-economic assessment of university energy communities with on/off microgrid," Renewable Energy, Elsevier, vol. 193(C), pages 538-553.
    3. Fathy, Ahmed, 2023. "Bald eagle search optimizer-based energy management strategy for microgrid with renewable sources and electric vehicles," Applied Energy, Elsevier, vol. 334(C).
    4. Siamak Hoseinzadeh & Daniele Groppi & Adriana Scarlet Sferra & Umberto Di Matteo & Davide Astiaso Garcia, 2022. "The PRISMI Plus Toolkit Application to a Grid-Connected Mediterranean Island," Energies, MDPI, vol. 15(22), pages 1-14, November.
    5. Hoseinzadeh, Siamak & Astiaso Garcia, Davide & Huang, Lizhen, 2023. "Grid-connected renewable energy systems flexibility in Norway islands’ Decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    6. Eunsung Oh, 2022. "Fair Virtual Energy Storage System Operation for Smart Energy Communities," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    7. Weijie Zhou & Huimin Jiang & Jiaxin Chang, 2023. "Forecasting Renewable Energy Generation Based on a Novel Dynamic Accumulation Grey Seasonal Model," Sustainability, MDPI, vol. 15(16), pages 1-26, August.
    8. Qingqing He & Lei Liu & Mingyang Qiu & Quanming Luo, 2021. "A Step-by-Step Design for Low-Pass Input Filter of the Single-Stage Converter," Energies, MDPI, vol. 14(23), pages 1-25, November.
    9. Bruck, Axel & Díaz Ruano, Santiago & Auer, Hans, 2022. "One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective," Energy, Elsevier, vol. 254(PA).
    10. Gilani, Hooman Azad & Hoseinzadeh, Siamak & Karimi, Hirou & Karimi, Ako & Hassanzadeh, Amir & Garcia, Davide Astiaso, 2021. "Performance analysis of integrated solar heat pump VRF system for the low energy building in Mediterranean island," Renewable Energy, Elsevier, vol. 174(C), pages 1006-1019.
    11. Popescu, Daniela & Dragomirescu, Andrei, 2024. "Cost-benefit analysis of a hydro-solar microsystem with Archimedean screw hydro turbine sized for a prosumer building," Renewable Energy, Elsevier, vol. 226(C).
    12. Khan, Irfan & Hou, Fujun & Irfan, Muhammad & Zakari, Abdulrasheed & Le, Hoang Phong, 2021. "Does energy trilemma a driver of economic growth? The roles of energy use, population growth, and financial development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    13. Javier Parra-Domínguez & Esteban Sánchez & Ángel Ordóñez, 2023. "The Prosumer: A Systematic Review of the New Paradigm in Energy and Sustainable Development," Sustainability, MDPI, vol. 15(13), pages 1-44, July.
    14. Petrucci, Andrea & Ayevide, Follivi Kloutse & Buonomano, Annamaria & Athienitis, Andreas, 2023. "Development of energy aggregators for virtual communities: The energy efficiency-flexibility nexus for demand response," Renewable Energy, Elsevier, vol. 215(C).
    15. Hassan, Rakibul & Das, Barun K. & Hasan, Mahmudul, 2022. "Integrated off-grid hybrid renewable energy system optimization based on economic, environmental, and social indicators for sustainable development," Energy, Elsevier, vol. 250(C).
    16. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    17. Jie Liu & Quan Shi & Ruilian Han & Juan Yang, 2021. "A Hybrid GA–PSO–CNN Model for Ultra-Short-Term Wind Power Forecasting," Energies, MDPI, vol. 14(20), pages 1-22, October.
    18. Velásquez, Laura & Romero-Menco, Fredys & Rubio-Clemente, Ainhoa & Posada, Alejandro & Chica, Edwin, 2024. "Numerical optimization and experimental validation of the runner of a gravitational water vortex hydraulic turbine with a spiral inlet channel and a conical basin," Renewable Energy, Elsevier, vol. 220(C).
    19. Chang, Weiguang & Dong, Wei & Yang, Qiang, 2023. "Day-ahead bidding strategy of cloud energy storage serving multiple heterogeneous microgrids in the electricity market," Applied Energy, Elsevier, vol. 336(C).
    20. Zhang, Bin & Hu, Weihao & Xu, Xiao & Li, Tao & Zhang, Zhenyuan & Chen, Zhe, 2022. "Physical-model-free intelligent energy management for a grid-connected hybrid wind-microturbine-PV-EV energy system via deep reinforcement learning approach," Renewable Energy, Elsevier, vol. 200(C), pages 433-448.

    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:3:p:690-:d:727468. 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.