IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v14y2023i5d10.1007_s13198-023-01983-4.html
   My bibliography  Save this article

An efficient way to schedule dispersed generators for a microgrid system's economical operation under various power market conditions and grid involvement

Author

Listed:
  • Srikant Misra

    (GIET University)

  • P. K. Panigrahi

    (GIET University)

  • Bishwajit Dey

    (IIT (Indian School of Mines)
    Adani University, Shantigram)

Abstract

A microgrid is a collection of distributed energy resources (DERs) It might encompass both traditional and unconventional energy sources. The way a microgrid functions determines whether it is categorized as either islanded or grid-connected. The focus of this study is to explore five different optimal scheduling operation scenarios for Distributed Energy Resources (DERs) with the aim of achieving economic benefits for a low voltage microgrid system. The scenarios being studied are developed using several approaches to grid participation and pricing strategies within the power market. The optimization tool used in the research was the Crow Search Algorithm (CSA), a widely recognized and recently developed algorithm known for its speed and efficiency. The results of the study indicate that the microgrid's most profitable operational scenario involved active participation of the grid in the purchase and sale of electricity, utilizing a dynamic pricing approach based on time-of-usage (TOU). Based on numerical data, the Crow Search Algorithm method produced solutions of superior quality in less time compared to several other algorithms with similar designs that were employed in the study. The CSA approach was able to achieve this consistently, regardless of the scale of the problem being addressed.

Suggested Citation

  • Srikant Misra & P. K. Panigrahi & Bishwajit Dey, 2023. "An efficient way to schedule dispersed generators for a microgrid system's economical operation under various power market conditions and grid involvement," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1799-1809, October.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:5:d:10.1007_s13198-023-01983-4
    DOI: 10.1007/s13198-023-01983-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-023-01983-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-023-01983-4?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. Yuan, Xiaohui & Su, Anjun & Yuan, Yanbin & Nie, Hao & Wang, Liang, 2009. "An improved PSO for dynamic load dispatch of generators with valve-point effects," Energy, Elsevier, vol. 34(1), pages 67-74.
    2. Wu, Kunming & Li, Qiang & Chen, Ziyu & Lin, Jiayang & Yi, Yongli & Chen, Minyou, 2021. "Distributed optimization method with weighted gradients for economic dispatch problem of multi-microgrid systems," Energy, Elsevier, vol. 222(C).
    3. Ma, Haiping & Yang, Zhile & You, Pengcheng & Fei, Minrui, 2017. "Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging," Energy, Elsevier, vol. 135(C), pages 101-111.
    4. Dai, Wei & Yang, Zhifang & Yu, Juan & Cui, Wei & Li, Wenyuan & Li, Jinghua & Liu, Hui, 2021. "Economic dispatch of interconnected networks considering hidden flexibility," Energy, Elsevier, vol. 223(C).
    5. Toopshekan, Ashkan & Yousefi, Hossein & Astaraei, Fatemeh Razi, 2020. "Technical, economic, and performance analysis of a hybrid energy system using a novel dispatch strategy," Energy, Elsevier, vol. 213(C).
    6. Roy, Sanjoy, 2018. "The maximum likelihood optima for an economic load dispatch in presence of demand and generation variability," Energy, Elsevier, vol. 147(C), pages 915-923.
    7. Singh, Diljinder & Dhillon, J.S., 2019. "Ameliorated grey wolf optimization for economic load dispatch problem," Energy, Elsevier, vol. 169(C), pages 398-419.
    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. Swarupa Pinninti & Srinivasa Rao Sura, 2023. "Renewables based dynamic cost-effective optimal scheduling of distributed generators using teaching–learning-based optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 353-373, March.
    2. Sourav Basak & Bishwajit Dey & Biplab Bhattacharyya, 2023. "Uncertainty-based dynamic economic dispatch for diverse load and wind profiles using a novel hybrid algorithm," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(5), pages 4723-4763, May.
    3. Sourav Basak & Biplab Bhattacharyya & Bishwajit Dey, 2022. "Combined economic emission dispatch on dynamic systems using hybrid CSA-JAYA Algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2269-2290, October.
    4. Loau Al-Bahrani & Mehdi Seyedmahmoudian & Ben Horan & Alex Stojcevski, 2021. "Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
    5. Le Chi Kien & Thanh Long Duong & Van-Duc Phan & Thang Trung Nguyen, 2020. "Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization," Sustainability, MDPI, vol. 12(3), pages 1-35, February.
    6. Lingling Li & Jiarui Pei & Qiang Shen, 2023. "A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids," Energies, MDPI, vol. 16(10), pages 1-23, May.
    7. Mohammadi-ivatloo, Behnam & Rabiee, Abbas & Soroudi, Alireza & Ehsan, Mehdi, 2012. "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch," Energy, Elsevier, vol. 44(1), pages 228-240.
    8. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Roosta, Alireza & Amiri, Babak, 2012. "A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch," Energy, Elsevier, vol. 42(1), pages 530-545.
    9. Narang, Nitin & Dhillon, J.S. & Kothari, D.P., 2012. "Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method," Energy, Elsevier, vol. 47(1), pages 237-252.
    10. Ghulam Abbas & Irfan Ahmad Khan & Naveed Ashraf & Muhammad Taskeen Raza & Muhammad Rashad & Raheel Muzzammel, 2023. "On Employing a Constrained Nonlinear Optimizer to Constrained Economic Dispatch Problems," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    11. Soares, J. & Silva, M. & Sousa, T. & Vale, Z. & Morais, H., 2012. "Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization," Energy, Elsevier, vol. 42(1), pages 466-476.
    12. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Shamim, Tariq & Domenighini, Piergiovanni & Cotana, Franco & Wang, Jinwen & Fantozzi, Francesco & Bianchi, Francesco, 2023. "Transition toward net zero emissions - Integration and optimization of renewable energy sources: Solar, hydro, and biomass with the local grid station in central Italy," Renewable Energy, Elsevier, vol. 207(C), pages 672-686.
    13. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "Reserve constrained dynamic optimal power flow subject to valve-point effects, prohibited zones and multi-fuel constraints," Energy, Elsevier, vol. 47(1), pages 451-464.
    14. Mousavi, Seyed Ali & Toopshekan, Ashkan & Mehrpooya, Mehdi & Delpisheh, Mostafa, 2023. "Comprehensive exergetic performance assessment and techno-financial optimization of off-grid hybrid renewable configurations with various dispatch strategies and solar tracking systems," Renewable Energy, Elsevier, vol. 210(C), pages 40-63.
    15. Zhou, Xu & Ma, Zhongjing & Zou, Suli & Zhang, Jinhui, 2022. "Consensus-based distributed economic dispatch for Multi Micro Energy Grid systems under coupled carbon emissions," Applied Energy, Elsevier, vol. 324(C).
    16. Tingli Cheng & Minyou Chen & Yingxiang Wang & Bo Li & Muhammad Arshad Shehzad Hassan & Tao Chen & Ruilin Xu, 2018. "Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage," Complexity, Hindawi, vol. 2018, pages 1-13, June.
    17. Li, Chaoshun & Wang, Wenxiao & Chen, Deshu, 2019. "Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer," Energy, Elsevier, vol. 171(C), pages 241-255.
    18. Rajakumar, R. & Sekaran, Kaushik & Hsu, Ching-Hsien & Kadry, Seifedine, 2021. "Accelerated grey wolf optimization for global optimization problems," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    19. Mengqi Zhao & Xiaoling Wang & Jia Yu & Lei Bi & Yao Xiao & Jun Zhang, 2020. "Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm," Energies, MDPI, vol. 13(1), pages 1-17, January.
    20. Panigrahi, B.K. & Ravikumar Pandi, V. & Das, Sanjoy & Das, Swagatam, 2010. "Multiobjective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatch problem," Energy, Elsevier, vol. 35(12), pages 4761-4770.

    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:spr:ijsaem:v:14:y:2023:i:5:d:10.1007_s13198-023-01983-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.