IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i11p1770-d117507.html
   My bibliography  Save this article

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

Author

Listed:
  • Vahid Amir

    (Department of Electrical Engineering, Faculty of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Shahram Jadid

    (Department of Electrical Engineering, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran)

  • Mehdi Ehsan

    (Department of Electrical Engineering, Faculty of Electrical Engineering, Sharif University of Technology, Tehran PO Box 1136511155, Iran)

Abstract

A microgrid (MG) is a small-scale version of the power system which makes possible the integration of renewable resources as well as achieving maximum demand side management (DSM) utilization. The future power system will be faced with severe uncertainties owing to penetration of renewable resources. Consequently, the uncertainty assessment of system performance is essential. The conventional energy scheduling in an MG may not be suitable for active distribution networks. Hence, this study focuses on the probabilistic analysis of optimal power dispatch considering economic aspects in a multi-carrier networked microgrid. The aim is to study the impact of uncertain behavior of loads, renewable resources, and electricity market on the optimal management of a multi-carrier networked microgrid. Furthermore, a novel time-based demand side management is proposed in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. The optimization model is formulated as a mixed integer nonlinear program (MINLP) and is solved using MATLAB and GAMS software. Results show that the energy sharing capability between MCMGs and MCMGs and the main grids as well as utilization of demand side management can decrease operating costs for smart distribution grids.

Suggested Citation

  • Vahid Amir & Shahram Jadid & Mehdi Ehsan, 2017. "Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties," Energies, MDPI, vol. 10(11), pages 1-21, November.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1770-:d:117507
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/11/1770/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/11/1770/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2016. "Robust Optimization-Based Scheduling of Multi-Microgrids Considering Uncertainties," Energies, MDPI, vol. 9(4), pages 1-21, April.
    2. Baziar, Aliasghar & Kavousi-Fard, Abdollah, 2013. "Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices," Renewable Energy, Elsevier, vol. 59(C), pages 158-166.
    3. Nah-Oak Song & Ji-Hye Lee & Hak-Man Kim, 2016. "Optimal Electric and Heat Energy Management of Multi-Microgrids with Sequentially-Coordinated Operations," Energies, MDPI, vol. 9(6), pages 1-18, June.
    4. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    5. Hao Liang & Weihua Zhuang, 2014. "Stochastic Modeling and Optimization in a Microgrid: A Survey," Energies, MDPI, vol. 7(4), pages 1-24, March.
    6. Kumbaroğlu, Gürkan & Madlener, Reinhard, 2011. "Evaluation of Economically Optimal Retrofit Investment Options for Energy Savings in Buildings," FCN Working Papers 14/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    7. Chongxin Huang & Dong Yue & Song Deng & Jun Xie, 2017. "Optimal Scheduling of Microgrid with Multiple Distributed Resources Using Interval Optimization," Energies, MDPI, vol. 10(3), pages 1-23, March.
    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. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    2. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    3. Castellanos, Johanna & Correa-Flórez, Carlos Adrián & Garcés, Alejandro & Ordóñez-Plata, Gabriel & Uribe, César A. & Patino, Diego, 2023. "An energy management system model with power quality constraints for unbalanced multi-microgrids interacting in a local energy market," Applied Energy, Elsevier, vol. 343(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. Craparo, Emily & Karatas, Mumtaz & Singham, Dashi I., 2017. "A robust optimization approach to hybrid microgrid operation using ensemble weather forecasts," Applied Energy, Elsevier, vol. 201(C), pages 135-147.
    2. Zhenya Ji & Xueliang Huang & Changfu Xu & Houtao Sun, 2016. "Accelerated Model Predictive Control for Electric Vehicle Integrated Microgrid Energy Management: A Hybrid Robust and Stochastic Approach," Energies, MDPI, vol. 9(11), pages 1-18, November.
    3. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    4. Hyeong-Jun Yoo & Thai-Thanh Nguyen & Hak-Man Kim, 2017. "Multi-Frequency Control in a Stand-Alone Multi-Microgrid System Using a Back-To-Back Converter," Energies, MDPI, vol. 10(6), pages 1-18, June.
    5. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    6. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim & Yong-Hoon Im & Jae-Yong Lee, 2017. "Optimal Energy Management of Combined Cooling, Heat and Power in Different Demand Type Buildings Considering Seasonal Demand Variations," Energies, MDPI, vol. 10(6), pages 1-21, June.
    7. Boram Kim & Sunghwan Bae & Hongseok Kim, 2017. "Optimal Energy Scheduling and Transaction Mechanism for Multiple Microgrids," Energies, MDPI, vol. 10(4), pages 1-17, April.
    8. Ho-Sung Ryu & Mun-Kyeom Kim, 2020. "Two-Stage Optimal Microgrid Operation with a Risk-Based Hybrid Demand Response Program Considering Uncertainty," Energies, MDPI, vol. 13(22), pages 1-25, November.
    9. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    10. Hou, Rui & Deng, Guangzhi & Wu, Minrong & Wang, Wei & Gao, Wei & Chen, Kang & Liu, Lijun & Dehan, Sim, 2023. "Optimum exploitation of an integrated energy system considering renewable sources and power-heat system and energy storage," Energy, Elsevier, vol. 282(C).
    11. Yu, Min Gyung & Pavlak, Gregory S., 2023. "Risk-aware sizing and transactive control of building portfolios with thermal energy storage," Applied Energy, Elsevier, vol. 332(C).
    12. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    13. Wen, Xin & Abbes, Dhaker & Francois, Bruno, 2021. "Modeling of photovoltaic power uncertainties for impact analysis on generation scheduling and cost of an urban micro grid," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 183(C), pages 116-128.
    14. Marcin Rabe & Dalia Streimikiene & Yuriy Bilan, 2019. "The Concept of Risk and Possibilities of Application of Mathematical Methods in Supporting Decision Making for Sustainable Energy Development," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    15. Andrea Bonfiglio & Massimo Brignone & Marco Invernizzi & Alessandro Labella & Daniele Mestriner & Renato Procopio, 2017. "A Simplified Microgrid Model for the Validation of Islanded Control Logics," Energies, MDPI, vol. 10(8), pages 1-28, August.
    16. Guoqiang Sun & Wenxue Wang & Yi Wu & Wei Hu & Zijun Yang & Zhinong Wei & Haixiang Zang & Sheng Chen, 2019. "A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network," Energies, MDPI, vol. 12(7), pages 1-20, March.
    17. Zhao, Bo & Xue, Meidong & Zhang, Xuesong & Wang, Caisheng & Zhao, Junhui, 2015. "An MAS based energy management system for a stand-alone microgrid at high altitude," Applied Energy, Elsevier, vol. 143(C), pages 251-261.
    18. Xu, Zhirong & Yang, Ping & Zheng, Chengli & Zhang, Yujia & Peng, Jiajun & Zeng, Zhiji, 2018. "Analysis on the organization and Development of multi-microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2204-2216.
    19. Ben Christopher, S.J. & Carolin Mabel, M., 2020. "A bio-inspired approach for probabilistic energy management of micro-grid incorporating uncertainty in statistical cost estimation," Energy, Elsevier, vol. 203(C).
    20. Harmsen - van Hout, Marjolein & Ghosh, Gaurav & Madlener, Reinhard, 2013. "The Impact of Green Framing on Consumers’ Valuations of Energy-Saving Measures," FCN Working Papers 7/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).

    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:10:y:2017:i:11:p:1770-:d:117507. 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.