IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i12p3499-d190723.html
   My bibliography  Save this article

Application of Particle Swarm Optimization to a Scheduling Strategy for Microgrids Coupled with Natural Gas Networks

Author

Listed:
  • Muhammad Yousif

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai 200240, China)

  • Qian Ai

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai 200240, China)

  • Yang Gao

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai 200240, China)

  • Waqas Ahmad Wattoo

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai 200240, China
    Department of Electrical and Computer Engineering, COMSATS University Islamabad (CUI), Sahiwal Campus, Punjab 57000, Pakistan)

  • Ziqing Jiang

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai 200240, China)

  • Ran Hao

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai 200240, China)

Abstract

This article focuses on the minimization of operational cost and optimal power dispatch associated with microgrids coupled with natural gas networks using particle swarm optimization (PSO). Introducing a natural gas turbine in a microgrid to overcome the drawbacks of renewable energy resources is a recent trend. This results in increased load and congestion in the gas network. To avoid congestion and balance the load, it is necessary to coordinate with the electric grid to plan optimal dispatch of both interactive networks. A modification is done in applying PSO to solve this coupled network problem. To study the proposed approach, a 7-node natural gas system coupled with the IEEE bus 33 test system is used. The proposed strategy provides the optimal power dispatch. Moreover, it indicates that power sharing between the main grid and microgrid is reduced in such a way that it may help the main grid to shave the load curve peaks.

Suggested Citation

  • Muhammad Yousif & Qian Ai & Yang Gao & Waqas Ahmad Wattoo & Ziqing Jiang & Ran Hao, 2018. "Application of Particle Swarm Optimization to a Scheduling Strategy for Microgrids Coupled with Natural Gas Networks," Energies, MDPI, vol. 11(12), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3499-:d:190723
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/12/3499/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/12/3499/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    2. Fei Wang & Lidong Zhou & Hui Ren & Xiaoli Liu, 2017. "Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimizat," Energies, MDPI, vol. 10(12), pages 1-23, November.
    3. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Liao, Siyang & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao, 2018. "Coordinated operation of gas-electricity integrated distribution system with multi-CCHP and distributed renewable energy sources," Applied Energy, Elsevier, vol. 211(C), pages 237-248.
    4. Usama Khaled & Ali M. Eltamaly & Abderrahmane Beroual, 2017. "Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation," Energies, MDPI, vol. 10(7), pages 1-14, July.
    5. Wei-Tzer Huang & Tsai-Hsiang Chen & Hong-Ting Chen & Jhih-Siang Yang & Kuo-Lung Lian & Yung-Ruei Chang & Yih-Der Lee & Yuan-Hsiang Ho, 2015. "A Two-stage Optimal Network Reconfiguration Approach for Minimizing Energy Loss of Distribution Networks Using Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 8(12), pages 1-17, December.
    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. Szymon Kuczyński & Mariusz Łaciak & Andrzej Olijnyk & Adam Szurlej & Tomasz Włodek, 2019. "Techno-Economic Assessment of Turboexpander Application at Natural Gas Regulation Stations," Energies, MDPI, vol. 12(4), pages 1-21, February.
    2. Muhammad Yousif & Qian Ai & Yang Gao & Waqas Ahmad Wattoo & Ran Hao & Ziqing Jiang, 2019. "Dataset for Scheduling Strategies for Microgrids Coupled with Natural Gas Networks," Data, MDPI, vol. 4(1), pages 1-4, February.
    3. Zhao, Xin & Zheng, Wenyu & Hou, Zhihua & Chen, Heng & Xu, Gang & Liu, Wenyi & Chen, Honggang, 2022. "Economic dispatch of multi-energy system considering seasonal variation based on hybrid operation strategy," Energy, Elsevier, vol. 238(PA).
    4. Aqsa Naeem & Naveed Ul Hassan & Chau Yuen & S. M. Muyeen, 2019. "Maximizing the Economic Benefits of a Grid-Tied Microgrid Using Solar-Wind Complementarity," Energies, MDPI, vol. 12(3), pages 1-22, January.
    5. Rovick Tarife & Yosuke Nakanishi & Yining Chen & Yicheng Zhou & Noel Estoperez & Anacita Tahud, 2022. "Optimization of Hybrid Renewable Energy Microgrid for Rural Agricultural Area in Southern Philippines," Energies, MDPI, vol. 15(6), pages 1-29, 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. Xiaofeng Dong & Chao Quan & Tong Jiang, 2018. "Optimal Planning of Integrated Energy Systems Based on Coupled CCHP," Energies, MDPI, vol. 11(10), pages 1-27, October.
    2. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2020. "Optimal planning and operation of multi-vector energy networks: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    3. Gui, Yonghao & Wei, Baoze & Li, Mingshen & Guerrero, Josep M. & Vasquez, Juan C., 2018. "Passivity-based coordinated control for islanded AC microgrid," Applied Energy, Elsevier, vol. 229(C), pages 551-561.
    4. Chi, Lixun & Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Bai, Hua, 2020. "Integrated Deterministic and Probabilistic Safety Analysis of Integrated Energy Systems with bi-directional conversion," Energy, Elsevier, vol. 212(C).
    5. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    6. Xu, Jing & Wang, Xiaoying & Gu, Yujiong & Ma, Suxia, 2023. "A data-based day-ahead scheduling optimization approach for regional integrated energy systems with varying operating conditions," Energy, Elsevier, vol. 283(C).
    7. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    8. Wei Wei & Yusong Guo & Kai Hou & Kai Yuan & Yi Song & Hongjie Jia & Chongbo Sun, 2021. "Distributed Thermal Energy Storage Configuration of an Urban Electric and Heat Integrated Energy System Considering Medium Temperature Characteristics," Energies, MDPI, vol. 14(10), pages 1-34, May.
    9. Samson Ademola Adegoke & Yanxia Sun, 2023. "Diminishing Active Power Loss and Improving Voltage Profile Using an Improved Pathfinder Algorithm Based on Inertia Weight," Energies, MDPI, vol. 16(3), pages 1-14, January.
    10. 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.
    11. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "A general model for energy hub economic dispatch," Applied Energy, Elsevier, vol. 190(C), pages 1090-1111.
    12. Xie, Shiwei & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "The optimal planning of smart multi-energy systems incorporating transportation, natural gas and active distribution networks," Applied Energy, Elsevier, vol. 269(C).
    13. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    14. Qin, Xin & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "A generalized quasi-dynamic model for electric-heat coupling integrated energy system with distributed energy resources," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Yu Huang & Weiting Zhang & Kai Yang & Weizhen Hou & Yiran Huang, 2019. "An Optimal Scheduling Method for Multi-Energy Hub Systems Using Game Theory," Energies, MDPI, vol. 12(12), pages 1-20, June.
    16. Gayo-Abeleira, Miguel & Santos, Carlos & Javier Rodríguez Sánchez, Francisco & Martín, Pedro & Antonio Jiménez, José & Santiso, Enrique, 2022. "Aperiodic two-layer energy management system for community microgrids based on blockchain strategy," Applied Energy, Elsevier, vol. 324(C).
    17. Zhang, Suhan & Gu, Wei & Lu, Hai & Qiu, Haifeng & Lu, Shuai & Wang, Dada & Liang, Junyu & Li, Wenyun, 2021. "Superposition-principle based decoupling method for energy flow calculation in district heating networks," Applied Energy, Elsevier, vol. 295(C).
    18. Maurer, Jona & Tschuch, Nicolai & Krebs, Stefan & Bhattacharya, Kankar & Cañizares, Claudio & Hohmann, Sören, 2023. "Toward transactive control of coupled electric power and district heating networks," Applied Energy, Elsevier, vol. 332(C).
    19. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    20. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).

    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:11:y:2018:i:12:p:3499-:d:190723. 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.