IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i20p13209-d942344.html
   My bibliography  Save this article

Optimal Operational Planning of RES and HESS in Smart Grids Considering Demand Response and DSTATCOM Functionality of the Interfacing Inverters

Author

Listed:
  • Abdelfatah Ali

    (Department of Electrical Engineering, South Valley University, Qena 83523, Egypt
    Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Mostafa F. Shaaban

    (Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Hatem F. Sindi

    (Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

With countries moving toward renewable energy sources (RES), the need for dispatchability and storage solutions has become more prevalent. The uncertainty associated with wind turbine (WT) units and photovoltaic (PV) systems further complex a system with a high level of intermittency. This work addresses this problem by proposing an operational planning approach to determine the optimal allocation of WT units, PV systems, and hybrid energy storage systems (HESS) in smart grids. The proposed approach considers the uncertainties of the RES and load demand, price-based demand response, and distribution static compensator (DSTATCOM) functionality of the RES interfacing inverters. The operational planning problem is divided into two subcategories: (1) optimal long-term planning and (2) optimal operation. In the first problem, probabilistic models of RES and load reflect on the sizes and locations of the used RES and storage technologies. This allocation is further optimized via the optimal operation of the smart grid. The proposed operational planning approach is formulated as a nested optimization problem that guarantees the optimal planning and operation of the RES and HESS simultaneously. This approach is tested on the IEEE 33-bus distribution system and solved using meta-heuristic and mathematical algorithms. The effectiveness of the proposed approach is demonstrated using a set of case studies. The results demonstrate that the proposed approach optimally allocates the RES and HESS with a 30.4% cost reduction and 19% voltage profile improvement.

Suggested Citation

  • Abdelfatah Ali & Mostafa F. Shaaban & Hatem F. Sindi, 2022. "Optimal Operational Planning of RES and HESS in Smart Grids Considering Demand Response and DSTATCOM Functionality of the Interfacing Inverters," Sustainability, MDPI, vol. 14(20), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13209-:d:942344
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/20/13209/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/20/13209/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sk Abdul Aleem & S. M. Suhail Hussain & Taha Selim Ustun, 2020. "A Review of Strategies to Increase PV Penetration Level in Smart Grids," Energies, MDPI, vol. 13(3), pages 1-28, February.
    2. Nestor A. Sepulveda & Jesse D. Jenkins & Aurora Edington & Dharik S. Mallapragada & Richard K. Lester, 2021. "The design space for long-duration energy storage in decarbonized power systems," Nature Energy, Nature, vol. 6(5), pages 506-516, May.
    3. Zhao, Bo & Ren, Junzhi & Chen, Jian & Lin, Da & Qin, Ruwen, 2020. "Tri-level robust planning-operation co-optimization of distributed energy storage in distribution networks with high PV penetration," Applied Energy, Elsevier, vol. 279(C).
    4. Vahidinasab, Vahid, 2014. "Optimal distributed energy resources planning in a competitive electricity market: Multiobjective optimization and probabilistic design," Renewable Energy, Elsevier, vol. 66(C), pages 354-363.
    5. Ferreira, R.S. & Barroso, L.A. & Carvalho, M.M., 2012. "Demand response models with correlated price data: A robust optimization approach," Applied Energy, Elsevier, vol. 96(C), pages 133-149.
    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. Te-Tien Ku & Chia-Hung Lin & Chao-Shun Chen & Yih-Der Lee & Jheng-Lun Jiang & Sing-Jia Tzeng & Chen-Min Chan, 2023. "A Distribution Static Synchronous Compensator Application to Mitigate Voltage Variation for Distribution Feeders," Sustainability, MDPI, vol. 15(15), pages 1-13, July.

    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. A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
    2. Jing-Li Fan & Zezheng Li & Xi Huang & Kai Li & Xian Zhang & Xi Lu & Jianzhong Wu & Klaus Hubacek & Bo Shen, 2023. "A net-zero emissions strategy for China’s power sector using carbon-capture utilization and storage," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Vassilis M. Charitopoulos & Mathilde Fajardy & Chi Kong Chyong & David M. Reiner, 2022. "The case of 100% electrification of domestic heat in Great Britain," Working Papers EPRG2206, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    4. Lazzari, Florencia & Mor, Gerard & Cipriano, Jordi & Solsona, Francesc & Chemisana, Daniel & Guericke, Daniela, 2023. "Optimizing planning and operation of renewable energy communities with genetic algorithms," Applied Energy, Elsevier, vol. 338(C).
    5. Gonocruz, Ruth Anne Tanlioco & Yoshida, Yoshikuni & Ozawa, Akito & Aguirre, Rodolfo A. & Maguindayao, Edward Joseph H., 2023. "Impacts of agrivoltaics in rural electrification and decarbonization in the Philippines," Applied Energy, Elsevier, vol. 350(C).
    6. Cosgrove, Paul & Roulstone, Tony & Zachary, Stan, 2023. "Intermittency and periodicity in net-zero renewable energy systems with storage," Renewable Energy, Elsevier, vol. 212(C), pages 299-307.
    7. Jin, S.W. & Li, Y.P. & Huang, G.H. & Nie, S., 2018. "Analyzing the performance of clean development mechanism for electric power systems under uncertain environment," Renewable Energy, Elsevier, vol. 123(C), pages 382-397.
    8. Risthaus, Kai & Linder, Marc & Schmidt, Matthias, 2022. "Experimental investigation of a novel mechanically fluidized bed reactor for thermochemical energy storage with calcium hydroxide/calcium oxide," Applied Energy, Elsevier, vol. 315(C).
    9. Shen, Feifei & Zhao, Liang & Du, Wenli & Zhong, Weimin & Qian, Feng, 2020. "Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach," Applied Energy, Elsevier, vol. 259(C).
    10. Yong, Qingqing & Jin, Kaiyuan & Li, Xiaobo & Yang, Ronggui, 2023. "Thermo-economic analysis for a novel grid-scale pumped thermal electricity storage system coupled with a coal-fired power plant," Energy, Elsevier, vol. 280(C).
    11. Mohsen Jalalimajidi & SM Seyedhosseini & Ahmad Makui & Masoud Babakhani, 2018. "Developing a comprehensive model for new energy replacement in the country’s development program using a robust optimization approach," Energy & Environment, , vol. 29(6), pages 868-890, September.
    12. Guillermo Almonacid-Olleros & Gabino Almonacid & David Gil & Javier Medina-Quero, 2022. "Evaluation of Transfer Learning and Fine-Tuning to Nowcast Energy Generation of Photovoltaic Systems in Different Climates," Sustainability, MDPI, vol. 14(5), pages 1-15, March.
    13. Dhanuja Lekshmi J & Zakir Hussain Rather & Bikash C Pal, 2021. "A New Tool to Assess Maximum Permissible Solar PV Penetration in a Power System," Energies, MDPI, vol. 14(24), pages 1-21, December.
    14. Sheha, Moataz & Mohammadi, Kasra & Powell, Kody, 2021. "Techno-economic analysis of the impact of dynamic electricity prices on solar penetration in a smart grid environment with distributed energy storage," Applied Energy, Elsevier, vol. 282(PA).
    15. Keck, Felix & Jütte, Silke & Lenzen, Manfred & Li, Mengyu, 2022. "Assessment of two optimisation methods for renewable energy capacity expansion planning," Applied Energy, Elsevier, vol. 306(PA).
    16. Dan Tong & David J. Farnham & Lei Duan & Qiang Zhang & Nathan S. Lewis & Ken Caldeira & Steven J. Davis, 2021. "Geophysical constraints on the reliability of solar and wind power worldwide," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    17. Ganesh Sampatrao Patil & Anwar Mulla & Taha Selim Ustun, 2022. "Impact of Wind Farm Integration on LMP in Deregulated Energy Markets," Sustainability, MDPI, vol. 14(7), pages 1-20, April.
    18. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2015. "Performance evaluation of power demand scheduling scenarios in a smart grid environment," Applied Energy, Elsevier, vol. 142(C), pages 164-178.
    19. Liqun Peng & Denise L. Mauzerall & Yaofeng D. Zhong & Gang He, 2023. "Heterogeneous effects of battery storage deployment strategies on decarbonization of provincial power systems in China," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    20. Jarosław Kulpa & Piotr Olczak & Tomasz Surma & Dominika Matuszewska, 2021. "Comparison of Support Programs for the Development of Photovoltaics in Poland: My Electricity Program and the RES Auction System," Energies, MDPI, vol. 15(1), pages 1-17, December.

    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:jsusta:v:14:y:2022:i:20:p:13209-:d:942344. 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.