IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i14p5549-d1200103.html
   My bibliography  Save this article

Optimal Sizing of Photovoltaic/Energy Storage Hybrid Power Systems: Considering Output Characteristics and Uncertainty Factors

Author

Listed:
  • Ye Liu

    (School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China)

  • Yiwei Zhong

    (School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China)

  • Chaowei Tang

    (School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China)

Abstract

The integration of PV and energy storage systems (ESS) into buildings is a recent trend. By optimizing the component sizes and operation modes of PV-ESS systems, the system can better mitigate the intermittent nature of PV output. Although various methods have been proposed to optimize component size and achieve online energy management in PV-ESS systems, the optimal interconnection between them has received less attention. In order to maximize the effectiveness of systems with limited component sizes and address the impact of uncertainty on the system, an optimization framework is proposed for determining the optimal size of the PV-ESS system. The proposed framework consists of five parts: determination of optimal size, analysis of component output characteristics, system state prediction, parameter calibration of energy management strategies, and update of system components output features, and it considers uncertain factors, including climate, different components, and battery degradation caused by irregular charging and discharging, to establish the model for energy saving. To validate the results, four different climates in a year were considered. The obtained results indicate that the proposed framework can effectively achieve the optimal working state of the system, realizing a matching degree of 94.55% between the offline size optimization and online management strategy. The proposed framework’s universality and effectiveness were demonstrated through simulation analysis across four cities with different climates in China.

Suggested Citation

  • Ye Liu & Yiwei Zhong & Chaowei Tang, 2023. "Optimal Sizing of Photovoltaic/Energy Storage Hybrid Power Systems: Considering Output Characteristics and Uncertainty Factors," Energies, MDPI, vol. 16(14), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5549-:d:1200103
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/14/5549/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/14/5549/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    2. Erdinc, Ozan & Paterakis, Nikolaos G. & Pappi, Iliana N. & Bakirtzis, Anastasios G. & Catalão, João P.S., 2015. "A new perspective for sizing of distributed generation and energy storage for smart households under demand response," Applied Energy, Elsevier, vol. 143(C), pages 26-37.
    3. Ahmad, Riaz & Murtaza, Ali F. & Sher, Hadeed Ahmed, 2019. "Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 82-102.
    4. Majed A. Alotaibi & Ali M. Eltamaly, 2021. "A Smart Strategy for Sizing of Hybrid Renewable Energy System to Supply Remote Loads in Saudi Arabia," Energies, MDPI, vol. 14(21), pages 1-24, October.
    5. Heinisch, Verena & Göransson, Lisa & Erlandsson, Rasmus & Hodel, Henrik & Johnsson, Filip & Odenberger, Mikael, 2021. "Smart electric vehicle charging strategies for sectoral coupling in a city energy system," Applied Energy, Elsevier, vol. 288(C).
    6. Ye, Min & Guo, Hui & Cao, Binggang, 2017. "A model-based adaptive state of charge estimator for a lithium-ion battery using an improved adaptive particle filter," Applied Energy, Elsevier, vol. 190(C), pages 740-748.
    7. de la Parra, I. & Muñoz, M. & Lorenzo, E. & García, M. & Marcos, J. & Martínez-Moreno, F., 2017. "PV performance modelling: A review in the light of quality assurance for large PV plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 780-797.
    8. Korjani, Saman & Casu, Fabio & Damiano, Alfonso & Pilloni, Virginia & Serpi, Alessandro, 2022. "An online energy management tool for sizing integrated PV-BESS systems for residential prosumers," Applied Energy, Elsevier, vol. 313(C).
    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. Elias Roumpakias & Olympia Zogou & Antiopi-Malvina Stamatellou, 2024. "Optimization of Electrical and Thermal Storage in a High School Building in Central Greece," Energies, MDPI, vol. 17(8), pages 1-29, April.

    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. Farhat Afzah Samoon & Ikhlaq Hussain & Sheikh Javed Iqbal, 2023. "ILA Optimisation Based Control for Enhancing DC Link Voltage with Seamless and Adaptive VSC Control in a PV-BES Based AC Microgrid," Energies, MDPI, vol. 16(21), pages 1-23, October.
    2. Trigo-González, Mauricio & Batlles, F.J. & Alonso-Montesinos, Joaquín & Ferrada, Pablo & del Sagrado, J. & Martínez-Durbán, M. & Cortés, Marcelo & Portillo, Carlos & Marzo, Aitor, 2019. "Hourly PV production estimation by means of an exportable multiple linear regression model," Renewable Energy, Elsevier, vol. 135(C), pages 303-312.
    3. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    4. Hussain Abdalla Sajwani & Bassel Soudan & Abdul Ghani Olabi, 2024. "Empowering Sustainability: Understanding Determinants of Consumer Investment in Microgrid Technology in the UAE," Energies, MDPI, vol. 17(9), pages 1-28, May.
    5. Ray, Manojit & Chakraborty, Basab, 2022. "Impact of demand flexibility and tiered resilience on solar photovoltaic adoption in humanitarian settlements," Renewable Energy, Elsevier, vol. 193(C), pages 895-912.
    6. Dimitrios Trigkas & Chrysovalantou Ziogou & Spyros Voutetakis & Simira Papadopoulou, 2021. "Virtual Energy Storage in RES-Powered Smart Grids with Nonlinear Model Predictive Control," Energies, MDPI, vol. 14(4), pages 1-22, February.
    7. Jihed Hmad & Azeddine Houari & Allal El Moubarek Bouzid & Abdelhakim Saim & Hafedh Trabelsi, 2023. "A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids," Energies, MDPI, vol. 16(13), pages 1-41, June.
    8. Wenxian Duan & Chuanxue Song & Silun Peng & Feng Xiao & Yulong Shao & Shixin Song, 2020. "An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery," Energies, MDPI, vol. 13(23), pages 1-19, December.
    9. Matija Kostelac & Lin Herenčić & Tomislav Capuder, 2022. "Planning and Operational Aspects of Individual and Clustered Multi-Energy Microgrid Options," Energies, MDPI, vol. 15(4), pages 1-17, February.
    10. Ahmed Y. Hatata & Mohamed A. Essa & Bishoy E. Sedhom, 2022. "Implementation and Design of FREEDM System Differential Protection Method Based on Internet of Things," Energies, MDPI, vol. 15(15), pages 1-24, August.
    11. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    12. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    13. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2020. "Community Resilience-Oriented Optimal Micro-Grid Capacity Expansion Planning: The Case of Totarabank Eco-Village, New Zealand," Energies, MDPI, vol. 13(15), pages 1-29, August.
    14. Zhang, Minhui & Zhang, Qin & Zhou, Dequn & Wang, Lei, 2021. "Punishment or reward? Strategies of stakeholders in the quality of photovoltaic plants based on evolutionary game analysis in China," Energy, Elsevier, vol. 220(C).
    15. Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
    16. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    17. Fachrizal, Reza & Shepero, Mahmoud & Åberg, Magnus & Munkhammar, Joakim, 2022. "Optimal PV-EV sizing at solar powered workplace charging stations with smart charging schemes considering self-consumption and self-sufficiency balance," Applied Energy, Elsevier, vol. 307(C).
    18. Zhao, Huiru & Li, Bingkang & Lu, Hao & Wang, Xuejie & Li, Hongze & Guo, Sen & Xue, Wanlei & Wang, Yuwei, 2022. "Economy-environment-energy performance evaluation of CCHP microgrid system: A hybrid multi-criteria decision-making method," Energy, Elsevier, vol. 240(C).
    19. Roth, Jonathan & Martin, Amory & Miller, Clayton & Jain, Rishee K., 2020. "SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods," Applied Energy, Elsevier, vol. 280(C).
    20. Hammad Alnuman & Kuo-Hsien Hsia & Mohammadreza Askari Sepestanaki & Emad M. Ahmed & Saleh Mobayen & Ammar Armghan, 2023. "Design of Continuous Finite-Time Controller Based on Adaptive Tuning Approach for Disturbed Boost Converters," Mathematics, MDPI, vol. 11(7), pages 1-23, April.

    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:16:y:2023:i:14:p:5549-:d:1200103. 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.