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Optimal Sizing and Control of Battery Energy Storage System for Peak Load Shaving

Author

Listed:
  • Chao Lu

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Hanchen Xu

    (Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

  • Xin Pan

    (College of Engineering, Peking University, Beijing 100871, China)

  • Jie Song

    (College of Engineering, Peking University, Beijing 100871, China)

Abstract

Battery Energy Storage System (BESS) can be utilized to shave the peak load in power systems and thus defer the need to upgrade the power grid. Based on a rolling load forecasting method, along with the peak load reduction requirements in reality, at the planning level, we propose a BESS capacity planning model for peak and load shaving problem. At the operational level, we consider the optimal control policy towards charging and discharging power with two different optimization objectives: one is to diminish the difference between the peak load and the valley load, the other is to minimize the daily load variance. Particularly, the constraint of charging and discharging cycles, which is an important issue in practice, is taken into consideration. Finally, based on real load data, we provide simulation results that validate the proposed optimization models and control strategies.

Suggested Citation

  • Chao Lu & Hanchen Xu & Xin Pan & Jie Song, 2014. "Optimal Sizing and Control of Battery Energy Storage System for Peak Load Shaving," Energies, MDPI, vol. 7(12), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:12:p:8396-8410:d:43537
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    Citations

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    Cited by:

    1. Reihani, Ehsan & Sepasi, Saeed & Ghorbani, Reza, 2016. "Scheduling of price-sensitive residential storage devices and loads with thermal inertia in distribution grid," Applied Energy, Elsevier, vol. 183(C), pages 636-644.
    2. Chua, Kein Huat & Lim, Yun Seng & Morris, Stella, 2017. "A novel fuzzy control algorithm for reducing the peak demands using energy storage system," Energy, Elsevier, vol. 122(C), pages 265-273.
    3. Jie Song & Xin Pan & Chao Lu & Hanchen Xu, 2017. "A Simulation-Based Optimization Method for Hybrid Frequency Regulation System Configuration," Energies, MDPI, vol. 10(9), pages 1-14, August.
    4. Hinz, Juri & Yee, Jeremy, 2018. "Optimal forward trading and battery control under renewable electricity generation," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 244-254.
    5. Lange, Christopher & Rueß, Alexandra & Nuß, Andreas & Öchsner, Richard & März, Martin, 2020. "Dimensioning battery energy storage systems for peak shaving based on a real-time control algorithm," Applied Energy, Elsevier, vol. 280(C).
    6. Mazhar Abbas & Eung-sang Kim & Seul-ki Kim & Yun-su Kim, 2016. "Comparative Analysis of Battery Behavior with Different Modes of Discharge for Optimal Capacity Sizing and BMS Operation," Energies, MDPI, vol. 9(10), pages 1-19, October.
    7. Paolo Falbo & Juri Hinz & Piyachat Leelasilapasart & Cristian Pelizzari, 2021. "A Computational Approach to Sequential Decision Optimization in Energy Storage and Trading," Research Paper Series 422, Quantitative Finance Research Centre, University of Technology, Sydney.
    8. B. V. Rajanna & Malligunta Kiran Kumar, 2021. "Chopper-Based Control Circuit for BESS Integration in Solar PV Grids," Energies, MDPI, vol. 14(6), pages 1-17, March.
    9. Uddin, Moslem & Romlie, Mohd Fakhizan & Abdullah, Mohd Faris & Abd Halim, Syahirah & Abu Bakar, Ab Halim & Chia Kwang, Tan, 2018. "A review on peak load shaving strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3323-3332.
    10. Moses Amoasi Acquah & Daisuke Kodaira & Sekyung Han, 2018. "Real-Time Demand Side Management Algorithm Using Stochastic Optimization," Energies, MDPI, vol. 11(5), pages 1-14, May.
    11. Ebrahimi, Armin & Ziabasharhagh, Masoud, 2022. "Introducing a novel control algorithm and scheduling procedure for optimal operation of energy storage systems," Energy, Elsevier, vol. 252(C).
    12. Ng, Rong Wang & Begam, K.M. & Rajkumar, Rajprasad Kumar & Wong, Yee Wan & Chong, Lee Wai, 2022. "A novel dynamic two-stage controller of battery energy storage system for maximum demand reductions," Energy, Elsevier, vol. 248(C).
    13. Paolo Falbo & Juri Hinz & Piyachat Leelasilapasart & Cristian Pelizzari, 2021. "A Computational Approach to Sequential Decision Optimization in Energy Storage and Trading," JRFM, MDPI, vol. 14(6), pages 1-22, May.
    14. Mustafa Cagatay Kocer & Ceyhun Cengiz & Mehmet Gezer & Doruk Gunes & Mehmet Aytac Cinar & Bora Alboyaci & Ahmet Onen, 2019. "Assessment of Battery Storage Technologies for a Turkish Power Network," Sustainability, MDPI, vol. 11(13), pages 1-33, July.
    15. José Luis Monroy-Morales & Rafael Peña-Alzola & David Campos-Gaona & Olimpo Anaya-Lara, 2022. "Complete Transitions of Hybrid Wind-Diesel Systems with Clutch and Flywheel-Based Energy Storage," Energies, MDPI, vol. 15(19), pages 1-18, September.
    16. Saboori, Hedayat & Hemmati, Reza & Jirdehi, Mehdi Ahmadi, 2015. "Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems," Energy, Elsevier, vol. 93(P2), pages 2299-2312.
    17. Bhagya Nathali Silva & Murad Khan & Kijun Han, 2020. "Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    18. Srete Nikolovski & Hamid Reza Baghaee & Dragan Mlakić, 2018. "ANFIS-Based Peak Power Shaving/Curtailment in Microgrids Including PV Units and BESSs," Energies, MDPI, vol. 11(11), pages 1-23, October.
    19. Abbassi, Abdelkader & Dami, Mohamed Ali & Jemli, Mohamed, 2017. "A statistical approach for hybrid energy storage system sizing based on capacity distributions in an autonomous PV/Wind power generation system," Renewable Energy, Elsevier, vol. 103(C), pages 81-93.
    20. Feras Alasali & Stephen Haben & Victor Becerra & William Holderbaum, 2017. "Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems," Energies, MDPI, vol. 10(10), pages 1-18, October.
    21. Yanjuan Yu & Hongkun Chen & Lei Chen, 2018. "Comparative Study of Electric Energy Storages and Thermal Energy Auxiliaries for Improving Wind Power Integration in the Cogeneration System," Energies, MDPI, vol. 11(2), pages 1-16, January.

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