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Stochastic Convex Cone Programming for Joint Optimal BESS Operation and Q-Placement in Net-Zero Microgrids

Author

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  • Milad Mohammadyari

    (Department of Electrical Engineering, University of Tehran, Tehran 1417466191, Iran)

  • Mohsen Eskandari

    (School of Electrical Engineering and Telecommunications, University of New South Wales Sydney, Sydney, NSW 2052, Australia)

Abstract

Microgrids have emerged as a pivotal solution in the quest for efficient, resilient, and sustainable energy systems. Comprising diverse distributed energy resources, microgrids present a compelling opportunity to revolutionize how we generate, store, and distribute electricity, while simultaneously reducing carbon footprints. This paper proposes an optimal battery energy storage system (BESS) management scheme, along with capacitor placement for reactive power (Q)-compensation, and scheduling for the purpose of a renewable-based microgrid’s loss minimization. The proposed model evaluates the impact of BESS management on energy efficiency and analyzes how optimal scheduling of BESS influences system losses. Furthermore, it investigates the coordinated planning and operation of active assets within the microgrid, such as controllable capacitor banks, in enhancing overall efficiency. The model is formulated as a mixed-integer second-order cone programming (MISOCP) problem which is solved for both deterministic and stochastic generation and consumption data. The proposed model is tested on a 21-bus microgrid comprising photovoltaic and hydropower energy resources, and the efficacy of the model is approved by several case studies. The simulation results show that the proposed method can reduce microgrid energy losses by approximately 12 percent using the deterministic approach and around 14 percent with the stochastic approach.

Suggested Citation

  • Milad Mohammadyari & Mohsen Eskandari, 2024. "Stochastic Convex Cone Programming for Joint Optimal BESS Operation and Q-Placement in Net-Zero Microgrids," Energies, MDPI, vol. 17(17), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4292-:d:1465479
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    References listed on IDEAS

    as
    1. Song, Xiaoling & Zhang, Huqing & Fan, Lurong & Zhang, Zhe & Peña-Mora, Feniosky, 2023. "Planning shared energy storage systems for the spatio-temporal coordination of multi-site renewable energy sources on the power generation side," Energy, Elsevier, vol. 282(C).
    2. Farhad Amiri & Mohsen Eskandari & Mohammad Hassan Moradi, 2023. "Virtual Inertia Control in Autonomous Microgrids via a Cascaded Controller for Battery Energy Storage Optimized by Firefly Algorithm and a Comparison Study with GA, PSO, ABC, and GWO," Energies, MDPI, vol. 16(18), pages 1-22, September.
    3. Zhang, Rufeng & Chen, Yan & Li, Zhengmao & Jiang, Tao & Li, Xue, 2024. "Two-stage robust operation of electricity-gas-heat integrated multi-energy microgrids considering heterogeneous uncertainties," Applied Energy, Elsevier, vol. 371(C).
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