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Energy Hub’s Structural and Operational Optimization for Minimal Energy Usage Costs in Energy Systems

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  • Thanh Tung Ha

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

  • Yongjun Zhang

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

  • Jinbao Hao

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

  • V. V. Thang

    (Department of Electric Power Systems, Thai Nguyen University of Technology, Thai Nguyen 250000, Vietnam)

  • Canbing Li

    (College of Electric and Information Engineering, Hunan University, Changsha 410082, China)

  • Zexiang Cai

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

Abstract

The structural and optimal operation of an Energy Hub (EH) has a tremendous influence on the hub’s performance and reliability. This paper envisions an innovative methodology that prominently increases the synergy between structural and operational optimization and targets system cost affordability. The generalized energy system structure is presented theoretically with all selective hub sub-modules, including electric heater (EHe) and solar sources block sub-modules. To minimize energy usage cost, an energy hub is proposed that consists of 12 kinds of elements (i.e., energy resources, conversion, and storage functions) and is modeled mathematically in a General Algebraic Modeling System (GAMS), which indicates the optimal hub structure’s corresponding elements with binary variables (0, 1). Simulation results contrast with 144 various scenarios established in all 144 categories of hub structures, in which for each scenario the corresponding optimal operation cost is previously calculated. These case studies demonstrate the effectiveness of the suggested model and methodology. Finally, avenues for future research are also prospected.

Suggested Citation

  • Thanh Tung Ha & Yongjun Zhang & Jinbao Hao & V. V. Thang & Canbing Li & Zexiang Cai, 2018. "Energy Hub’s Structural and Operational Optimization for Minimal Energy Usage Costs in Energy Systems," Energies, MDPI, vol. 11(4), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:707-:d:137366
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    References listed on IDEAS

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    1. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
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    Cited by:

    1. Yongjie Zhong & Hongwei Zhou & Xuanjun Zong & Zhou Xu & Yonghui Sun, 2019. "Hierarchical Multi-Objective Fuzzy Collaborative Optimization of Integrated Energy System under Off-Design Performance," Energies, MDPI, vol. 12(5), pages 1-27, March.
    2. Wen Fan & Qing Liu & Mingyu Wang, 2021. "Bi-Level Multi-Objective Optimization Scheduling for Regional Integrated Energy Systems Based on Quantum Evolutionary Algorithm," Energies, MDPI, vol. 14(16), pages 1-15, August.
    3. Chen, Zexing & Zhang, Yongjun & Tang, Wenhu & Lin, Xiaoming & Li, Qifeng, 2019. "Generic modelling and optimal day-ahead dispatch of micro-energy system considering the price-based integrated demand response," Energy, Elsevier, vol. 176(C), pages 171-183.
    4. Yu Huang & Kai Yang & Weiting Zhang & Kwang Y. Lee, 2018. "Hierarchical Energy Management for the MultiEnergy Carriers System with Different Interest Bodies," Energies, MDPI, vol. 11(10), pages 1-18, October.
    5. Teodora Melania Șoimoșan & Ligia Mihaela Moga & Gelu Danku & Aurica Căzilă & Daniela Lucia Manea, 2019. "Assessing the Energy Performance of Solar Thermal Energy for Heat Production in Urban Areas: A Case Study," Energies, MDPI, vol. 12(6), pages 1-19, March.
    6. Antonio Pepiciello & Alfredo Vaccaro & Mario Mañana, 2019. "Robust Optimization of Energy Hubs Operation Based on Extended Affine Arithmetic," Energies, MDPI, vol. 12(12), pages 1-15, June.

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