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Distributionally robust optimal dispatch of CCHP campus microgrids considering the time-delay of pipelines and the uncertainty of renewable energy

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  • Liang, Weikun
  • Lin, Shunjiang
  • Lei, Shunbo
  • Xie, Yuquan
  • Tang, Zhiqiang
  • Liu, Mingbo

Abstract

Considering the time-delay of energy transmission in cooling/heating pipelines and the uncertainty of renewable energy (RE), a distributionally robust optimal (DRO) dispatch model of combined cooling, heating and power campus microgrids (CCHP-CMG) is established. The method of characteristics is used to obtain the analytical algebraic solution of the partial differential equation (PDE) describing the energy transmission in pipelines and to add the solution to the optimal dispatch model. Based on the Jensen–Shannon divergence distance, an ambiguity set including the probability distribution (PD) information of the actual historical data is proposed to describe the uncertainty of RE outputs, and a min–max bi-level DRO dispatch model is established. An alternative iteration method is proposed to solve the bi-level model to obtain the solution that satisfies the constraints for the worst PD of uncertain variables. Additionally, a method for reconstructing the inner-layer problem is proposed to significantly reduce the computational complexity. Test results for an actual CCHP-CMG demonstrated the high computational accuracy and efficiency of the method of characteristics in solving the PDE compared to the finite difference method. The proposed reconstruction method is accurate and efficient, and the proposed DRO method can easily adjust the conservativeness of the obtained dispatch scheme.

Suggested Citation

  • Liang, Weikun & Lin, Shunjiang & Lei, Shunbo & Xie, Yuquan & Tang, Zhiqiang & Liu, Mingbo, 2022. "Distributionally robust optimal dispatch of CCHP campus microgrids considering the time-delay of pipelines and the uncertainty of renewable energy," Energy, Elsevier, vol. 239(PC).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pc:s0360544221024488
    DOI: 10.1016/j.energy.2021.122200
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    References listed on IDEAS

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    Cited by:

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    2. Siqin, Zhuoya & Niu, DongXiao & Wang, Xuejie & Zhen, Hao & Li, MingYu & Wang, Jingbo, 2022. "A two-stage distributionally robust optimization model for P2G-CCHP microgrid considering uncertainty and carbon emission," Energy, Elsevier, vol. 260(C).
    3. Dai, Yiru & Zeng, Yipu, 2022. "Optimization of CCHP integrated with multiple load, replenished energy, and hybrid storage in different operation modes," Energy, Elsevier, vol. 260(C).
    4. He, Shuaijia & Gao, Hongjun & Chen, Zhe & Liu, Junyong & Zhao, Liang & Wu, Gang & Xu, Song, 2022. "Low-carbon distribution system planning considering flexible support of zero-carbon energy station," Energy, Elsevier, vol. 244(PB).
    5. Zhou, Kaile & Fei, Zhineng & Hu, Rong, 2023. "Hybrid robust decentralized optimization of emission-aware multi-energy microgrids considering multiple uncertainties," Energy, Elsevier, vol. 265(C).
    6. Saberi-Beglar, Kasra & Zare, Kazem & Seyedi, Heresh & Marzband, Mousa & Nojavan, Sayyad, 2023. "Risk-embedded scheduling of a CCHP integrated with electric vehicle parking lot in a residential energy hub considering flexible thermal and electrical loads," Applied Energy, Elsevier, vol. 329(C).
    7. Qiu, Haifeng & Vinod, Ashwin & Lu, Shuai & Gooi, Hoay Beng & Pan, Guangsheng & Zhang, Suhan & Veerasamy, Veerapandiyan, 2023. "Decentralized mixed-integer optimization for robust integrated electricity and heat scheduling," Applied Energy, Elsevier, vol. 350(C).

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