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Robust environmental-economic dispatch incorporating wind power generation and carbon capture plants

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  • Wei, Wei
  • Liu, Feng
  • Wang, Jianhui
  • Chen, Laijun
  • Mei, Shengwei
  • Yuan, Tiejiang

Abstract

Utilizing clean renewable generation and carbon capture plants (CCPs) can remarkably reduce the carbon emission from electricity production. Because operating carbon capture facility consumers additional energy, minimizing the production cost and reducing the carbon emission may conflict with each other. To compromise these two objectives and cope with uncertain wind generation, this paper proposes a robust environmental-economic dispatch (EED) method that jointly optimizes energy and reserve schedules in the upcoming dispatch period. The operating characteristic of CCP and the volatility of wind energy are considered in the proposed model. Because both objectives are convex functions, the Pareto front can be readily computed by using the ε-constraint method. The Nash bargaining criterion is adopted to determine a fair trade-off between the generation cost and the carbon emission in the absence of a clear carbon tax or emission cap. A second-order cone program (SOCP) is proposed to locate the bargaining solution on the Pareto front. An adaptive scenario generation algorithm is derived to solve the robust EED problem in a tractable manner. The PJM 5-bus system is used to illustrate the obtained dispatch strategy, and demonstrate the contribution of CCPs on reducing the carbon emissions and enhancing the operational flexibility. Case studies on the IEEE 118-bus system corroborate the applicability of the proposed method.

Suggested Citation

  • Wei, Wei & Liu, Feng & Wang, Jianhui & Chen, Laijun & Mei, Shengwei & Yuan, Tiejiang, 2016. "Robust environmental-economic dispatch incorporating wind power generation and carbon capture plants," Applied Energy, Elsevier, vol. 183(C), pages 674-684.
  • Handle: RePEc:eee:appene:v:183:y:2016:i:c:p:674-684
    DOI: 10.1016/j.apenergy.2016.09.013
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    5. Li, M.S. & Lin, Z.J. & Ji, T.Y. & Wu, Q.H., 2018. "Risk constrained stochastic economic dispatch considering dependence of multiple wind farms using pair-copula," Applied Energy, Elsevier, vol. 226(C), pages 967-978.
    6. Zhang, Gaohang & Li, Fengting & Wang, Sen & Yin, Chunya, 2023. "Robust low-carbon energy and reserve scheduling considering operational risk and flexibility improvement," Energy, Elsevier, vol. 284(C).
    7. Shin, Hansol & Kim, Tae Hyun & Kim, Hyoungtae & Lee, Sungwoo & Kim, Wook, 2019. "Environmental shutdown of coal-fired generators for greenhouse gas reduction: A case study of South Korea," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Wang, Jianxiao & Zhong, Haiwang & Wu, Chenye & Du, Ershun & Xia, Qing & Kang, Chongqing, 2019. "Incentivizing distributed energy resource aggregation in energy and capacity markets: An energy sharing scheme and mechanism design," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    9. Danyang Guo & Jilai Yu & Mingfei Ban, 2018. "Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    10. Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    11. Goudarzi, Arman & Swanson, Andrew G. & Van Coller, John & Siano, Pierluigi, 2017. "Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators," Applied Energy, Elsevier, vol. 189(C), pages 667-696.
    12. Qingshan Xu & Yifan Ding & Aixia Zheng, 2017. "An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability," Sustainability, MDPI, vol. 9(5), pages 1-20, May.
    13. Chen, F. & Huang, G.H. & Fan, Y.R. & Chen, J.P., 2017. "A copula-based fuzzy chance-constrained programming model and its application to electric power generation systems planning," Applied Energy, Elsevier, vol. 187(C), pages 291-309.
    14. Jin, Jingliang & Wen, Qinglan & Cheng, Siqi & Qiu, Yaru & Zhang, Xianyue & Guo, Xiaojun, 2022. "Optimization of carbon emission reduction paths in the low-carbon power dispatching process," Renewable Energy, Elsevier, vol. 188(C), pages 425-436.
    15. Moret, Stefano & Babonneau, Frédéric & Bierlaire, Michel & Maréchal, François, 2020. "Overcapacity in European power systems: Analysis and robust optimization approach," Applied Energy, Elsevier, vol. 259(C).

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