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A Distributionally Robust Chance-Constrained Unit Commitment with N-1 Security and Renewable Generation

Author

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  • Qiangyi Sha

    (Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Control, Xinjiang University, Urumqi 830047, China)

  • Weiqing Wang

    (Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Control, Xinjiang University, Urumqi 830047, China)

  • Haiyun Wang

    (Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Control, Xinjiang University, Urumqi 830047, China)

Abstract

With the increasing penetration of renewable energy generation, one of the major challenges is the problem of how to express the stochastic process of wind power and photovoltaic output as the exact probability density and distribution, in order to improve the security and accuracy of unit commitment results, a distributed robust security-constrained optimization model based on moment uncertainty is proposed, in which the uncertainty of wind and photovoltaic power is captured by two uncertain sets of first- and second-order moments, respectively. The two sets contain the probability distribution of the forecast error of the wind and photovoltaic power, and in the model, the energy storage is considered. In order to solve the model effectively, firstly, based on the traditional chance-constrained second-order cone transformation, according to the first- and second-order moments polyhedron expression of the distribution set, a cutting plane method is proposed to solve the distributed robust chance constraints. Secondly, the modified IEEE-RTS 24 bus system is selected to establish a simulation example, an improved generalized Benders decomposition algorithm is developed to solve the model to optimality. The results show that the unit commitment results with different emphasis on economy and security can be obtained by setting different conservative coefficients and confidence levels and, then, provide a reasonable decision-making basis for dispatching operation.

Suggested Citation

  • Qiangyi Sha & Weiqing Wang & Haiyun Wang, 2021. "A Distributionally Robust Chance-Constrained Unit Commitment with N-1 Security and Renewable Generation," Energies, MDPI, vol. 14(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5618-:d:630802
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    References listed on IDEAS

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    1. Wang, Bo & Wang, Shuming & Zhou, Xianzhong & Watada, Junzo, 2016. "Multi-objective unit commitment with wind penetration and emission concerns under stochastic and fuzzy uncertainties," Energy, Elsevier, vol. 111(C), pages 18-31.
    2. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
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