Robust economic optimization of microgrid based on scenario probability distribution uncertainty and probability combination scenario performance

Authors

Xiaoxu XU, School of Automation Engineering, Shanghai University of Electric Power, Yangpu District, Shanghai 200090, China
Pengyuan ZHENG, School of Automation Engineering, Shanghai University of Electric Power, Yangpu District, Shanghai 200090, ChinaFollow
Haijie QIN, School of Automation Engineering, Shanghai University of Electric Power, Yangpu District, Shanghai 200090, China
Yalin WANG, School of Automation Engineering, Shanghai University of Electric Power, Yangpu District, Shanghai 200090, China

Keywords

uncertainty; data-driven; binary expansion; fuzzy sets of probability distributions; robust optimization

Abstract

Addressing the uncertainties of renewable energy and load within isolated microgrids, a robust economic optimization approach for microgrids is proposed based on scenario probability distribution uncertainty and probabilistic combined scenario performance. The K-means clustering method is employed to preprocess extensive historical data, constructing a fuzzy set of data-driven scenario probability distributions. In the day-ahead planning phase, the binary expansion concept is introduced to discretize the probabilistic combination coefficients in continuous variable form, simplifying and effectively parameterizing the intensity and search interval of the worst-case scenario search. This extends the search range of the worst-case scenario effectively from the boundary of the uncertainty set to its interior, enabling the search for the worst probabilistic combined scenario. By optimizing the performance of the worst probabilistic combined scenario, the day-ahead optimal solution for microgrid operation is calculated. Subsequently, in the real-time scheduling phase, real-time measurement data of renewable energy and load are utilized to perform secondary optimization adjustments on part of the day-ahead planning optimization solutions, enhancing the economic efficiency and robustness of the microgrid control scheme. Simulation examples demonstrate the effectiveness of the proposed method.

DOI

10.19781/j.issn.1673-9140.2024.04.022

First Page

187

Last Page

200

Recommended Citation

XU, Xiaoxu; ZHENG, Pengyuan; QIN, Haijie; and WANG, Yalin (2024) "Robust economic optimization of microgrid based on scenario probability distribution uncertainty and probability combination scenario performance," Journal of Electric Power Science and Technology: Vol. 39: Iss. 4, Article 22.
DOI: 10.19781/j.issn.1673-9140.2024.04.022
Available at: https://jepst.researchcommons.org/journal/vol39/iss4/22