@Article{ee.2023.027215,
AUTHOR = {Ming Li, Cairen Furifu, Chengyang Ge, Yunping Zheng, Shunfu Lin, Ronghui Liu},
TITLE = {Distributed Robust Optimal Dispatch for the Microgrid Considering Output Correlation between Wind and Photovoltaic},
JOURNAL = {Energy Engineering},
VOLUME = {120},
YEAR = {2023},
NUMBER = {8},
PAGES = {1775--1801},
URL = {http://www.techscience.com/energy/v120n8/52964},
ISSN = {1546-0118},
ABSTRACT = {As an effective carrier of integrated clean energy, the microgrid has attracted wide attention. The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the economics and reliability of microgrids. This paper proposes an optimization scheme based on the distributionally robust optimization (DRO) model for a microgrid considering solar-wind correlation. Firstly, scenarios of wind and solar power output scenarios are generated based on non-parametric kernel density estimation and the Frank-Copula function; then the generated scenario results are reduced by K-means clustering; finally, the probability confidence interval of scenario distribution is constrained by 1-norm and ∞-norm. The model is solved by a column-and-constraint generation algorithm. Experimental studies are conducted on a microgrid system in Jiangsu, China and the obtained scheduling solution turned out to be superior under wind and solar power uncertainties, which verifies the effectiveness of the proposed DRO model.},
DOI = {10.32604/ee.2023.027215}
}