Ming Li^1,*, Cairen Furifu¹, Chengyang Ge², Yunping Zheng¹, Shunfu Lin², Ronghui Liu²

Energy Engineering, Vol.120, No.8, pp. 1775-1801, 2023, DOI:10.32604/ee.2023.027215

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… More >

Xuan Zhao^1,2, Jianteng Xu^2,*, Hongling Lu²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1813-1833, 2023, DOI:10.32604/cmes.2023.025828

Abstract The cap-and-offset regulation is a practical scheme to lessen carbon emissions. The retailer selling fresh products can adopt sustainable technologies to lessen greenhouse gas emissions. We aim to analyze the optimal joint strategies on order quantity and sustainable technology investment when the retailer faces stochastic market demand and can only acquire the mean and variance of distribution information. We construct a distributionally robust optimization model and use the Karush-Kuhn-Tucker (KKT) conditions to solve the analytic formula of optimal solutions. By comparing the models with and without investing in sustainable technologies, we examine the effect of sustainable technologies on the operational… More > Graphic Abstract

Wenlu Ji, Yong Wang^*, Xing Deng, Ming Zhang, Ting Ye

Energy Engineering, Vol.119, No.5, pp. 1967-1983, 2022, DOI:10.32604/ee.2022.020011

Abstract Virtual power plants can effectively integrate different types of distributed energy resources, which have become a new operation mode with substantial advantages such as high flexibility, adaptability, and economy. This paper proposes a distributionally robust optimal dispatch approach for virtual power plants to determine an optimal day-ahead dispatch under uncertainties of renewable energy sources. The proposed distributionally robust approach characterizes probability distributions of renewable power output by moments. In this regard, the faults of stochastic optimization and traditional robust optimization can be overcome. Firstly, a second-order cone-based ambiguity set that incorporates the first and second moments of renewable power output… More >