TY  - EJOU
AU  - Ji, Wenlu 
AU  - Wang, Yong 
AU  - Deng, Xing 
AU  - Zhang, Ming 
AU  - Ye, Ting 

TI  - Distributionally Robust Optimal Dispatch of Virtual Power Plant Based on Moment of Renewable Energy Resource
T2  - Energy Engineering

PY  - 2022
VL  - 119
IS  - 5
SN  - 1546-0118

AB  - 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 is constructed, and a day-ahead two-stage distributionally robust optimization model is proposed for virtual power plants participating in day-ahead electricity markets. Then, an effective solution method based on the affine policy and second-order cone duality theory is employed to reformulate the proposed model into a deterministic mixed-integer second-order cone programming problem, which improves the computational efficiency of the model. Finally, the numerical results demonstrate that the proposed method achieves a better balance between robustness and economy. They also validate that the dispatch strategy of virtual power plants can be adjusted to reduce costs according to the moment information of renewable power output.
KW  - Virtual power plant; optimal dispatch; uncertainty; distributionally robust optimization; affine policy

DO  - 10.32604/ee.2022.020011