Adjustable and distributionally robust chance-constrained economic dispatch considering wind power uncertainty

• Published in: Journal of modern power systems and clean energy Vol. 7; no. 3; pp. 658 - 664
• Main Authors: FANG, Xin, HODGE, Bri-Mathias, LI, Fangxing, DU, Ershun, KANG, Chongqing
• Format: Journal Article
• Language: English
• Published: Singapore Springer Singapore 01.05.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); IEEE
• Subjects: Adjustable and distributionally robust chance-constrained optimization; Coefficients; Economic dispatch; Economic forecasting; Economic models; Electrical Machines and Networks; Energy; Energy Systems; Mathematical models; Normal distribution; Power dispatch; Power Electronics; Power flow; Renewable and Green Energy; Robust control; Robustness; Uncertainty; Wind power; Wind power forecasting; Adjustable and distributionally robust chance-constrained optimization; Uncertainty; Economic dispatch; Wind power forecasting
• ISSN: 2196-5625; 2196-5420
• DOI: 10.1007/s40565-019-0526-5

This paper proposes an adjustable and distributionally robust chance-constrained (ADRCC) optimal power flow (OPF) model for economic dispatch considering wind power forecasting uncertainty. The proposed ADRCC-OPF model is distributionally robust because the uncertainties of the wind power forecasting are represented only by their first- and second-order moments instead of a specific distribution assumption. The proposed model is adjustable because it is formulated as a second-order cone programming (SOCP) model with an adjustable coefficient. This coefficient can control the robustness of the chance constraints, which may be set up for the Gaussian distribution, symmetrically distributional robustness, or distributionally robust cases considering wind forecasting uncertainty. The conservativeness of the ADRCC-OPF model is analyzed and compared with the actual distribution data of wind forecasting error. The system operators can choose an appropriate adjustable coefficient to tradeoff between the economics and system security.