Open AccessEconomic dispatch coordinated with information granule chance constraint goal programming under the manifold uncertainties
Author(s) -
Yin Jiafu,
Zhao Dongmei
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2018.5329
Subject(s) - mathematical optimization , schedule , economic dispatch , computer science , grid , constraint (computer aided design) , power flow , integer programming , electric power system , constraint programming , scheduling (production processes) , linear programming , operations research , power (physics) , engineering , mathematics , stochastic programming , mechanical engineering , physics , quantum mechanics , geometry , operating system
With the increasing integration of wind power and demand response into power system, the complex uncertainties from supply‐side and demand‐side have brought great challenges to daily operation of the power system. It is essential for enabling a comprehensive and adequate consideration of the manifold uncertainties in the grid. In this study, information granule chance constraint goal programming (IGCCGP) is proposed by a combination of chance constraint goal programming and information granule to provide a uniform representation of the multifaceted uncertainties. Leveraging on IGCCGP, the reserve constraints and branch flow constraints for accommodating the complex uncertainties in the grid are developed and the economic dispatch model considering the combined uncertainties from both supply‐side and demand‐side is established. To accelerate model solutions without losing much of model accuracy, the deviation in the IGCCGP is transformed to a deterministic equivalent and the optimal schedule is obtained by a mixed linear integer programming. Finally, a computational study is illustrated in the IEEE 39‐bus system to verify the efficiency of the proposed method.