Open AccessA Novel Multi-information Fusion Algorithm Based on Population for Wind Power System
Author(s) -
Yufeng Wang,
Chao Xu
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/646/1/012045
Subject(s) - mathematical optimization , population , optimization problem , evolutionary algorithm , electric power system , computer science , capacity optimization , power (physics) , scale (ratio) , algorithm , mathematics , geography , demography , sociology , physics , cartography , quantum mechanics
Reserve capacity optimization of power system plays an important role in large-scale Wind Power System. In this paper, a novel multi-information fusion algorithm based on population (MIFA-P) is proposed, which can balance the problem of reserve capacity optimization. MIFA-P determines the type of optimization problem by counting the maximum number of projections on the principal characteristic axis of the optimal individuals of the current population. Therefore, the corresponding class of evolutionary algorithm is chosen to solve the problem. In the process of evolution, each evolutionary algorithm achieves the organic integration through sharing population information. Finally, the validity and applicability of MIFA-P algorithm for large-scale decision variable black box optimization problem are verified by solving a practical scenario optimization problem of reserve capacity distribution in power system after wind power integration.