The scheme of wind-storage combined system capacity configuration based on random fuzzy chance constrained bi-level programming

A random fuzzy chance constrained bilevel programming scheme for distributed wind-storage combined system is proposed. The random fuzzy simulation is used to describe the uncertainty of distributed wind power output. The reliability of randomness and ambiguity is taken as the index to evaluate the c...

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Bibliographic Details
Published in:MATEC web of conferences 2018-01, Vol.232, p.4060
Main Authors: OU, Mingyong, WU, Zhenyu, YU, Haifeng, JIANG, Xing, LI, Yinyi, LU, Wenlin
Format: Article
Language:English
Subjects:
Confidence intervals
Constraints
Electric power distribution
Genetic algorithms
Optimization
Power flow
Reliability analysis
Security
Simulation
Wind power
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Summary:A random fuzzy chance constrained bilevel programming scheme for distributed wind-storage combined system is proposed. The random fuzzy simulation is used to describe the uncertainty of distributed wind power output. The reliability of randomness and ambiguity is taken as the index to evaluate the capacity allocation scheme of the distributed wind-storage combined system. Considering system power balance, opportunity measurement constraint of static security index and active management (AM) measures, the random fuzzy expectation value of maximum annual profit is set as the upper optimization goal, and the minimum random fuzzy expectation value of the distributed wind power active reduction is set as the lower optimization target. The scheme is constructed by judging whether the static security index of the upper goal satisfies the confidence level of the random fuzzy chance constraint and the coordination of the upper and lower goals. Finally, the random fuzzy simulation, the forward pushback power flow calculation and the genetic algorithm (GA) are applied to solve the model. The simulation result of IEEE 14-bus example shows the effectiveness and superiority of the model and scheme.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/201823204060