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An Improved Self-Adaptive Particle Swarm Optimization Approach for Short-Term Scheduling of Hydro System

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2 Author(s)
Shuangquan Liu ; Sch. of Hydropower & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan ; Jinwen Wang

An improved particle swarm optimization approach is introduced in this paper, the improvements involves the dasiaworstpsila particlepsilas impact on the particles in addition to that of the dasiabestpsila one. Meanwhile, a self-adaptive inertia weight is adopted to enhance the performance of the approach. With nonlinear constraints handled by a penalty function, the proposed approach is applied to solve the short-term hydro scheduling of an example hydro system, the proposed approach shows a higher performance and obtains promising results compared to the standard particle swarm optimization and other methods of previous researches.

Published in:

2009 International Asia Conference on Informatics in Control, Automation and Robotics

Date of Conference:

1-2 Feb. 2009