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Energies 2015, 8(1), 233-256; doi:10.3390/en8010233

A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming

School of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
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Author to whom correspondence should be addressed.
Academic Editor: Erik Gawel
Received: 30 September 2014 / Accepted: 18 December 2014 / Published: 29 December 2014
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Abstract

In order to maintain the stability and security of the power system, the uncertainty and intermittency of wind power must be taken into account in economic dispatch (ED) problems. In this paper, a dynamic economic dispatch (DED) model based on chance constrained programming is presented and an improved particle swarm optimization (PSO) approach is proposed to solve the problem. Wind power is regarded as a random variable and is included in the chance constraint. New formulation of up and down spinning reserve constraints are presented under expectation meaning. The improved PSO algorithm combines a feasible region adjustment strategy with a hill climbing search operation based on the basic PSO. Simulations are performed under three distinct test systems with different generators. Results show that both the proposed DED model and the improved PSO approach are effective. View Full-Text
Keywords: wind power; dynamic economic dispatch; spinning reserve; chance constraintprogramming; particle swarm optimization wind power; dynamic economic dispatch; spinning reserve; chance constraintprogramming; particle swarm optimization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Cheng, W.; Zhang, H. A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming. Energies 2015, 8, 233-256.

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