Scenario-Based Multi-Objective Optimal Dispatch Considering Forecast Uncertainties

Xiao Hui Zhang; Ke Ke Yan; Jia Qing Zhong

doi:10.4028/www.scientific.net/AMM.427-429.337

Paper Titles

Analysis on Usage Comfort of Highway Based on Lateral Acceleration and Lateral Acceleration Change Rate
p.320

Applicability Research for Masonry Mortar Compressive Strength Curve Using Penetration Resistance Method
p.325

Study on Equivalent Damping in Nonlinear Fluidlastic Damper of Helicopter Rotor
p.329

Rubber Block Granular Control Study in the Crushing Process Waste Tires
p.333

Scenario-Based Multi-Objective Optimal Dispatch Considering Forecast Uncertainties
p.337

Co-Optimization of Output and Reserve with Significant Penetration of Renewables
p.341

Dynamical Analysis of a Cantilever Column with a Tip Mass Subjected to Subtangential Follower Force
p.346

The Reliability Analysis of Car Electronic Horn Sound Level Based on the Fault Tree
p.350

Combined Improved EEMD with SVM in the Bearing Low Dimensional Small Sample Fault Diagnosis
p.354

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429Scenario-Based Multi-Objective Optimal Dispatch...

Scenario-Based Multi-Objective Optimal Dispatch Considering Forecast Uncertainties

Abstract:

Renewable energy recourses and Wind Power Generators are playing an ever-increasing role in power generation. In this paper, a two stage scenario-based approach considering load/wind forecast uncertainty is implemented for multi-objective economic emission dispatch problem which concludes minimize total fuel cost and emission simultaneously. Besides, an improved optimization algorithm of multi-objective based on Particle Swarm Optimization (MOIPSO) is implemented to extract the best solution for the stochastic problem. The proposed method is tested on a power system having 6-unit in order to measure its efficiency and feasibility.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

337-340

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.337

Citation:

Cite this paper

Online since:

September 2013

Authors:

Xiao Hui Zhang*, Ke Ke Yan, Jia Qing Zhong

Keywords:

Component, Multi-Objective Improved Particle Swarm Optimization, Stochastic Dynamic Economic Emission Dispatch, Wind Power

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] C-L Chen, W-C Lee, Multi-objective optimization of multi-objective supply chain networks with uncertain product demands and prices [J]. Computers and Chemical Engineering, 2004(28) 1131–1144.

DOI: 10.1016/j.compchemeng.2003.09.014

Google Scholar

[2] R. H. Liang,J. H. Liao. A fuzzy-optimization approach for generation scheduling with wind and solar energy systems [J]. IEEE Trans. Power Syst, 2007(22).

DOI: 10.1109/tpwrs.2007.907527

Google Scholar

[3] N. Amjady,J. Aghaei,H. A. Shayanfar. Stochastic Multi-objective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security[J]. IEEE Trans. Power Syst, 2009(24).

DOI: 10.1109/tpwrs.2009.2030364

Google Scholar

[4] R. Billinton,R. N. Allan. Reliability Evaluation of Power Systems, 2nd ed. New York: Plenum, (1996).

Google Scholar

[5] Z. Michalewicz. Genetic Algorithm + Data Structure = Evalution Program, Comput. New York: Springer-Verlag, (1996).

Google Scholar

[6] Dun-wei Gong, Yong Zhang, Cheng-liang Qi. Environmental/economic power dispatch using a hybrid multi-objective optimization algorithm [J]. Electrical Power and Energy Systems, 2010 (32) 607–614.

DOI: 10.1016/j.ijepes.2009.11.017

Google Scholar

[7] Taher Niknam, Rasoul Azizipanah　Abarghooee. An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation [J]. Applied Energy, 2012 (99)455–470.

DOI: 10.1016/j.apenergy.2012.04.017

Google Scholar