Scheduling Scheme Based on Smart Grid of Energy-Saving

Ke Zhang

doi:10.4028/www.scientific.net/AMM.340.908

Paper Titles

Computational Research of Internal Temperature Distribution for Liver Tissues under Laser Irradiation
p.887

Numerical Simulation of Roadway Deformation of Different Cutting Aperture
p.892

Influence of Noise to Chaotic Time Series Prediction in Environment
p.896

Study on the Property Dynamic Filtration Performance of Anthranilic Acid Copper in Environment Engineering
p.903

Scheduling Scheme Based on Smart Grid of Energy-Saving
p.908

Online Monitoring System of Tailing Dam Seepage Line in Abominable Weather
p.913

Research on Sedimentary Facies of Formation of Neogene in Oilfield
p.920

Quality and Safety Warning of Edible Forest Products Based on Gray Forecast Model
p.924

Research on Water Pollution Monitoring System
p.929

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 340Scheduling Scheme Based on Smart Grid of...

Scheduling Scheme Based on Smart Grid of Energy-Saving

Abstract:

The smart grid is an ideal solution of the future electricity system, and scheduling aspects of the smart grid, the nerve center of the most intelligent can best embody the intelligent characteristic, this article summarizes the development of smart grid technologies, energy-saving scheduling, and the smart grid ofsignificance analysis to explore the implementation of energy-saving dispatch to the power industry, an energy efficient scheduling model and highlight the superiority of the energy-saving scheduling in order to ensure the smooth implementation of energy-saving scheduling.

You might also be interested in these eBooks

Green Manufacturing, Mechanical and Automation Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 340)

Pages:

908-912

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.340.908

Citation:

Cite this paper

Online since:

July 2013

Authors:

Ke Zhang

Keywords:

Optimal Combination of Unit, Power System, Scheduling Control, Smart Grid (SG)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] C Kang, Q Cheng, Q Xia. (2009), Prospects of low-carbon electricity. Power System Technology, Vol. 33 pp.1-7.

Google Scholar

[2] J Li, H Wei (2008) Unit commitment via local search point method. Proceedings of the CSEE, Vol. 28p. 33-40.

Google Scholar

[3] Z Wang, Y Yu, H Zhang. (2004) Social evolutionary programming based unit commitment. Proceedings of the CSEE, Vol. 24p. 12-17.

Google Scholar

[4] J.H. Irschenhofer, (2000)D.B. Stauffer, R.R.E. Ngleman, Fuel Cell and book (Fifth Edition), EG&G Services Parsons, Inc, U. S. 2(4): 38-45.

Google Scholar

[5] A.W. Burke, U.L. Paeitors, (2000) Why, how, and where is the technology, Journal of Power Sources, vol. 1p. 37-50.

Google Scholar

[6] B.E. Conway (1999), Electronic technical SuPer capacitor Kluwer Acaderni Plenum Publisher, New York, 93-97.

Google Scholar

[7] G Wu. (2008)Economic load dispatching based on chaos genetic algorithm and fuzzy decision. Beijing Jiaotong University, 02(11): 33-39.

Google Scholar

[8] F.F. Wu , (1990)Power System State Estimation: A Survey. Electrical Power&Energy Systems. Vol. 12p. 80-87.

Google Scholar

[9] Draft Nistir 7628. (2010) Smart Grid Cyber Security Strategy and Requirements. 4(2): 40-47.

Google Scholar

[10] Steve Collier. (2009)Ten Steps to a Smarter Grid. Rurral Electric Power Conference. Vol. 9p. 35-39.

Google Scholar