Coordination and Optimization of Energy Using the Multiple Linear Regression Analysis in a Green Power System

Xiao Na Niu; Ying Sun; Chuan Hui Zhao; Shen Hang Yu

doi:10.4028/www.scientific.net/AMR.201-203.539

Paper Titles

Finite Element Analysis of Heavy-Duty Dump Truck Subframe Based on ANSYS
p.518

Design and Application of Flexible Auxiliary Haulage System for Material Supply in Underground Coal Mine
p.524

Study on Optimal Real-Time Feedback Scheduling of Networked Collaborative Design Project under Uncertainty
p.529

Study on Topology Optimum Design of Middle Pan
p.534

Coordination and Optimization of Energy Using the Multiple Linear Regression Analysis in a Green Power System
p.539

Optimization on Motion Errors of Ultra-Precision Machine Tools Based on Multi-Body System and Monte Carlo Simulation
p.543

Scroll Profiles Geometric Parameters Optimization Based on CPSO
p.550

Design of Non-Contact Balance Head for Grinding Wheel
p.557

Design of 4-Axis Reconfigurable CNC Machine Tool for Relief Grinding Sphere Gear Hob
p.561

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 201-203Coordination and Optimization of Energy Using the...

Coordination and Optimization of Energy Using the Multiple Linear Regression Analysis in a Green Power System

Abstract:

The State Grid has proposed to construct a strong smart grid to solve the resource scarcity, environmental pollution and other social problems, which will certainly drive the development of green energy, such as wind energy, solar energy, tidal energy and biomass energy. The study will build a Green Power System Assessment Model (GPSAM) using multivariate statistical analysis to optimize the energy resources of a region and finally to provide reference for the construction of a new plant or the plant expansion to get the balance of environment benefit, economic benefit and social benefit.

You might also be interested in these eBooks

Advanced Manufacturing Systems, ICMSE 2011

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 201-203)

Pages:

539-542

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.201-203.539

Citation:

Cite this paper

Online since:

February 2011

Authors:

Xiao Na Niu, Ying Sun, Chuan Hui Zhao, Shen Hang Yu

Keywords:

GPSAM, Green Energy, Multiple Linear Regression Analysis, Optimise

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] C. Genesi, G .P. Granelli, P. Marannino: Power Tech Conference (Bucharest 2009).

Google Scholar

[2] Renhui Huang, Lizi Zhang: The Fifth International Conference on Natural Computation Vol. 6 (2009) p.293.

Google Scholar

[3] Liangchun Yu , Feng Lin: Shandong Social Science Vol. 125(2006) p.1 (In Chinese).

Google Scholar

[4] Bin Xia, Cang Zhao. The Application of Multiple Regression Analysis Forecast in Economical Forecast. Second International Workshop on Knowledge Discovery and Data Mining, 2009: 1-4.

DOI: 10.1109/wkdd.2009.50

Google Scholar

[5] Chinglin Zong, Jangwu Wen: Transactions on Semiconductor Manufacturing Vlo. 121(1999) p.1.

Google Scholar

[6] Youming Wang: Journal of Anhui Technical College of Water Resources and Hydro Electric Vol. 2(2003) p.42 (In Chinese).

Google Scholar

[7] Shigang Feng, Qian Ai: Journal of Power Engineering Vol. 28(2008) p.404 (In Chinese).

Google Scholar

[8] Fu Deyin: Multivariate Statistical Analysis Methods to Test the System Vol. 208(2009) p.76.

Google Scholar

[9] Maofang Hou. The Project Post-evaluation for Hebi Power Plant. North of China Electric Power University, 2008 (In Chinese).

Google Scholar

[10] Backhaus. K: Multivariate Statistical Analysis. (Shanghai-Gezhi Publication, Shanghai, 2009. ).

Google Scholar