An Overview of the Energy Systems Allocation Model under Uncertainty

Zhong Ming Zhang; Hong Xue Wang

doi:10.4028/www.scientific.net/AMM.733.986

Paper Titles

Based on the Identification and Location Quotient Measure Law CES Yulin New Energy Industry Clusters and Analysis
p.960

The Research of Supply Chain Optimization Theory Based on Service-Oriented Manufacturing
p.964

Safety Management Pattern for Equipment Complex System
p.968

Development of High-End Agriculture Based on Dynamic Diamond Model
p.974

Analysis of Technique-Economy Studies of Branch System Calculation Method
p.978

Based on ARCGIS-SDE Spatial Evolution Trend of Industrial Clusters Space
p.982

An Overview of the Energy Systems Allocation Model under Uncertainty
p.986

The Feasibility Analysis and Development of the PET Regenerated Staple Fiber Industry
p.990

Theoretical Framework and Research Case of the Energy Enterprise Internal Auditing Management System’s Innovation and Upgrade
p.994

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 733An Overview of the Energy Systems Allocation Model...

An Overview of the Energy Systems Allocation Model under Uncertainty

Abstract:

Energy is the basic industry of the national economy, the social and economic development. It plays a very important role in the improvement of human living standards. However, in the actual planning process, a lot of the energy system complexity and uncertainty of information exists, the traditional energy model does not reflect this characteristic. Therefore, this short paper will make a brief introduction of the uncertainty of the Energy System allocation model.

You might also be interested in these eBooks

Engineering Decisions for Industrial Development

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 733)

Pages:

986-989

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.733.986

Citation:

Cite this paper

Online since:

February 2015

Authors:

Zhong Ming Zhang*, Hong Xue Wang

Keywords:

Energy Systems Allocation Model, Optimization, Uncertain

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Lin Q.G., Huang G.H. IPEM an interval-parameter energy systems planning model[J]. Energy Source, Part A, 2008, 30, pp.1382-1399.

DOI: 10.1080/15567030801929043

Google Scholar

[2] Li Y.P., Huang G.H., Chen X. An interval-valued minimax-regret analysis approach for the identification of optimal greenhouse-gas abatement strategies under uncertainty[J]. Energy Policy, 2011, 39, pp.4313-4324.

DOI: 10.1016/j.enpol.2011.04.049

Google Scholar

[3] Zhang Y.M., Huang G,H., Lin Q.G., et al Integer fuzzy credibility constrained programming for power system management[J]. Energy, 2012, 38: 398-405.

DOI: 10.1016/j.energy.2011.11.035

Google Scholar

[4] Liu Y., Huang G.H., Cai Y.P., et al. Development of an inexact optimization model for coupled coal and power management in North China[J]. Energy Policy, 2009, 37(11): 4345-4363.

DOI: 10.1016/j.enpol.2009.05.050

Google Scholar

[5] Chen W.T., Li Y.R., Huang G.H., et al. A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty[J]. Applied Energy, 2010, 87(3): 1033-1047.

DOI: 10.1016/j.apenergy.2009.09.016

Google Scholar

[6] Zhang Y.M., Huang G.H. Inexact credibility constrained programming for environmental system management[J]. Resources, Conservation and Recycling 2011, 55: 441-447.

DOI: 10.1016/j.resconrec.2010.11.007

Google Scholar

[7] Liu Z.F., Huang G.H., Li N. A dynamic optimization approach for power generation planning under uncertainty [J]. Energy source (Part A) 2008, 30: 1413-1431.

Google Scholar