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Energy Sources, Part B: Economics, Planning, and Policy Volume 6, 2011 - Issue 4
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Original Articles

DESPU: Dynamic Optimization for Energy Systems Planning Under Uncertainty

Q. G. Lin Adaptation and Impacts Research Section, Environment Canada, Regina, Saskatchewan, Canada; China-Canada Research Center on Climate Change Scenarios, MOE Key Laboratory of Regional Energy Systems Optimization, North China Electric Power University, Beijing, China
,
G. H. Huang Center for Studies in Energy and Environment, University of Regina, Regina, Saskatchewan, Canada; MOE Key Laboratory of Regional Energy Systems Research, North China Electric Power University, Beijing, China
,
B. Bass Institute for Environmental Studies, University of Toronto, Toronto, ON, Canada
,
Y. F. Huang Department of Hydraulic Engineering, Tsinghua University, Beijing, China
&
X. D. Zhang Center for Studies in Energy and Environment, University of Regina, Regina, Saskatchewan, Canada
Pages 321-338 | Received 12 Oct 2007, Published online: 28 Jul 2011
 
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Abstract

The planning of energy systems is associated with various uncertainties. Such uncertainties may only be expressed by interval numbers or fuzzy sets rather than probability distributions. In addition, issues of capacity expansion related to timing, sizing and siting under such uncertainties needs to be addressed. Therefore, the objective of this research is to develop a dynamic optimization model for energy systems planning under uncertainty (DESPU) through integrating interval-parameter, fuzzy and mixed integer programming techniques within an energy systems management framework. The developed methodology is then applied to a hypothetical regional energy system. The results indicate that DESPU has advantages in reflecting complexities of various uncertainties as well as dealing with problems of capacity expansion within energy systems.

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