Integrated Regional Renewable and Nonrenewable Energy Policies Identified through Interval Stochastic Semi-Infinite Programming
Publication: Journal of Energy Engineering
Volume 139, Issue 2
Abstract
This paper proposes an interval stochastic semi-infinite programming (ICCSIP) method for identification of regional renewable and nonrenewable energy policies under multiple uncertainties. Relative to conventional methods (e.g., interval linear programming and chance-constrained programming), it has the advantages of addressing the association of system cost with nonrenewable energy price, generating reliable solutions with a low risk of system failure, and providing flexible capital availability that varies with respect to nonrenewable energy price. A case study is used to illustrate the performance of ICCSIP with respect to two scenarios. Scenario 1 neglects control of air pollutant emissions and scenario 2 attempts to address it. Nonrenewable energy sources would be primarily used under scenario 1; in particular, coal would play the most important role with respect to optimum energy supply schemes. Under scenario 2, hydrological and wind energy would be the first and second choices, respectively, in terms of electricity generation. Moreover, air pollutant emissions under scenario 2 would be dramatically less than scenario 1; however, an increased system cost would be required for control of air pollutant emissions.
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Acknowledgments
The Program for China National Funds for Excellent Young Scientists (51222906), The Program for New Century Excellent Talents in University of China (NCET-11-0632), National Natural Science Foundation of China (41271540), and the Fundamental Research Funds for the Central Universities.
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Information & Authors
Information
Published In
Journal of Energy Engineering
Volume 139 • Issue 2 • June 2013
Pages: 80 - 90
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Nov 9, 2010
Accepted: Sep 10, 2012
Published online: May 15, 2013
Published in print: Jun 1, 2013
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