Regional Electric-Power Systems Planning and Carbon Dioxide Emissions Management under Uncertainty

Authors

  • Y.F. Li MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Resources and Environmental Research Academy, North China Electric Power University
  • Y.P. Li MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Resources and Environmental Research Academy, North China Electric Power University
  • G.H. Huang MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Resources and Environmental Research Academy, North China Electric Power University

DOI:

https://doi.org/10.6000/1929-6002.2015.04.04.3

Keywords:

CO2 emission, electric-power systems, optimization, planning, renewable energy, uncertainty analysis

Abstract

In this study, an interval two-stage integer programming model is formulated for planning electric-power systems and managing carbon dioxide (CO2) emissions under uncertainty. The developed model can reflect dynamic, interactive, and uncertain characteristics of regional energy systems. Besides, the model can be used for answering questions related to types, times, demands and mitigations of energy systems planning practices, with the objective of minimizing system cost over a long-time planning horizon. The developed model is also applied to a case study of planning CO2-emission mitigation for an electric-power system that involves fossil-fueled and renewable energy sources. Solutions can help generate electricity-generation schemes and capacity-expansion plans under different CO2-mitigation options and electricity-demand levels. Different CO2-emission management policies corresponding to different renewable energy development plans are analyzed. A high system cost will increase renewable energy supply and reduce CO2 emission, while a desire for a low cost will run into risks of a high energy deficiency and a high CO2 emission.

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Published

2015-12-18

How to Cite

Li, Y., Li, Y., & Huang, G. (2015). Regional Electric-Power Systems Planning and Carbon Dioxide Emissions Management under Uncertainty. Journal of Technology Innovations in Renewable Energy, 4(4), 129–146. https://doi.org/10.6000/1929-6002.2015.04.04.3

Issue

Vol. 4 No. 4 (2015)

Section

Articles

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Copyright (c) 2015 Journal of Technology Innovations in Renewable Energy

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