Inexact Credibility-Constrained Programming Approach for Electricity Planning in Ontario, Canada
Publication: Journal of Energy Engineering
Volume 147, Issue 4
Abstract
Under current changing climatic conditions, there has been a growing interest in green energy to mitigate carbon emissions. As such, proper management and planning of electricity are essential to mitigating climate change. This paper presents a hybrid inexact credibility constraint programming (ICCP) model for planning and optimization in the electricity sector for Ontario, Canada. The model considers the costs and emissions of electricity generated from six sources over a planning horizon of , minimizing system cost while meeting provincial emission goals. The ICCP method addresses uncertainties by transforming fuzzy variables into crisp equivalents with credibility levels, allowing decision-makers to address uncertainties in planning by tackling uncertainties as intervals through an interactive two-step algorithm. This model was applied to electricity planning in Ontario to address uncertainties due to demand predictions, technological advancements, and shifting energy consumption. The cap-and-trade program was compared to the federal carbon pricing backstop program, and the results over the planning horizon were similar. Through this model, expansion options to address future demands were also compared to minimize emissions while meeting electricity demand.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request:
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Historical and current electricity supply and demand; and
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Electrical power generation expansion cost and supply increase.
Acknowledgments
This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).
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Received: Jun 6, 2020
Accepted: Dec 30, 2020
Published online: Apr 29, 2021
Published in print: Aug 1, 2021
Discussion open until: Sep 29, 2021
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