A dynamic two-stage energy systems planning model for Saskatchewan, Canada

Energy is an indispensable input for socio-economic development. Over the past decades, the increase of energy consumption significantly elevated greenhouse gases emissions and resulted in tremendous environmental problems. To evaluate these impacts associated with energy activities, many optimization-based energy-system models were developed. However, none of these models were capable of handling management and planning of energy systems from a macroscopic point of view. There is also a lack of effective linkage between system objective and emission-reduction policies.;Therefore, two energy models based on two-stage stochastic programming were developed in this study, which considerably extended the previous programming methods for energy systems planning. A dynamic two-stage energy-system planning (DTEP) model was developed through incorporating a mixed-integer method and a two-stage stochastic programming approach within a general optimization framework. An inexact two-stage energy-system planning (ITEP) model was then advanced through integrating an interval-programming approach into the DTEP model. The DTEP model was then used for energy-system planning of Saskatchewan, with two scenarios being examined under various emissions policies.;In the application of the DTEP model to Saskatchewan energy system for accommodating planning, two cases are examined based on different GHG emission policies. The Saskatchewan energy system planning model incorporates GHG mitigation targets and economic objective in energy system, takes advantage of marginal prices as system penalty, employs optimization methods to address capacity expansion and system capacity expansion and system uncertainty issues, classifies GHG emissions by intermediate technologies and by energy end-users. The results indicate that this is a powerful and efficient tool for evaluating feasibility of emissions policies and their effects on energy system planning.