Analyzing the performance of clean development mechanism for electric power systems under uncertain environment

As the leading contributor of carbon dioxide (CO2) emissions, electric-power systems (EPS) are facing tremendous pressure to curb their emissions. However, a variety of complexities and uncertainties exist in CO2-emission processes and some impact factors (e.g., mitigation measure, system parameters). In this study, a robust interval-fuzzy programming (RIFP) method is developed for supporting low-carbon transition of EPS that is associated with various uncertainties and risks. Then, a RIFP-based clean development mechanism (RIFP-CDM) model is formulated for planning EPS of Bayingolin Mongol Autonomous Prefecture (Bazhou), in which two cases are designed to analyze the impacts of CDM on the local energy produce. Results indicate that CDM can create an opportunity for large-scale renewable energy project because Bazhou has abundant hydro and wind resources; compared with the basic case, renewable energy CDM project has advantages in realizing CO2-emission reduction as well as adjusting the local energy mix. Besides, uncertainty analysis can help decision makers to gain insight to tradeoffs among risk-control level, satisfaction level, economic penalty, and system cost. The findings can help Bazhou exploring the transition pathways of sustainable development through CDM and offer useful information for policy investigation under multiple uncertainties.