A Structural Adjustment optimization model for electric-power system management under multiple Uncertainties—A case study of Urumqi city, China

In this study,a structural adjustment optimization model for electric-power system management under fuzzy-random environment was developed for regional electric power system management in Urumqi, China. The emission control policy andstructural adjustment are considered and quantified in the developed model to tackle the electric power problems of a regional electric-power system. The objective of this study was to develop a power structural adjustment optimization model with fuzzy-random parameters for discussing the effects, merits and defects of structural adjustment and policy adjustment to manage the electric power system of the city Urumqi. Finally, the results and comparisons analysis of the case study demonstrated the practicality and efficiency of the optimization method. The results indicated that the model can provide an effective linkage between conflicting economic cost and the system stability, and different power demand levels correspond to different electricity generation schemes with varied energy policy and power structural adjustment. The power generation schemes, pollution emission and CO2 emission were analyzed. The modeling results are valuable for supporting the adjustment or justification of the energy policies and structures within a complicated power system under uncertainty.