Abstract
Generation expansion planning (GEP) problem involves determining new power plants in terms of type, capacity and allocation for meeting future load demands. The GEP problem incorporates large number of constraints and it is a highly complex, large scale, non linear optimization problem. Large scale integration of Renewable Energy systems (RES) in GEP problem has always been averted by the high cost and poor availability rates of RES as compared to conventional fossil fuel fired power plants. However internalizing environmental externalities in GEP problem could help to promote large scale integration of RES. The proposed model in this paper examines the effect of internalizing externalities on the GEP problem. External cost values for China are evaluated using the unit damage costs of pollutants. The model has been implemented in MATLAB using Genetic Algorithm and is applied to a case study of one of the district power companies of China. The results show significant structural changes in favor of RES confirming that internalizing externalities can be used as a driving policy tool for large scale integration of RES.
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