A Stochastic Programming Model for Power Generation Expansion Planning in Iran

In this paper, by developing a mixed integer stochastic programming model, total cost of construction of new power generation capacity using various technologies and the cost of generating electricity during a planning horizon is minimized. The demand is considered uncertain in this model and is assumed to follow three possible scenarios. In this study, the country is divided to several regions and the investment decisions are taken for each region in an integrated model. Furthermore, a learning mechanism of technologies is considered in the model, so the cost of investment in technologies will decrease as installed capacity of each technology is increasing. Finally, in order to analyze the output of optimization model, by developing a system dynamic model, the impacts of the proposed plan on some power industry indicators such as cost and profit is shown with respect to each demand scenario.
The resulting capacity expansion plan consists of various power generation technologies among which gas turbine power plant constitutes the biggest part of the expansion plan. Other technologies such as hydro, combined cycle, nuclear, geothermal and wind power plants exist in the expansion plan.