A long-term capacity expansion planning model for an electric power system integrating large-size renewable energy technologies

The recent interest in reducing greenhouse gas emissions and the recent technical evolution of energy networks to smart grids have facilitated the integration of renewable energy technologies (RETs) into the electricity sector around the world. Although renewable energy provides substantial benefits for the climate and the economy, the large-size deployment of RETs could possibly hurt the level of power system reliability because of the RETs' technical limitations, intermittency, and non-dispatchability. Many power system planners and operators consider this a critical problem. This paper proposes a possible solution to this problem by designing a new stochastic optimization model for the long-term capacity expansion planning of a power system explicitly incorporating the uncertainty associated with RETs, and develops its solution by using the sample average approximation method. A numerical analysis then shows the effects of the large-scale integration of RETs on not only the power system's reliability level but also, and consequentially, its long-term capacity expansion planning. From the results of the numerical analysis, we show that our proposed model can develop a long-term capacity expansion plan that is more robust with respect to uncertain RETs and quantify the capacity the system requires to be reliable.