Scenario Selection for Generation Expansion Planning with Demand and Wind Uncertainty

In this paper, representative operating scenario selection for generation expansion planning with demand and wind uncertainty is addressed. Kmeans++ clustering technique is used to generate the operating scenarios and the results are compared with the commonly used duration curve and kmeans clustering techniques in terms of cost and reliability. Furthermore, impact of data correlation on the scenario selection and investment results is investigated. The planning problem is simulated for the IEEE 24-bus test system.