Implementing Robust Optimization to Cope with the Uncertainty of Wind Power Generation in the Generation Expansion Planning

The aim of the generation expansion planning (GEP) is finding suitable technology, time and installation location of new plants in a specified time period such that the installed capacity will satisfy the load demand growth with acceptable level of reliability. In this paper, we investigate one of the important approaches known as robust optimization (RO) to consider uncertainties such as forecasted electricity load demand, wind power generation, as well as investment and operation costs. The optimal generation expansion plan obtained from the proposed RO approach is immunized against worst-case planning uncertainties considering the adopted degree of conservatism for each uncertainty set. A decomposition algorithm technique has been implemented to solve the robust counterpart of the original GEP problem in terms of cutting planes. To reduce the utility cost, the wind power plant has been utiled in robust generation expansion planning. Accordingly, the uncertaint parameters (including wind power genaration uncertainty and investment cost) have been modeled based the metod of Bertsymas and Sim.