Improved Risk Allocation-Based Algorithm for Chance-Constrained Generation Expansion Planning

Generation Expansion Planning (GEP) with load uncertainty is modeled in this paper using chance constrained programming, and new iterative solution algorithms identifying the stressed and non-stressed buses in the system are developed for solving this model. The algorithms use a risk-based approach to dynamically allocate risk at each bus depending on the response of the system to the load behaviour. Computational results for the IEEE 30- and 118- bus systems are presented and compared with previous approaches. It is observed that expansion solutions meeting the required reliability at lower cost are obtained using this approach.