Evaluating the impact of smart grid technologies on generation expansion planning under uncertainties

This paper presents a robust evaluation framework for the application of smart grid technologies in generation expansion planning with enforced uncertainties. Considering the availability of smart grid technologies, mainly including load shifting, cost reduction, and environmental benefits, a deterministic optimization model underlying a robust investment plan is designed as the original generation planning problem that minimizes both cost and emission and subjects to the constraints of the basic plan. The proposed robust optimization methodology is used to explore the robust counterparts of the original planning problem with the uncertainties from the forecast load demand and the availability of new technologies. Moreover, the theoretical issue that the different types of uncertainties lead to different tractable robust measures is addressed by the application of the proposed approach in this paper. The optimal generation planning solution obtained from the presented approach can show the impact of smart grid technologies on investment scheduling under the worst-case uncertainties. The evaluation framework can identify a robustness decision for all realizations of the plan uncertainties, in which simulation results will demonstrate the benefits of the proposed models in case studies.