Adaptive Robust Planning-Operation Co-optimization of Energy Hubs with Modified Column-and-Constraint Generation Algorithm

The uncertainties due to large numbers of distributed renewable energy resources integration and load demand variation in power system have brought great challenges to planning and operation strategies. In this paper, an adaptive two-stage robust optimization (RO) program is built to model the planning-operation co-optimization problem for Energy Hubs. Based on adjustable RO theories and corresponding validations, the constraint-wise property of some uncertainties is recast and simplified before Column-and-Constraint Generation (CCG) is applied, thus we proposed a Modified CCG (MCCG) algorithm, which is even more efficient in large-scale problems than traditional CCG. Case studies with multiple Energy Hubs proved the efficiency and effectiveness of MCCG, which is believed to be also applicable in other two-stage RO problems.