Data-Driven Approach based Tri-Level Generation and Transmission Expansion Planning Model with High Wind Penetration

Renewable energy (RE) has received considerable attention in the last decades due to its advantage of sustainability and environmental friendliness. Power system expansion is faced with unneglible challenge when integrating renewable energy. To make the investment decisions robust and economic, a date-driven tri-level generation and transmission expansion planning model is proposed, considering the renewable output uncertainty and operational flexibility. By taking advantage of the historical data, an ambiguity set is developed to cover all the possible distribution of renewable resource, and then to find the worst-case scenarios. The operational flexibility is captured by modeling flexibility limits of thermal generators. To handle with the nonlinear constraints, a quasi-exact approach is introduced to linearize the proposed planning model. Then a Column-and-Constraint generation based decomposition framework is developed to tackle the solution complexity. Simulation results on the modified 6 bus test system are presented to demonstrate the effectiveness of the proposed model. Case studies show the advantage of the proposed model in the aspect of decreasing conservativeness, and the importance of considering flexibility into the generation and transmission expansion planning involving the high level of renewable energy integration.