A Rolling Optimization Generation Expansion Planning under Uncertainty of Planning Boundary

A green-oriented transition of power system is of great significance to achieve carbon peaking and carbon neutrality goals. In order to tackle the uncertainty of boundary condition in generation expansion planning, this paper proposes a novel generation expansion planning model under the uncertainty of boundary condition. Firstly, a pre-planning model aimed at minimize the expected cost of the system during the planning period is established, which considers the constraints of power balance and natural resources. Secondly, a rolling optimization generation expansion planning is established to obtain the whole decision sequence. Each rolling optimization is based on the decision obtained by the previous optimization, and the current decision results are obtained by predicting the future boundary conditions. Finally, Case studies construct the evolution route of the power structure from 2025 to 2060 in detail. Compared with the results of the traditional method, the total expected cost of the system is reduced by 10.71 %, and the expected carbon emission is reduced by 5.51%, which verifies the effectiveness of the model.