考虑直流输电灵活性的大规模新能源基地容量规划方法OA

With the large-scale development of renewable energy bases focusing on deserts,the Gobi and barren areas,the cross-regional transmission of a high proportion of renewable energy via HVDC channels faces the challenge of coordinating output uncertainty with transmission flexibility.Traditional planning methods often treat the HVDC transmission curve as a static constraint and seldom consider the load characteristics of the receiving-end.To address these issues,this paper proposes a capacity expansion planning method for large-scale renewable energy bases considering HVDC transmission flexibility.First,a conditional generative adversarial network(CGAN)is employed to model the uncertainty of renewable energy output,generating and clustering multiple typical temporal scenarios.Second,a stochastic planning model is established that accounts for both HVDC operational flexibility and renewable energy uncertainty.This model is the first to integrate receiving-end load characteristics and HVDC flexibility constraints into the sending-end power source planning framework,establishing a highly synergistic capacity allocation mechanism among power sources,the grid,and the load.Aiming at optimizing the total investment and operational costs,the model incorporates key flexibility constraints such as HVDC constant operation duration and ramp rates.It optimizes the power base capacity while considering the HVDC power curve optimization to avoid the dilemma where inflexible HVDC transmission leads to renewable energy curtailment at the sending end and peaking challenges at the receiving end.Finally,a simulation based on a typical renewable energy base in Western China is conducted.The results show that improving transmission flexibility can significantly reduce the total system cost and increase renewable energy penetration,verifying the effectiveness of the proposed planning method.