Summary
To ensure the secure, stable, and economic operation of receiving-end grids with multi-DC and renewable energy integration, this paper proposes a bi-level optimization method to enhance
Read more Read lessDC infeed capacity and renewable utilization. First, a joint probability distribution model of wind power and load is constructed using Interval-Partition-based Adaptive Kernel Density
Estimation (IP-AKDE) and Copula functions, with typical correlation scenarios generated via
Gibbs sampling. Subsequently, a bi-level optimization framework is established: the upperlevel model optimizes DC infeed points and reactive power compensation to maximize infeed capacity and transient voltage support while minimizing installation costs of compensation devices; the lower-level model optimizes source-storage operation modes under the generated scenarios to minimize operating costs and facilitate wind power integration. The bi-level model is solved iteratively using the MOEA/D algorithm and Gurobi solver. Simulation results on a modified IEEE 39-bus system and an actual provincial grid in China demonstrate that the proposed method effectively improves both the DC infeed scale and renewable energy integration levels.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | C1_11470_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | China, People's Republic of |
| Study committees | |
| File size | 763 KB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
TANG Wei - Anhui Electric Power Research Institute; MAO Xun - Anhui Electric Power Research Institute; DONG Wangchao - Anhui Electric Power Research Institute; LV Kai - Anhui Electric Power Research Institute
Keywords
Receiving-end grid, multi-DC infeed capacity, renewable energy integration, scenario construction, IP-AKDE, Copula, bi-level optimization, DC infeed points, source-storage coordination
