Dual Layer Source Grid Load Storage Collaborative Planning Model Based on Benders Decomposition: Distribution Network Optimization Considering Low-Carbon and Economy

The author proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network. The model plans the configuration of photovoltaic (3.8 MW), wind power (2.5 MW), energy storage (2.2 MWh), and SVC (1.2 Mvar) through interaction between upper and lower layers, and modifies lines 2–3, 8–9, etc. to improve transmission capacity and voltage stability. The author uses normal distribution and Monte Carlo method to model load uncertainty, and combines Weibull distribution to describe wind speed characteristics. Compared to the traditional three-layer model (TLM), Benders decomposition-based two-layer model (BLBD) has a 58.1% reduction in convergence time (5.36 vs. 12.78 h), a 51.1% reduction in iteration times (23 vs. 47 times), a 8.07% reduction in total cost (12.436 vs. 13.528 million yuan), and a 9.62% reduction in carbon emissions (12,456 vs. 13,782 t). After optimization, the peak valley difference decreased from 4.1 to 2.9 MW, the renewable energy consumption rate reached 93.4%, and the energy storage efficiency was 87.6%. The model has been validated in the IEEE 33 node system, demonstrating its superiority in terms of economy, low-carbon, and reliability.