As distributed renewable energy generators proliferate across electricity networks, utilities face mounting pressure to plan grid expansions that accommodate variable renewable output while maintaining reliability. A new optimization framework tackles this challenge by integrating multiple flexibility resources into a cohesive distribution network expansion strategy.
The research proposes a two-stage planning model that simultaneously considers traditional infrastructure upgrades—substation construction and line extensions—alongside emerging technologies. Soft open points, which are remotely controlled switches that can rapidly adjust voltage and power flow, are deployed strategically to enhance network adaptability. Energy storage systems are also sized and located to smooth renewable variability and support flexibility.
A key innovation is the introduction of "flexibility zones" as metrics to evaluate how well the distribution network can respond to uncertainty. Rather than relying on historical data alone, the methodology employs multivariate copula functions to capture correlations between renewable generation patterns and customer loads, enabling more realistic scenario modeling.
The planning model uses a three-level solution approach grounded in distributionally robust optimization theory. This technique handles worst-case uncertainty without requiring exhaustive historical datasets, making it practical for regions with limited operational experience or rapidly changing generation patterns.
Validation on a modified 54-bus Portuguese distribution system demonstrates the methodology's robustness. The framework successfully identified optimal combinations of new substations, line extensions, soft open points, and storage systems that balance capital costs with operational flexibility.
For utilities planning grid modernization, this approach offers a systematic way to allocate limited investment capital across competing technology options while explicitly accounting for renewable variability. As distribution networks evolve toward active, bidirectional power flows, such integrated planning methods become essential for cost-effective, reliable grid operation.
