A generative-AI-driven risk framework for PV hosting capacity assessment shows that permitting a 5% risk of voltage violations increases allowable PV capacity by about 18% compared with zero-risk deterministic methods.
Probabilistic hosting capacity for active distribution networks,
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A neural network approximates the second-stage recourse model in two-stage stochastic Volt-VAR optimization, allowing the full problem to be solved as a mixed-integer linear program with over 50x speedup and sub-0.3% optimality gap on a 123-bus test system.
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Risk-Based PV-Rich Distribution System Planning Using Generative AI
A generative-AI-driven risk framework for PV hosting capacity assessment shows that permitting a 5% risk of voltage violations increases allowable PV capacity by about 18% compared with zero-risk deterministic methods.
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Neural Two-Stage Stochastic Volt-VAR Optimization for Three-Phase Unbalanced Distribution Systems with Network Reconfiguration
A neural network approximates the second-stage recourse model in two-stage stochastic Volt-VAR optimization, allowing the full problem to be solved as a mixed-integer linear program with over 50x speedup and sub-0.3% optimality gap on a 123-bus test system.