电力系统工程师看过来：GENCO一个模型搞定潮流、最优潮流和状态估计，比传统求解器快几十倍，还开源了框架和数据集，想上手试试的别错过。
GENCO（几何神经校正优化器）是一个统一神经求解器，用于稳态输电网分析，涵盖潮流（PF）、最优潮流（OPF）和状态估计（SE）。在PFDelta和OPFData基准上，GENCO在大规模PF中比牛顿-拉夫逊法快30倍，同时匹配DC-PF的功率平衡残差。在OPF中，它比IPOPT快85倍，并提高了可行性和最优性。在SE中，GENCO对噪声和参数误差的鲁棒性优于加权最小二乘法。配套的开源GridFM开发框架和百万级数据集支持可复现的基准测试。
GENCO - A Unified Neural Solver Embedded in a Development Framework for Steady-State Grid Analysis
Foundation models are transforming business workflows and boosting productivity, yet they remain largely absent from engineering domains such as power system analysis, where strict physical consistency must be enforced. We present GENCO (GEometric Neural Corrective Optimizer), a unified neural solver for steady-state transmission grid analysis that handles power flow (PF), optimal power flow (OPF), and state estimation (SE) within a single architecture and shared network representation. To support advances in neural power system solvers, we introduce the open-source GridFM Development Framework, which standardizes synthetic data generation and training in a low-code environment. We also release large-scale datasets with millions of PF and OPF scenarios across diverse grid topologies to support reproducible benchmarking. We evaluate GENCO on the PFDelta and OPFData benchmarks against state-of-the-art neural solvers and classical solvers, including Newton-Raphson and IPOPT, as well as on real-world Hydro-Québec SCADA data. For large-scale PF, GENCO recovers the full AC operating state, including voltage magnitudes and reactive power that DC-PF cannot provide, while matching DC-PF-level active power-balance residuals. It achieves up to 30x speedups over Newton-Raphson at only 2x the runtime of DC-PF. For OPF, it achieves up to 85x speedups over IPOPT while improving feasibility, optimality, and runtime over DC-OPF. For SE, GENCO is more robust than classical weighted least squares to noisy measurements and network parameter errors, and always returns a high-quality estimate even when weighted least squares fails to converge. Together, the unified architecture and development framework provide a new approach to large-scale steady-state grid analysis, lowering the barrier to entry for power system engineers and marking a step toward Grid Foundation Models.