Solar energy paper index
Data-Driven Operational Risk Assessment in Renewable-Rich Power System. An Automated Probabilistic Power Flow and SCADA Data Mining Framework
One-line summary
A solar energy research paper on Data-Driven Operational Risk Assessment in Renewable-Rich Power System. An Automated Probabilistic Power Flow and SCADA Data Mining Framework.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
The increasing penetration of variable renewable energy (VRE) introduces profound stochastic uncertainties into power systems, rendering traditional deterministic security assessments insufficient. This paper addresses this challenge by developing a comprehensive, AI-ready operational risk assessment framework based on a data-driven Probabilistic Power Flow (PPF) approach. Unlike conventional methods that rely on assumed statistical distributions, the proposed methodology employs a statistical learning pipeline to identify suitable probability density functions directly from historical SCADA telemetry, thereby ensuring high-fidelity input modeling. Furthermore, a cluster-based correlation strategy, rooted in unsupervised pattern recognition, is constructed to rigorously capture the spatiotemporal dependencies among renewable generation sources. The probabilistic framework is executed via an enhanced Monte Carlo simulation (MCS) utilizing Latin Hypercube Sampling (LHS) to improve computational efficiency. Validated through a case study on the Central Vietnam Power System, the results demonstrate that the proposed framework effectively uncovers hidden operational vulnerabilities, specifically identifying a 4.57% probability of exceeding the 90% branch-loading warning threshold on the critical 220 kV Quy Nhon - Tuy Hoa transmission line, while the probability of actual thermal overload above 100% is nearly zero. This near-limit operating risk profile may be masked by conventional deterministic snapshots. The findings emphasize that accurately modeling the correlation structure of renewable sources is indispensable for realistic risk quantification, providing system operators with a robust, algorithm-driven decision-support tool for grid security management.
Links and sources
Need this topic turned into a technical roadmap?
Power for Solar can prepare a custom solar energy literature review, simulation code map, dataset map, and B2B photovoltaic technology assessment.
Request B2B research
Comments