Virtual power plant-power distribution network voltage dynamic cooperative control method and device

By employing a virtual power plant-distribution network voltage dynamic collaborative control method, and utilizing quantum feature extraction and hierarchical control decision-making, the challenges of traditional voltage control in scenarios with a high proportion of renewable energy integration are addressed. This approach improves voltage prediction accuracy and the interpretability of control strategies, reduces computational costs, and enhances the resilience of the distribution network and its renewable energy absorption capacity.

CN120955692APending Publication Date: 2025-11-14STATE GRID SHANDONG ELECTRIC POWER CO
0 Cites 2 Cited by

Patent Information

Application Number
CN202511225619.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-29
Publication Date
2025-11-14

AI Technical Summary

Technical Problem

Traditional voltage control methods cannot adapt to the dynamic changes of distributed energy sources, have low voltage prediction accuracy, and artificial feature engineering models are difficult to capture complex spatiotemporal coupling relationships. Deep learning algorithms lack interpretability, resulting in voltage regulation lag and the risk of control strategy violations.

Method used

A virtual power plant-distribution network voltage dynamic collaborative control method is adopted. Through quantum feature extraction, Transformer-XL model fusion, quantum probabilistic modeling, and hierarchical control decision-making, an interpretable scheduling strategy is generated. Combined with quantum Monte Carlo tree search and SHAP value quantification of feature contribution, the model parameters are rapidly iteratively optimized.

Benefits of technology

It improves the prediction accuracy of distributed energy output, shortens the root cause location time of voltage over-limit events, enhances the resilience and security of the distribution network, reduces edge computing costs, improves the renewable energy absorption rate and operation and maintenance efficiency, and ensures that control strategies comply with power system specifications.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention provides a virtual power plant-power distribution network voltage dynamic cooperative control method and device, and the method comprises the steps: obtaining multi-source heterogeneous data to construct a mixed data set, and mapping the mixed data set to a quantum state space for feature extraction; fusing the quantum features, the satellite cloud picture and the voltage waveform data, and modeling by adopting quantum probability; generating a DERs output scene based on a quantum state superposition principle, searching and quantifying the voltage out-of-limit probability amplitude of each node, and generating a power distribution network risk thermodynamic diagram; constructing a hierarchical control decision; the hierarchical control decision is executed, then a causal logic chain of a voltage out-of-limit event is generated through an invariant graph reasoning network, the contribution degree of features to the control decision is quantified, and iterative optimization of model parameters is achieved in combination with a meta-learning mechanism. Based on the method, the invention further provides a voltage dynamic cooperative control device, self-adaptive response of distributed energy uncertainty is achieved, and a solution is provided for voltage stabilization of the power distribution network in a high-proportion new energy access scene.
Need to check novelty before this filing date? Find Prior Art