# Power Systems Data Fusion based on Belief Propagation

arXiv: https://arxiv.org/abs/1705.08815 · HTML: https://mlsanity.com/paper/1705.08815/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 May 2017.

## Built on by (most cited first, 1 of 1)

- [Multi-Source Data Fusion for Cyberattack Detection in Power Systems](https://mlsanity.com/paper/2101.06897/) (2021)

## Abstract (arXiv)

The increasing complexity of the power grid, due to higher penetration of distributed resources and the growing availability of interconnected, distributed metering devices re- quires novel tools for providing a unified and consistent view of the system. A computational framework for power systems data fusion, based on probabilistic graphical models, capable of combining heterogeneous data sources with classical state estimation nodes and other customised computational nodes, is proposed. The framework allows flexible extension of the notion of grid state beyond the view of flows and injection in bus-branch models, and an efficient, naturally distributed inference algorithm can be derived. An application of the data fusion model to the quantification of distributed solar energy is proposed through numerical examples based on semi-synthetic simulations of the standard IEEE 14-bus test case.