Multi-agent semantic interoperability in complex energy systems simulation and decision support

Abstract

This work introduces a multi-agent systems' society, in power and energy, for simulation and decision support. A semantic data model is considered to describe the domain concepts, providing a way to achieve semantic communication between the systems involved. Sharing a common vocabulary enables systems' interoperability. A semantic registration and search platform, where systems can register their services and/or search for services they require, is also considered to facilitate interoperability in a (semi-)automatic way. Advanced context-aware decision support models and methods based on a strong artificial intelligence approach are also available to enhance players' outcomes from their participation in the sector. The case study presents an integrated laboratorial simulation and emulation infrastructure, enabling a realistic test and validation of the results.