The Working Group on Big Data & Analytics for Transmission Systems belongs to the IEEE PES ​​Subcommittee on Big Data & Analytics for Power Systems and is part of the IEEE Power & Energy Society (IEEE PES).

The energy demand is continuously growing as result of a more digital and technological Society and energy transitions are pushing towards more sustainable societies demanding for modern and carbon-free energy grids.

Implementing measures to fulfil the energy demand mainly based on green energy sources involves technical and economic challenges such as dependency on cross border exchange, the reinforcement of the existing transmission capacity and the need of flexibility by means of creating new interconnections with border countries. As a consequence, the transmission system is becoming vulnerable and operates closer to its boundary conditions, hence becoming more difficult to operate in real time. Consequently, utilities require higher degree of observability in the network from of advance measuring infrastructure in order to improve the decision making and situational awareness of the transmission system.

Under this context, big data analytic (data mining, artificial intelligence and machine learning) unfolds new opportunities to develop sophisticated online and offline dynamic security assessment tools, particularly in bulk power systems where transmission system operators are struggling to cope with expanding data flows and computational demands.