A Data Analytics Perspective of Power Grid Analysis-Part 1: The Clarke and Related Transforms [Lecture Notes

Abstract

Affordable, reliable, and readily accessible electric power underpins our modern society in a multitude of ways, and in this context, the smart grid is becoming an increasingly important factor in power generation, transmission, and distribution. Current analytical tools for the planning, operation, and circuit design in power systems derive from the antecedent technology area of circuit theory, which is both nonobvious for modern data analysts and assumes balanced conditions and a steady state, even though future power networks will routinely experience transient and steady-state unbalances. Next-generation analytical tools should therefore be fully equipped for dynamically unbalanced systems to approach the physical limits of power networks; data analytics is both well suited and necessary for this endeavor but is nonobvious for power engineers. Hence, to fully exploit their evident and promised advantages, an analysis of the smart grid requires close collaboration and convergence between power engineers and experts in signal processing and machine learning, whereby analytical tools expressed in a common language would be a natural step forward.