Smart Grid Simulations and Their Supporting Implementation Methods

In this tutorial we present the state-of-the-art as well as new methods for simulating various planning, operation, stability, reliability, and economic models of electric power systems. The discussion is driven by both first-principle models and empirical models. First-principle models result from the fundamental physics and engineering principles that govern the behavior of various components of a grid. Empirical models, on the other hand, are models that result from statistics and data analysis. We overview a wide spectrum of applications starting from planning models with a time-scale of simulation in years to real-time models where the time-scale can be in the order of milliseconds. We present a list of simulation software popularly used by the power engineering research community across the world. The increasingly important roles of power electronics, communication and computing, model aggregation, hybrid simulation, faster-than-real-time simulation, and co-simulation in emulating the daily operation of a grid are enumerated. The importance of research testbeds for testing, verification and validation of complex grid models at various temporal and spatial scales is also highlighted. The overall goal is to provide a vision on how simulations and their supporting implementation methods can help us in understanding the evolving behavior of tomorrow's power networks as a truly intelligent cyber-physical system.