PowerSimulations.jl -- A Power Systems operations simulation Library

TL;DR

PowerSimulations.jl addresses the need for transparent, reproducible, long-horizon power-system operation simulations by providing a modular, open-source framework written in Julia. It formalizes an operations simulation as sequential solutions of multiple optimization problems that mimic operator procedures across time horizons, with explicit decision and emulation problem definitions and feedforward links. The software emphasizes in-memory model construction, flexible component templates, and an efficient simulation sequence with persistent storage via HDF5 to support large-scale experiments. Validation against classical operations simulations and public datasets demonstrates the framework's ability to reproduce established results while enabling flexible experimentation beyond proprietary tools.

Abstract

PowerSimulations.jl is a Julia-based BSD-licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion. This paper discusses the software implementation of PowerSimulations.jl as a template for the development and implementation of operation simulators, providing solutions to commonly encountered issues like time series read/write and results sharing between models. The paper includes a publicly-available validation of classical operations simulations as well as examples of the advanced features of the software.

Figures (7)

• Figure 1: Sequential properties of a decision model. Each calculation step is taken at a particular interval and employs information about the state of the system and a forecast to estimate future estates.
• Figure 2: Sequential properties of an emulation model. At each calculation step, the model uses the incoming decisions and the realization of the uncertain quantities such that the state values at a time $t$ are independent of future system states.
• Figure 3: operations simulation chronological sequence of calculations.
• Figure 4: Model relationship graph of a generic operations simulation.
• Figure 5: Modular Optimization Build Flow Chart.