I’m building a research-grade environment to study cyberattack detection in smart grids and need two tightly linked deliverables: 1) a software-only smart-grid simulator I can run on my workstation, complete with the ability to trigger, observe, and log various attack scenarios (DoS, data manipulation, false-data injection, and others we agree on), and 2) a hardware-in-the-loop replica of the same scenario running on a Raspberry Pi or comparable single-board computer so I can demonstrate real-time behaviour at the edge. Key points you should know: • The simulator must model generation, distribution, and consumption nodes well enough for anomalies to surface in measurable signals. • I’m flexible on language or framework—Python with libraries such as GridLAB-D, OpenDSS, or custom MQTT-based code is welcome, but suggest what you’re fastest with. • Logs, packets, and metrics need to be exportable so I can feed them into my detection algorithms later. • For the hardware stage, lean solutions that compile or run unchanged on a Pi (or that can be containerised) are preferred. Deliverables • Source code for the desktop simulator plus a short README on setup and usage • Attack scripts or modules with clear toggles to enable/disable each tactic • Raspberry Pi image or install script replicating the same topology and attacks • A brief demo video or live session proving the attack reproduces identically in both environments Acceptance criteria • I can run the simulator on a fresh machine in under 30 minutes following your README. • Attacks reliably alter grid metrics in ways we can graph. • Switching to the Pi shows the same alterations within the expected timing tolerance. If this workflow sounds straightforward to you, let’s talk about your proposed stack and timelines.