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Finalist • IQM-Quantum Hackathon

Finalist in IQM-Quantum Hackathon

Our team Paseo was selected as a finalist for building a strong solution to a real-world energy-optimization challenge. We modeled a 24-hour wind farm + battery portfolio with uncertain wind output (multiple scenarios) and known hourly market prices. The work focused on turning operational constraints into a clean optimization formulation that can be explored with both classical and quantum approaches. The result highlights practical decision-making: when to charge, when to discharge, and how to maximize expected revenue responsibly.

View Team & Problem
What this means
Result note

Being a finalist reflects both the quality of the model and the clarity of the approach. It also recognizes innovation in bridging energy-system constraints with optimization methods suitable for emerging quantum tooling.

Team & Problem

Team: Paseo
Problem: Wind + Battery Revenue Maximization (24h)

Goal

Choose an hour-by-hour battery operation plan (charge / discharge / idle) to maximize expected revenue from wind generation sales and battery arbitrage, under uncertain wind production scenarios and fixed hourly prices.

Key constraints
  • Energy capacity and max charge/discharge power
  • Charge/discharge efficiency and state-of-charge tracking
  • Charge OR discharge OR idle each hour (no simultaneous actions)
  • Daily cycling / throughput limit, with zero end-of-day SOC target
Repository
GitHub

Full details, notebooks, and formulations are available in the PASEO repository.

Open PASEO on GitHub