At the 2024 Gurobi Summit EMEAI in Amsterdam, researchers Christian Alvarez Pelaez and Dr. Sara Neira Castro took the stage to showcase Reganosa’s innovative approach to energy optimization.
They explored how Reganosa blends the power of machine learning with Gurobi’s robust optimization techniques, to unlock significant cost savings in energy portfolio management. Their case study highlighted challenges, solutions, and the remarkable results that can be achieved through cutting-edge decision intelligence.
The Challenge: Complex Data and the Need for Precision
Managing energy contracts isn’t as simple as matching supply and demand. Reganosa faced two critical hurdles: First, the available data on energy consumption and pricing was inconsistent and incomplete. This made it difficult to build accurate forecasts or establish reliable baselines.
Second, energy markets impose hefty penalties for overuse or underutilization of contracted power, requiring precision in managing power agreements. These challenges demanded more than conventional methods—they required advanced optimization strategies and sophisticated modeling.
The Solution: Smarter Energy Decisions with Optimization
To tackle these issues, the team harnessed the synergy of machine learning and stochastic optimization. They built dynamic models that simulate various energy consumption scenarios, factoring in real-world complexities like penalties and price volatility. Using techniques such as Conditional Value-at-Risk (CVaR), their models made conservative yet cost-effective decisions.
For instance, their system can recommend whether it’s cheaper to contract power or pay penalties based on demand forecasts. By introducing scalable models tailored for both medium and large consumers, they addressed unique consumption patterns with precision.
Real-World Impact: Big Savings
The results speak for themselves. In one case, Reganosa reduced energy costs from €2,000 to €1,700, saving €350 for a single period. Over time, these savings could add up to 30%-50% reductions in energy expenses. The models not only optimized costs but also ensured compliance with constraints, avoiding penalties while delivering reliable results.
With a user-friendly interface, these complex models are distilled into actionable insights, allowing users to easily understand and implement recommendations. This balance of sophistication and simplicity makes the solution a game-changer for energy management.
Key Takeaways
Reganosa’s presentation drove home some powerful lessons:
- Optimization and AI are a winning duo. Combining these technologies allows for smarter decisions, even in complex markets.
- Tailored solutions matter. Reganosa’s models addressed the distinct needs of medium and large consumers, proving there’s no one-size-fits-all approach.
- Data preprocessing is key. Even incomplete datasets can yield meaningful insights with the right techniques.
Unlocking Energy Efficiency with Optimization and AI
Reganosa’s work with Gurobi shows what’s possible when decision intelligence meets energy optimization. Despite challenges, their innovative solutions delivered impressive savings and better energy management for customers. As energy markets grow more complex, solutions like these will be pivotal in creating sustainable, cost-efficient systems.
Curious about how optimization can transform your business? Reach out to the Gurobi team to learn more about leveraging decision intelligence for your toughest challenges!
