How optimization helps energy leaders make confident decisions when supply, demand, and prices are all moving at once.
Picture a trading desk at 8 a.m. New weather forecasts, updated price curves, asset availability, battery charge levels, and long term commitments all arrive at once, and every bid has to be submitted before the market closes, often within the hour. In this episode, Álvaro García Sánchez and Guillermo González Santander, Partners at Baobab, join host David O'Keefe to explain why these decisions still rely heavily on spreadsheets and individual experience, and how optimization gives teams a clear, auditable way to compare alternatives before they commit.
The conversation spans every timescale. Batteries and renewables now link each hour to the next, and longer horizons bring even greater uncertainty. García argues that uncertainty is a reason to use models, not avoid them: a model turns assumptions into something a team can discuss, test, and explain to a regulator years later. González covers the impact of data quality in wind and hydro assets and introduces DecisionOps, the practice of managing a model's life cycle as markets and regulation evolve. They close with lessons from Spain and why, for US leaders, the challenge of a high renewables grid will appear as a market and coordination problem before it becomes a physical one.
What you'll take away:
How to prove that value comes from the model and not from market conditions, using a baseline set in advance, backtesting, shadow mode, and A/B comparisons
How to choose a first use case: frequent, high impact decisions with many constraints, a single owner, and measurable results
What it takes to move from pilot to production, including engaged users, executive sponsorship, the right scope, and ongoing model monitoring
Why batteries and flexibility are the next battleground, and what markets running above 50% renewables are learning first
