HydroBoost: Realistic Revenue Optimization for Hydropower and Battery Storage

The Challenge

Hydropower operators and battery storage managers face increasing pressure to maximize revenue while navigating unpredictable energy markets. Existing optimization tools assume perfect foresight, failing to account for market price uncertainty, leading to unrealistic revenue projections. Without a model that reflects real-world scheduling practices, operators struggle to make informed decisions about dispatch strategies, missing out on potential earnings.

How It Works

HydroBoost is an advanced optimization solver designed to maximize revenue for hybrid hydropower and battery storage systems by factoring in energy market price uncertainty. Unlike conventional models, HydroBoost generates a range of potential revenues, providing more realistic insights into system performance.

• Forecast-Driven Optimization: Uses multiple forecasting techniques—including additive models, random forests, and neural networks—to model future energy market prices with uncertainty.

• Flexible Market Participation: Primarily designed for the day-ahead market but also considers ancillary services.

• Realistic Hydropower Scheduling: Reflects how operators actually manage hydropower assets, ensuring practical and accurate predictions.

• User-Friendly Workflow:

    1. Forecast Generation: Python script generates price forecasts.

    2. Optimization Execution: Model runs in Julia to determine optimal dispatch.

    3. Results Analysis: Outputs revenue projections and operational insights in CSV and graphical formats.

• Broad Compatibility: Works for both run-of-river and reservoir storage sites, requiring year-long hourly data.

Key Advantages

• Realistic Revenue Projections: Unlike other solvers, HydroBoost models price uncertainty rather than assuming perfect foresight.

• Data-Driven Decision-Making: Provides both upper and lower revenue bounds to support risk-aware financial planning.

• Comprehensive Market Participation: Optimizes for both energy markets and ancillary services.

• Seamless Integration: Uses Excel for easy data input and Python/Julia for streamlined execution.

• Customizable Forecasting Models: Allows additional forecast techniques for deeper market insight.

Market Applications

• Hydropower Owners & Operators – Maximize profitability by optimizing hydro-battery dispatch strategies.

• Utility Companies – Improve grid reliability and integrate renewable storage efficiently.

• Renewable Energy Developers – Assess the economic viability of hybrid hydropower-battery projects.

• Energy Consultants – Conduct detailed techno-economic analyses for clients.

This software is open source and available at no cost. Download now by visiting the product's GitHub page.