We Optimize Profits for Grid-connected Batteries
Our algorithms analyze 5 markets to find best bids, maximizing revenue & reducing risk.
Our Offer
Storage assets are essentials to integrate renewables and lower the carbon footprint of electricity. StackEase empowers companies to maximize profits from large battery energy storage systems by unlocking the full potential of grid integration. Our innovative algorithms analyze and optimize bids across five distinct energy markets, considering factors like price, volatility, transfer fees and battery degradation cost. This holistic approach transcends the limitations of single-market dependence, ensuring a robust and profitable business model for your batteries.
We use an innovative approach based on advanced mathematical and machine learning techniques to provide secure revenues for battery owners. By increasing the feasibility of storage projects, StackEase paves the way for a better integration of low carbon electricity sources.
Our method goes beyond revenue diversification and profit maximization; it prioritizes ensuring the highest Return on Investment throughout the battery’s lifespan.
Analysis
Gain insights into revenue streams, their impacts on battery lifespan, and determine optimal battery sizes for current and future market conditions.
API
Integrate our software to gain full control over your battery assets, empowering you to optimize trading strategies and maximize revenue potential with ease.
Optimizer
StackEase handles trading, market access, battery control, and asset certification for you. Focus on your core tasks while we ensure the success of your investments.
Our Technology
StackEase’s core strength lies in its expertise in electricity markets, advanced mathematical optimization and machine learning techniques. Our decision-making tool uses deep reinforcement learning and optimization strategies to adapt to its market environment and take the most optimal decision across the different revenue streams from a techno-economical perspective.
Our Team
Business developper with experience in developing startup in the web industry. Former general manager of an automotive company.
Machine Learning scientist with experience in control system algorithms development. Former manager of a software developers team.
Ex quant analyst at Orsted, Gauthier optimized battery operation in the UK. He is a Polytechnique Paris alumni.