The startup develops operation and trading software that utilizes machine learning to optimize energy storage participation in electricity and balancing markets. By employing forecasting and algorithmic trading techniques, it enhances profit stability and reduces risks for energy storage investments.
Funding
$4.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
SCSIFounders
Product
Problem
Energy storage systems face challenges in optimizing their participation in electricity and balancing markets due to the complexity of forecasting and algorithmic trading. This can lead to reduced profit stability and increased risks for energy storage investments.
Solution
Suena provides operation and trading software that leverages machine learning to optimize energy storage participation in electricity and balancing markets. The software employs advanced forecasting, optimization, and algorithmic trading techniques to maximize profits and minimize risks associated with energy storage assets. By automating trading decisions in real-time, the platform enables efficient trading across various markets, including day-ahead, intraday, and ancillary services. This results in higher revenues, extended battery lifetime, and minimized financial project risk through multi-market strategies and customizable compensation models.
Target Audience
The primary target audience includes project developers, power generators, investors, municipal utilities, and energy suppliers involved in battery storage and renewable energy projects.
Features
- AI-powered Energy Trading Autopilot for fully automated trading
- Advanced forecasting algorithms for precise market predictions
- Real-time optimization of trading decisions across electricity and balancing markets
- Support for stand-alone battery storage, co-located battery storage with solar or wind power, and combined portfolios with renewables
- Digital twin technology for optimized cycle management and extended battery lifetime
- Multi-market strategy for risk diversification
- Integration of market forecasts for optimization and actual prices for settlements
- Internal index based on price-volume-percentiles representing the volatility of continuous intraday prices