Accurate price forecasts for every service and node
Contact us to evaluate performance for your project.
Legible optimal bid/offer and dispatch decisions
Detailed breakdown of expected and perfect P&L
Visualize and reports on performance
Learn how Tyba's latest updates will boost your revenue capture and streamline your development and financing processes.
We are excited to announce the latest updates to Tyba’s Virtual Bidder module, a significant improvement to our short-term price forecasting capabilities, and continued usability improvements in our web-app and API.
These updates are designed to help you capture higher revenues, improve your decision-making, and help streamline your efforts. At Tyba, we are committed to continuous improvement. We appreciate your feedback and encourage you to let us know about any areas where we can improve. Without further ado, let’s dive in!
The revamped Virtual Bidder module now shadows daily forecasting and dispatch optimization for strategies that co-optimize energy arbitrage and ancillary service applications. As discussed in our previous blog, the rapid growth of energy storage in California and Texas is requiring operators to look beyond ancillary service revenues to capture maximum merchant storage revenue.
Our customers use this module to understand how to implement Tyba's models to capture higher revenues and apply these strategies in the field. Companies often begin using this module during the development and financing stage to understand revenue potential and dispatch assumptions, and then apply these approaches in the field once the project is operational.
The components of this module are:
Accurate price forecasts for every service and node
Contact us to evaluate performance for your project.
Legible optimal bid/offer and dispatch decisions
Detailed breakdown of expected and perfect P&L
Visualize and reports on performance
We've upgraded our price forecasting model to predict not only prices but also the distribution of prices. This allows us to model the uncertainty of any given price forecast and incorporate that uncertainty into our dispatch and bidding strategy. As a result, you'll achieve better revenue outcomes, as revenue opportunities are often driven by large price spikes (positive or negative).
Impact on optimization:
If the distribution forecast suggests a higher probability of a spike, the dispatch algorithm will adjust to discharge/charge in that hour, even if it wasn't the highest/lowest mean price forecast.
Note: in this example including the distribution allowed for the optimizer to find cheaper hours to charge. The discharge hours were correctly predicted in both cases.