In VPP, the resource “demand forecast” and “control schedule” affect the aggregator’s payoff, so it is necessary to improve the accuracy. We are developing these two functions to automatically perform predictions based on time series using machine learning algorithms and deep learning.
For example, our AI-based “demand forecast engine” makes demand forecasts through resource performance data and external weather information APIs. In addition, the “optimization engine” creates a supply and demand schedule so that the payoff is optimized based on the linked demand forecast and price information from the supply and demand adjustment market.
We present a use case of our microgrid solution
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