Veritone Alpha, Inc.

David Kettler

Wolf Kohn

Michael Luis Sandoval

Jonathan Cross

Vishnu Vettrivel

Brandon Weiss

Pengbo Zhang

Brian Schaper

Neel Master

Techniques are described for implementing automated control systems to control operations of specified physical target systems, such as with one or more batteries used to store and provide electrical power. Characteristics of each battery's state may be used to perform automated control of DC power from the battery, such as in a real-time manner and to optimize long-term operation of the battery. In some situations, multiple batteries are controlled by using multiple control systems each associated with one of the batteries, and with overall control being coordinated in a distributed manner using interactions between the multiple control systems. A system that includes one or more batteries to be controlled may further include additional components in some situations, such as one or more electrical sources and/or one or more electrical loads, with one non-exclusive example of a type of such system being one or more home electrical power systems.

Using battery DC characteristics to control power output

Techniques are described for implementing automated control systems to control operations of specified physical target systems. In some situations, the described techniques include forecasting future values of parameters that affect operation of a target system, and using the forecasted future values as part of determining current automated control actions to take for the target system&#x2014;in this manner, the current automated control actions may be improved relative to other possible actions that do not reflect such forecasted future values. Various automated operations may also be performed to improve the forecasting in at least some situations, such as by combining the use of multiple different types of forecasting models and multiple different groups of past data to use for training the models, and/or by improving the estimated internal non-observable state information reflected in at least some of the models.

Using forecasting to control target systems

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Seattle, WA, United States of America

David Kettler