Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

Abstract: Apparatuses, systems, and methods of apportioning an aggregate maneuver is disclosed. An aggregation engine receives aggregation opportunity information requesting an aggregate change in power of one or more sites. The aggregation engine transmits participation opportunity information to a plurality of site controllers. The participation opportunity information indicates a site benefit for providing a site change in power. The aggregation engine also receives commitment information from the plurality of site controllers, the commitment information indicating levels of commitment of the plurality of site controllers to contribute site change in power to a target change in power of the aggregation opportunity.

Abstract: Apparatuses, systems, and methods of apportioning an aggregate maneuver are disclosed. An aggregation engine receives aggregation opportunity information requesting an aggregate change in power of one or more sites. The aggregation engine transmits participation opportunity information to a plurality of site controllers. The participation opportunity information indicates a site benefit for providing a site change in power. The aggregation engine receives commitment information from the plurality of site controllers, the commitment information indicating levels of commitment of the plurality of site controllers to contribute site change in power to a target change in power of the aggregation opportunity. The aggregation engine further transmits updated participation opportunity information including an adjusted proposed site benefit or adjusted proposed site change in power until an aggregate change in power of the one or more sites is within a threshold level of the target change in power.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments include an input device to receive input from a user. The site information may include an indication from the user of a site participation preference for a response event for an aggregation opportunity.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments include an input device to receive input from a user. The site information may include an indication from the user of a site participation preference for a response event for an aggregation opportunity.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. A two-stage controller includes an optimizer and a high speed controller to effectuate a change to one or more components of the electrical system. The high speed controller receives a set of control parameters for an upcoming extended time period. The control parameters include a plurality of bounds for an adjusted net power of the electrical system. The high speed controller sets an energy storage system command control variable (ESS command) based on a state of adjusted net power of the electrical system and the set of control parameters.

Abstract: The present disclosure is directed to systems and methods for controlling an electrical system using setpoints. Some embodiments include control methods that monitor an adjusted net power associated with the electrical system and adjust the setpoint based on a comparison of the adjusted demand to the setpoint. If the adjusted demand has not exceeded the demand setpoint, the setpoint is reduced. If the adjusted demand has exceeded the demand setpoint, the setpoint is increased.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments include an input device to receive input from a user. The site information may include an indication from the user of a site participation preference for a response event for an aggregation opportunity.

Abstract: The present disclosure is directed to machine learning of electrical power system behavior, and related systems, apparatuses, and methods. A controller of an electrical power system includes a data storage device configured to store model data indicating a model load power consumed by loads of the electrical power system. The controller also includes a processor configured to determine current data including current load power consumed by the loads, modify the model data by aggregating the model data with the current data, and determine a set of control values for a set of control variables to effectuate a change to operation of the electrical power system based, at least in part, on the model data.

Abstract: The present disclosure is directed to machine learning of electrical power system behavior, and related systems, apparatuses, and methods. A controller of an electrical power system includes a data storage device configured to store model data indicating a model load power consumed by loads of the electrical power system. The controller also includes a processor configured to determine current data including current load power consumed by the loads, modify the model data by aggregating the model data with the current data, and determine a set of control values for a set of control variables to effectuate a change to operation of the electrical power system based, at least in part, on the model data.

Abstract: The present disclosure is directed to systems and methods for controlling an electrical system using setpoints. Some embodiments include control methods that monitor an adjusted net power associated with the electrical system and adjust the setpoint based on a comparison of the adjusted demand to the setpoint. If the adjusted demand has not exceeded the demand setpoint, the setpoint is reduced. If the adjusted demand has exceeded the demand setpoint, the setpoint is increased.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. A two-stage controller includes an optimizer and a high speed controller to effectuate a change to one or more components of the electrical system. The high speed controller receives a set of control parameters for an upcoming extended time period. The control parameters include a plurality of bounds for an adjusted net power of the electrical system. The high speed controller sets an energy storage system command control variable (ESS command) based on a state of adjusted net power of the electrical system and the set of control parameters.

Abstract: Apparatuses, systems, and methods of apportioning an aggregate maneuver is disclosed. An aggregation engine receives aggregation opportunity information requesting an aggregate change in power of one or more sites. The aggregation engine transmits participation opportunity information to a plurality of site controllers. The participation opportunity information indicate a site benefit for providing a site change in power. The aggregation engine also receives commitment information from the plurality of site controllers, the commitment information indicating levels of commitment of the plurality of site controllers to contribute site change in power to a target change in power of the aggregation opportunity.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. A two-stage controller includes an optimizer and a high speed controller to effectuate a change to one or more components of the electrical system. The high speed controller receives a set of control parameters for an upcoming extended time period. The control parameters include a plurality of bounds for an adjusted net power of the electrical system. The high speed controller sets an energy storage system command control variable (ESS command) based on a state of adjusted net power of the electrical system and the set of control parameters.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. A two-stage controller includes an optimizer and a high speed controller to effectuate a change to one or more components of the electrical system. The high speed controller receives a set of control parameters for an upcoming extended time period. The control parameters include a plurality of bounds for an adjusted net power of the electrical system. The high speed controller sets an energy storage system command control variable (ESS command) based on a state of adjusted net power of the electrical system and the set of control parameters.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.