Abstract: The present disclosure is directed to systems and methods for enhancing control of a system using a graph system. A graph system is constructed comprising one or more vertices, one or more edges, and one or more graph layers. Each vertex represents an entity in the system that includes one or more attributes. Each edge represents a flow of an attribute with respect to at least one vertex (entity in the system). Each graph layer comprising one or more vertices and one or more intra-layer edges. An optimization model is constructed from the graph system. The optimization model can be optimized utilizing an optimization algorithm to identify the set of control values that optimize the optimization model. A dispatch set of control values for a set of controllable output attributes of the system is provided to the system to control operation of the system.

Abstract: The present disclosure is directed to systems, apparatuses, and methods for controlling an electrical system using setpoints. Some embodiments include systems that receive a meter read schedule comprising anticipated meter read occurrences. The systems may set a demand setpoint representing a desired upper limit of demand of the electrical power system and adjust the demand setpoint during a billing period. The system may also reset the demand setpoint multiple times at different reset points around each of the anticipated meter read occurrences.

Abstract: The present disclosure is directed to systems, apparatuses, and methods for controlling an electrical system using setpoints. Some embodiments include systems that receive a meter read schedule comprising anticipated meter read occurrences. The systems may set a demand setpoint representing a desired upper limit of demand of the electrical power system and adjust the demand setpoint during a billing period. The system may also reset the demand setpoint multiple times at different reset points around each of the anticipated meter read occurrences.

Abstract: The present disclosure is directed to systems, apparatuses, and methods for controlling an electrical system using setpoints. Some embodiments include systems that receive a meter read schedule comprising anticipated meter read occurrences. The systems may set a demand setpoint representing a desired upper limit of demand of the electrical power system and adjust the demand setpoint during a billing period. The system may also reset the demand setpoint multiple times at different reset points around each of the anticipated meter read occurrences.

Abstract: Electrical system controllers, computer-readable storage media, and related methods for generating random variables for stochastic control of electrical systems. An electrical power system controller includes a processor. The processor is configured to generate an uncertainty metric based on observed input data, the uncertainty metric configured to indicate an uncertainty of an input variable. The processor is configured to generate a random variable based on the uncertainty metric to forecast the input data during a future period of time. The processor is also configured to generate a cost function corresponding to a cost of operating the electrical power system during the future period of time. The cost function is a function of the one or more random variables. The processor is further configured to control operation of the electrical power system during the future period of time based on an optimization of the cost function.

Abstract: Electrical system controllers, computer-readable storage media, and related methods for stochastic control of electrical systems. An electrical system controller includes one or more data storage devices and one or more processors. The one or more data storage devices are configured to store data corresponding to one or more random variables associated with operation of an electrical system. The one or more processors are configured to determine a set of control values for a set of control variables to effectuate a change to the electrical system toward meeting a controller objective for economical optimization of the electrical system. The set of control values are determined by the one or more processors utilizing an optimization algorithm to identify the set of control values as a function of the one or more random variables. The one or more processors are also configured to control the electrical system based on the control values.