Abstract: A method, system, and device for managing off-grid power supply are provided. The method includes acquiring data from one or more loads. The one or more loads are connected to the off-grid power supply. The method further includes modeling the one or more loads based on the acquired data, estimating a state of charge of an energy storage device (ESD) associated with the off-grid power supply, and determining an operational status of each of the one or more loads. The operational status is based on at least the state of charge of the ESD and a category of each of the one or more loads. Each load is controlled based on the operational status.

Abstract: A method, system, and device for managing off-grid power supply are provided. The method includes acquiring data from one or more loads. The one or more loads are connected to the off-grid power supply. The method further includes modeling the one or more loads based on the acquired data, estimating a state of charge of an energy storage device (ESD) associated with the off-grid power supply, and determining an operational status of each of the one or more loads. The operational status is based on at least the state of charge of the ESD and a category of each of the one or more loads. Each load is controlled based on the operational status.

Abstract: Systems and methods for including overstay and human behavior in the pricing structure of a plug-in electric vehicle (PEV) charging station, in order to maximize operating revenue, and manage overstay duration. A mathematical framework with discrete choice models (DCM) is incorporated to operate a PEV charging station with an optimal pricing policy and charge control. The framework determines the probability of a PEV driver selecting various charging options, including overstay price. The pricing options are charging-flexibility, which allows a controller to manage charging costs over a parking duration, charging-asap, which charges the electric vehicle immediately and continuously until the vehicle departs, the battery is fully charged, or a desired level of charge has been reached, and leaving, which is an opportunity cost to the charging station.

Abstract: An aggregated distribution system includes an HVAC controller, a battery controller, and an aggregated data management engine. The aggregated data management engine is configured to retrieve an HVAC energy usage profile and retrieve a battery energy usage profile. The aggregated distribution system also includes distribution engine configured to forward a first set of HVAC dual variables and forward a first set of battery dual variables to a first neighboring unit of the aggregated distribution system, receive one or more additional sets of HVAC dual variables and one or more additional sets of battery dual variables from one or more neighboring units of the aggregated distribution system, update the HVAC energy usage profile with the one or more additional sets of HVAC dual vehicles and update the battery energy usage profile with the one or more additional sets of battery dual vehicles.

Abstract: A method for assessing a state of health of a battery having a plurality of heterogeneous cells includes subjecting the cells of the battery to a plurality of diagnostic current pulse cycles; identifying extreme cells based upon the cycles; estimating model parameters of the extreme cells; and estimating upper and lower bounds for the estimated model parameters. Estimating model parameters includes performing a recursive least squares analysis on the extreme cells. Estimating the upper and lower bounds for the estimated model parameters includes performing a sparse Gaussian process regression using the estimated model parameters.

Abstract: A method of predicting state of power (SOP) for a battery includes estimating first state parameter bounds of the battery using an internal observer process; obtaining a current value based upon the first state parameter bounds, system constraint variables, a scaling factor and a reference current using a modified reference governor process; performing adaptive parameter bounding to obtain second state parameter bounds using the current value; determining a constraint variable based upon the second state parameter bounds and whether the constraint variable is within the system constraint variables the using an interval prediction process; and generating a modified scaling factor based upon whether the constraint variable is within the system constraint variables. Using the modified scaling factor, the obtaining, performing, determining and modifying are repeated to generate a final current value. The SOP is estimated based upon the final current value.

Abstract: An aggregated distribution system includes an HVAC controller, a battery controller, and an aggregated data management engine. The aggregated data management engine is configured to retrieve an HVAC energy usage profile and retrieve a battery energy usage profile. The aggregated distribution system also includes distribution engine configured to forward a first set of HVAC dual variables and forward a first set of battery dual variables to a first neighboring unit of the aggregated distribution system, receive one or more additional sets of HVAC dual variables and one or more additional sets of battery dual variables from one or more neighboring units of the aggregated distribution system, update the HVAC energy usage profile with the one or more additional sets of HVAC dual vehicles and update the battery energy usage profile with the one or more additional sets of battery dual vehicles.

Abstract: A decoupled ETP model processor is configured to store power consumption data retrieved from power systems; convert the power consumption data into power activated time cycles and power non-activated time cycles; derive a thermal resistance (R) parameter and a capacitance (C) parameter for a predetermined heat flow (Q) parameter at each of the outdoor temperatures; compare the converted power activated time cycles to the actual power activated time cycles; compare the converted power non-activated time cycles to the actual power non-activated time cycles; calculate a first improved resistance-capacitance-heat flow (RCQ) parameter set and a respective first outdoor temperature for the compared and converted power activated time cycles to the actual power activated time cycles; calculate the Q parameter at each outdoor temperature during the power activated time cycles; and calculate the R parameter and the C parameter at each outdoor temperature during the power non-activated time cycles.

Abstract: A station-level framework to operate one or multiple plug-in electric vehicle (PEV) charging stations with optimal pricing policy and charge scheduling, which incorporates human behavior to capture the driver charging decision process. The user is presented with menu of price-differentiated charging services, which differ in per-unit price and the energy delivery schedule. Involving human in the loop dynamics, the operation model results in the alleviation of the overstay issue may occur when a charging session has completed. A multi-block convex transformation is used to reformulate the resulting non-convex problem via the Fenchel-Young Inequality and a Block Coordinate Descent algorithm is applied to solve the overall problem with an efficiency which enables real-time implementation. The pricing control policy realizes benefits in three aspects: (i) net profits gain, (ii) overstay reduction, and (iii) increased quality-of-service.

Abstract: Systems and methods for including overstay and human behavior in the pricing structure of a plug-in electric vehicle (PEV) charging station, in order to maximize operating revenue, and manage overstay duration. A mathematical framework with discrete choice models (DCM) is incorporated to operate a PEV charging station with an optimal pricing policy and charge control. The framework determines the probability of a PEV driver selecting various charging options, including overstay price. The pricing options are charging-flexibility, which allows a controller to manage charging costs over a parking duration, charging-asap, which charges the electric vehicle immediately and continuously until the vehicle departs, the battery is fully charged, or a desired level of charge has been reached, and leaving, which is an opportunity cost to the charging station.

Abstract: An interval observer based on an equivalent circuit-thermal model for lithium-ion batteries is presented. State of charge-temperature-dependent parameters are considered as unknown but bounded uncertainties in a single cell model. A parallel and a series arrangement of five cells are used for observer design, where cell heterogeneity is accounted for through the uncertainty bounding functions.

Abstract: An interval observer based on an equivalent circuit-thermal model for lithium-ion batteries is presented. State of charge-temperature-dependent parameters are considered as unknown but bounded uncertainties in a single cell model. A parallel and a series arrangement of five cells are used for observer design, where cell heterogeneity is accounted for through the uncertainty bounding functions.

Abstract: A method, system, and device for managing off-grid power supply are provided. The method includes acquiring data from one or more loads. The one or more loads are connected to the off-grid power supply. The method further includes modeling the one or more loads based on the acquired data, estimating a state of charge of an energy storage device (ESD) associated with the off-grid power supply, and determining an operational status of each of the one or more loads. The operational status is based on at least the state of charge of the ESD and a category of each of the one or more loads. Each load is controlled based on the operational status.

Abstract: A decoupled ETP model processor is configured to store power consumption data retrieved from power systems; convert the power consumption data into power activated time cycles and power non-activated time cycles; derive a thermal resistance (R) parameter and a capacitance (C) parameter for a predetermined heat flow (Q) parameter at each of the outdoor temperatures; compare the converted power activated time cycles to the actual power activated time cycles; compare the converted power non-activated time cycles to the actual power non-activated time cycles; calculate a first improved resistance-capacitance-heat flow (RCQ) parameter set and a respective first outdoor temperature for the compared and converted power activated time cycles to the actual power activated time cycles; calculate the Q parameter at each outdoor temperature during the power activated time cycles; and calculate the R parameter and the C parameter at each outdoor temperature during the power non-activated time cycles.

Abstract: An aggregated distribution system includes an HVAC controller, a battery controller, and an aggregated data management engine. The aggregated data management engine is configured to retrieve an HVAC energy usage profile and retrieve a battery energy usage profile. The aggregated distribution system also includes distribution engine configured to forward a first set of HVAC dual variables and forward a first set of battery dual variables to a first neighboring unit of the aggregated distribution system, receive one or more additional sets of HVAC dual variables and one or more additional sets of battery dual variables from one or more neighboring units of the aggregated distribution system, update the HVAC energy usage profile with the one or more additional sets of HVAC dual variables, and update the battery energy usage profile with the one or more additional sets of battery dual variables.

Abstract: A method and system for sizing energy storage device capacity. The method includes generating a load profile of at least an entity based on at least information acquired by a user interface, generating an ensemble of net load profiles based on at least the load profile and based on at least one energy source profile, determining values of cumulative distribution functions associated with a plurality of energy storage device capacities as a function of at least the ensemble of net load profiles, generating a graphical representation of a combination of the composite cumulative distribution functions and a cluster of equal probability line, rendering the graphical representation, and sizing a capacity of the energy storage device based on the rendered graphical representation.

Abstract: A method, a system, and computer readable medium for managing thermostatically controlled loads (TLCs). The method includes acquiring data from a plurality of TCLs including at least thermal parameters associated with each TCL of the plurality of TCLs and a regulation signal data and prioritizing the plurality of TCLs. The prioritization is based on a contribution of each TCL to an overall service. The method further includes generating an optimization curve based on the prioritization, determining an optimization attribute associated with each TCL of the plurality of TCLs, and outputting the optimization attribute associated with each TCL for a regulation period to each TCL. The optimization curve has at least reward criteria as an optimization parameter.

Abstract: A method, an apparatus, and a system for determining a state of a battery are provided. The method includes acquiring battery information from a sensor associated with the battery. The battery information includes at least terminal voltage and a terminal current. The method further includes estimating degradation information based on a first principle degradation model and the battery information. The first principle degradation model is a three dimensional model that includes a plurality of layers having one or more attributes representative of physical parameters of the battery. The method further includes identifying a circuit model based on the degradation information and the battery information, determining the state of the battery using the identified circuit model, and implementing a control action or a notification based on the determined state of the battery.

Abstract: A method, a system, and computer readable medium for managing thermostatically controlled loads (TLCs). The method includes acquiring data from a plurality of TCLs including at least thermal parameters associated with each TCL of the plurality of TCLs and a regulation signal data and prioritizing the plurality of TCLs. The prioritization is based on a contribution of each TCL to an overall service. The method further includes generating an optimization curve based on the prioritization, determining an optimization attribute associated with each TCL of the plurality of TCLs, and outputting the optimization attribute associated with each TCL for a regulation period to each TCL. The optimization curve has at least reward criteria as an optimization parameter.

Abstract: A method, an apparatus, and a system for determining a state of a battery are provided. The method includes acquiring battery information from a sensor associated with the battery. The battery information includes at least terminal voltage and a terminal current. The method further includes estimating degradation information based on a first principle degradation model and the battery information. The first principle degradation model is a three dimensional model that includes a plurality of layers having one or more attributes representative of physical parameters of the battery. The method further includes identifying a circuit model based on the degradation information and the battery information, determining the state of the battery using the identified circuit model, and implementing a control action or a notification based on the determined state of the battery.