North Carolina State University

Total Solar International

University of California

Total Sa

UniversitÉ Libre De Bruxelles

Total Se

Wente Zeng

Ning Lu

Mo-Yuen Chow

Scott Moura

Sebastien Benjamin

Xiangqi Zhu

Jiahong Yan

Sangjae Bae

Preet Gill

Teng Zeng

Maziar Vanouni

Bharat Balagopal

Carl Lenox

Jian Lu

Luis Couto

Jiyu Wang

Dong Zhang

Alberto Castelo Becerra

Bertrand Travacca

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.

Methods and systems for optimal pricing and charging control of a plug-in electric vehicle charging station

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.

Aggregated distribution for energy demand response

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.

Decoupled modeling methods and systems

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.

Interval estimation for state-of-charge and temperature in battery packs with heterogeneous cells

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.

System and method for sizing a capacity of an energy storage device

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.

Systems and methods for controlling and managing thermostatically controlled loads

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.

Method and apparatus for identifying a battery model

Large-scale, time-sensitive secure distributed control systems and methods are disclosed. According to an aspect, a method includes detecting an anomaly at a module among a plurality of modules in a network. The method also includes adjusting a reputation level of the module associated with the detected anomaly. Further, the method includes controlling interaction of the module associated with the detected anomaly within the network based on the adjusted reputation level.

Large-scale, time-sensitive secure distributed control systems and methods

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Cary, NC, United States of America

Wente Zeng