North Carolina State University

Total Solar International

Battelle Memorial Institute

Roche Molecular Systems, Inc.

Quest Diagnostics Investments, Inc.

Total Sa

Totalenergies Onetech

Ning Lu

Wente Zeng

Yuri Makarov

Michelle M Tabb

Lilly I Kong

Jules Chen

Dirk Zimmermann

Michael Aye

Karen K Young

Hermann Leying

Fan Chen

Ming-Chou Lee

Nick Newton

Gonzague Henri

Xiangqi Zhu

Andreas Wolfelschneider

Jiahong Yan

Pengwei Du

Donald J Hammerstrom

Robert G Pratt

Jesse T Holzer

Bharat Vyakaranam

Nader A Samaan

Carlos Carrejo

Mallikarjuna Vallem

Renke Huang

Marcelo A Elizondo

Jian Lu

Jiyu Wang

Fuhong Xie

David Mulcahy

Catherine McEntee

Maziar Vanouni

Yu Zhang

Xinxin Guo

Xinda Ke

Chunlian Jin

Shuai Lu

Catherine Mcentee

Gonzaque Henri

A method, system, and device for controlling an energy storage device are provided. The method includes determining an operating schedule for the energy storage device based on at least an initial cost. The initial cost is a function of at least a load profile and a power production profile of at least one renewable energy source associated with the energy storage device. The operating schedule is for a predetermined period. The method further includes determining an updated cost based on at least the operating schedule, identifying an operating mode from a plurality of operating modes for a predetermined operating period based on the updated cost and the operating schedule; and operating using the operating mode for the predetermined operating period.

System, device, and method for mode-based energy storage management

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.

System, device, and method for off-grid microgrids management

A method, system, and device for controlling energy storage devices are provided, the method including receiving a trained machine learning model from a centralized machine learning system, recording temporal data for a respective energy storage device, periodically transmitting the temporal data to the machine learning system, performing a mode prediction for controlling the energy storage device using the trained machine learning model and the temporal data, and sending a control signal to the energy storage device to operate in the predicted mode. The machine learning system aggregates the temporal data transmitted by each agent and uses the aggregated temporal data to update the machine learning model. By using aggregated temporal data, less data is needed from an individual energy storage device so that when a new energy storage device joins the machine learning system, the new energy storage device can benefit from increased performance with less computation.

Multi-agent shared machine learning approach for real-time battery operation mode prediction and control

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

Disclosed herein are methods and compositions for detectingandby detecting the presence of the IS481 and IS1001 genomic insertion sequences, respectively.

Bordetella detection assay

Systems and methods are described for coordinating volt-var control between sub-transmission and distribution systems. Distributed energy resources of a distribution system are aggregated into virtual power plants from which reactive power can optimally be dispatched to the sub-transmission system. A sub-transmission controller executes a volt-var AC optimal power flow optimisation function to minimize voltage fluctuations that might otherwise occur when coordinating with a distribution system having distributed energy resources. The distribution system can use a sensitivity matrix for regulating voltage at distribution feeders while fulfilling a transmission or sub-transmission system's demand requests.

Coordinated voltage control and reactive power regulation between transmission and distribution systems

Methods for detecting HAV in a biological sample are provided, comprising amplifying a target nucleic acid comprising the sequence of HAV in a reaction mixture. The reaction mixture comprises a biological sample which may contain the target nucleic acid and set of oligonucleotides. The invention also provides kits for the detection of HAV.

HAV detection

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

detection assay

A system and method of controlling aggregated thermostatically controlled appliances (TCAs) for demand response is disclosed. A targeted load profile is formulated and a forecasted load profile is generated. The TCAs within an 'on' or 'off' control group are prioritized based on their operating temperatures. The &#x201c;on&#x201d; or &#x201c;off&#x201d; status of the TCAs is determined. Command signals are sent to turn on or turn off the TCAs.

Controller for thermostatically controlled loads

Disclosed herein are representative embodiments of methods, apparatus, and systems for controlling and scheduling power distribution in a power network, such as household power network. One disclosed embodiment is a system comprising a central controller and a control device coupled to a household appliance. The central controller can comprise computing hardware coupled to a wireless transceiver. The central controller can be configured to generate and transmit control signals for controlling the operational state of the household appliance according to the schedule. Furthermore, the control device can be configured to receive the transmitted control signals from the central controller and to control the operational state of the household appliance in response to the control signals.

Scheduling and modeling the operation of controllable and non-controllable electronic devices

A controller is disclosed for hybrid systems providing power to an electrical power grid. The controller reduces wear on hybrid systems by having only a fast unit tuned to track fluctuations of a regulation signal in a normal mode of operation. By contrast, the slow unit does not track fluctuations in the regulation signal in the normal mode of operation, which reduces wear on the slow unit. The normal mode of operation is defined by an energy range of the fast unit. Energy band parameters associated with the energy range can be dynamically modified in order to optimize the efficiency of the hybrid system.

Controller for hybrid energy storage

Growing community of inventors

Cary, NC, United States of America

Ning Lu