Abstract: The present invention relates to a computer-implemented method of providing technical sizing parameters for an energy supply system supplying electrical energy to an installation connected to a public grid subject to potential service interruptions, said computer-implemented method comprising the steps of: ?entering electricity consumption chronology (S1) of said installation; ?entering photovoltaic production capacity limits and energy storage unit capacity limits (S9); ?estimating a ratio (S11) of self-sufficiency or of self-consumption, or of internal rate of return; ?displaying (S13) a plurality of energy supply system configurations on user interface means; wherein each configuration is associated to a sensitivity parameter, said sensitivity parameter enabling to determine the optimized technical sizing parameters of the energy supply system regarding the reliability of the public grid.

Abstract: 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.

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: 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: 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: Methods of recycling silicon swarf into electronic grade polysilicon or metallurgical-grade silicon are described herein are described. In an example, a method includes cutting a silicon ingot and recovering silicon swarf having a first purity from the cutting process. The recovered silicon is purified in an upgraded metallurgical silicon process to produce electronic grade polysilicon particles having a second purity higher than the first purity. The upgraded metallurgical silicon process can include dissolving the recovered silicon particles in a molten aluminum metal smelt.

Abstract: 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.

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 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 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.

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 flexible laminate of photovoltaic cells is provided, including a layer of photovoltaic cells connected to one another; a frontal layer and a rear layer encapsulating the layer of photovoltaic cells, the frontal layer and the rear layer sandwiching the layer of photovoltaic cells; and at least one transparent layer of polymer-based varnish deposited on one of the frontal layer and/or the rear layer, the at least one transparent layer being disposed on an outside of the flexible laminate and being configured to ensure a protection of the flexible laminate. A method for manufacturing a flexible laminate of photovoltaic cells is also provided.

Abstract: 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.

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 is provided for recycling sub-micron Si-particles from a Si wafer production process resulting from a diamond fixed abrasive process including slicing and cutting, the method including the steps of: providing a paste of sub-micron Si-particles resulting from the diamond fixed abrasive process; drying and shaping the paste of sub-micron Si-particles into a layer; and applying a zone melting step to the dried and shaped layer of Si-particles on a substrate.

Abstract: A photovoltaic panel is provided, including a plastic support sheet having a cellular core; a laminate of photovoltaic cells fixed to the support sheet; and a plastic and/or composite frame including longitudinal profile sections for laterally protecting the laminate of photovoltaic cells and the support sheet, and corner-shaped portions connecting the longitudinal profile sections together in order therewith to form a closed frame.

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.