Abstract: A method for performing validation, estimation, and editing (VEE), including: employing HVAC subsystems to adjust comfort in a building; performing VEE on energy consumption streams; executing VEE rules on each of the streams to generate and store a corresponding post VEE readings, the post VEE readings comprising tagged energy consumption data sets each associated with a corresponding one of the streams, each of the data sets comprising first groups of contiguous interval values tagged as having been validated and second groups of contiguous interval values tagged as having been edited, the first groups of contiguous interval values corresponding to correct data; for the each of the data sets, creating anomalies having different durations using only the first groups of contiguous interval values; generating estimates for the anomalies by employing estimation techniques; for each of the durations, selecting one of the estimation techniques for subsequent employment when performing VEE of subsequent energy con

Abstract: A remote visual indicator of a state of charging of an electric and/or plug-in hybrid electric vehicle (EV and PHEV). In one or more embodiments, the aforesaid visual indicator incorporates a multi-color light source, such as a multi-color LED and uses the color of the emitted light to indicate the state of the EV/PHEV charging. In one or more embodiment, the aforesaid visual indicator incorporates one or more buttons or other user-activated controls configured to alter the charging of the EV/PHEV by the charging stations. In one or more embodiments, a sound generation element may be additionally provided for creating audible indicators of charging state.

Abstract: A control system that performs VEE on consumption streams, including: data stores that provides data sets, each of the data sets comprising groups of contiguous values that correspond to correct data; a rules processor that reads the data stores and, for the each of the data sets, that creates anomalies having different durations using only the groups of contiguous values, that generates estimates for the anomalies by employing estimation techniques for each of the different durations and, for the each of the different durations, that selects a corresponding one of the estimation techniques for subsequent employment when performing VEE of subsequent energy consumption data associated with the each of the different durations for the corresponding one of the consumption streams; a peak prediction element that estimates future cumulative energy consumption and that predicts a brown out time; and a peak controller that triggers exceptional measures to manage the cumulative energy consumption in order to preclude

Abstract: A method for predicting when a grid will exceed production capacity including generating time shifted versions of consumption data for each of the buildings, each version comprising consumption values along with time and temperature values, where the consumption values are shifted by lag values relative to the time and temperature values, and where each lag value is different; performing a regression analysis on each version to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual indicating a corresponding energy lag for each of the buildings; using outside temperatures, regression model parameters, and lags for all of the buildings to estimate a cumulative consumption for the buildings, and to predict the time when the grid will exceed production capacity; and receiving the time when the grid will exceed production capacity, and preparing and commencing exceptional measures required to manage the consumption.

Abstract: A control system that performs VEE on consumption streams, including: data stores that provides data sets, each of the data sets comprising groups of contiguous values that correspond to correct data; a rules processor that reads the data stores and, for the each of the data sets, that creates anomalies having different durations using only the groups of contiguous values, that generates estimates for the anomalies by employing estimation techniques for each of the different durations and, for the each of the different durations, that selects a corresponding one of the estimation techniques for subsequent employment when performing VEE of subsequent energy consumption data associated with the each of the different durations for the corresponding one of the consumption streams; a peak prediction element that estimates future cumulative energy consumption and that predicts a brown out time; and a peak controller that triggers exceptional measures to manage the cumulative energy consumption in order to preclude

Abstract: A method for predicting when consumption on a grid will exceed normal capacity for buildings including generating time shifted versions of consumption data for the buildings, each version comprising consumption values along with time and outside temperature values, where the energy consumption values within each version are shifted by one of a plurality of lag values relative to the time and outside temperature values; performing regression analysis on each version to yield regression model parameters and a residual; determining a least valued residual indicating an energy lag for each of the buildings; using outside temperatures, regression model parameters, and energy lags to estimate a cumulative consumption for the buildings, and to predict when consumption on the grid will exceed normal capacity; and receiving the time when consumption on the grid will exceed normal capacity, and preparing and commencing exceptional measures required to manage the consumption.

Abstract: An apparatus is provided for performing validation, estimation, and editing (VEE) on interval based energy consumption streams. The apparatus includes a VEE processor and a VEE configuration engine. The VEE processor executes VEE rules on each of the interval based energy consumption streams within a specified time period to generate and store corresponding post VEE readings that are stored in a post VEE readings data stores. The post VEE readings include tagged energy consumption data sets that are each associated with a corresponding one of the interval based energy consumption streams. Each of the tagged energy consumption data sets has groups of contiguous interval values tagged as having been validated.

Abstract: An apparatus is provided for performing validation, estimation, and editing (VEE) on interval based energy consumption streams. The apparatus includes a VEE processor and a VEE configuration engine. The VEE processor executes VEE rules on each of the interval based energy consumption streams within a specified time period to generate and store corresponding post VEE readings that are stored in a post VEE readings data stores. The post VEE readings include tagged energy consumption data sets that are each associated with a corresponding one of the interval based energy consumption streams. Each of the tagged energy consumption data sets has groups of contiguous interval values tagged as having been validated.

Abstract: A method for predicting when consumption on a grid will exceed production capacity for buildings within the grid including time shifted version for each of the buildings, each version comprising consumption values along with time and temperature values, where the consumption values within each set are shifted by one of a plurality of lag values relative to the time and temperature values; performing a regression analysis on each set to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual indicating a corresponding energy lag for each of the buildings; using temperatures, regression model parameters, and energy lags for all of the buildings to estimate a cumulative consumption, and to predict the time when consumption on the grid will exceed production capacity; and receiving the time, and preparing and commencing exceptional measures required to manage the consumption.

Abstract: A method for predicting when energy consumption will exceed normal production capacity for buildings including generating data sets for each of the buildings, where energy consumption values within each set are shifted by one of a plurality of lag values relative to time and temperature values, and where each lag value is different; performing a regression model analysis on each set to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual indicating a corresponding energy lag for each of the buildings; using outside temperatures, regression model parameters, and energy lags for all of the buildings to estimate a cumulative energy consumption for the buildings, and to predict the time when energy consumption will exceed normal production capacity; and receiving the time when energy consumption will exceed normal production capacity, and preparing and commencing exceptional measures required to manage the energy consumption.

Abstract: Systems and methods for enabling automatic management of arbitrary power loads and power generation based on user-specified set of rules. The aforesaid rules may be applied based on the grid conditions, parameters of specific grid equipment, as well as any other (external) factors. In various embodiments, the aforesaid user-specified rules may be automatically executed by one or more servers in response to sensed grid conditions and arbitrary external factors. In various embodiments, the aforesaid rules may cause execution of local site functions, such as powering down specific load that may help stabilize the wider power grid. In one or more embodiments, the rules may be executed on a central server or on EVSE nodes in a decentralized manner using, for example, blockchain technology well-known to persons of ordinary skill in the art.

Abstract: Systems and methods may use a low speed controller in addition to an economic optimizer to achieve long-term objectives without significantly disrupting or destabilizing an electrical system. Specific long-term objectives include maximizing a capacity factor incentive and regulating battery degradation, but the methods and systems herein can be extended to more long-term objectives. A low speed controller can adjust one or more parameters of a cost function based on the relation between the projected state of the electrical system and the one or more parameters to effectuate a change to the electrical system to attempt to comply with the long-term objective.

Abstract: In accordance with one aspect of the embodiments described herein, there are provided systems and methods for integration of electric vehicle charging stations with photovoltaic, wind, hydro, thermal and other alternative energy generation equipment. In various embodiments, the aforesaid integration is used to perform balancing of the electrical power generated by the aforesaid photovoltaic, wind, hydro, thermal and other alternative energy generation equipment and the electrical power consumed by the aforesaid EVSE equipment. In one exemplary embodiment, the aforesaid balancing may be performed on a house (building) level. In another exemplary embodiment, the balancing may be performed on a neighborhood level.

Abstract: A method for predicting when energy consumption will exceed normal production capacity for buildings including generating data sets for each of the buildings, where energy consumption values within each set are shifted by one of a plurality of lag values relative to time and temperature values, and where each lag value is different; performing a regression model analysis on each set to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual indicating a corresponding energy lag for each of the buildings; using outside temperatures, regression model parameters, and energy lags for all of the buildings to estimate a cumulative energy consumption for the buildings, and to predict the time when energy consumption will exceed normal production capacity; and receiving the time when energy consumption will exceed normal production capacity, and preparing and commencing exceptional measures required to manage the energy consumption.

Abstract: A method for predicting when energy consumption will exceed normal production capacity for buildings including generating data sets for each of the buildings, where energy consumption values within each set are shifted by one of a plurality of lag values relative to time and temperature values, and where each lag value is different; performing a regression model analysis on each set to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual indicating a corresponding energy lag for each of the buildings; using outside temperatures, regression model parameters, and energy lags for all of the buildings to estimate a cumulative energy consumption for the buildings, and to predict the time when energy consumption will exceed normal production capacity; and receiving the time when energy consumption will exceed normal production capacity, and preparing and commencing exceptional measures required to manage the energy consumption.

Abstract: An occupancy-based traffic control system for augmenting traffic control mechanisms corresponding to buildings of one or more building types within a geographic subsector is provided. The system includes, a subsector aggregator, an other facility occupancy estimator, and a subsector processor. The subsector aggregator receives energy consumption and outside temperature streams corresponding to a portion of the buildings, and employs occupancy components to generate average occupancy components corresponding to each building type. The other facility occupancy estimator matches the average occupancy components to remaining ones of the buildings not in the first portion according to building type. The subsector processor uses the first and second aggregated occupancy components modify defaults of traffic control devices based on the occupancy estimate to optimize flow of pedestrians.

Abstract: An apparatus for controlling consumption of a resource by a facility includes devices, an occupancy determination system, and control nodes. The devices each consume a portion of the resource and perform a function. The occupancy determination system is disposed in a network operations center that is external to the facility and generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An apparatus for controlling consumption of a resource by a facility includes devices, an occupancy determination system, control nodes, and monitor nodes. The devices each consume a portion of the resource and perform a function. The occupancy determination system is disposed in a network operations center that is external to the facility and generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An apparatus for controlling facility resource consumption includes devices, a network operations center (NOC), and control nodes. The devices each consume a portion of the resource and perform a function. The NOC generates schedules which coordinate run times for the devices to control the consumption of the resource and adjusts the schedules based upon occupancy components and occupancy levels that are generated based on the consumption of the resource and outside temperature only. The control nodes are coupled to a corresponding one of the devices, and are coupled together via an energy management network that is operatively coupled to the NOC, The control nodes transmit sensor data and device status to the NOC for generation of the plurality of run time schedules, and where the control nodes execute selected ones of the run time schedules to cycle the devices on and off.

Abstract: An occupancy-based traffic control system for augmenting traffic control mechanisms corresponding to buildings of one or more building types within a geographic subsector is provided. The system includes, a subsector aggregator, an other facility occupancy estimator, and a subsector processor. The subsector aggregator receives energy consumption and outside temperature streams corresponding to a portion of the buildings, and employs occupancy components to generate average occupancy components corresponding to each building type. The other facility occupancy estimator matches the average occupancy components to remaining ones of the buildings not in the first portion according to building type. The subsector processor uses the first and second aggregated occupancy components modify defaults of traffic control devices based on the occupancy estimate to optimize flow of automotive vehicles.