Abstract: A method and system for controlling demand events in a utility network with multiple customer sites. The value of a demand response parameter threshold for invoking a demand response event is calculated based on the number of available demand response events and the number of opportunities remaining to issue the available demand response events. This parameter represents the utility objectives for using the demand response program (e.g., cost savings, reliability, avoided costs). A current value of the demand response parameter is compared to the threshold value, and a determination is made whether or not to call a demand response event for the current opportunity, or to save the event for a future opportunity based upon this comparison.

Abstract: Method and system to provide co-optimized utilization of demand response and energy storage resources in an electrical grid system. The system may include a module to evaluate a marginal savings relative to a dispatch cost, if a demand response event is performed. The system may further include a module to evaluate a marginal savings relative to the dispatch cost, if an energy storage event is performed, and a controller including circuitry may be configured to determine a control strategy to perform a dispatch including a demand response event and/or an energy storage event, based at least in part on the respective marginal savings of the demand response event and/or the energy storage event, which may be selected to co-optimize an integrated utilization of the demand response and energy storage resources to meet a given objective.

Abstract: A method for providing VAR support in a power distribution network having a demand response management system can include querying the demand response management system for an inductive device on the power distribution network and power cycling the inductive device to effect reactive power in the power distribution network.

Abstract: A method includes receiving at least one event parameter for a demand response event and identifying a pool of customers. The pool of customers includes a plurality of customers potentially usable to support the demand response event. Characteristics of each customer in the pool of customers are retrieved and a plurality of groups of customers are created from the pool of customers based on the retrieved characteristics and the at least one event parameter.

Abstract: A phase balancing system includes a load forecasting module, a phase unbalance identification module and a demand response module. The load forecasting module determines a load forecast for the distribution system for the period of interest and the phase unbalance identification module determines voltage unbalance on the distribution system for the period of interest. The demand response module estimates an available demand response on the distribution system for the period of interest and allocates an optimized demand response from the available demand response to minimize the voltage unbalance on the distribution system for the period of interest.

Abstract: A protection system for a power distribution system includes a bus voltage sensing unit to measure a bus voltage or a load voltage and a demand response module for estimating available demand resources on the distribution system for a period of interest. A distribution system analyzer is provided in the system for analyzing the bus voltage or the load voltage and system parameters to obtain voltage trip points for the available demand resources. A load control circuit controls the available demand resources based on the voltage trip points.

Abstract: A system for optimal planning of electric power demand is presented. The system includes a node comprising one or more smart charging plug-in electric vehicles (SCPEVs), a processing subsystem, wherein the processing subsystem receives relevant data from one or more sources; and determines an optimized SCPEV load and optimal charging schedule for the node by applying an operations research technique on the relevant data.

Abstract: A power forecasting module determines a load forecast of a distribution system (DS) and a power generation forecast of distributed energy resources (DERs) A demand response (DR) module estimates an available DR based on the load and the power generation forecast and modifies the load forecast by dispatching an optimal DR. An energy storage commitment module determines a charging/discharging schedule of energy storage devices in the system based on the modified load profile and generates a second load profile by incorporating the charging/discharging schedule of energy storage devices. An unit commitment (UC) module determines a DER schedule of supplying electrical power to the loads in the second load profile based on a first objective function. An economic dispatch (ED) module determines an optimum operating point for each DER and an Integrated Volt-VAR Control (IVVC) module controls distribution assets to maintain a voltage profile in the system.

Abstract: A method and system for controlling load in a utility distribution network are provided that initiates a shed event for a node in the distribution network by selecting premisess associated with the node that are participating in a demand response program to reduce the load at the node to desired levels. More specifically, the system and method provide for selecting only enough participating premisess associated with the node that are necessary to reduce the load to desired levels.

Abstract: A method for demand response management includes determining a number of available demand response events and a number of opportunities available to issue the available demand response events. A priority for each demand response event is provided and a threshold value for each demand response vent is determined. A highest priority demand response event among the available demand response events whose threshold value is lower than an observed value of a selected demand response trigger is selected and control signals to utilize the selected demand response event for a current opportunity are transmitted to customer sites.

Abstract: A frequency regulation system includes a sensor to detect a power grid signal and a frequency deviation identification module to determine a power grid frequency deviation from the power grid signal. A demand response module identifies an operating schedule for available demand response resources based on frequency deviation set points and ramp rates and a load control module controls the available demand response resources based on the operating schedule.

Abstract: A system and method for simultaneously restoring power to loads in a distribution network that experienced an outage. The pickup load on the feeder in the distribution network is estimated and the load limit on the feeder is determined. The load on the feeder is divided into groups based on the load limit. A restoration load control process is determined, and power is restored to each of the groups simultaneously based on the power restoration control process.

Abstract: Method and system to provide co-optimized utilization of demand response and energy storage resources in an electrical grid system. The system may include a module to evaluate a marginal savings relative to a dispatch cost, if a demand response event is performed. The system may further include a module to evaluate a marginal savings relative to the dispatch cost, if an energy storage event is performed, and a controller including circuitry may be configured to determine a control strategy to perform a dispatch including a demand response event and/or an energy storage event, based at least in part on the respective marginal savings of the demand response event and/or the energy storage event, which may be selected to co-optimize an integrated utilization of the demand response and energy storage resources to meet a given objective.

Abstract: A power forecasting module determines a load forecast of a distribution system (DS) and a power generation forecast of distributed energy resources (DERs). A demand response (DR) module estimates an available DR based on the load and the power generation forecast and modifies the load forecast by dispatching an optimal DR. An energy storage commitment module determines a charging/discharging schedule of energy storage devices in the system based on the modified load profile and generates a second load profile by incorporating the charging/discharging schedule of energy storage devices. An unit commitment (UC) module determines a DER schedule of supplying electrical power to the loads in the second load profile based on a first objective function. An economic dispatch (ED) module determines an optimum operating point for each DER and an Integrated Volt-VAR Control (IVVC) module controls distribution assets to maintain a voltage profile in the system.

Abstract: A method includes receiving at least one event parameter for a demand response event and identifying a pool of customers. The pool of customers includes a plurality of customers potentially usable to support the demand response event. Characteristics of each customer in the pool of customers are retrieved and a plurality of groups of customers are created from the pool of customers based on the retrieved characteristics and the at least one event parameter.

Abstract: A system for implementing congestion pricing in a power distribution network includes a monitoring and control engine configured to receive an actual power consumption value for a node in the power distribution network and a congestion engine coupled to the monitoring and control engine configured to determine that a power consumption value exceeds a capacity related set point of the node. The system further includes a pricing calculator that establishes a congestion price for power to be applied while the actual power consumption value exceeds the set point of the node and a credit calculator that provides credits to consumers coupled to the node that consume power at a rate below a threshold while the actual power consumption value exceeds the set point of the node.

Abstract: A protection system for a power distribution system includes a bus voltage sensing unit to measure a bus voltage or a load voltage and a demand response module for estimating available demand resources on the distribution system for a period of interest. A distribution system analyzer is provided in the system for analyzing the bus voltage or the load voltage and system parameters to obtain voltage trip points for the available demand resources. A load control circuit controls the available demand resources based on the voltage trip points.

Abstract: A method for selecting consumers is presented. The method comprises the steps of receiving consumers' data, historical response data, contractual obligations data of a plurality of consumers; receiving a demand response event's description data, determining at least one parameter corresponding to each of the plurality of consumers based upon one or more of the consumers' data, the historical response data, the contractual obligations data and the demand response event's description data, and selecting a subset of consumers from the plurality of consumers based upon the at least one parameter, wherein the at least one parameter comprises a potential load reduction for each of the plurality of consumers.

Abstract: A method for providing VAR support in a power distribution network having a demand response management system can include querying the demand response management system for an inductive device on the power distribution network and power cycling the inductive device to affect reactive power in the power distribution network.

Abstract: A system for optimal planning of electric power demand is presented. The system includes a node comprising one or more smart charging plug-in electric vehicles (SCPEVs), a processing subsystem, wherein the processing subsystem receives relevant data from one or more sources; and determines an optimized SCPEV load and optimal charging schedule for the node by applying an operations research technique on the relevant data.