1816 results about "Demand response" patented technology

Thermostatic HVAC and other energy management controls that are connected to a computer network. For instance, remotely managed load switches incorporating thermostatic controllers inform an energy management system, to provide enhanced efficiency, and to verify demand response with plug-in air conditioners and heaters. At least one load control device at a first location comprises a temperature sensor and a microprocessor. The load control device is configured to connect or disconnect electrical power to the an attached air conditioner or heater, and the microprocessor is configured to communicate over a network. In addition, the load control device is physically separate from an air conditioner or heater but located inside the space conditioned by the air conditioner or heater.

The present invention discloses a system for transferring electrical power between a grid and at least one vehicle. The vehicle can be Battery Electric Vehicle (BEV), Plug-in Hybrid Electric Vehicle (PHEV) or Fuel Cell Vehicle (FCV). The type of vehicle will be recognized and controlled by the system to support demand response and supply side energy management. Vehicle recognition can be carried out by load signature analysis, power factor measurement or RFID techniques. In an embodiment of the invention, the grid is a Smart Grid. The present invention also discloses a method for facilitating electrical power transfer between the grid and the vehicle.

Disclosed herein are systems and methods for demand forecasting that enable multiple-scenario comparisons and analyses by letting users create forecasts from multiple history streams (for example, shipments data, point-of-sale data, customer order data, return data, etc.) with various alternative forecast algorithm theories. The multiple model framework of the present invention enables users to compare statistical algorithms paired with various history streams (collectively referred to as “models”) so as to run various simulations and evaluate which model will provide the best forecast for a particular product in a given market. Once the user has decided upon which model it will use, it can publish forecast information provided by that model for use by its organization (such as by a downstream supply planning program). Embodiments of the present invention provide a system and method whereby appropriate demand responses can be dynamically forecasted whenever given events occur, such as when a competitor lowers the price on a particular product (such as for a promotion), or when the user's company is launching new sales and marketing campaigns. Preferred embodiments of the present invention use an automatic tuning feature to assist users in determining optimal parameter settings for a given forecasting algorithm to produce the best possible forecasting model.

An intelligent user-side power management device (PMD) that is comprised of an optional energy storage unit and can interface with a utility grid or microgrid to eliminate power theft and efficiently provide clean energy to the users of the grid while helping the grid to do smart demand response management, particularly for renewable energy based grids that need to efficiently manage the slack due to the large variability in power generation through these energy sources.

Apparatus, systems, methods, and related computer program products for managing demand-response programs and events. The systems disclosed include an energy management system in operation with an intelligent, network-connected thermostat located at a structure. The thermostat acquires various information about the residence, such as a thermal retention characteristic of the residence, a capacity of an HVAC associated with the residence to cool or heat the residence, a likelihood of the residence being occupied, a forecasted weather, a real-time weather, and a real-time occupancy. Such information is used to manage the energy consumption of the structure during a demand-response event.

Various utility portals that enable utility companies to manage demand-response events are disclosed. The disclosed utility portals include several different options for enabling utility companies to communicate information to and received information from an energy management system. The energy management system can host the portal and can carry out a demand response event via intelligent, network-connected devices based on information provided by the utility company.

A multi-level automation control architecture, methods, and systems are disclosed, which provide enhanced scalability, functionality, and cost effectiveness for energy, access, and control. The systems include various combinations of automation controllers, remote controllers and peripheral devices that are used to provide monitoring and control functionality over the various systems in a structure, such as HVAC, water, lighting, etc. In various embodiments, the automation controller and various peripheral devices are implemented to provide an integrated energy management system for the structure. The system allows the user to manage energy based on the day, time, the presence of people, and the availability of natural lighting and heating, as well as prioritize and participate in demand-response program. The system can be implemented using a remote controller and expanded through the addition of automation controllers, remote controllers, and peripheral devices to enable the system to be tailored to specific user requirements.

The power flexibility of energy loads is maximized using a value function for each load and outputting optimal control parameters. Loads are aggregated into a virtual load by maximizing a global value function. The solution yields a dispatch function providing: a percentage of energy for each individual load, a time-varying power level for each load, and control parameters and values. An economic term represents the value of the power flexibility to different players. A user interface includes for each time interval upper and lower bounds representing respectively the maximum power that may be reduced to the virtual load and the maximum power that may be consumed. A trader modifies an energy level in a time interval relative to the reference curve for the virtual load. Automatically, energy compensation for other intervals and recalculation of upper and lower boundaries occurs. The energy schedule for the virtual load is distributed to the actual loads.

According to various implementations, a demand response (DR) strategy system is described that can effectively model the HVAC energy consumption of a house using a learning based approach that is based on actual energy usage data collected over a period of days. This modeled energy consumption may be used with day-ahead energy pricing and the weather forecast for the location of the house to develop a DR strategy that is more effective than prior DR strategies. In addition, a computational experiment system is described that generates DR strategies based on various energy consumption models and simulated energy usage data for the house and compares the cost effectiveness and energy usage of the generated DR strategies.

A load control system for a building having a lighting load, a window, and a heating and cooling system comprises a lighting control device for controlling the amount of power delivered to the lighting load, a daylight control device (such as a motorized window treatment) for adjusting the amount of natural light to be admitted through a window, and a controller for adjusting a setpoint temperature of the heating and cooling system to thus control a present temperature in the building. In response to receiving a demand response command, the controller controls the lighting control device, the daylight control device, and the heating and cooling system so as to decrease a total power consumption of the load control system. The load control system may comprise a controllable switching device for disconnecting power to or disconnecting the control lines to one or more components of the heating and cooling system.

A multi-level automation control architecture, methods, and systems are disclosed, which provide enhanced scalability, functionality, and cost effectiveness for energy, access, and control. The systems include various combinations of automation controllers, remote controllers and peripheral devices that are used to provide monitoring and control functionality over the various systems in a structure, such as HVAC, water, lighting, etc. In various embodiments, the automation controller and various peripheral devices are implemented to provide an integrated energy management system for the structure. The system allows the user to manage energy based on the day, time, the presence of people, and the availability of natural lighting and heating, as well as prioritize and participate in demand-response program. The system can be implemented using a remote controller and expanded through the addition of automation controllers, remote controllers, and peripheral devices to enable the system to be tailored to specific user requirements.

The present invention comprises a method, and corresponding system, apparatus and memory for trading energy commitments to reduce or increase energy demand (a demand response commitment), to increase or reduce energy production (a supply response commitment) upon demand or to deliver or to not deliver energy (an energy delivery commitment). Such commitments are made available by energy consumers, energy generators and energy delivery companies, respectively, to an entity that provides consideration for these energy commitments and trades them as fungible commodities to energy market participants. In one embodiment, the present invention comprises a method for trading energy commitments to reduce or increase energy consumption, to increase or reduce energy generation, or to deliver energy, comprising receiving a plurality of multi-year energy commitments; providing consideration for each of the multi-year energy commitments; and trading at least one of the plurality of energy commitments upon demand.

Provided is a day-ahead load reduction system based on a customer baseline load for inducing a user to efficiently manage energy consumption by applying an incentive (user compensation according to load reduction) to achieve load reduction and load decentralization. The day-ahead load reduction system based on a customer baseline load operates in connection with a provider terminal and a user terminal through a network to induce a reduction in the load of a user and includes an AMI/AMR translator collecting load profile data of the user in real time, converting the load profile data and storing the load profile data in a meter data warehouse; a meter data management system monitoring and analyzing the load profile data stored in the meter data warehouse in real time; a demand response operation system managing the demand of the user by using the load profile data and performing overall management, analysis and verification of a day-ahead load reduction event; a customer energy management system operating in connection with the demand response operation system and providing information on the load to the user through the user terminal in real time to allow the user to control the load; and an account system operating in connection with the demand response operation system and the customer energy management system, calculating an incentive for the day-ahead load reduction event and notifying a provider and the user of the incentive through the provider terminal and the user terminal.

There is provided a power control method for secondary batteries constituting, in a grid connection system supplying electric power to a power system by combining a power generator where output power fluctuates with a power storage compensator, the power storage compensator and compensating fluctuation of output power of the power generator. The method includes the steps of: dividing the secondary batteries into a “constant power control” group and a “demand responsive” group, and distributing predetermined constant input-output power out of power to be input and output provided to all the secondary batteries in order to compensate fluctuation of output power of the power generator to the “constant power control group” and the remaining input-output power to the “demand responsive” group to control input-output power of the secondary batteries respectively depending on the belonging groups.

A system and method for distributed intelligence of power tracking and power allocation may include: receiving data by at least one computer from a plurality of identified charging stations and vehicles of customers at distributed locations throughout a power grid; analyzing, with at least one processor of the at least one computer, the data with respect to available power for those locations and customer historical usage and profiles; and sending commands, with the at least one processor, to reallocate power to assets of the power grid to handle fluctuations or forecasted fluctuations in power demand based on the analysis. Customer preferences may also be considered in predicting power demand issues and need for demand response. Economic rules may be executed to incentivize the customers to comply with demand response requirements where demand is greater than power supply.

Apparatus, systems, methods, and related computer program products for carrying out a demand response (DR) event via an intelligent, network-connected thermostat associated with a structure. The systems disclosed include an energy management system in operation with an intelligent, network-connected thermostat located at a structure. The thermostat is operable to control an HVAC system. Control during a DR event period may be performed based on an optimal control trajectory of the HVAC system, where the control trajectory is optimal in that it minimizes a cost function comprising a combination of a first factor representative of a total energy consumption during the DR event period, a second factor representative of a metric of occupant discomfort, and a third factor representative of deviations of a rate of energy consumption over the DR event period.

A load control system for a building having a heating and cooling system and a window located in a space of the building is operable to control a motorized window treatment in response to a demand response command in order to attempt to reduce the power consumption of the heating and cooling system. When the window may be receiving direct sunlight, the motorized window treatment closes a fabric covering the window when the heating and cooling system is cooling the building, and opens the fabric when the heating and cooling system is heating the building. In addition, when the space is unoccupied and the heating and cooling system is heating the building, the motorized window treatment may open the fabric if the window may be receiving direct sunlight, and may close the fabric if the window may not be receiving direct sunlight.

A system and process/method is provided, which economically optimizes the dispatch of various electrical energy resources. The disclosed process/method is linked to and communicates with various sources of input data, including but not limited to, EMS/SCADA legacy Energy Management Systems (EMS), legacy Supervisory Control and Data Acquisition (SCADA) Systems, Demand Response (DR) and Distributed Energy Resources (DER) monitor, control, schedule, and lifecycle management systems (DR/DER Management System), and Energy Markets, electrical energy commodity trading systems (Trading Systems), and Operations System (OPS) in order to compute optimal day-ahead, day-of, and real-time schedules of various durational length for generation, demand response and storage resources while taking into account bilateral contracts and market-based trade opportunities.