A control apparatus includes a controller configured to: acquire first information indicating the number of people in a target building during a predetermined time period, second information indicating electrical energy consumed in the target building during the predetermined time period, and/or third information indicating the number of people heading to the target building during the predetermined time period; and estimate, based on the first information, the second information, or the third information, a demand for electrical energy for the building during a future target time period.

An energy optimization system for a building includes a processing circuit configured to generate a user interface including an indication of one or more economic load demand response (energy) operation parameters, one or more first participation hours, and a first load reduction amount for each of the one or more first participation hours. The processing circuit is configured to receive one or more overrides of the one or more first participation hours from the user interface, generate one or more second participation hours, a second load reduction amount for each of the one or more second participation hours, and one or more second equipment loads for the one or more pieces of building equipment based on the received one or more overrides, and operate the one or more pieces of building equipment to affect an environmental condition of the building based on the one or more second equipment loads.

A power calculation apparatus calculating an amount of power suppliable to a power system by an energy source connectable, at a connection point, to the power system and capable of power generation and power storing, the power calculation apparatus includes: a microprocessor and a memory connected to the microprocessor, wherein the microprocessor is configured to perform: specifying a position of the connection point of the energy source in connection with the power system; acquiring a capacity information indicating a power generation capacity or a remaining storage capacity of the energy source; and calculating an amount of power suppliable by the energy source to the power system in an area within a predetermined range including the connection point, based on the capacity information and the position of the connection point.

A method tests the configuration of an aggregated DERs system using distributed asset managers in a decentralized hardware-in-the-loop (“HIL”) scheme. The managers contain the model of the asset they are meant to control. The method programs an asset manager with a model of a DERs asset. A plurality of asset managers are connected to a central controller. The plurality of asset managers are also connected to a simplified hardware-in-the-loop platform. The simplified HIL platform is configured to solve a network model, a load model, a non-controllable asset model, and a grid model. The method tests the DERs system control structure by using: (a) the simplified HIL platform to solve the network model, the load model, the non-controllable asset model, and the grid model, and (b) the asset manager to solve the model of the DERs asset, without any simulation between the central controller and the distributed asset managers.

According to an embodiment of the present invention, there is provided a method for managing charging and discharging of an energy storage system (ESS) group for voltage stabilization of a grid having a distributed resource connected thereto in a power management device, the method including measuring a voltage and current amount of the grid to which the distributed resource is connected, performing control so that a voltage of the grid to which the distributed resource is connected is reduced through charging of an ESS group to be charged, by determining that a plurality of ESSs connected to a power distribution line are required to be charged when it is confirmed that the voltage and current amount of the grid to which the distributed resource is connected are greater than a preset reference voltage and current amount, calculating a required charge amount through a difference between the voltage and current amount of the grid to which the distributed resource is connected and the reference voltage and current amount, checking the chargeable capacity for each of ESS groups in which the plurality of ESSs are classified according to a preset condition, selecting the ESS group to be charged from among the ESS groups based on the required charge amount and the chargeable capacity for each ESS group, and transmitting a charging command for the required charge amount to the ESS group to be charged, performing control so that the voltage of the grid to which the distributed resource is connected is increased through charging of an ESS group to be discharged, by determining that the plurality of ESSs are required to be discharged when it is confirmed that the voltage and current amount of the grid to which the distributed resource is connected are smaller than the reference voltage and current amount, calculating a required discharge amount through the difference between the voltage and current amount of the grid to which the distributed resource is connected and the reference voltage and current amount, checking the dischargeable capacity for each of the ESS groups, selecting the ESS group to be discharged from among the ESS groups based on the required discharge amount and the dischargeable capacity for each ESS group, and transmitting a discharging command for the required discharge amount to the ESS group to be discharged, calculating a voltage control amount through a charge amount and a discharge amount for each ESS group when the voltage of the grid to which the distributed resource is connected is stabilized by charging and discharging the plurality of ESSs, and providing a performance incentive for voltage stabilization to the ESS group in which it is co

In a power control system a server maintains asset models that represent asset behaviour, each asset model being in real-time communication with its asset to dynamically inform the model of the status of the asset. A test is performed at the server by issuing a command to an asset requesting the asset to perform a function. Sensors at the asset measure physical parameters at the asset and report these to the server. The server determines whether the asset responded to the command and, if the asset responded, how it responded over time. The server establishes a model for the asset in terms of an energy capacitance and a time constant based on the measured response. An optimizer determines which assets are to participate in which service models. The server sends instructions to the selected assets to attempt to fulfill the services.

A power prediction method includes obtaining evaluation metrics of models in a model pool, where the evaluation metrics are used to indicate precision of the models; selecting, based on the evaluation metrics, a first model for a power prediction on a first electrical unit; and presenting a result of the power prediction of the first electrical unit using the first model.

To ensure safety of people needing to service a low-voltage network of an electric power distribution system, dwellings being connected to this network may include autonomous units for producing electricity, thus generating voltage and endangering the people servicing the work. Data are obtained from consumption records from the meter of each dwelling, in regular time intervals, and meteorological data are also obtained in the geographical area of these dwellings, in order to identify at least some weather conditions conducive to the production of energy by autonomous units. A model is then applied for detecting, based on the first and second data, a coincidence between periods of lower consumption measured by a meter and weather conditions conducive to electricity production by autonomous units during these periods. Therefore, information on the presence of autonomous units in the dwelling can be deduced and given to people before their servicing.

A system for allocating resources across equipment that operate to serve one or more loads of a building. The system includes one or more memory devices storing instructions that cause one or more processors to receive operational data defining at least one of planned loads to be served by the equipment or utility rates for one or more time steps within a simulation period, determine whether the operational data define the planned loads or the utility rates for each time step within the simulation period, and in response to a determination that the operational data do not define the planned loads or the utility rates for each time step within the simulation period, identify one or more time steps for which the planned loads or the utility rates are not defined and initiate an action to define the planned loads or the utility rates for the identified time steps.

Systems and methods for controlling power flow to and from an energy storage system are provided. One implementation relates to an energy storage system comprising an energy storage device, an inverter configured to control a flow of power out of the energy storage device, a rectifier configured to control the flow of power into the energy storage device and one or more controllers. The one or more controllers may be configured to determine a schedule of a plurality of time periods based on historical price data. Each of the plurality of time periods may be associated with one of a state of charging, discharging, or idle. The one or more controllers may be configured to control the inverter and the rectifier based on the determined schedule.