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.

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.

Methods and systems are disclosed that automatically determine solar access values. In one implementation, a 3D geo-referenced model of a structure is retrieved in which geographic location on the earth of points in the 3D geo-referenced model are stored or associated with points in the 3D geo-referenced model. Object point cloud data indicative of object(s) that cast shade on the structure is retrieved. The object point cloud data may be generated from one or more georeferenced images and the object point cloud data is indicative of an actual size, shape, and location of the object(s) on the earth. The structure in the 3D geo-referenced model is divided into one or more sections, which are divided into one or more areas, each area having at least three vertices. Then, a solar access value for the particular vertex is determined.

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.

An electric power management system is a system that performs an exchange of electric power with an electric power system of an electric power company that is a counterparty of the exchange of the electric power, and includes a plurality of the vehicles, each including a battery, and a server that manages an exchange of the electric power between the battery of each of the vehicles and the electric power system. The server manages the exchange of the electric power for each vehicle group in which the vehicles are bundled, and configures the vehicle groups in advance such that distributions of the electric power supply and demand characteristics of the batteries of the vehicles included in the vehicle groups are the same or similar.

An example operation includes one or more of determining a modified use of energy by an entity, based on a current environmental factor, and providing an energy offset to the entity based on the modified use. The offset derives an alternate benefit to overcome a negative balance by another entity.

A photovoltaic system can include multiple photovoltaic power inverters that convert sunlight to power. An amount of power for each of the inverters can be measured over a period of time. These measurements, along with other data, can be collected. The collected measurements can be used to generate artificial neural networks that predict the output of each inverter based on input parameters. Using these neural networks, the total solar power generation forecast for the photovoltaic system can be predicted.

A system and method for optimizing utilization of a plurality of energy sources of a power site are provided. The optimization can involve receiving a weather forecast and expected power output for a predefined time duration, and a power source for one or more time intervals to provide output power for the power site. The determination can be based on a future weather forecast and expected power output. The optimization can involve minimizing an amount of time that generator(s) are the power source and maximizing an amount of time that solar panel(s) are the power source.

The present invention pertains to an energy management device 50 of a microgrid S1 which is associated with a power system 1 and is provided with a power storage device 15, the energy management device calculating a target value of received power of the microgrid, the target value optimizing the utilization efficiency of the energy of the microgrid S1, on the basis of power demand prediction in the microgrid S1 by taking, as constraint conditions, the upper and lower limits of the received power of the microgrid S1 and the upper and lower limits of output power of the power storage device.