Systems and methods related to resource distribution for a fleet of machines are disclosed. A system may include a fleet of machines each having an associated resource capacity and a resource requirement to perform a task. The system may further include a controller having a resource requirement circuit to determine an aggregated amount of the resource requirement and an aggregated amount of the resource capacity. A resource distribution circuit may adaptively improve, in response to an aggregated amount of the resource capacity, an aggregated resource delivery of the resource.

Systems include one or more critical datacenter connected to behind-the-meter flexible datacenters. The critical datacenter is powered by grid power and not necessarily collocated with the flexboxes, which are powered “behind the meter.” When a computational operation to be performed at the critical datacenter is identified and determined that it can be performed at a lower cost at a flexible datacenter, the computational operation is instead routed to the flexible datacenters for performance. The critical datacenter and flexible datacenters preferably shared a dedicated communication pathway to enable high-bandwidth, low-latency, secure data transmissions.

A power system includes a power sourcing device, a first splice enclosure including a first power input port, a first power output port, and a first power tap port that is connected to a first remote powered device, and a second splice enclosure including a second power input port, a second power output port, and a second power tap port that is connect to a second remote powered device. The power system includes a composite power-data cable configured to carry power signals transmitted from the power sourcing device to the first splice enclosure and to the second splice enclosure. The power sourcing device is configured to disable the power signals to at least one of the first power input port, the first power output port, or the first power tap port of the first splice enclosure without disabling the power signals at the second splice enclosure.

A control device is connected to power loads installed in a consumer facility so as to be able to communicate with the power loads. The control device includes: a control unit; and a display unit. The control unit determines the power loads and predicted power consumption when the power loads are used, determines at least one usable power load out of the power loads based on a remaining amount of available electric power in the consumer facility and the predicted power consumption, displays the usable power load on the display unit such that the usable power load is selectable, and controls use of the selected power load.

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning (ML) to forecast energy demand and to generate an energy plan for one or more facilities of an organization. For example, a system may forecast an occupancy of the facilities for use with historical demand data in forecasting the energy demand. The forecasting may be performed by one or more trained ML models. Additional ML models may be trained to select energy resources that satisfy the forecasted energy demand and that prioritize constraint(s). The system may generate an energy plan that indicates information related to the selected energy resources, such as cost, energy type, environmental impact, etc., for use in increasing an amount of renewable energy resources used at the facilities. In some implementations, the system may recommend actions to reduce a negative environmental impact associated with the selected energy resources.

A method for stabilising a power grid by at least one backup battery of a network element for use in a communications network. The method comprises determining (402) future power consumption of the network element, determining (404) a required backup energy level of said at least one backup battery based on said determined future power consumption for operation of the network element for a defined period and providing (406) a fraction of capacity of said at least one backup battery to stabilise a power grid.

Example computer-implemented methods, media, and systems for configuring an energy consuming system are described. One example computer-implemented method includes receiving, for each type of energy of multiple types of energy, data defining a set of parameters related to a capacity of the type of energy for a particular region. The capacity for each type of energy is converted into a common unit of energy using the set of parameters for each type of energy. A determination is made, by evaluating a model using at least on the capacity of two o1r more of the types of energy and a required amount for each of the two or more types of energy, an operational adjustment to one or more components of an energy consuming system that adjusts energy consumption of the one or more components. The one or more components are reconfigured according to the operational adjustment.

The invention relates to a method and apparatus for monitoring the condition of subsystems within a renewable generation plant or microgrid which are using Supervisory Control and Data Acquisition (SCADA) systems for allowing plant operators to monitor and interact with a plant via human machine interfaces.

Various embodiments include a method for controlling an energy exchange among a plurality of energy systems using a control center, wherein a component of one of the plurality of energy systems is coupled to the control center via an interface module for data exchange. The method includes: transmitting a first data set to the interface module with a prediction profile regarding an energy exchange of the component; transmitting a second data set to the control center using the interface module including the first data set and component-specific data of the component; determining control data using the control center using the prediction profile and the component-specific data and data communicated to the control center by further energy systems to determine the control data; transmitting the determined control data to the interface module; and operating the component based on the control data.

The present invention is a method of “Demand Side Management” (DSM) that is intended to manage the increasingly chaotic nature of the power grid, and is designed to adapt to the future impact to the grid patterns caused by the ongoing introduction of renewable power generation sources, battery charging associated with the increasing number of electric vehicles, and future unforeseen developments, by utilizing “Statistical Process Control” (SPC) techniques. SPC is typically a method for controlling manufacturing process variation in a factory, analogously the present invention adapts SPC methods to help monitor the quality of the grid by treating said grid as if said grid were a process with varying levels of quality, to which the present invention can detect, anticipate and respond by making immediate and adaptive future scheduling decisions for the control of device loads, or generation, for the benefit of consumers as well as power companies.