A control system for an energy storage system located behind a utility meter uses a unique, feedback-based, communication and control method to reliably and efficiently maximize economic return of the energy storage system. Operating parameters for the energy storage system are calculated at an external, centralized data center, and are selected to prevent electrical power demand of an electric load location from exceeding a specified set-point by discharging energy storage devices, such as DC batteries, through a bidirectional energy converter during peak demand events. The control system can operate autonomously in the case of a communications failure.

Distributed energy resources are validated by dispatching a distributed energy resources individually in known ambient conditions and monitoring the particular effect of dispatch to then establish a database of performance for multiple different distributed energy resources. The distributed energy resources can be permanently monitored to further build up this database and to verify that the distributed energy resource 1s performing consistent with its validation or other expected performance. Distributed energy resources of a slow responding variety and a fast responding variety can be paired together and dispatched together, so that the paired fast responding and slow responding distributed energy resources mimic a large fast responding distributed energy resource. The benefits of a high capacity fast responding distributed energy resource is thus provided, such as for the load shedding and grid support benefits thereof.

The invention includes systems and methods for power cogeneration. In certain embodiments the cogeneration systems include one or more units that are modularized; in some of these embodiments, the modules contain components that are integrated and ready for use with a control system that optimizes a result for the cogeneration plant. In some cases, the cogeneration system is part of a network of cogeneration systems.

The present disclosure describes transaction-enabling systems and methods for enabling machine resource transactions. A system can include a machine having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement; and a controller. The controller can include a resource requirement circuit to determine an amount of a resource for the machine to service task requirement, a resource market circuit to access a resource market, and a resource distribution circuit to execute a transaction of the resource on the resource market in response to the determined amount of the resource.

Systems and methods for forward market price prediction and sale of energy storage capacity are disclosed. An example transaction-enabling system may include a fleet of machines having an aggregate energy storage capacity; and a controller, comprising: an external data circuit structured to monitor an external data source and collect data from the external data source; an expert system circuit structured to predict a forward market price for energy storage capacity based on the collected data and the aggregate energy storage capacity; and a smart contract circuit structured to automatically sell at least a subset of the aggregate energy storage capacity on a forward market for energy storage capacity in response to the predicted forward market price.

An energy grid network includes multiple distributed energy resources (DERs) or DER nodes. A DER node includes a local energy source and a local energy load. The DER nodes in the network generate realtime data about energy availability from local energy sources and realtime data about energy demand. The DER nodes can share the realtime data with other DER nodes in the network to provide a constant view in the network about the energy generation and energy demand within the network. The shared realtime data can be scaled at each DER node based on physical distance, time to exchange energy between nodes, or both distance and time. A DER node generates its own realtime data and receives data from one or more other DER nodes and determines the value of energy use from local or non-local sources by local and non-local loads.

[Object] As compared with the case where a device supplies power to an electric line regardless of an index regarding the capacity of power in an electric path, the device may supply the power to the electric line according to the content of supply suitable for the electric path.

[Solution] A power control system includes an acquisition unit that acquires capacity information on capacity of power in an electric path through which power supplied from a power plant passes before the power is received by a device, and a control unit that performs control on, based on the capacity information, supply of power from the device to an electric line through which the power supplied from the power plant passes before the power is received by the device.

A smart meter system is described for managing demand side electrical transactions with shifted demand in a smart grid. The smart meter controller uses non-cooperative game theoretic analysis for managing multi-periodic smart grid shifted demand. The problems of user based electricity demand, production, storage, and sales of energy to providers are addressed. The smart meter system described is used in the control of Home-Area-Network (HAN) or Wide-Area-Network (WAN) demand response management (DRM).

A method for controlling an electrical installation at least one of an electrical energy source or an energy sink. The electrical installation is coupled to a power grid. The method includes a period of time having a start time and a duration being specified, an upward flexibility Fo, which includes a forecast maximum feed-in power increase or feed-out power decrease, and a downward flexibility Fu, which includes a forecast maximum feed-out power increase or feed-in power decrease, being set for the period of time, a selling threshold price Pv and a purchasing threshold price Pe being set for the period of time, and an electricity trading transaction being concluded for the period of time. The electricity trading transaction includes a base value, a base quantity, a base price, a date on which the electricity trading transaction is to be carried out.

A method, an internet of things system and a storage medium for government power supply regulation in a smart city are provided. The method may be implemented by a government power supply regulation and management platform and include: obtaining weather features of a target area in a future time period, time event features of the target area in the future time period, and basic economic development features of the target area in a current time period; predicting, based on the features, per capita living electricity consumption of the target area in the future time period through an electricity consumption prediction model; and determining, based on the per capita living electricity consumption of the target area in the future time period, a power supply strategy of the target area in the future time period.