A system and a method for regulating charging and discharging of an energy storage device as part of an electrical power distribution network is described. The invention is a smart control algorithm for a bi-directional switch in which an energy storage device, such as a battery set, is charged when electricity prices are low and discharged when electricity prices are high. The invention uses two different types of pricing data: forecasted price data and real-time price data. The forecasted price data is used to set a threshold. When the real-time price data of electricity exceeds this threshold, the energy storage device is set to discharge and send power to the grid. Otherwise the energy storage device is set to charge. The threshold is set periodically, typically in 30 minute to several hour intervals to capture the latest data.

A method for controlling an energy terminal, comprises determining a metric indicating a future availability of an energy resource at an energy terminal based on usage data associated to use of the energy resource by the energy terminal, generating control data to control the distribution of the energy resource between the energy terminal and an energy infrastructure based on the metric, and communicating the control data to the energy terminal.

Methods for implementing power delivery transactions between a buyer and a seller of electrical energy supplied to an electrical grid by an integrated renewable energy source (RES) and energy storage system (ESS) of a RES-ESS facility are provided. Estimated total potential output of the RES is compared to a point of grid interconnect (POGI) limit to identify potential RES overgeneration, and the buyer is charged if potential RES overgeneration is less than potential overgeneration during one or more retrospective time windows. The method provides a basis for the RES-ESS facility owner to be paid for an estimated amount of energy that did not get stored as a result of a grid operator not fully discharging an ESS prior to the start of a new day.

Systems and methods for financial settlement of transactions within an electric power grid network are disclosed. A multiplicity of active grid elements are constructed and configured for electric connection and network-based communication over a blockchain-based platform. The multiplicity of active grid elements are operable to make peer-to-peer transactions based on their participation within the electric power grid by generating and executing a digital contract. The multiplicity of active grid elements generate messages autonomously and/or automatically within a predetermined time interval. The messages comprise energy related data and settlement related data. The energy related data of the multiplicity of active grid elements are based on measurement and verification. The energy related data and the settlement related data are validated and recorded on a distributed ledger with a time stamp and a geodetic reference.

A power controller configured to fit in a circuit breaker panel powering one or more loads. The power controller is further configured to dynamically manage critical loads of the one or more loads each controlled by a component that is capable of being actuated by the power controller and operated from a smartphone via the power controller, wherein the critical loads need not be wired to a dedicated circuit breaker panel.

A computer-implemented method and system is provided. The system adaptively switches prediction strategies to optimize time-variant energy demand and consumption of built environments associated with renewable energy sources. The system analyzes a first, second, third, fourth and a fifth set of statistical data. The system derives of a set of prediction strategies for controlled and directional execution of analysis and evaluation of a set of predictions for optimum usage and operation of the plurality of energy consuming devices. The system monitors a set of factors corresponding to the set of prediction strategies and switches a prediction strategy from the set of derived prediction strategies. The system predicts a set of predictions for identification of a potential future time-variant energy demand and consumption and predicts a set of predictions. The system manipulates an operational state of the plurality of energy consuming devices and the plurality of energy storage and supply means.

A smart grid information processing apparatus is applied to a smart grid including a transmission grid being connected to a plurality of electrical equipment units and a communication network transmitting information of at least an amount of electric energy transmitted through the transmission grid. The information processing apparatus is configured to execute a first recording process and a withdrawal process. The first recording process is a process of recording virtual electrical storage capacities in association with respective users, each of the virtual electrical storage capacities corresponding to an amount of electric energy in which a corresponding user is allowed to receive from the smart grid. The withdrawal process is a process of reducing the virtual electrical storage capacity of the user according to an amount of electric energy that has been received by the user from the transmission grid.

A power controller configured to fit in a circuit breaker panel powering one or more loads. The power controller is further configured to manage critical loads of the one or more loads each controlled by a component that is capable of being actuated by the power controller and operated from a smartphone via the power controller, wherein the critical loads need not be wired to a dedicated circuit breaker panel.

A computer executes resource classification and resource selection. In the resource classification, each of a plurality of resources is classified as a first resource or a second resource having lower rated charging power than the first resource. In the resource selection, resources to act as reserves are selected for a reserve request from among the plurality of resources. In the resource selection for a first reserve request, the computer selects resources corresponding to the first resource with priority over resources corresponding to the second resource, and in the resource selection for a second reserve request, the computer selects resources corresponding to the second resource with priority over resources corresponding to the first resource. An adjustment period of the second reserve request is longer than an adjustment period of the first reserve request.

A collaborative aggregation trading method for consuming clean energy includes: acquiring related data of clean energy power generation companies, the demand-side resources and energy storage service providers; acquiring a trading quotation and acquiring self-regulating ability data and regulating fees of shared energy storage service providers; performing trading of collaboratively consuming the clean energy through the demand-side resources and the shared energy storage: when the power generation output value exceeds the maximum regulating ability of user demands and the demand-side resources, storing the redundant power into shared energy storage systems for standby application; when the power generation output value is lower than the minimum operation load level of the user demands and the demand-side resources, calling the shared energy storage service providers participating in the trading according to energy storage ranking indexes, to acquire required power from the shared energy storage systems; and performing fees settlement.