A method for planning consumption of power by devices onboard a marine vessel from a power source having a finite capacity. The method includes storing a usage model within a memory system, where the usage model includes an amount of the power consumed by each of the devices over a time period. The method further includes receiving a usage plan for operating the marine vessel while the power source is limited to the finite capacity. The method further includes analyzing with a control system the usage plan in view of the usage model and generating a projected performance of the power source, wherein the projected performance indicates the ability of the power source to supply the power needed by the devices while operating the marine vessel according to the usage plan.

An efficient system and method for usage, storage, and sharing of electrical energy with buildings, vehicles, and power grid distribution equipment. More specifically, a microgrid power system and method of use that interconnects an electric vehicle with a home grid-based power system for optimized energy management of the combined power sources.

A computing device can generate predictions for future consumptions for one or more buildings based on a variety of factors. The factors can include a local climate corresponding to each building, a mass and heat transfer for each building, a daily operation for each building, and an occupancy behavior for each building. A power flow can be determined for one or more power generators. The power flow can be determined based on the predictions of future consumption. A control input vector can be determined for the one or more buildings.

The present invention relates to an energy management method for an energy system (1) in a building. The energy system (1) comprises a plurality of uncontrollable energy consumers (HH), at least one controllable energy consumer (WP), an energy storage device (BAT), a net connection point (NAP) through which energy can be drawn from the net and/or fed into the net, and a feedback-control or control device (EMS) which is designed to feedback-control or control the at least one controllable energy consumer (WP) and the energy storage device (BAT). The plurality of uncontrollable energy consumers (HH) is configured to draw energy from the net or from the energy storage device (BAT). The method comprises the following steps: detecting a current state of charge (SOC.sub.act) of the energy store device (BAT), defining a period of time (ΔT.sub.0) during which the uncontrollable energy consumers (HH) are supplied with energy from the energy storage device, determining a limit value (SOC.sub.high) of the state of charge of the energy storage device (BAT) on the basis of a determined minimum energy demand of the plurality of uncontrollable energy consumers (HH) up to the time of charging (T.sub.0), operating the at least one controllable energy consumer (WP) with energy from the energy storage device (BAT) if the current charge state (SOC.sub.act) of the energy storage device (BAT) is greater than the determined limit value (SOC.sub.high) of the charge state and operating the at least one controllable energy consumer (WP) with energy from the net if the current charge state (SOC.sub.act) of the energy storage device (BAT) is less than or equal to the determined limit value (SOC.sub.high) of the charge state.

Embodiments of the disclosure relate to methods and systems for modeling, controlling and computer-platform implementation of a Synthetic Reserve Provisioning System (SRPS) needed to aggregate and integrate small devices closer to consumers, referred to as Distributed Energy Resources (DERs). This know-how is based on data-driven physics-based modeling and it supports the dispatch and scheduling of DERs so that they can participate in system level provision of electricity service. An SRPS generally comprises multiple levels of consumer aggregators (Synthetic Reserve Provisioning (SRP) modules) which interact by exchanging well-defined information about provable consumer characteristics and their own loading and pricing conditions. Three different SRPS designs are described. They differ with respect to implementation requirements for communications, control, technical and economic risks assumed by different SRP modules. Depending on the control and available communication architecture, it is ultimately possible to ensure DER integration at value, even with a limited number of participating devices.

A practical method for short-term operations of large-scale hydropower plants divides all hydropower plants into three categories using operation characteristics such as system hierarchy, space attributes, task requirements, and schedule particularity. A strategy for adjusting spillage based on peak-shaving response and a strategy for equal load reduction in off-peak hours check and adjust power generation of hydropower plants with specified dispatching modes. For medium- and small-sized cascaded hydropower plants, the load distribution among plants is optimized with an objective of minimizing total power release subject to control condition of total generation profile. For large-size cascaded hydropower plants, an optimization model for peak-shaving operations and a method for balancing power plants with equal load rate are combined to respond to system peak demands and guarantee power balance in all periods.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for shaping compute load using virtual capacity. In one aspect, a method includes obtaining a load forecast that indicates forecasted future compute load for a cell, obtaining a power model that models a relationship between power usage and computational usage for the cell, obtaining a carbon intensity forecast that indicates a forecast of carbon intensity for a geographic area where the cell is located, determining a virtual capacity for the cell based on the load forecast, the power model, and the carbon intensity forecast, and providing the virtual capacity for the cell to the cell.

A method for increasing a battery life of a rechargeable battery, the method performed on a system having a renewable energy resource, a rechargeable battery, a battery charger for charging the rechargeable battery, and a load, the method comprising the steps of forecasting a power production of the renewable energy resource and a power consumption of the load for a future time period, determining a net power between a value of the forecasted power production and a value of the forecasted power consumption, and charging the rechargeable battery during a given time period, such that a charging power is lower than the determined net power when the determined net power is positive.

A power control system and method for suppressing purchase power peaks or controlling surplus power household consumption according to changes. The power control system comprises a monitoring unit, an electricity storage quantity acquisition unit, and an electricity storage controller. The monitoring unit monitors a generated power quantity which an electricity generator generates using renewable energy and a purchase power quantity which a consumer purchases via a power grid. The electricity storage controller executes processes of discharging power from an electricity storage cell if the purchase power quantity is greater than or equal to a first threshold value; charging the storage cell if the generated power quantity is greater than zero and the purchase power quantity is less than or equal to a second threshold value less than the first threshold value; and charging and discharging the storage cell such that the acquired electricity storage quantity reaches a target value.

A system and method of tracking energy usage is disclosed. The system utilizes a variety of tools including periodicity and normalizing of data based on weather and building usage, to obtain more accurate and relevant energy and utility data. This allows the user to more readily find and locate energy waste, which allows the user to remedy the waste event. This reduces energy and utility costs.