A method for offsetting power used by an air conditioning system coupled to an AC power grid at a point of common coupling (PCC), the method including: receiving a point of common coupling (PCC) setpoint, a charge limit, a discharge limit and a power demand of the first unit; selecting an operating mode from the following operating modes: a normal mode during which a first unit of the air conditioning system is powered by only the AC power grid; a charging mode during which the first unit of the air conditioning system is powered by only the AC power grid and an energy storage device is charged, a discharging mode during which the first unit of the air conditioning system is powered by both the AC power grid and the energy storage device.

The present disclosure relates to a battery system supporting a plurality of operation modes according to the SoC. To this end, the battery system is characterized by comprising: one or more batteries supporting multiple operation modes for power storage or supply according to the state of charge (SoC); and a controller which determines an operation mode of the batteries among the plurality of operation modes according to the power supply state of a grid and the SoC of the batteries, wherein the batteries include a battery supporting an uninterrupted power supply (UPS) mode at an SoC at or below a first standard.

A power system supervisory control apparatus, a power system supervisory control system, and a power system supervisory control method for reducing social cost and improving resilience of a power system are provided. The power system supervisory control apparatus including multiple renewable energy power supplies includes: a system influence degree evaluation section that evaluates a system influence degree when a renewable energy fluctuation or an assumed fault has an influence on the power system by using, as computation conditions, system data for obtaining a state of the power system, renewable energy fluctuation data indicative of a fluctuation of a power generation output, and assumed fault data of an assumed fault in the power system, and calculates system influence degree evaluation result data; a computation condition selection index calculation section that calculates a selection index for the computation conditions; and a condition selection section that selects the computation conditions.

A battery swapping system includes: a transformer, a power conversion system, a bus apparatus, a control apparatus, and a plurality of battery swapping compartments, where the plurality of battery swapping compartments are connected to the power conversion system through the bus apparatus; the power conversion system is connected to an external power grid of the battery swapping system through the transformer; the control apparatus is connected to the plurality of battery swapping compartments; the plurality of battery swapping compartments are configured to store a plurality of traction batteries; and the control apparatus is configured to control a first target traction battery to transmit electric energy to the power grid, and is further configured to control a second target traction battery to acquire electric energy from the power grid.

A system and method for managing power analysis and power allocation in a high density computing environment. The system includes at least one edge computing device that receives power budget information from at least one high density computing workload scheduler, at least one power quality monitor that collects power quality measurements across three-phase power distribution, at least one programmable relay with at least one adjustable threshold, and at least one process controller that adjusts the at least one threshold of the at least one programmable relay based on at least one of the power budget information and the power quality measurements.

Disclosed is a coordinated peak shaving optimization method for a plurality of power supplies based on a fluctuation characteristic of a renewable energy source, including the following steps: s1: determining a weekly generated electricity quantity of hydropower based on an available capacity and a storage capacity of an electricity quantity; s2: predicting a renewable energy power generation curve and a load curve of a system weekly; s3: determining a start point of peak shaving of the hydropower based on an external transmission curve, the renewable energy generation curve, and the load curve of the system and a generating capacity of the hydropower; s4: determining a weekly peak shaving demand of the system; and s5: establishing an optimization model with a maximum peak shaving demand. The present disclosure proposes a reasonable arrangement for peak shaving, so as to resolve an accommodation problem caused by large-scale access of a renewable energy source.