Source Network Load Storage Real-Time Monitoring Energy Management System

1.Descriptions

The new energy micro-grid energy management system can monitor the source, load, storage, vehicle and other equipment in the system in real time, and interact remotely with the charging cloud platform and energy storage cloud platform to maximize the use of distributed generation energy, ensure the optimal power quality and user economic benefits, and provide auxiliary response and collaborative scheduling services for the distribution network.

2.Specifications

1. Multi-purpose strategy parallel operation, intelligent decision-making, automatic adjustment.

2. Improve the power supply quality of the load through redundant design, accurate detection and high-speed control.

3. Graphical design is adopted to display the operation status of power distribution, power generation, power consumption, charging and discharging of the system in layers.

4. Comprehensively perceive the operation status of power grid, new energy generation, energy storage and load in the system.

5. Control and coordinate different types of equipment and systems, break information islands, and realize the unification of system monitoring and management.

3.Functions

1.Support centralized monitoring of multi-energy access and visually display the operation of distributed energy

2. Reasonably arrange the scheduling plan of distributed power supply and energy storage equipment within the scope of regulation, so as to maximize the overall operation economy of the system

3. Take advantage of the controllable characteristics and regulation ability of distributed power generation to participate in the power market to provide auxiliary services and demand-side response

4. Make full use of V2G technology to excavate the economic benefits of electric vehicle charging and discharging on the microgrid and the regulation and reserve function

5. Store real-time data, forecast data and operation logs as required, automatically count and form relevant reports

6. Use traditional algorithm and intelligent algorithm to predict the output capacity of new energy