This method determines a microgrid's capacity by applying a load, measuring current through an integrated energy storage device, and deciding capacity on the basis of the device's charging status.

Microgrids are localized grid systems that can function independent of a traditional grid. Ensuring their efficiency and efficacy depends on accurately predicting their capacity. An inaccurate capacity reading can disrupt microgrid-dependent operations and lead to inefficiencies in power usage, adding to operational complications. Current approaches for estimating microgrid capacity tend to rely heavily on energy storage device readings. However, these methods often overlook the fluctuating nature of power-consumption patterns, leading to imprecise results. An effective solution is needed to minimize the likelihood of inaccurate readings that can adversely impact effective power distribution and overall electricity consumption.

Technology Description

This novel methodology for determining the capacity of a microgrid entails applying a current test load to the microgrid and measuring the current flowing through an energy storage device integrated with the microgrid. The test load helps to ascertain the device's charging status. Further, the method incorporates figuring the capacity if the measured current indicates that the energy storage device is discharging. This capacity is the current load applied to the microgrid through previously activated power outlets and a test load prior to the current test load. The technology is differentiated by its unique approach to microgrid capacity determination. Unlike traditional methods, this approach systematically combines load application, current measurement, and analysis of charging status to accurately establish the microgrid's capacity. This methodology can help manage microgrids more effectively by adjusting power distribution and usage on the basis of the determined capacity.

Benefits

  • Enables accurate microgrid capacity prediction, leading to better power distribution and usage
  • Uses an integrative approach to account for fluctuating power consumption, thus improving accuracy
  • Enhances the reliability and efficiency of microgrids
  • Helps optimize energy consumption, leading to cost savings for energy companies and microgrid-dependent entities
  • Helps relief organizations efficiently manage power distribution to affected areas during emergencies

Potential Use Cases

  • Energy companies can utilize this technology to optimize microgrid management and improve efficiency
  • Industries relying on self-contained power systems can ensure consistent power supply through accurate capacity readings
  • In remote areas where access to the main grid is limited, this technology ensures better electricity distribution management through microgrids
  • Research facilities or universities managing their independent microgrids can utilize this method for better power management
  • In disaster-hit or war-torn areas, emergency relief organizations can use the method to effectively manage power distribution through deployed microgrids