Advanced energy management strategy for microgrid using real-time monitoring interface

Recently, the integration of renewable energy sources in microgrids has seen a significant rise due to their attractive prices, reliability etc. However, besides the techno-economic benefits, the renewable energy sources are intermittent, and the high penetration of renewable sources into the microgrid poses design and operation challenges. Indeed, an efficient energy management strategy (EMS) is required to govern power flows across the entire microgrid. This paper introduces an advanced EMS design with a real-time monitoring interface for the effective operation of the hybrid microgrid and data analysis. The proposed advanced EMS model uses a realtime monitoring interface, and it provides the optimum operation and control in terms of balanced power supply and voltage profile with stable frequency. We designed the microgrid, which comprises hybrid sources such as solar and wind power sources, Li-ion battery storage system, backup electrical grids, and AC/DC loads, considering the functional constraints of a microgrid energy management and stability. In addition, the battery energy storage is effectively managed through the performance control of battery charging and discharging using an efficiency controller. The proposed system control is based on the optimum power supply of loads through the available renewable sources and the battery State of Charge (SOC). The microgrid measurement data is transmitted through the Python platform and a graphical user interface (GUI) software developed for data analysis. The simulation results using Matlab Simulink and Python platforms demonstrate the relevance and effectiveness of the proposed EMS and monitoring interface for the stable and reliable operation of the developed hybrid microgrid.

Automated summary

This paper introduces an advanced energy management strategy with a real-time monitoring interface for the effective operation and data analysis of a hybrid microgrid. The proposed model provides optimal operation and control in terms of power supply balance, voltage stability, and frequency stability. By optimizing the supply from renewable sources and battery charging status, the best power supply for loads is achieved.