IoT-based optimization of microgrid operation

The incremental ramifications in the electrical system, such as high peak demand, renewable energy penetration levels, and frequency fluctuations, made an urgent need for innovative technology and hence the microgrid. This paper proposes an IoT-based optimum operation of a microgrid model. The microgrid is equipped with several residential loads, a photo-voltaic farm (PV), electric vehicles (EVs), and energy storage system (ESS) in a grid-connected mode. The model is validated through two scenarios. First, the model is simulated excluding the ESS, while the other components were involved. The generation/load forecast is then estimated via Neural Network Fitting. Thereafter, in the second scenario, the optimized ESS is included. The utility grid power and frequency measurement are monitored in each scenario as an indication of the microgrid stability and optimum operation, and the differences between the two scenarios are assessed.