An IoT-Enabled Stochastic Operation Management Framework for Smart Grids

The idea of Internet of Things (IoT) has revolutionized the smart grids by providing the opportunity for remote control and monitoring of the distributed generations (DGs), switches, renewable sources and electrical loads. This study investigates the smart grid concept along with IoT in the automation and optimal energy management of these grids incorporating the high uncertainties of the renewable energy sources and plug-in hybrid electric vehicles (PHEVs) charging demand. A private blockchain technology is developed to make secure data transactions. A novel stochastic structure according to the scenario generation is developed to capture the power randomness of these sources. It is tried to assess the switching effect on the energy management based on remote control in the IoT bed. Moreover, a new optimizer using the social spider algorithm (SSA) is proposed which helps in scheduling the smart grid in an economic way. In addition, a modified method is developed which can suitably enhance the SSA convergence and thus get into more optimal switching and scheduling programs. The proposed model is investigated using an IEEE test system.