Smart Renewable Energy Management System for Consumer Applications

Due to the benefits of Smart Grid Technology and renewable energy systems, consumer demand for a controller design that allows effective integration of these two systems has been growing over the last few years. This article proposes a new controller designed with the objective of increasing efficiency and reliability of a consumer's renewable energy system. It describes the system model design and data selection, as well as the controller considerations and design method. The model subsystems are designed either as raw real world data, formulated models based on real world data as reasonable approximations, or as models that allow for proper testing of the system under relevant abnormal conditions and limitations. The controller is designed while considering the necessary flexibility to accommodate a wide variety of subsystems and the need for correct behavior for normal and abnormal states. The applied methods include frequency pattern analysis, forecasting, probability estimation, payoff estimation, expected value calculation, and neural-state-space modeling. For the analysis, a comparison to alternative non-controlled methods has been conducted to determine the relative performance of the controller in terms of energy efficiency, reliability, and monetary savings. The results of the analysis show that the controller did not reduce energy losses, but is reliable with respect to performance under blackout and cyber-attack conditions, and offers at least an 8% savings on energy expenses and as much as 25% of the expected profit from immediately selling excess renewable energy.