Intelligent Real-Time Utilization of Hybrid Energy Resources for Cost Optimization in Smart Microgrids

With ever-depleting fossil fuels and significant increase in the carbon footprint worldwide, efficient utilization of renewable energy sources plays an important role. Installation of solar rooftops and photovoltaic panels is getting a broader response, even in residential and commercial buildings. However, at the same time, it is of paramount importance to manage the appliances in these buildings according to the local energy generated from these renewable sources to obtain a better supply-demand ratio. We address this problem by proposing a coordinated scheduling approach for flexible devices and the optimal usage of heterogeneous energy sources to minimize the energy drawn from the main grid and thereby reduce electricity costs for the users. We present a mixed-integer linear programming formulation for the problem and solve it optimally using Gurobi optimizer. Moreover, we also propose a set of efficient heuristic algorithms that consider the predicted renewable energy and price information to obtain the solutions efficiently for a large dataset. The results obtained show that the proposed algorithms deviate within 2.28%-18.47% from the optimal solutions in various settings, depicting their capability to be implemented in a real-world system.