Optimal Energy Management of an Autonomous Hybrid Energy System

The rising operating cost of power systems and over-utilization of fossil fuel deposits have led to continuous energy scarcity and a wide gap between energy demand and supply. These pose critical challenges across the world. The renewable energy sources (RESs) provide a viable and sustainable energy alternative which is capable of meeting the exponential energy growth, reducing over-dependency on fossil fuels as well as minimizing global warming. This paper presents an optimal control and management of an autonomous hybrid energy system (AHES) that reliably supplies energy demand at a minimum daily operating cost. The non-linear cost function is formulated as a mixed integer nonlinear programming (MINLP) problem to optimize the use of renewable resources and minimize the utilization of diesel generator (DG). The unpredictability inherent in RESs is addressed through the optimal design and management of multiple energy generation sources, and battery storage system (BSS). The MINLP optimization technique employed is validated with a dynamic commercial daily load profiles. The simulation results show that the proposed hybrid system significantly minimizes daily operating cost and improves supply reliability when compared to DG-single system.