A review of optimization approaches for hybrid distributed energy generation systems: Off-grid and grid-connected systems

Distributed generation is a collective term that covers the generation of energy at micro level, distributed in a location near the end user by using renewable and nonrenewable distributed energy generation (DEG) resources including among others, solar, wind, hydro, geothermal and diesel generators. This paper presents a review on the optimization approaches for hybrid DEG systems, considering both stand-alone and grid-connected systems. There are several optimization techniques used on DEG systems, comprising of analytical and artificial intelligent (AI) and hybrid techniques. This work encompasses the selected journal papers published especially in the last five years. A brief background of the optimization approaches been highlighted, particularly identifying the most common techniques to give the basis for analysis of the approaches currently applied on hybrid DEG systems. The analysis shows that AI techniques are still dominating the techniques used for optimization of DEG systems, with particle swarm optimization (PSO) recognized as the most used AI method. The objective functions in the optimization of hybrid DEG systems are currently defined to maximize the reliability, to minimize the expected interruption cost, and to optimize operation schedule of DEG resources.