A review of optimization approaches for hybrid distributed energy generation systems: off-grid and grid-connected systems
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Date
2018
Authors
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Publisher
Sustainable Cities and Society
Abstract
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
A review of optimization approaches for hybrid distributed energy generation
systems: off-grid and grid-connected systems 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.
Description
Keywords
Hybrid DEG systems, Optimization techniques, Off-grid systems, Grid-connected systems
Citation
Twaha S, Ramli MAM, A review of optimization approaches for hybrid distributed energy generation systems: off-grid and grid-connected systems, Sustainable Cities and Society (2018), https://doi.org/10.1016/j.scs.2018.05.027