GA-Based Permutation Logic for Grid Integration of Offshore Multi-Source Renewable Parks

This paper proposes and analyzes a genetic algorithm based permutation control logic applied to the aggregator of an offshore multi-source park. The energy losses at the common coupling point are accounted for in the feedback. This paper focuses on offshore distributed energy resources, such as floating photovoltaic (PV), wind, and wave power. The main contributions of this research are the development of a control system that is capable of tracking the set-point imposed by the demand curve for each source individually, the introduction of a capacity factor for combined offshore floating PV/wind/wave power farms, and the unveiling of pure offshore renewable sources as potential storage-less flexibility service providers. The results of a case study for a site near San Francisco showed that energy losses and capacity factors are positively influenced by implementing the proposed approach.

Automated summary

This paper proposes and analyzes a genetic algorithm based permutation control logic applied to the aggregator of an offshore multi-source park. The results show that implementing this approach can positively influence energy losses and capacity factors. The research also developed a control system capable of tracking the set-point imposed by the demand curve for each source individually and unveiled pure offshore renewable sources as potential storage-less flexibility service providers.