Multi-objective manta ray foraging algorithm for efficient operation of hybrid AC/DC power grids with emission minimisation

The current paper presents a multi-objective manta ray foraging algorithm (MO-MRFA) for efficient operation of hybrid AC and multi-terminal direct current (MTDC) power grids. The multi-objective framework aims at achieving economical, technical and environmental benefits by minimising the total production fuel costs, minimising the transmission power losses and minimising the environmental emissions in the AC/MTDC transmission systems. The MRFA imitates three separate independent foraging organisations of the manta rays. It is updated incorporating an additional Pareto archive to preserve the non-dominated solutions. A dynamic adaptation of the fitness feature is employed by iteratively varying the form of the employed fitness function. Furthermore, a fuzzy decision-making technique is activated to finally pick the appropriate operating point of the AC/MTDC power grids. The proposed technique is compared with other reported algorithms in the literatures. The applications are conducted on three test systems. These systems are IEEE 30-bus, IEEE 57-bus test power systems in addition to real part of the Egyptian grid at West Delta region. Numerical results demonstrate that the proposed MO-MRFA has great effectiveness and robustness indices over the others. Nevertheless, the proposed MO-MRFA is successfully extracting several Pareto solutions that meet the techno-economic requirements with accepted environmental concerns.

Automated summary

The paper introduces a multi-objective manta ray foraging algorithm for hybrid AC and MTDC power grids. The algorithm aims to minimize production fuel costs, transmission power losses, and environmental emissions for economic, technical, and environmental benefits. It demonstrates effectiveness, robustness, and ability to extract multiple solutions that meet techno-economic and environmental requirements.