Multi-Objective Optimization of a Hybrid Renewable Energy System for a Remote Mobile Telecommunication Station

Hybrid renewable energy systems (HRESs) are increasingly used because they integrate diverse energy resources whose availability can complement one another over the day–night cycle. However, the high cost of system components, particularly batteries, and the dependence of energy generation on weather conditions can undermine their economic viability. Researchers, therefore, seek to optimize HRES configurations to achieve a balance between reliability and lifecycle cost by performing techno-economic studies using different techniques. One of the industries that started relying more on renewable energy is the mobile telecommunication industry, especially in the remote stations where the expansion of the grid is expensive and the renewable resources are abundant. This study introduces the scope of hybrid renewable energy system optimization and applies a study case to a remote telecommunication station where the existing energy system was installed without prior techno-economic assessment. Using mathematical models, single and multi-objective (lexicographic) optimizations are conducted using the particle swarm optimization algorithm and a deterministic exhaustive search numerical algorithm, to minimize the lifecycle cost of the system, maintain reliability for a full continuity of service, and reduce the dependency to the diesel generator to contribute to the decarbonization objective of the world. The computational results show a significant reduction in the cost of the system from USD 525,512.83 for the existing system to approximately USD 197,879.03 (reduction of 62.3% of the actual cost), and the operating hours of the diesel generator from 1401 h/year to 770 h/year. More details are presented in the Discussion section.