In a world increasingly focused on sustainability and energy independence, a groundbreaking review published in *Applied Sciences* (translated from Polish as *Applied Sciences*) is shedding light on how advanced modeling and simulation tools could revolutionize Smart Local Energy Systems (SLESs) and even pave the way for closed ecological systems (CES) and life support systems (LSSs). Led by Andrzej Ożadowicz from the Department of Power Electronics and Energy Control Systems at AGH University of Krakow, the research delves into the evolving landscape of microgrids and their potential applications beyond Earth.
The study highlights the growing complexity of SLESs, which integrate buildings with distributed energy resources and storage. “As these systems become more decentralized and interconnected, the need for sophisticated modeling and simulation tools becomes paramount,” Ożadowicz explains. These tools are essential for addressing multi-domain integration, predictive control, and smart automation, all of which are critical for optimizing energy efficiency and reliability.
One of the most intriguing aspects of the review is its exploration of CES and LSSs—environments designed to sustain human life through autonomous recycling of air, water, and other resources. “Concepts developed for building and energy systems, such as demand-side management, IoT-based monitoring, and edge computing, can be adapted to these contexts, which demand isolation, autonomy, and high reliability,” Ożadowicz notes. This opens up exciting possibilities for applications in space exploration and remote terrestrial environments.
The research also addresses the challenges of model integration, simulation scalability, and the bidirectional transfer of technologies between Earth-based and space systems. “The potential for these technologies to shape future energy infrastructures—both on Earth and beyond—is immense,” Ożadowicz says. The study concludes with a SWOT analysis and a roadmap for future research, laying the foundation for developing sustainable, intelligent, and autonomous energy systems.
For the energy sector, the implications are significant. The ability to model and simulate complex energy systems with high precision can lead to more efficient and resilient energy networks. This could translate into cost savings, improved reliability, and enhanced sustainability for commercial and industrial applications. As the world moves towards a more decentralized and interconnected energy future, the insights from this research could be instrumental in shaping the next generation of energy solutions.
In summary, Ożadowicz’s review not only advances our understanding of SLESs but also opens up new avenues for innovation in closed ecological and life support systems. As the energy sector continues to evolve, the tools and methodologies highlighted in this research could play a pivotal role in driving progress and achieving sustainability goals.