A recent study led by Kang Ligai from the School of Civil Engineering and Architecture at Hebei University of Science and Technology has unveiled a new optimization method for combined cooling, heating, and power (CCHP) systems that incorporate renewable energy sources. Published in the journal Science and Technology for Energy Transition, this research is particularly significant as it addresses the growing need for low-carbon energy solutions.
CCHP systems are designed to efficiently utilize energy for heating, cooling, and electricity generation. When coupled with renewable energy sources like solar and wind, these systems can significantly reduce carbon emissions and enhance energy efficiency. However, the challenge lies in optimizing the performance of these systems when integrating different types of renewable energy.
In this study, Kang Ligai and his team employed a long short-term memory (LSTM) network to predict the output of renewable energy. They then utilized the Non-dominated Genetic Sorting Algorithm (NSGA-II) to generate Pareto frontiers, which are crucial for understanding the trade-offs between different optimization objectives. The final decision-making process involved analyzing the distance between superior and inferior solutions using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).
The results were promising. The research indicated that a CCHP system integrating photovoltaic (PV) panels and solar thermal (ST) collectors outperformed other configurations, such as those using photovoltaic-photovoltaic-thermal integrated devices. Furthermore, the addition of wind turbines to the PV and ST system demonstrated potential for further performance enhancement.
This study opens up commercial opportunities in the energy sector by showcasing the effectiveness of combining various renewable technologies. As businesses and municipalities look to transition towards sustainable energy solutions, the findings highlight the importance of optimizing CCHP systems to maximize efficiency and reduce costs. Companies involved in renewable energy installations and energy efficiency technologies can leverage these insights to develop more effective systems that align with global carbon reduction goals.
Kang Ligai emphasized the significance of their findings, stating, “The optimization of CCHP systems with renewable energy not only improves performance but also contributes to a sustainable energy future.” As the demand for low-carbon solutions continues to rise, the methodologies developed in this research could play a crucial role in advancing the energy sector.
For more information about Kang Ligai’s work, you can visit the School of Civil Engineering and Architecture at Hebei University of Science and Technology.
