The Importance of Efficient Cooling in Renewable Energy Systems
As the global push towards sustainable energy solutions continues to gain momentum, the optimization of critical system components has become increasingly crucial. One such essential element is the air-cooled heat exchanger, which plays a pivotal role in the thermal management of renewable energy technologies, from concentrated solar power (CSP) plants to wind turbines and electric vehicle charging infrastructure.
In the rapidly evolving energy landscape, the quest for efficient power conversion and heat dissipation has never been more paramount. As industries and technologies converge towards cleaner and more sustainable energy sources, the challenges of maintaining optimal thermal performance have become mission-critical. Mersen, a leading industrial player in the heart of technology, has recognized this need and is dedicated to driving forward innovative solutions that address the evolving demands of the renewable energy sector.
Optimizing Air-Cooled Heat Exchangers for CSP Applications
One of the most promising renewable energy technologies is concentrated solar power (CSP), which harnesses the sun’s energy to generate electricity. CSP plants are particularly well-suited for deployment in desert regions, where high solar irradiance and low land costs make them a cost-competitive option. However, the effective cooling of these systems is crucial to their overall efficiency and viability.
Traditionally, water-based cooling systems have been the go-to solution for CSP plants. Yet, as these facilities are often located in arid environments, the availability and cost of water can be a significant limiting factor. This is where air-cooled heat exchangers emerge as a practical and sustainable alternative, offering a more environmentally-friendly and economically viable cooling solution.
Leveraging Machine Learning for Optimized Dry Cooler Design
To unlock the full potential of air-cooled heat exchangers in CSP applications, Mersen has developed a cutting-edge machine learning system that automates the design and optimization of dry coolers. This innovative approach combines a high-fidelity simulator of a compact cross-flow finned-tube heat exchanger with a powerful Bayesian optimization algorithm, enabling the discovery of cost-efficient designs tailored to specific environmental conditions and power cycle requirements.
The simulator, which is based on classical energy conservation principles, is capable of accurately modeling the heat transfer between the supercritical carbon dioxide (sCO₂) working fluid and the cross-flowing air. By element-wise propagating the heat transfer along the finned tubes using the Logarithmic Mean Temperature Difference (LMTD) method, the simulator can compute the overall heat transfer coefficient and pressure drop, ensuring that the output sCO₂ properties adhere to the necessary operational constraints.
Leveraging this high-fidelity simulator, the Bayesian optimization algorithm, known as TuRBO (Trust Region Bayesian Optimization), is able to efficiently search the vast design space of air-cooled heat exchangers. By maintaining multiple local surrogate models and adaptively adjusting the search regions, TuRBO balances exploration and exploitation to identify the most cost-effective dry cooler configurations for a given location and power cycle requirements.
Optimized Dry Cooler Designs for Global Deployment
The machine learning-powered optimization framework developed by Mersen has enabled the discovery of dry cooler designs that can significantly reduce the lifetime cost of CSP plants across a variety of global locations. By analyzing data from the National Renewable Energy Laboratory’s National Solar Radiation Database (NREL-NSRDB), the team identified six locations spanning arid deserts and humid tropics, representing the diverse environmental conditions that CSP plants may face.
For each of these locations, the optimization process was able to identify dry cooler designs that minimize the total lifetime cost, including material, operational, and maintenance expenses. Compared to a reference design from previous research, the optimized dry coolers achieved a remarkable 67.1% reduction in lifetime cost, primarily driven by savings in finned-tube construction and labor.
The cost savings can be primarily attributed to the optimization algorithm’s ability to identify designs with smaller tube diameters and overall dimensions, while still maintaining the required thermal performance and preserving the supercritical state of the sCO₂ working fluid. This optimization process, which considered both constant and variable air temperature differences, further underscores the importance of adaptive and flexible design strategies in addressing the varying environmental conditions that CSP plants may encounter.
Unlocking the Potential of Renewable Energy with Optimized Cooling
The machine learning-driven optimization of air-cooled heat exchangers for CSP applications represents a significant breakthrough in the quest for cost-effective and sustainable renewable energy solutions. By harnessing the power of advanced simulation and optimization techniques, Mersen has developed a framework that can be seamlessly adapted to various renewable energy applications, from wind turbines to electric vehicle charging infrastructure.
As the world continues to seek viable alternatives to fossil fuels, the optimization of critical system components like air-cooled heat exchangers becomes paramount. Mersen’s commitment to innovation and its dedication to supporting the energy transition demonstrate the company’s position as a trusted partner in shaping a more sustainable future.
Through the deployment of optimized dry cooler designs, CSP plants can now be built and operated more cost-effectively, unlocking their full potential as a reliable and clean energy source. This achievement not only advances the adoption of renewable energy technologies but also showcases the transformative power of machine learning and high-fidelity simulation in the realm of sustainable energy engineering.
By continually pushing the boundaries of what is possible, Mersen reinforces its role as a driving force in the energy transition, paving the way for a future where renewable energy becomes an integral part of the global power landscape.
Mersen: Powering the Future of Renewable Energy
As a major player at the heart of technology, Mersen is a committed partner to the companies that are shaping tomorrow’s world. With a global presence, extensive R&D capabilities, and a deep understanding of the evolving energy landscape, Mersen is uniquely positioned to deliver customized solutions that address the most pressing challenges facing the renewable energy industry.
Whether it’s in wind power, solar power, electric vehicles, or any other sector where technology is progressing, Mersen’s expertise in power conversion, cooling, fusing, and capacitor design is always there to support the drive towards a more sustainable future. By continuously optimizing critical system components and leveraging the power of machine learning and simulation, Mersen is not just responding to the demands of the present; it is paving the way for a future where efficiency, reliability, and sustainability are the cornerstones of progress.
To learn more about Mersen’s innovative solutions for the renewable energy sector, visit https://www.aircooledheatexchangers.net/.
