The efficiency of Concentrated Solar Power (CSP) plants strongly depends on steam condensation temperatures. Current cooling systems, either wet (water-cooled) or dry (air-cooled), present trade-offs. Wet cooling towers (WCT) optimize performance but raise concerns due to substantial water usage, especially in water-scarce prone locations of CSP plants. Dry cooling conserves water but sacrifices efficiency, specially during high ambient temperatures, coinciding with peak electricity demand. A potential compromise is a combined cooling system, integrating wet and dry methods, offering lower water consumption, improved efficiency and flexibility. Incorporating such systems into CSP plants is of considerable interest, aiming to optimize operations under diverse conditions. This research focuses on the first step towards this goal; developing static models for WCTs. Two approaches, Poppe and Artificial Neural Networks (ANN), are developed and thoroughly compared in terms of prediction capabilities, experimental and instrumentation requirements, sensitivity analysis, execution time, implementation and scalability. Both approaches have proven to be reliable, with Poppe providing better results, based on MAPE, for the outlet temperature and water consumption (0.87 % and 3.74 %, respectively) compared to a cascade-forward ANN model (1.82 % and 5.21 %, respectively). However, for the target application, the better execution time favours the use of ANNs.

Combined Cooling Systems constitute a promising strategy to reduce water consumption in Concentrated Solar Power plants. This paper addresses the comparative evaluation of two different theories based on physical equations (Poppe and Merkel) and three correlations, including a novel and unreferenced one, to predict the performance and water consumption of a wet cooling tower for heat rejection in Concentrated Solar Power plants. Sixteen sets of experiments were conducted in a fully instrumented pilot plant of combined cooling systems to assess the thermal performance of the cooling tower. Key findings indicate accurate prediction of cooling tower outlet water temperature by both Poppe and Merkel theories, as well as the three correlations, with minimal differences, less than 0.94 °C (2.78%), corresponding to values of R2 = 0.9918 and RMSE = 0.4650. When considering all key variables for CSP performance, the three correlations under comparison exhibited comparable prediction accuracy. This study recommends the combination of the Poppe theory with the correlation ṁw and ṁa, which accounts for air and water mass flow rates independently. This combination demonstrated reasonable accuracy in predicting the outlet water temperature and the water consumption, with average differences of 0.14 °C and 0.01 kg s−1, respectively. These differences correspond to percentage variations of 0.91% and 9.21% for the previously mentioned variables. This study provides valuable insights for the modelling and analysis of combined cooling systems integrated in CSP plants, advancing beyond previous efforts in the literature.

Repository that contains experimental data obtained from a Wet Cooling Tower (WCT) plant located at Plataforma Solar de Almería. A total of 132 steady-state experimental points have been obtained thanks to the thorough experimentation conducted. These data cover a large variety of ambient conditions (different seasons, days and nights) and thermal loads (from 27 kW to 207 kW).

Water reduction in refrigeration circuits, such as those in Concentrating Solar Power plants and in Solar Thermal Desalination systems is becoming a hot topic since the implementation of these systems is more common in arid areas. Because of their highest conversion efficiency, wet cooling systems have traditionally been preferred. However, their main drawback is the large water consumption. On the contrary, dry cooling systems do not require water but they consume much more electricity and have higher capital costs. Combined cooling systems (CCS) are proposed as a possible solution to overcome the problems of only-dry and only-wet cooling systems due to their operation flexibility depending on the ambient and operating conditions. The most common CCS configuration is the one that considers an Air Cooled Condenser (ACC) in parallel with a wet cooling tower (WCT) connected to a surface condenser (ACC+SC-WCT). This work presents the experimental assessment of this kind of CCS in terms of water and electricity consumption reduction in comparison with the only-wet and only-dry methods. Tests have been performed at a pilot plant at Plataforma Solar de Almería.

El uso de captadores solares planos está muy extendido principalmente para aplicaciones de calefacción y refrigeración de edificios y agua caliente sanitaria. Una de las líneas de investigación para mejorar el rendimiento térmico y reducción de espacio ocupado es el uso de reflectores que permiten incrementar la radiación solar incidente sobre la cubierta de los captadores. Aunque el modelado de este tipo de sistemas está ampliamente estudiado, es importante disponer de modelos sencillos pero fiables que permitan el diseño y evaluación de lazos de control. En este artículo se presenta una modificación de un modelo de parámetros concentrados para estimar la temperatura de salida del fluido cuando se dispone de espejos reflectores con seguimiento solar. Calibrando un valor medio de los parámetros de pérdidas ópticas en torno al mediodía solar, los resultados obtenidos muestran que el error cuadrático medio es menor def 0.79 °C².

The effectiveness of Concentrated Solar Power (CSP) plants is significantly influenced by the temperatures at which steam condensation occurs. The existing cooling systems, whether wet (water-cooled) or dry (air-cooled), involve trade-offs. Wet cooling enhances performance but raises concerns due to substantial water usage, particularly in water-scarce regions where CSP plants are often located. On the other hand, dry cooling conserves water but at the cost of reduced efficiency, especially during high ambient temperatures that coincide with peak electricity demand. A possible compromise solution involves a combined cooling system that integrates both wet and dry methods, providing flexibility for overall reduced water consumption and enhanced efficiency.The incorporation of such systems into CSP plants is thus of great interest, owed to the potential adaptability of its operation to changing conditions. In order to make this optimally and feasible, a suitable control system needs to be developed. In this work we present the first implementation, in a real pilot plant, of a two-layer hierarchical control strategy, where the upper layer solves a multi-objective optimization problem for conflicting water and electricity consumptions, and a regulatory PID-based control layer adapts the system operation to the generated optimal references.

One of the challenges related to solar thermal power plants is the high water consumption, which mainly comes from the cooling process of the power cycle. Combined cooling systems are presented as a potential solution to reduce water consumption, while also avoiding a high penalty due to efficiency loss in the power block. This paper analyzes the application of optimization strategies for a combined cooling system in order to evaluate the most suitable operating configuration according to different operating and environmental criteria. For this purpose, it has been necessary to carry out an exhaustive experimental campaign in a pilot plant at Plataforma Solar de Almer´ıa - CIEMAT, in order to train and obtain models based on neural networks. The potential of the optimization strategy is analyzed by simulating different case studies.