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Abstract The need to increase energy system flexibility, alongside the need to lower fossil fuel use in the food sector, and the importance of refrigeration infrastructure presents an opportunity for Liquid Air Energy Storage (LAES) integrated with refrigerated warehouses. To quantify this opportunity in Europe we analyse energy scenarios and existing refrigeration infrastructure for four countries with diverse energy systems (UK, Spain, Bulgaria and Germany). We find that with growing levels of electricity generation from variable renewable sources and numerous refrigerated warehouses, LAES has the potential to provide value in many areas of the EU through the 2020s. However, LAES is still pre-commercial, and with the proportion of electricity from variable renewable sources still low in many countries it is likely that LAES will not be deployed widely alongside refrigerated warehouses under current market conditions. Countries such as the UK and Spain, which have the greatest need for additional energy system flexibility and the most refrigerated warehouses are likely to gain the most value initially.

The global increase in energy demand and exponential exhaustion of fossil recourses has favored the development of new systems of electricity production. Photovoltaic solar energy is undoubtedly one that has the highest application in housings, due to its simplicity and easy implementation. In this work, a new prototype of photovoltaic solar tracker with Arduino platform was developed. Feedback control system that allows carrying out solar tracking with two axes using a stepper motor and linear actuator was established through an electronic circuit based on photodiodes. Moreover, real construction of the prototype was carried out, where the effectiveness of the design and its capacity to draw a maximum benefit of an incident radiation can be observed, placing the panel perpendicularly to the received energy and improving its performance for its application in future installations in housings. Results obtained from the comparison between the developed prototype and a static panel oriented according to the latitude of the area, show about 18% energy gain.

Summary of modifications delivered to the shemaorg standard for energy M18

[Abstract] This research work presents an artificial intelligence approach to predicting the hydrogen concentration in the producer gas from biomass gasification. An experimental gasification plant consisting of an air-blown downdraft fixed-bed gasifier fueled with exhausted olive pomace pellets and a producer gas conditioning unit was used to collect the whole dataset. During an extensive experimental campaign, the producer gas volumetric composition was measured and recorded with a portable syngas analyzer at a constant time step of 10 seconds. The resulting dataset comprises nearly 75 hours of plant operation in total. A hybrid intelligent model was developed with the aim of performing fault detection in measuring the hydrogen concentration in the producer gas and still provide reliable values in the event of malfunction. The best performing hybrid model comprises six local internal submodels that combine artificial neural networks and support vector machines for regression. The results are remarkably satisfactory, with a mean absolute prediction error of only 0.134% by volume. Accordingly, the developed model could be used as a virtual sensor to support or even avoid the need for a real sensor that is specific for measuring the hydrogen concentration in the producer gas. Junta de Andalucía; 1381442 Xunta de Galicia; ED431G 2019/01 Ministerio de Universidades; FPU19/00930

Throughout the 21st century, urban reports demand solutions to the obsolescence and aging process suffered by the existing buildings, due to the growth and expansion of cities that took place in the second half of the 20th century [...]

In the current situation with the unprecedented deployment of clean technologies for electricity generation, it is natural to expect that storage will play an important role in electricity networks. This paper provides a qualitative methodology to select the appropriate technology or mix of technologies for different applications. The multiple comparisons according to different characteristics distinguish this paper from others about energy storage systems. Firstly, the different technologies available for energy storage, as discussed in the literature, are described and compared. The characteristics of the technologies are explained, including their current availability. In order to gain a better perspective, availability is cross-compared with maturity level. Moreover, information such as ratings, energy density, durability and costs is provided in table and graphic format for a straightforward comparison. Additionally, the different electric grid applications of energy storage technologies are described and categorised. For each of the categories, we describe the available technologies, both mature and potential. Finally, methods for connecting storage technologies are discussed.

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