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Thermal performance of SS-PCM composites, simulating building envelope conditions, is difficult to asset with traditional laboratory equipment. However, in this work, the evaluation of three SS-PCM based on eutectic fatty acid mixtures of capric-myristic (CA/MA), lauric-myristic (LA/MA) and palmitic-stearic (PA/SA) was accomplished by a testing setup that allows to test samples in steady-state and dynamic conditions. Moreover, a SS-PCM-based acrylic plaster was evaluated as a fiber cement siding finish. The obtained values were used to calculate the thermal transmittance (U-value), heat storage capacity, and thermal inertia parameters under a simulated diurnal cycle. Results showed that the use of phase change materials in powder form increase thermal lag between 148% and 180% and present a decrement factor <0.2. Furthermore, building envelopes as fiber cement siding with a SS-PCM-based acrylic plaster coating decreased 20.8% the indoor temperature, increase 67.26% the thermal lag and decrease 9% of the decrement factor. The authors are pleased to acknowledge the financial assistance of the “Ministerio de Ciencia, Tecnología e Innovación-MINCIENCIAS” through the PhD grant 758-2016-Contract 036–2016, Universidad de Antioquia and Sumicol S.A.S. The work is partially funded by the Ministerio de Ciencia, Innovación y Universidades de España (RTI2018-093849-B-C31—MCIU/AEI/FEDER, UE) and by the Ministerio de Ciencia, Innovación y Universidades—Agencia Estatal de Investigación (AEI) (RED2018-102431-T). This work is partially supported by ICREA under the ICREA Academia programme. Dr. Cabeza would like to thank the Catalan Government for the quality accreditation given to her research group GREiA (2017 SGR 1537). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia.

Artículos en revistas Units within a control area, participating in the secondary frequency control, are usually spinning generating units already connected to the network and operating outside their range of optimal performance. This paper deals with an alternative method of providing secondary frequency control called rapid-start (RS). It consists in assigning a regulation band to several offline units (RS units) which are capable of being started and connected rapidly, therefore allowing the online units to function more closely to their nominal power. RS units have commonly been used for peaking generation and for tertiary control reserve, and have been rarely used for secondary control reserve. As RS operation may have economic benefits, since it allows for better dispatch of the other units in the control area, an appropriate algorithm to start up an RS unit needs to be developed. This paper proposes a machine learning based system (MLBS) to be employed in the decision to start up an RS unit while being used to provide secondary frequency control. The decision-making procedure is carried out by a decision tree. The building and implementation of the RS machine learning based system is illustrated for a secondary frequency control zone within the Spanish power system. info:eu-repo/semantics/publishedVersion

Decentralized detection in a network of wireless sensor nodes involves the fusion of information about a phenomenon of interest (PoI) from geographically dispersed nodes. In this paper, we investigate the problem of binary decentralized detection in a dense and randomly deployed wireless sensor network (WSN), whereby the communication channels between the nodes and the fusion center are bandwidth-constrained. We consider a scenario in which sensor observations, conditioned on the alternate hypothesis, are independent but not identically distributed across the sensor nodes.We compare two different fusion architectures, namely, the parallel fusion architecture (PFA) and the cooperative fusion architecture (CFA), for such bandwidthconstrained WSNs, where each sensor node is restricted to send a 1-bit information to the fusion center. For each architecture, we derive expression for the probability of decision error at the fusion center. We propose a consensus flooding protocol for CFA and analyze its average energy consumption. We analyze the effects of PoI intensity, realistic link models, consensus flooding protocol, and network connectivity on the system reliability and average energy consumption for both fusion architectures. We demonstrate that a trade-off exists among spatial diversity gain, average energy consumption, delivery ratio of the consensus flooding protocol, network connectivity, node density, and PoI intensity in CFA. We then provide insight into the design of cooperative WSNs.

Analysis of interdependencies in Electric Power Systems (EPS) has been recognized as a crucial and challenging issue to improve their trustworthiness. The recent liberalization process in energy markets has promoted the entry of a variety of operators in the electricity industry. The resulting new organization contributed to increase in complexity, heterogeneity and interconnection. This paper proposes a framework for analyzing EPS organized as a set of interconnected regions, both from the point of view of the electric power grid and of the cyber control infrastructure. The emphasis is on interdependencies and in assessing their impact on indicators representative of the QoS perceived by users. Taking a reference power grid as test case, the effects of failures on selected measures are shown, both in case the grid is partitioned in a number of regions and in case of a single region, to illustrate the behavior of different grid and control configurations.

In this study, air concentrations of BaP in two different seasons (winter 2015 and summer 2016) and BaP levels in ground vegetation from Tarragona County were used as control simulations performed with the WRF-CHIMERE air quality modelling system, in order to reproduce the incidence of that hazardous chemical in air and soils. The CTM was validated for the present climatology, showing a good ability to represent air and soil concentrations of BaP over the target domain (petrochemical, chemical, urban and background sites), particularly in the winter. Then, the variation of the BaP concentrations in air and soils were simulated for the time series 1996-2015 and for the climate change scenario RCP8.5 (2031-2050). While an increase is projected for the levels in air, particularly in chemical and remote sites where the variation can go up to 10%, in terms of soil deposition the findings are the opposite, with an evident decrease in soil BaP concentrations, particularly for background sites. Finally, a potential health effect of BaP for the local population (lung cancer) was assessed. Although according to the projections the EU threshold for BaP atmospheric incidence (1 ng m-3) will not be reached by 2050, there will be an increase in the life-time risk of lung cancer, particularly in the most populated areas within the simulation domain.

Wood biomass is turned into industrial fuel through chipping. The efficiency of chipping depends on many factors, including chipper knife wear. Chipper knife wear was determined through a long-term follow-up study, conducted at a waste wood recycling yard. Knife wear determined a sharp drop of productivity (>20%) and a severe decay in product quality. Dry sharpening with a grinder mitigated this effect, but it could not replace proper wet sharpening. Increasing the frequency of wet sharpening sessions determined a moderate increase of knife depreciation cost, but it could drastically enhance machine performance and reduce biomass processing cost. Since benefits largely exceed costs, increasing the frequency of wet sharpening sessions may be an effective measure for reducing overall chipping cost. If the main goal of a chipper operator is to increase productivity and/or decrease fuel consumption, then managing knife wear should be a primary target. (C) 2014 Elsevier Ltd. All rights reserved.

Artículos en revistas In this paper we propose a methodology to approximate closed loop capacity equilibria using only open loop capacity equilibrium models. In the closed loop model, generation companies choose capacities that maximize their individual profit in the first stage while the second stage represents the conjecturedprice- response market equilibrium. In the open loop model, firms simultaneously choose capacities and quantities to maximize their individual profit, while each firm conjectures a price response to its output decisions. The closed loop equilibrium model is an equilibrium problem with equilibrium constraints, which belongs to a class of problems that is very hard to solve. The open loop equilibrium model is much easier to solve, however, it is also less realistic. With the approximation scheme proposed in this paper, we are able to solve the closed loop model reasonably well when market behavior is closer to oligopoly than to perfect competition by smartly employing open loop models which reduces the computational time by two orders of magnitude. We achieve this by transforming the open loop equilibrium problem into an equivalent convex quadratic optimization problem which can be solved efficiently. Finally, a case study is presented in order to validate the proposed approximation scheme. info:eu-repo/semantics/publishedVersion

Alternative fuels and energy vectors are becoming increasingly important in terms of technical, geopolitical, economic, and environmental aspects. In particular, gaseous fuels and vectors, such as fossil or synthetic natural gas (NG) blended with hydrogen, commonly help provide optimal strategies to reduce global and toxic emissions of internal combustion engines, owing to their adaptability, anti-knock capacity, lower toxicity of pollutants, reduced CO2 emissions, and costeffectiveness. However, diesel engines still represent the reference category among internal combustion engines in terms of maximum thermodynamic efficiency. The possibility offered by dual-fuel (DF) systems to combine the efficiency and performance of diesel engines with the environmental advantages of gaseous fuels has been the subject of extensive investigations. However, the simple replacement of diesel fuel with gaseous fuel does not allow for optimising the engine performance, owing to the high percentage of unburned gaseous fuel, which compromises the potential reduction of CO2; therefore, more complex combustion strategies should be realised. In this study, with the aim of improving the DF combustion process, an experimental investigation was performed to analyse low-temperature combustion (LTC), using NG and two enriched hydrogen-compressed NG blends as primary fuels. The LTC mode was activated by means of a very early advanced pilot injection and carried out in two close steps. The double pilot injection was used to control the energy release rate in the first combustion stage, thereby minimizing the increase of the rate of pressure and allowing the extension of the operation range under LTC. The experimental activity was also focused on analysing the particle emissions, as it is well known that these emissions, together with those of nitrogen oxide, constitute the main pollutants resulting from diesel fuel combustion. The results demonstrated the potential to reduce the unburned fuel, NOx, and particle emissions simultaneously, while maintaining equivalent CO2 emissions to a diesel-only engine. Both the timing and pressure of the pilot injection proved to be critical parameters for optimising the emissions and performance