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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

Abstract Thermal energy storage systems for both heat and cold are necessary for many industrial processes. High energy density and high power capacity are desirable properties of the storage. The use of latent heat increases the energy density of the storage tank with high temperature control close to the melting point. Tube in PCM tank is a very promising system that provides high packing factor. This work presents an experimental study of a PCM tank for cold storage applications. Two different configurations and different flow rates of the heat transfer fluid were studied. The effectiveness of the PCM storage system was defined as that of a heat exchanger. The results showed that the heat exchange effectiveness of the system did not vary with time, decreased with increasing flow rate and increased with increasing heat transfer area. The effectiveness was experimentally determined to only be a function of the ratio m ˙ /A. This equation was found to be adequately be used to design a PCM storage system, and a case study is presented. It was shown that the tube in tank design together with a low temperature PCM is suitable as a thermal storage facility for cold storage.

Artículos en revistas A major aim of Capacity Remuneration Mechanisms (CRMs) is to lead the power system expansion towards the level of security of supply that the regulator considers adequate. When introducing a capacity mechanism, therefore, regulators must ensure that the resulting mix will actually provide the firmness pursued, in such a way that both the generation and the demand resources awarded with the capacity remuneration actually perform as expected when the system needs them. In order to achieve this goal, some experts stressed the importance of including performance incentives in the CRM design. However, first capacity mechanisms (implemented mainly in the American continent) did not pay enough attention to this aspect. Two decades of operation have evidenced the need for performance incentives and these instruments are, at this writing, at the centre of the regulatory discussion. On the basis of a model analysis, this article demonstrates how the introduction of properly designed explicit penalty schemes for under-delivery can positively impact the CRM outcomes, providing resources with effective incentives to maximise their reliability, discriminating against non-firm generation units, and therefore increasing the effectiveness of the mechanism in achieving its objectives. info:eu-repo/semantics/publishedVersion

The acceptability, energy consumption, and environmental benefits of electric vehicles are highly dependent on travel patterns. With increasing ride-hailing popularity in mega-cities, urban mobility patterns are greatly changing; therefore, an investigation of the extent to which electric vehicles would satisfy the needs of ride-hailing drivers becomes important to support sustainable urban growth. A first step in this direction is reported here. GPS-trajectories of 144,867 drivers over 104 million km in Beijing were used to quantify the potential acceptability, energy consumption, and costs of ride-hailing electric vehicle fleets. Average daily travel distance and travel time for ride-hailing drivers was determined to be 129.4 km and 5.7 h; these values are substantially larger than those for household drivers (40.0 km and 1.5 h). Assuming slow level-1 (1.8 KW) or moderate level-2 (7.2 KW) charging is available at all home parking locations, battery electric vehicles with 200 km all electric range (BEV200) could be used by up to 47% or 78% of ride-hailing drivers and electrify up to 20% or 55% of total distance driven by the ride-hailing fleet. With level-2 charging available at home, work, and public parking, the acceptance ceiling increases to up to 91% of drivers and 80% of distance. Our study suggests that long range BEVs and widespread level-2 charging infrastructure are needed for large-scale electrification of ride-hailing mobility in Beijing. The marginal benefits of increased all electric range, effects on charging infrastructure distribution, and payback times are also presented and discussed. Given the observed heterogeneity of ride-hailing vehicle travel, our study outlines the importance of individual-level analysis to understand the electrification potential and future benefits of electric vehicles in the era of shared smart transportation.

Abstract Life Cycle Assessment (LCA) has been conducted for seven experimental cubicles located in Puigverd de Lleida (Spain). The objective of this experimental set-up is to test different constructive solutions in order to point out the most sustainable solution with lower energy demand during the operational phase. Therefore, different building, insulation and Phase Change Materials (PCMs) have been tested under controlled temperature conditions to examine the thermal performance of the whole system. Although some of these materials are able to reduce the energy demand and consequently the environmental impact during the operational phase, they still have high embodied energy that can cause high environmental impact during the manufacturing phase. Therefore the LCA study in this paper focuses on assessing the impact of the embodied energy needed during the manufacturing and disposal phase by highlighting and comparing the effect of using different building materials, insulating materials, and phase change materials.

Aquifer thermal energy storage (ATES) is a cost-effective technology that enables the reduction of energy use and CO2 emissions associated with the heating and cooling of buildings by storage and recovery of large quantities of thermal energy in the subsurface. Reducing the distance between wells in large-scale application of ATES increases the total amount of energy that can be provided by ATES in a given area. However, due to thermal interference the performance of individual systems can decrease. In this study a novel method is presented that can be used to (a) determine the impact of thermal interference on the economic and environmental performance of ATES and (b) optimize well distances in large-scale applications. The method is demonstrated using the hydrogeological conditions of Amsterdam, Netherlands. Results for this case study show that it is cost-effective to allow a limited amount of thermal interference, such that 30–40% more energy can be provided in a given area compared to the case in which all negative thermal interference is avoided. Sensitivity analysis indicates that optimal well distance is moderately insensitive to changes in hydrogeological and economic conditions. Maximum economic benefit compared to conventional heating and cooling systems on the other hand is sensitive, especially to changes in the gas price and storage temperatures.

Central solar heating plants with seasonal storage (CSHPSS) are among the most promising technologies to save energy in the industrial and residential-commercial building sectors. This work introduces a systematic approach to optimize these systems according to economic and environmental criteria. Our method, which combines the TRNSYS 17 simulation software with life cycle assessment and multi-objective optimization, identifies optimal CSHPSS designs for any climatic condition and heating demand profile considering economic and environmental criteria simultaneously. The capabilities of this approach are illustrated through its application to a case study of a CSHPSS located in Barcelona (Spain), which satisfies a heating demand for a neighborhood of 1120 dwellings. Numerical results show that the CSHPSS plant leads to significant environmental and economic improvements compared to the use of a conventional natural gas heating system. Our tool can guide engineers and architects in the transition towards a more sustainable residential sector.

Artículos en revistas As outlined in the Paris Agreement on climate change, efforts to mitigate and adapt to climate change will require new modes of development of the energy sector including the transformation and expansion of power systems to low-carbon and more resilient designs. However, there is a need for more systematic tools to support decision-making processes in the context of climate change impacts and adaptation strategies for the energy and power sectors. For instance, quantitative approaches should be developed and implemented for the assessment of the impacts and hedging strategies associated with the uncertainties inherent to energy and power planning problems. This study addresses the development and implementation of an integrated model-based system analysis, which uses general circulation models, global sensitivity analysis, and stochastic optimization techniques, for the optimal design and planning of the Colombian power system in view of submitted climate pledges and climate change adaptation. It was found that during the 2015 to 2029 time frame, climate change will likely reduce the capacity factor of hydropower generation by 5.5-17.1%. Additionally, it was established that the independent effects of three key uncertain parameters, i.e., capacity factor of hydropower generation, gas prices, and emission reduction target, account for ~96% of the variance in the total cost for the required expansion and operation of the power system. Furthermore, when uncertainty is taken into account, the optimal expansion strategy consists of rescheduling of investments in hydropower plants and investing more in carbon management technologies and renewable power plants to compensate for the uncertainty in hydropower generation, climate policy, and gas prices. info:eu-repo/semantics/publishedVersion