• Energy Research

Póster presentado en ESCAPE-21, 21st European Symposium on Computer‐Aided Process Engineering, May 29-June 1, 2011, Chalkidiki, Thessaloniki, Greece. This work introduces a systematic method for the optimization of absorption cycles by combining the capabilities of simulation packages and optimization tools, including the Life Cycle Assessment (LCA). The case presented is a multi objective mixed-integer nonlinear programming (moMINLP) problem that is decomposed following the outer-approximation schema. The primal level entails the solution of the nonlinear programming (NLP) subproblem, where the binary variables are fixed. The master is a specially tailored mixed integer linear programming (MILP) problem. The NLP subproblems are solved by combining gradient-based NLP solvers (i.e., fmincon) linked with rigorous process simulation (Aspen Plus®). The methodology is tested using an absorption cooling system. The results obtained and the corresponding Paretto Curves of optimal design show that the objective function can be significantly reduced with the presented methodology. Financial support from the Consellería de Educación of the Generalitat Valenciana (BEST/2010/085) and Ministerio de Ciencias e Innovación (PPQ, CTQ2009-14420-C02-02).

Abstract An exergy analysis, which only considers the unavoidable exergy destruction, is conducted for single, double, triple and half effect Water–Lithium bromide absorption cycles. Thus, the obtained performances represent the maximum achievable performance under the given operation conditions. The coefficient of performance (COP), the exergetic efficiencies and the exergy destruction rates are determined and the effect of the heat source temperature is evaluated. As expected, the COP increases significantly from double lift to triple effect cycles. The exergetic efficiency varies less among the different configurations. In all cycles the effect of the heat source temperature on the exergy destruction rates is similar for the same type of components, while the quantitative contributions depend on cycle type and flow configuration. Largest exergy destruction occurs in the absorbers and generators, especially at higher heat source temperatures.

The movement toward the 4th generation district heating (4GDH) embraces a great opportunity to support the future smart energy development concept. However, its development calls for addressing technological and economic obstacles aligning with the need for a reformation of the energy market to ensure the quality of service. In this context, our paper presents a comprehensive analysis based on a multi-objective optimization framework incorporating an artificial neural network-based model for the possibility of integrating heat pump (HP) into solar assisted district heating system (SDHS) with seasonal thermal energy storage to support the sustainable transition toward 4GDH. The study evaluates the performance of the proposed system with the help of key performance indicators (KPI) related to the 4GDH characteristics and key stakeholders for possible market growth with consideration for the environmental benefits. The proposed analysis is applied to a small neighbourhood of 10 residential buildings located in Madrid (Spain) to investigate the optimal integration of HP under different control strategies into a SDHS. Inherent the SDHS operator perspective, the results reveal a significant improvement in the stabilization of the SDHS performance due to the HP integration where the solar field temperature never exceeds 80 ◦C, and the seasonal storage tank (SST) temperature stands at 85.4 ◦C. In addition, the share of solar energy stands above 86.1% with an efficiency of 73.9% for the SST, while the seasonal HP performance factor stands above 5.5 for all optimal scenarios. From the investor viewpoint, an energy price of 59.1 Euro/MWh can be achieved for the proposed system with a payback period of 26 years. Finally, from the policymaker perspective, along with the significant economic and sustainable improvement in the SDHS performance, a substantial environmental improvement of 82.5% is achieved when compared to the conventional boiler heating system. The proposed analysis reflects a great motivation for different stakeholders to propose this system as a path toward the 4GDH in the future district energy systems. The work is funded by the Spanish government RTI2018-093849-B-C31 and RTI2018-093849-B-C33. The authors would like to thank the Catalan Government for the quality accreditation given to their research group (GREiA – 2017 SGR 1537, AGACAPE – 2017 SGR 1409). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia. This work is partially supported by ICREA under the ICREA Academia programme. This work is partially funded by the Ministerio de Ciencia, Innovación y Universidades – Agencia Estatal de Investigación (AEI) (RED2018-102431-T). This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713679 and from the Universitat Rovira i Virgili (URV).

Using recycled rubber crumbs as drainage layer in extensive green roofs have high potential to reduce the heating and cooling loads in buildings over traditional materials used as drainage layer, such as pozzolana gravel. However, the environmental impact due to the life cycle should be analyzed to assess its environmental benefit. This paper evaluates the environmental performance of green roofs in which the drainage layer is made of rubber crumbs, a recycled material the use of which is still experimental for this purpose. In this paper Life Cycle Assessment (LCA) is applied to compare the environmental impact of four constructive systems, two extensive green roofs without insulation layer and with different drainage materials, e a recycled material, rubber crumbs, and a conventional one, pozzolana gravel -, in front of two conventional flat roofs, with and without thermal insulation (polyurethane), built in an experimental set-up consisting of four monitored house-like cubicles, located in Mediterranean continental climate (Lleida, Spain). The LCA considered the production, construction, operational, and disposal phases of the roofs, according to UNE-EN 15643-2. The operational phase was carried out using data measured in the experimental set-up, considering heating and cooling energy consumptions in the winter and summer period, respectively.

With the recent trend of moving towards a more sustainable economy, the interest on designing buildings with lower cost and environmental impact has grown significantly. In this context, multi-objective optimization has attracted much attention in building design as a tool to study trade-off solutions (“cost” vs “environmental impact”) resulting from the optimization of conflicting objectives. One major limitation of this approach (as applied to building design) is that it is computationally demanding due to the need to optimize several objectives using complex models based on differential equations (which are used to estimate the energy consumed by a building). In this work, we propose a systematic framework for the design of buildings that combines a rigorous objective reduction method (which removes redundant objectives from the analysis) with a surrogate model (which simplifies the calculation of the energy requirements of the building), both of which expedite the identification of alternative designs leading to environmental improvements. The capabilities of our methodology are illustrated through a case study based on a thermal modelling of a house-like cubicle, in which we optimize the insulation thicknesses of the building envelope. Results show that significant economic and environmental improvements can be achieved compared to the base case (cubicle without insulation). Furthermore, it is clearly illustrated how the minimization of an aggregated environmental metric, like the Eco-Indicator 99, as unique environmental objective may overlook some Pareto solutions that may be appealing for decision-makers. The authors would like to acknowledge financial support from the Spanish Government (ENE2015-64117-C5-3-R (MINECO/FEDER, UE)). Joan Carreras would also like to acknowledge financial support from the Pump-Priming Research Programs of The University of Manchester.

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.

This research examines the viability of rooftop photovoltaic systems for electricity self-consumption in Spain's residential sector, analyzing municipality-level data on electricity demand, rooftop availability, solar irradiance, and various electricity market and surplus policy scenarios. Differences are found between rural and urban contexts, with rural areas exhibiting greater potential for photovoltaic systems deployment due to more available rooftop space. The study highlights the crucial role of surplus electricity management, showing that an efficient use can significantly boost self-consumption potential, particularly in rural areas where surplus constitutes about two-thirds of the photovoltaic production. Economic analyses under different electricity market conditions and surplus compensation policies show that these factors critically affect the attractiveness and viability of these systems. Current high electricity prices in Spain have reduced their payback period, but the prevalent surplus compensation policy, a 1-month net billing feed-in tariff, reduces their cost-effectiveness by up to 60 % compared to a hypothetical 12-month net billing approach. The findings underscore the need for policy adjustments to maximize rooftop occupancy and ensure fair compensation of surpluses, highlighting the importance of tailored strategies for effective sustainable photovoltaic systems deployment in residential contexts. Renewable Energy, 229 ISSN:0960-1481 ISSN:1879-0682

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.