Self-consumption possibilities by rooftop PV and building retrofit requirements for a regional building stock: The case of Catalonia

European Union policies are encouraging the implementation of renewable energies to reduce fossil fuels dependency. This is further motivated by the effects of global warming and the relevant temperature rise in large cities. Thus, it is increasingly important to analyze the large-scale potential of solar energy, making use of the roof availability for renewable energy generation in cities. Furthermore, it is important to couple this analysis with the energy demand of the buildings analyzing the self-consumption possibilities and help in the decision-making process in regional investments. The proposed methodology estimates and matches the roof potential for electricity generation by PV and the building's energy demand, including the building characteristics as a novelty. As a result, we calculate the self-consumption possibilities and the retrofit requirements of a selected housing stock. Our methodology starts with the quantification and classification of the residential stock. This includes the characterization of the types of dwellings in the regional residential stock, taking into account the size of the municipalities. Then the energy demand of the dwellings, depending on the characteristics of the buildings and the roof generation potential, is compared. Catalonia region (Spain), including the city of Barcelona is studied to show the contributions of this methodology to the energy transition. Results indicate that between 8 and 30% of the residential electricity demand of the municipalities can be covered by rooftop PV. Important energy retrofits (reductions of 80% of the energy demand) are required to approach the feasibility of self-consumption. Nevertheless, there is a limited potential impact in larger cities due to the reduced available roof area per habitant.Peer ReviewedPostprint (published version

Comparing biofuels through the lens of sustainability: A data envelopment analysis approach

Liquid biofuels can facilitate the transition towards a more sustainable transportation sector by curbing carbon emissions while maintaining most of the current vehicle fleet. Today, a myriad of alternatives are available to produce biofuels, where different decisions for the fuel type, blend, conversion process and carbon source will affect the final cost and environmental impact of the product. In this contribution, we analyze the performance of 72 different biofuels routes based on 12 indicators that cover the three sustainability dimensions: economic, environmental and social. The proposed multi-criteria approach combines Data Envelopment Analysis with Life Cycle Assessment to evaluate biofuels from a cradle-to-wheel perspective, that is, considering the production chain spanning from biomass production to the combustion of the biofuel in the engine. Results reveal that there are 35 biofuels routes performing better than the rest, with renewable diesel being a better option than ethanol-based blends or biodiesel, and waste biomass preferred over cellulosic biomass or bio-oils. The selection of the carbon source proofed to be the most important decision, highlighting the need to consider regional aspects related to soil and climate before promoting a certain biofuel. Overall, our results can help to derive effective policies for the adoption of biofuels attaining the best performance at minimum cost and environmental risks.Peer ReviewedPostprint (published version

Costs and environmental impacts multi-objective heat exchanger networks synthesis using a meta-heuristic approach

DOI: 10.1016/j.apenergy.2017.06.015 http://www.sciencedirect.com/science/article/pii/S0306261917307754?via%3Dihub Filiació URV: SIHeat Exchanger Network (HEN) synthesis approaches based on total annual costs (TAC) optimization can reduce CO2 emissions and electricity used in plants, since the use of utilities is reduced with a cost-optimal design. However, environmental impacts (EI) are not explicitly addressed in such methods. Life cycle assessment (LCA) metrics can quantify EI and can be used as objective function. This work proposes a meta-heuristic approach to perform a multi-objective optimization (MOO) of TAC and EI in medium and large-scale HEN. The method developed efficiently achieves near-Pareto fronts for four industrial-size case studies. Optimal-TAC and optimal-EI solutions, as well as configurations with low EI but still competitive TAC are presented. Cost-optimal solutions reported in the literature are compared with non-dominated solutions obtained in this work with similar TAC. In all cases, the approach developed is able to achieve solutions with remarkably lower EI, demonstrating the importance of multi-criteria optimization in HEN synthesis

Solar energy embodied in international trade of goods and services: A multi-regional input-output approach

In a globalized market, part of the goods/services consumed in a country might be produced abroad using diverse energy sources. To properly assess the extent to which a country is moving towards more sustainable energy sources, it is imperative to consider both, the amount of renewable energy produced within its boundaries along with that embodied in the imported goods/services. This work quantifies the amount of solar energy embodied in trade using environmentally extended input-output models. Numerical results reveal that some countries are net importers of solar energy (the amount of solar energy consumed anywhere in the world for producing the goods and services they require is greater than the amount of solar energy they generate locally), while others are net exporters (the opposite situation occurs). Additionally, it was found that the production of solar energy in the top economies has increased in the last two decades. Our analysis aims to facilitate the design of more effective environmental policies for promoting the use of solar energy worldwide. © 2015 Elsevier Ltd

Targeting Energy Efficiency through Air Conditioning Operational Modes for Residential Buildings in Tropical Climates, Assisted by Solar Energy and Thermal Energy Storage. Case Study Brazil

Economy and parsimony in the consumption of energy resources are becoming a part of common sense in practically all countries, although the effective implementation of energy efficiency policies still has a long way to go. The energy demand for residential buildings is one of the most significant energy sinks. We focus our analysis on one of the most energy-consuming systems of residential buildings located in regions of tropical climate, which are cooling systems. We evaluate to which degree the integration of thermal energy storage (TES) and photovoltaic (PV) systems helps to approach an annual net zero energy building (NZEB) configuration, aiming to find a feasible solution in the direction of energy efficiency in buildings. To conduct the simulations, an Energy Efficiency Analysis Framework (EEAF) is proposed. A literature review unveiled a potential knowledge gap about the optimization of the ASHRAE operational modes (full storage load, load leveled, and demand limiting) for air conditioning/TES sets using PV connected to the grid. A hypothetical building was configured with detailed loads and occupation profiles to simulate different configurations of air conditioning associated with TES and a PV array. Using TRNSYS software, a set of scenarios was simulated, and their outputs are analyzed in a life cycle perspective using life cycle costing (LCC). The modeling and simulation of different scenarios allowed for identifying the most economic configurations from a life cycle perspective, within a safe range of operability considering the energy efficiency and consequently the sustainability aspects of the buildings. The EEAF also supports other profiles, such as those in which the occupancy of residential buildings during the day is increased due to significant changes in people’s habits, when working and studying in home office mode, for example. These changes in habits should bring a growing interest in the adoption of solar energy for real-time use in residential buildings. The results can be used as premises for the initial design or planning retrofits of buildings, aiming at the annual net zero energy balance

Targeting Energy Efficiency through Air Conditioning Operational Modes for Residential Buildings in Tropical Climates, Assisted by Solar Energy and Thermal Energy Storage. Case Study Brazil

Economy and parsimony in the consumption of energy resources are becoming a part of common sense in practically all countries, although the effective implementation of energy efficiency policies still has a long way to go. The energy demand for residential buildings is one of the most significant energy sinks. We focus our analysis on one of the most energy-consuming systems of residential buildings located in regions of tropical climate, which are cooling systems. We evaluate to which degree the integration of thermal energy storage (TES) and photovoltaic (PV) systems helps to approach an annual net zero energy building (NZEB) configuration, aiming to find a feasible solution in the direction of energy efficiency in buildings. To conduct the simulations, an Energy Efficiency Analysis Framework (EEAF) is proposed. A literature review unveiled a potential knowledge gap about the optimization of the ASHRAE operational modes (full storage load, load leveled, and demand limiting) for air conditioning/TES sets using PV connected to the grid. A hypothetical building was configured with detailed loads and occupation profiles to simulate different configurations of air conditioning associated with TES and a PV array. Using TRNSYS software, a set of scenarios was simulated, and their outputs are analyzed in a life cycle perspective using life cycle costing (LCC). The modeling and simulation of different scenarios allowed for identifying the most economic configurations from a life cycle perspective, within a safe range of operability considering the energy efficiency and consequently the sustainability aspects of the buildings. The EEAF also supports other profiles, such as those in which the occupancy of residential buildings during the day is increased due to significant changes in people’s habits, when working and studying in home office mode, for example. These changes in habits should bring a growing interest in the adoption of solar energy for real-time use in residential buildings. The results can be used as premises for the initial design or planning retrofits of buildings, aiming at the annual net zero energy balance

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae