Nuestros investigadores

Carlos Fernández Bandera

Publicaciones científicas más recientes (desde 2010)

Autores: Lucas Segarra, Eva; Ramos Ruiz, Germán; Gutiérrez González, V; et al.
Revista: SUSTAINABILITY
ISSN 2071-1050  Vol. 12  Nº 17  2020  págs. 6788
The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoo
Autores: Lucas Segarra, E.; Ramos Ruiz, Germán (Autor de correspondencia); Fernández Bandera, Carlos
Revista: SENSORS
ISSN 1424-8220  Vol. 20  Nº 22  2020  págs. 6525
In the current energy context of intelligent buildings and smart grids, the use of load forecasting to predict future building energy performance is becoming increasingly relevant. The prediction accuracy is directly influenced by input uncertainties such as the weather forecast, and its impact must be considered. Traditional load forecasting provides a single expected value for the predicted load and cannot properly incorporate the effect of these uncertainties. This research presents a methodology that calculates the probabilistic load forecast while accounting for the inherent uncertainty in forecast weather data. In the recent years, the probabilistic load forecasting approach has increased in importance in the literature but it is mostly focused on black-box models which do not allow performance evaluation of specific components of envelope, HVAC systems, etc. This research fills this gap using a white-box model, a building energy model (BEM) developed in EnergyPlus, to provide the probabilistic load forecast. Through a Gaussian kernel density estimation (KDE), the procedure converts the point load forecast provided by the BEM into a probabilistic load forecast based on historical data, which is provided by the building¿s indoor and outdoor monitoring system. An hourly map of the uncertainty of the load forecast due to the weather forecast is generated with different prediction intervals. The map provides an overview of different prediction intervals for each hour, along
Autores: Campos Gordillo, Germán; Ramos Ruiz, Germán; Stauffer, Y.; et al.
Revista: SUSTAINABILITY
ISSN 2071-1050  Vol. 12  Nº 2  2020  págs. 672
There is a growing concern about how to mitigate climate change, in which the production and use of energy has a great impact as one of the largest sources of global greenhouse gases (GHG). Buildings are responsible for a large percentage of these emissions. Therefore, there has been an increase in research in this area, in order to reduce their consumption and increase their efficiency. One of the major simulation programs used in optimization research is EnergyPlus. The purpose of this software is the complete energy simulation of a building, although it lacks tools to analyze its results and, above all, to manage and edit its simulations. For this reason, we developed an application programming interface (API) that serves to merge two areas which are highly demanded by researchers: energy building simulation (using EnergyPlus) and tools for the management and design of research experiments (in this case, MATLAB®). The developed API allows the user to perform complex simulations using EnergyPlus in a simple way, as it allows the editing of each simulation and the analysis of the simulation results through MATLAB®. In addition, it enables the user to simultaneously run multiple simulations, using either all computer core processors or a selection of them (i.e., allowing parallel computing), reducing the simulation time. The API was developed in the C# language, such that it can be used with any software that can import .NET libraries.
Autores: Fernández Bandera, Carlos; Pachano, José; Salom, Jaume; et al.
Revista: SUSTAINABILITY
ISSN 2071-1050  Vol. 12  Nº 2  2020  págs. 553
The self-consumption without surplus to the grid is one of the aspects of the new Spanish law for prosumers. Increasing the share of renewable energy sources into the grid inherently leads to several constraints. The mismatch between the energy demand and the renewable energy production, which is intermittent in nature, is one of those challenges. Storage offers the possibility to decouple demand and supply, and therefore, it adds flexibility to the electric system. This research evaluates expanding electricity self-consumption without surplus to the grid by harnessing thermal mass storage in the residential sector. The methodology is investigated by using a variable refrigerant flow air conditioner system. Because there is no option to export the excess capacity to the grid, this research proposes an approach to profiting from this surplus energy by activating structural thermal mass, which is quantified from the information acquired using a building energy model. For this purpose, an EnergyPlus model of a flat in Pamplona (Spain) was used. The optimization analysis was based on a set-point modulation control strategy. Results show that under adequate climatological circumstances, the proposed methodology can reduce the total electric energy from the grid between by 60¿80%.
Autores: Gonzalez, V. G. , (Autor de correspondencia); Ramos Ruiz, Germán; Fernández Bandera, Carlos
Revista: SENSORS
ISSN 1424-8220  Vol. 20  Nº 17  2020 
The digital world is spreading to all sectors of the economy, and Industry 4.0, with the digital twin, is a reality in the building sector. Energy reduction and decarbonization in buildings are urgently required. Models are the base for prediction and preparedness for uncertainty. Building energy models have been a growing field for a long time. This paper proposes a novel calibration methodology for a building energy model based on two pillars: simplicity, because there is an important reduction in the number of parameters (four) to be adjusted, and cost-effectiveness, because the methodology minimizes the number of sensors provided to perform the process by 47.5%. The new methodology was validated empirically and comparatively based on a previous work carried out in Annex 58 of the International Energy Agency (IEA). The use of a tested and structured experiment adds value to the results obtained.
Autores: Lucas Segarra, Eva; Du, Hu; Ramos Ruiz, Germán; et al.
Revista: ENERGIES
ISSN 1996-1073  Vol. 12(7)  Nº 1309  2019  págs. 1 - 16
The use of Building Energy Models (BEM) has become widespread to reduce building energy consumption. Projection of the model in the future to know how different consumption strategies can be evaluated is one of the main applications of BEM. Many energy management optimization strategies can be used and, among others, model predictive control (MPC) has become very popular nowadays. When using models for predicting the future, we have to assume certain errors that come from uncertainty parameters. One of these uncertainties is the weather forecast needed to predict the building behavior in the near future. This paper proposes a methodology for quantifying the impact of the error generated by the weather forecast in the building¿s indoor climate conditions and energy demand. The objective is to estimate the error introduced by the weather forecast in the load forecasting to have more precise predicted data. The methodology employed site-specific, near-future forecast weather data obtained through online open access Application Programming Interfaces (APIs). The weather forecast providers supply forecasts up to 10 days ahead of key weather parameters such as outdoor temperature, relative humidity, wind speed and wind direction. This approach uses calibrated EnergyPlus models to foresee the errors in the indoor thermal behavior and energy demand caused by the increasing day-ahead weather forecasts. A case study investigated the impact of using up to 7-day weather forecasts on...
Autores: Ramos Ruiz, Germán; Lucas Segarra, Eva; Fernández Bandera, Carlos
Revista: ENERGIES
ISSN 1996-1073  Vol. 12(1)  Nº 34  2019  págs. 1 - 18
There is growing concern about how to mitigate climate change in which the reduction of CO2 emissions plays an important role. Buildings have gained attention in recent years since they are responsible for around 30% of greenhouse gases. In this context, advance control strategies to optimize HVAC systems are necessary because they can provide significant energy savings whilst maintaining indoor thermal comfort. Simulation-based model predictive control (MPC) procedures allow an increase in building energy performance through the smart control of HVAC systems. The paper presents a methodology that overcomes one of the critical issues in using detailed building energy models in MPC optimizations¿computational time. Through a case study, the methodology explains how to resolve this issue. Three main novel approaches are developed: a reduction in the search space for the genetic algorithm (NSGA-II) thanks to the use of the curve of free oscillation; a reduction in convergence time based on a process of two linked stages; and, finally, a methodology to measure, in a combined way, the temporal convergence of the algorithm and the precision of the obtained solution.
Autores: Gutiérrez-González, V., (Autor de correspondencia); Álvarez-Colmenares, L.; López Fidalgo, Jesús Fernando; et al.
Revista: ENERGIES
ISSN 1996-1073  Vol. 12  Nº 11  2019  págs. 2096
Building Energy Models (BEMs) are a key element of the Energy Performance of Buildings Directive (EPBD), and they are at the basis of Energy Performance Certificates (EPCs). The main goal of BEMs is to provide information for building stakeholders; they can be a powerful market tool to increase demand for energy efficiency solutions in buildings without affecting the comfort of users, as well as providing other benefits. The next generation of BEMs should value buildings in a holistic and cost-effective manner across several complementary dimensions: envelope performances, system performances, and controlling the ability of buildings to offer flexible services to the grid by optimizing energy consumption, distributed generation, and storage. SABINA is a European project that aims to look for flexibility to the grid, targeting the most economic source possible: existing thermal inertia in buildings. In doing so, SABINA works with a new generation of BEMs that tend to mimic the thermal behavior of real buildings and therefore requires an accurate methodology to choose the model that complies with the requirements of the system. This paper details our novel extensive research on which statistical indices should be chosen in order to identify the best model offered by the calibration process developed by Fernandez et al. in a previous paper and therefore is a continuation of that work.
Autores: Fernández Bandera, Carlos (Autor de correspondencia); Muñoz Mardones, Ana Fei; Du, H.; et al.
Revista: ENERGIES
ISSN 1996-1073  Vol. 11  Nº 11  2018  págs. 3139
This study presents a novel optimization methodology for choosing optimal building retrofitting strategies based on the concept of exergy analysis. The study demonstrates that the building exergy analysis may open new opportunities in the design of an optimal retrofit solution despite being a theoretical approach based on the high performance of a Carnot reverse cycle. This exergy-based solution is different from the one selected through traditional efficient retrofits where minimizing energy consumption is the primary selection criteria. The new solution connects the building with the reference environment, which acts as an unlimited sink or unlimited sources of energy, and it adapts the building to maximize the intake of energy resources from the reference environment. The building hosting the School of Architecture at the University of Navarra has been chosen as the case study building. The unique architectural appearance and bespoke architectural characteristics of the building limit the choices of retrofitting solutions. // therefore, retrofitting solutions on the facade, roof, roof skylight and windows are considered in multi-objective optimization using the jEPlus package. It is remarkable that different retrofitting solutions have been obtained for energy-driven and exergy-driven optimization, respectively. Considering the local contexts and all possible reference environments for the building, three unlimited sinks or unlimited sources of energy are selected for the case study building to explore exergy-driven optimization: the external air, the ground in the surrounding area and the nearby river. The evidence shows that no matter which reference environment is chosen, an identical envelope retrofitting solution has been obtained.
Autores: Ramos Ruiz, Germán; Fernández Bandera, Carlos
Revista: APPLIED ENERGY
ISSN 0306-2619  Vol. 185  Nº 1  2017  págs. 82 - 94
Nowadays there is a growing concern about climate change and the global warming effect produced by the concentration of greenhouse gases (GHG). At the Paris climate conference (COP21), 195 countries adopted a global climate agreement, limiting global warming to well below 2ºC. Buildings are large producers of GHG and therefore international standards such as ISO 50001 focus on improving their energy performance, including energy ef¿ciency, use and consumption. To achieve this goal it is important to have a detailed knowledge of the thermal behaviour of uildings. The International Performance Measurement and Veri¿cation Protocol (IPMVP), proposes a calibrated simulation model (Option D) to gather this knowledge and to determine the savings associated with Energy Conservation Measures (ECMs). This paper improves the calibration methodology proposed by Ramos et al. (2016) [1], solving the limitations regarding the number of thermal zones and the use of free-¿oating time periods. Through a real case-study that guides the process, the paper explains how to achieve a calibrated Building Energy Simulation (BES) model using an optimisation process based on a meta-heuristic strategy (genetic algorithm - NSGA-II). Different uncertainty indices such as: CV(RMSE) and Goodness of Fit (GOF) are used as objective function to obtain the calibrated model. These indices, frequently used to measure the accuracy of models, are combined to provide a double possibility to ¿nd the best solution,
Autores: Fernández Bandera, Carlos; Ramos Ruiz, Germán
Revista: ENERGIES
ISSN 1996-1073  Vol. 10  Nº 12  2017  págs. 2102
Building energy performance (BEP) is an ongoing point of re¿ection among researchers and practitioners. The importance of buildings as one of the largest activators in climate change mitigation was illustrated recently at the United Nations Framework Convention on Climate Change 21st Conference of the Parties (COP21). Continuous technological improvements make it necessary to revise the methodology for energy calculations in buildings, as has recently happened with the new international standard ISO 52016-1 on Energy Performance of Buildings. In this area, there is a growing need for advanced tools like building energy models (BEMs). BEMs should play an important role in this process, but until now there has no been international consensus on how these models should reconcile the gap between measurement and simulated data in order to make them more reliable and affordable. Our proposal is a new generation of models that reconcile the traditional data-driven (inverse) modelling and law-driven (forward) modelling in a single type that we have called law-data-driven models. This achievement has greatly simpli¿ed past methodologies, and is a step forward in the search for a standard in the process of calibrating a building energy model.
Autores: Ramos Ruiz, Germán; Fernández Bandera, Carlos
Revista: ENERGIES
ISSN 1996-1073  Vol. 10  Nº 10  2017  págs. 1587
Nowadays, there is growing interest in all the smart technologies that provide us with information and knowledge about the human environment. In the energy ¿eld, thanks to the amount of data received from smart meters and devices and the progress made in both energy software and computers, the quality of energy models is gradually improving and, hence, also the suitability of Energy Conservation Measures (ECMs). For this reason, the measurement of the accuracy of building energy models is an important task, because once the model is validated through a calibration procedure, it can be used, for example, to apply and study different strategies to reduce its energy consumption in maintaining human comfort. There are several agencies that have developed guidelines and methodologies to establish a measure of the accuracy of these models, and the most widely recognized are: ASHRAE Guideline 14-2014, the International Performance Measurement and Veri¿cation Protocol (IPMVP) and the Federal Energy Management Program (FEMP). This article intends to shed light on these validation measurements (uncertainty indices) by focusing on the typical mistakes made, as these errors could produce a false belief that the models used are calibrated.
Autores: Ramos Ruiz, Germán; Fernández Bandera, Carlos; Gómez-Acebo Temes, Tomás; et al.
Revista: APPLIED ENERGY
ISSN 0306-2619  Vol. 168  2016  págs. 691 - 705
Buildings today represent 40% of world primary energy consumption and 24% of greenhouse gas emissions. In our society there is growing interest in knowing precisely when and how energy consumption occurs. This means that consumption measurement and verification plans are well-advanced. International agencies such as Efficiency Valuation Organization (EVO) and International Performance Measurement and Verification Protocol (IPMVP) have developed methodologies to quantify savings. This paper presents a methodology to accurately perform automated envelope calibration under option D (calibrated simulation) of IPMVP ¿ vol. 1. This is frequently ignored because of its complexity, despite being more flexible and accurate in assessing the energy performance of a building. A detailed baseline energy model is used, and by means of a metaheuristic technique achieves a highly reliable and accurate Building Energy Simulation (BES) model suitable for detailed analysis of saving strategies. In order to find this BES model a Genetic Algorithm (NSGA-II) is used, together with a highly efficient engine to stimulate the objective, thus permitting rapid achievement of the goal. The result is a BES model that broadly captures the heat dynamic behaviour of the building. The model amply fulfils the parameters demanded by ASHRAE and EVO under option D.
Autores: Sánchez-Ostiz Gutiérrez, Ana; González Martínez, Purificación; Echeverria Trueba, Juan Bautista; et al.
Libro:  Adaptive Facade Network Europe
Vol. 1  Nº 1  2015  págs. 29
Autores: Ramos Ruiz, Germán; Fernández Bandera, Carlos
Libro:  Proceedings of World Sustainable Building: WSB 14
Vol. 4  2014  págs. 327 - 334
In the design of new buildings, project energy efficiency is nowadays one of the most important parameters on its development. The energy crisis on which we live and the greater social awareness have allowed efficiency be a major factor when we are thinking in a new building solution. This search for efficiency must be supported by studies to quantify these improvements. With this information we can assess which one of the different solutions is the best. The building sustainability is closely related to building efficiency. The present analysis shows through a semi-attached house, the importance of building orientation in heating and cooling demands. With this knowledge we can choose the orientation with low energy consumption.
Autores: Ramos Ruiz, Germán; Fernández Bandera, Carlos
Libro:  Jornadas internacionales de investigación en construcción
2013  págs. 126