Applying Renewable Energy Technologies in an Integrated Optimization Method for Residential Building’s Design

Designing a Zero Energy Building (ZEB) requires an optimal choice of the materials of a building envelope. Different material properties and window areas could be selected to generate a set of possibilities of the design of a building, being the demand defined by its thermal characteristics. The energy demand of a building could be produced with renewable systems such as photovoltaic. Moreover, the HVAC (Heating, Ventilation, and Air Conditioning) systems could be selected considering the system cost. The present methodology focuses on finding a balance between investment and low energy consumption for a building, based on an integrated optimization method. Such methodology applies a Tabu search algorithm and a simplified model to select the passive design. Afterwards, active elements of the design, as photovoltaic systems, are selected. Therefore, the methodology faces the problem of estimating the annual energy demand and the life cycle cost. The goal is the design of a building with a large amount of energy generated by renewable energy, to have a ZEB, and in the worst case, a nearly Zero Energy Building (nZEB). This methodology reduces investment, reduces the energy demand and selects the best construction materials, renewable energy, and air conditioning system. The present paper analyzes a set of case studies considering different climatic zones in Spain. The results conclude that the methodology could help builders in the design stage, to find a new design that allows a ZEB with the optimal life cycle cost.Ministerio de Economía y Competitividad BIA2016-77431-C2-1-

A field study on adaptive thermal comfort in Spanish primary classrooms during summer season

The assessment of indoor thermal comfort in schools has become an essential object of study; however, applying existing thermal comfort criteria would assume children and adults have a similar range of thermal comfort, without considering discrepancies regarding their level of activity or their behavioural adaptation. Therefore, the objective of the present study was to investigate the thermal comfort in a school building based on an adaptive thermal comfort field study in Seville, in the southwest of Spain, during a summer season. In this study, 2 free-running and 1 air-conditioned classroom were analysed; 67 students aged 10–11 years participated and 2010 thermal questionnaires were collected. A discrepancy was observed between the predicted mean vote and the thermal sensation vote, showing the former is not a good predictor of thermal perception. Thermoneutrality was not always the desired sensation for children; a preference for coolness was detected. A neutral temperature was observed at an average indoor temperature of 24–27 °C and a widening in the thermal comfort range was detected compared with international standards. Regarding adaptive strategies, they showed a preference towards opening windows and doors over using fans or changing clothes. The results suggest that the application of the current models for adults would not be suitable for estimating the thermal comfort of children, and these data could be used to promote natural strategies for assessing thermal comfort over conditioning systems in schools, with the aim of both space ventilation and energy efficiency

Building automation system with adaptive comfort in mixed mode buildings

Although there are many fieldstudies to achieve a model of comfort in free running buildings, fewer studies focus on mixed-mode buildings. Moreover, there are even fewer examples of implementing such algorithms into a building automation system for testing its real validity. In this study, a methodology for implementing and validating an Adaptive Control Algorithm in mixed mode buildings is proposed. In particular, the paper shows the implantation and application of an experimental adaptive control algorithm in the current installation of an office building and without additional costs or specific hardware. The experiment seeks to find a relationship between comfort of their occupants and with energy efficiency. The implementation into the building´s system shows the real applicability and the effectiveness of the adaptive model to hybrid buildings, highlighting that the methodology proposed could be applied in another type of building. The results show that it is possible to improve the energy efficiency, while maintaining the comfort of the users using only the tools yet available in the Building Automation System of the buildings and without additional systems, no extra costs and minimum intervention in its control systemMinisterio de Economía, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad Proyecto DACAR BIA2016-77431-C2-1-RConsejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía P11-TEP-724

A PLS multigroup analysis of the role of businesswomen in the tourism sector in Andalusia

The objective of this study is to determine the factors that influ-ence “business performance” or the “role of entrepreneurs”, as well as to analyse whether gender functions as a moderating variable, based on a survey conducted on a sample of 127 com-panies. Most of the literature in the tourism sector only considers hotel accommodation; thus, it is still limited in the case of non-hotel accommodation. Our research fills this gap by focusing on both types of establishments. An explanatory and confirmatory model has been carried out based on a PLS-SEM approach, taking the factors that determine business performance into ac-count. Moreover, a MICOM and a multi-group analysis have been undertaken in order to check whether gender acts as a modera-tor. Our findings reveal that there are no significant differences between tourist accommodation companies run by women and men in Andalusia; hence, gender is not a moderating variable regarding business performance. Furthermore, as full measure-ment invariance has been established, a comparison between groups emphasises that the influence of the environment, and the resources and capabilities of the entrepreneur, are factors that affect women more than men, and the number of employ-ees, work experience, and the occupancy rate are more impor-tant for businesswomen, whereas the distance to the nearest airport, check-in, and the occupancy rate are more important for businessmen. This empirical study has practical implications for hospitality industry professionals and concerned authorities which are responsible for designing strategies and policies related to this sector in Andalusia

Mathematical formulation and comparison of solution approaches for the vehicle routing problem with access time windows

The application of the principles of sustainability to the implementation of urban freight policies requires the estimation of all the costs and externalities involved. We focus here on the case of access time windows, which ban the access of freight vehicles to central urban areas in many European cities. Even though this measure seeks to reduce congestion and emissions in the most crowded periods of the day, it also imposes additional costs for carriers and results in higher emissions and energy consumption. We present here a mathematical model for the Vehicle Routing Problem with Access TimeWindows, a variant of the VRP suitable for planning delivery routes in a city subject to this type of accessibility restriction.We use the model to find exact solutions to small problem instances based on a case study and then compare the performance over larger instances of a modified savings algorithm, a genetic algorithm, and a tabu search procedure, with the results showing no clear prevalence of any of them, but confirming the significance of those additional costs and externalities.Ministerio de Economía y Competitividad EC2013-47286-C3-3-

Analizando la aplicabilidad de machine learning en la predicción del confort térmico

El confort térmico, relacionado con el establecimiento de la temperatura en el interior de los edificios, es el componente más determinante en el confort global y un factor decisivo en la salud y productividad y en el consumo energético de los edificios. En el estudio y predicción del confort térmico tradicionalmente han predominado dos enfoques: el estático y el dinámico o adaptativo. Aunque ambos modelos son ampliamente aceptados en el área de conocimiento, poseen ciertas limitaciones: precisan de variables ambientales y personales, no están enfocados a la predicción del confort individualizado y carecen de autaprendizaje. Por lo tanto, en el contexto del confort térmico, se han propuesto en los últimos años soluciones alternativas basadas en Machine Learning (ML) que permiten identificar nuevos aspectos que influyen en el confort térmico de los ocupantes de los edificios y enfocarse en su análisis individualizado. Por ello, en el presente trabajo se reflexiona sobre la aplicabilidad del ML en la predicción de variables relacionadas con el confort térmico en base a ocho papers de la literatura existente

Project management applied to a Logistics game

La transmisión de conceptos mediante juegos combina una aplicación práctica de la teoría junto con un incremento potencial del interés y la motivación de los alumnos. Este objetivo en el caso de la transmisión de conceptos de la gestión de proyectos ágil, mediante la metodología Scrum, se consigue mediante un juego aplicado a la logística, que se propone en esta comunicación, en la que se explica la dinámica del juego, y cómo se reflejan todos los conceptos de esta metodología ágil.The transmission of concepts through games combines a practical application of the theory together with a potential increase in the interest and motivation of the students. This objective in the case of the transmission of agile project management concepts, through the Scrum methodology, is achieved through a game applied to logistics, which is proposed in this communication, in which the dynamics of the game are explained, and how all the concepts of this agile methodology are reflected

Aplicación de la regresión logística para la predicción de roturas de tuberías en redes de abastecimiento de agua

Las roturas de tuberías en redes de abastecimiento de agua provocan serios problemas para las compañías encargadas de su gestión. Con objeto de reducir el número de roturas inesperadas, se propone un método predictivo de clasificación de las tuberías que utiliza la regresión logística, junto con técnicas avanzadas de procesamiento de datos, como el equilibrado de clases o la validación cruzada. La metodología se ha aplicado al caso real de la red de abastecimiento de Sevilla. Los resultados muestran que podría llegar a predecirse el 85.9% de las roturas de tuberías, siendo 76.6% la precisión total del modelo.Universidad de Sevilla (España) VI PPIT-U