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Energy Eficiency and Energy Performance Gap in centralized social housing buildings of the Basque Country

Authors: Pablo Hernandez-Cruza, Catalina Giraldo-Sotoa, César Escudero-Revillab, Juan María-Betanzosa, Iván Flores-Abascala

a ENEDI research group, Energy Engineering Department, Faculty of Engineering of Bilbao, University of Basque Country UPV/EHU, Pl. Ingeniero Torres Quevedo 1, Bilbao, Spain

b ENEDI Research Group, Department of Energy Engineering, University of the Basque Country (UPV/EHU), Nieves Cano 12, Araba, 01006, Spain

Keywords: Social housing, Energy consumption, Energy efficiency, Energy performance gap

Abstract: The energy consumption of households is under scrutiny since 27% of the final energy consumption in Europe is due to this sector. The scientific community is making great efforts to analyse the energy consumption of residential buildings; however, in the case of social housing buildings, there is still a significant lack of knowledge regarding their actual energy consumption. Thus, in this research, we have analysed the monthly energy consumption over the last three years of 481 dwellings distributed in 6 buildings of the social housing stock of the Basque Country. We have normalised the heating and DHW consumption so as to have a sample of observations only dependent on the user behaviour. The results of the statistical analysis performed show that there is a significant variability of consumption in dwellings within the same building. The user behaviour strongly affects the efficiency of the centralized systems of the buildings, whose average value has turned out to be 65%. The overall energy consumption in these social housing buildings has been found to be considerably lower than the regional, national and European average indicators. Furthermore, the Energy Performance Gap differs from the average values found in the literature. This means that the measured final energy consumption of these buildings is 0.70 to 2.28 times the predicted calculated consumption.

https://doi.org/10.1016/j.enbuild.2023.113534

Optimisation of LSTM neural networks with NSGA-II and FDA for PV installations characterisation

Authors: Miguel Martínez-Comesaña a, Javier Martínez-Torres b,c , Pablo Eguía-Oller a

a CINTECX – Research Center in Technologies, Energy, and Industrial Processes., Universidade de Vigo, Rúa Maxwell s/n, 36310 Vigo, Spain

b CINTECX – Research Center in Technologies, Energy, and Industrial Processes., University of Vigo (Universidade de Vigo), 36310 Vigo, Spain

c CITMAga, 15782 Santiago de Compostela, Spain

Engineering Applications of Artificial Intelligence, Volume 126, Part A, November 2023, 106770

Keywords: Deep learning, Genetic algorithm, Functional data analysis, Synthetic data, PV system

CiteScore: 12.3
Impact Factor: 8

Abstract: Solar PV generation is renewable energy source that in the last years has contributed to reduce the use of fossil fuels. Controlling the efficiency of photovoltaic (PV) installations is essential in order for its use to spread. Deep learning (DL) models have demonstrated their efficiency in this context. The purpose of this work is to show a methodology to optimised deep learning models and show a specific application of the optimised model to characterise PV installations. The estimations yielded by this model are obtained without the need for real PV data to the training process; synthetic data are used. The built multivariate neural network is optimised through the use of a multiobjective genetic algorithm and the use of a feature engineering tool based on functional data analysis (FDA) clustering. This method was applied on synthetic data and on a PV installation located in north-western Spain, where the number of parallel modules, the azimuth and the slope in the installation are estimated. The results show that the model optimised using the non-dominant sorting genetic algorithm (NSGA-II) and the customised dataset with FDA, achieve lower errors or in the same range by reducing the complexity of the model or the complexity of the dataset used. Specifically, the bests models generates estimations with an average error between 6% and 18% on synthetic data and between 6% and 12% on real data.

https://doi.org/10.1016/j.engappai.2023.106770

A mixed integer linear programming-based simple method for optimizing the design and operation of space heating and domestic hot water hybrid systems in residential buildings

Authors: E. Pérez-Iribarrena, I. González-Pinoa, Z.Azkorra-Larrinagaa, M. Odriozola-Maritonerab

a ENEDI Research Group, Department of Energy Engineering, Faculty of Engineering of Bilbao, University of the Basque Country UPV/EHU, Plaza Torres Quevedo 1, Bilbao 48013, Spain

b ENEDI Research Group, Department of Energy Engineering, Faculty of Engineering of Gipuzkoa, University of the Basque Country UPV/EHU, Europa Plaza 1, 20018 Donostia, Spain

Energy Conversion and Management Volume 292, 15 September 2023, 117326

Keywords: Thermal systems, Hybridization, Linear programming, Multicriteria optimization, Energy efficiency in buildings

CiteScore: 19.1
Impact Factor: 10.4

Abstract: The hybridization of energy systems is based on the combined integration of both renewable and non-renewable technologies and thermal energy storage. These hybrid installations improve cost effectiveness and energy efficiency when they are correctly designed and the operation strategy is suitable. Despite the relevance of achieving the optimal configuration, sizing and control strategy of hybrid thermal systems, there is no simple and generic methodology which allows this type of installations to be optimized in the project phase. In response to this issue, in this work, a mixed integer linear programming-based simple model is carried out with the aim of obtaining the optimal design, sizing and operation of thermal energy systems in residential buildings. To do so, a superstructure is defined that includes the main technologies commercialized for thermal energy systems in buildings. Technical, economic, environmental and legal constraints are determined in the proposed generic model. In order to validate the method, it is applied to a central space heating and domestic hot water installation of a residential building located in a cold climate in Spain. Optimal solutions are obtained considering three different perspectives —economic, environmental and multicriteria— and are compared to the current installation. According to the results, the overall cost of the economic optimal configuration is reduced by 15%, whereas the greenhouse gas emissions decrease by 56% in the environmental optimal solution. It is thus demonstrated that the proposed generic and simple model is a useful tool for determining the optimal hybridization of the plant and for analysing the technical, economic and environmental feasibility of these systems in the project phase.

https://doi.org/10.1016/j.enconman.2023.117326

Energy and Cost Analysis of an Integrated Photovoltaic and Heat Pump Domestic System Considering Heating and Cooling Demands

Authors: Arenas-Larrañaga Mikel a,b, Santos-Mugica Maider a , Alonso-Ojanguren Laura a , Martin-Escudero Koldobika b

a TECNALIA, Basque Research and Technology Alliance (BRTA), Area Anardi 5, Azpeitia, ES-20730, Spain

b ENEDI Research Group, Department of Energy Engineering, University of the Basque Country (UPV/EHU), Torres Quevedo 1, Bilbao, ES-48013, Spain

Energies, Open Access, Volume 16, Issue 13, July 2023, Article number 5156

Keywords: Dymola, heat pump, Modelica, photovoltaic panels, self-consumption

CiteScore: 5.5
Impact Factor: 3.2

Abstract: The integration of photovoltaic panels and heat pumps in domestic environments is a topic that has been studied extensively. Due to their electrical nature and the presence of elements that add thermal inertia to the system (water tanks and the building itself), the functioning of compression heat pumps can be manipulated to try to fulfill a certain objective. In this paper, following a rule-based control concept that has been identified in commercial solutions and whose objective is to improve the self-consumption of the system by actively modulating the heat pump compressor, a parametric analysis is presented. By making use of a lab-tested model, the performance of the implemented control algorithm is analyzed. The main objective of this analysis is to identify and quantify the effects of the main parameters in the performance of the system, namely the climate (conditioning both heating and cooling demands), the photovoltaic installation size, the thermal insulation of the building and the control activation criteria. A total of 168 yearly simulations have been carried out. The results show that the average improvement in self-consumption is around 13%, while the cost is reduced by 2.5%. On the other hand, the heat from the heat pump and the power consumed increase by 3.7% and 5.2%, respectively. Finally, a linear equation to estimate the performance of the controller is proposed.

https://doi.org/10.3390/en16135156

Thermal characterization of a modular living wall for improved energy performance in buildings

Authors: Zaloa Azkorra-Larrinaga, Aitor Erkoreka-González, Koldobika Martín-Escudero, Estibaliz Pérez-Iribarren, Naiara Romero-Antón

ENEDI Research Group, Department of Energy Engineering, University of the Basque Country (UPV/EHU), Torres Quevedo 1, 48013, Bilbao, Spain

Building and Enviroment, Volume 234, 15 April 2023, 110102

Keywords: Modular living wall, Vertical greenery, Energy performance, Energy saving, PASLINK test Cell

CiteScore: 11.3
Impact Factor: 7.4

Abstract: Vertical vegetation systems are an innovative passive method for decreasing the thermal energy demand of buildings while increasing the quality of urban life. The main objective of this work is to calculate the effectiveness of vegetation in reducing thermal loads analytically. For this purpose, the thermal energy performance of the modular living wall was compared with a traditional double façade construction system to evaluate the influence of vegetation using Stochastic Differential Equations models.

The research was carried out experimentally using a real-scale PASLINK test cell. The thermal behaviour of a double leaf bare wall and the same double leaf wall converted into a modular living wall were calculated for different summertime and wintertime periods. In both studied cases, the temperature of the exterior surface of the bare wall is taken at the same place regardless of whether or not there is greenery system in the energy balance. With this simplification, the effect of the modular living wall can be identified within the estimated coefficients.

The thermal resistance of the conventional double façade increased 0.74 (m2 K)/W over the non-greened wall, which represents a weighted increase of 49%. Additionally, the experimental results showed that the evapotraspiration processes that take place in the living wall lead to an increase in the combined convection-radiation coefficient, which reduces the overheating of the façade. Moreover, the effective solar absorptivity value of the outermost surface of the bare wall has been reduced an 85% thanks to the living wall, which confirms the high capacity of the living wall to reduce solar heat gains.

https://doi.org/10.1016/j.buildenv.2023.110102