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Documents published in Scipedia

• Operation and energy flexibility evaluation of direct load controlled buildings equipped with heat pumps

  G. Mor Martinez, J. Cipriano, B. Grillone

  Energy & Buildings (2021). S0378-7788(21)00768-4

  
  

  Abstract

  To date, the assessment of the energy flexibility to be delivered by existing buildings and by their legacy HVAC systems is hindered by a lack of commonly agreed-upon methodologies. There are many research works in the field; however, many of them are focused on the design stage or, in case of addressing building operation, they are based on controlled experimental setups.The novelty of this paper lies in the fact that it develops and validates an original methodology for the Flexibility Function estimation to evaluate the delivered energy flexibility of several Automated Demand Response services applied on different heat pump systems working under real operations. The active interaction with several electricity markets, ranging from the Spanish day-ahead market to the German and Swiss ancillary services markets, have also been evaluated during the winter and spring seasons. The method results showed that heat pumps could offer a significant potential of flexibility in the analysed countries. Nevertheless, it has also been envisaged that some restrictions concerning reaction times and reliability may affect its readiness for certain ancillary services markets.

  Abstract
  To date, the assessment of the energy flexibility to be delivered by existing buildings and by their legacy HVAC systems is hindered by a lack of commonly agreed-upon methodologies. [...]

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• Data-Driven Virtual Replication of Thermostatically Controlled Domestic Heating Systems

  G. Mor Martinez, J. Cipriano, E. Gabaldon, B. Grillone, D. Chemisana

  Energies (2021). -

  
  

  Abstract

  Thermostatic load control systems are widespread in many countries. Since they provide heat for domestic hot water and space heating on a massive scale in the residential sector, the assessment of their energy performance and the effect of different control strategies requires simplified modeling techniques demanding a small number of inputs and low computational resources. Data-driven techniques are envisaged as one of the best options to meet these constraints. This paper presents a novel methodology consisting of the combination of an optimization algorithm, two auto-regressive models and a control loop algorithm able to virtually replicate the control of thermostatically driven systems. This combined strategy includes all the thermostatically controlled modes governed by the set point temperature and enables automatic assessment of the energy consumption impact of multiple scenarios. The required inputs are limited to available historical readings from smart thermostats and external climate data sources. The methodology has been trained and validated with data sets coming from a selection of 11 smart thermostats, connected to gas boilers, placed in several households located in north-eastern Spain. Important conclusions of the research are that these techniques can estimate the temperature decay of households when the space heating is off as well as the energy consumption needed to reach the comfort conditions. The results of the research also show that estimated median energy savings of 18.1% and 36.5% can be achieved if the usual set point temperature schedule is lowered by 1○C and 2○C, respectively.

  Abstract
  Thermostatic load control systems are widespread in many countries. Since they provide heat for domestic hot water and space heating on a massive scale in the residential [...]

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• A data-driven method for unsupervised electricity consumption characterisation at the district level and beyond

  G. Mor Martinez, J. Cipriano, G. Martirano, F. Pignatelli, C. Lodi, F. Lazzari, B. Grillone, D. Chemisana

  Energy Reports (2021). -

  
  

  Abstract

  A bottom-up electricity characterisation methodology of the building stock at the local level is presented. It is based on the statistical learning analysis of aggregated energy consumption data, weather data, cadastre, and socioeconomic information. To demonstrate the validity of this methodology, the characterisation of the electricity consumption of the whole province of Lleida, located in northeast Spain, is implemented and tested. The geographical aggregation level considered is the postal code since it is the highest data resolution available through the open data sources used in the research work. The development and the experimental tests are supported by a web application environment formed by interactive user interfaces specifically developed for this purpose. The paper’s novelty relies on the application of statistical data methods able to infer the main energy performance characteristics of a large number of urban districts without prior knowledge of their building characteristics and with the use of solely measured data coming from smart meters, cadastre databases and weather forecasting services. A data-driven technique disaggregates electricity consumption in multiple uses (space heating, cooling, holidays and baseload). In addition, multiple Key Performance Indicators (KPIs) are derived from this disaggregated energy uses to obtain the energy characterisation of the buildings within a specific area. The potential reuse of this methodology allows for a better understanding of the drivers of electricity use, with multiple applications for the public and private sector.

  Abstract
  A bottom-up electricity characterisation methodology of the building stock at the local level is presented. It is based on the statistical learning analysis of aggregated [...]

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• Baseline Energy Use Modeling and Characterization in Tertiary Buildings Using an Interpretable Bayesian Linear Regression Methodology

  B. Grillone, G. Mor Martinez, S. Danov, J. Cipriano, F. Lazzari, A. Sumper

  Benedetto Grillone's personal collection (2021). 2

  
  

  Abstract

  Interpretable and scalable data-driven methodologies providing high granularity baseline predictions of energy use in buildings are essential for the accurate measurement and verification of energy renovation projects and have the potential of unlocking considerable investments in energy efficiency worldwide. Bayesian methodologies have been demonstrated to hold great potential for energy baseline modelling, by providing richer and more valuable information using intuitive mathematics. This paper proposes a Bayesian linear regression methodology for hourly baseline energy consumption predictions in commercial buildings. The methodology also enables a detailed characterization of the analyzed buildings through the detection of typical electricity usage profiles and the estimation of the weather dependence. The effects of different Bayesian model specifications were tested, including the use of different prior distributions, predictor variables, posterior estimation techniques, and the implementation of multilevel regression. The approach was tested on an open dataset containing two years of electricity meter readings at an hourly frequency for 1578 non-residential buildings. The best performing model specifications were identified, among the ones tested. The results show that the methodology developed is able to provide accurate high granularity baseline predictions, while also being intuitive and explainable. The building consumption characterization provides actionable information that can be used by energy managers to improve the performance of the analyzed facilities.

  Abstract
  Interpretable and scalable data-driven methodologies providing high granularity baseline predictions of energy use in buildings are essential for the accurate measurement [...]

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• A data-driven methodology for enhanced measurement and verification of energy efficiency savings in commercial buildings

  B. Grillone, G. Mor Martinez, S. Danov, J. Cipriano, A. Sumper

  Applied Energy (2021).

  
  

  Abstract

  Methods to obtain accurate estimations of the savings generated by building energy efficiency interventions are a topic of great importance, and considered to be one of the keys to increase capital investments in energy conservation strategies worldwide. In this study, a novel data-driven methodology is proposed for the measurement and verification of energy efficiency savings, with special focus on commercial buildings and facilities. The presented approach involves building use characterization by means of a clustering technique that allows to extract typical consumption profile patterns. These are then used, in combination with an innovative technique to evaluate the building’s weather dependency, to design a model able to provide accurate dynamic estimations of the achieved energy savings. The method was tested on synthetic datasets generated using the building energy simulation software EnergyPlus, as well as on monitoring data from real-world buildings. The results obtained with the proposed methodology were compared with the ones provided by applying the time-of-week-and-temperature (TOWT) model, showing up to 10% CV(RMSE) improvement, depending on the case in analysis. Furthermore, a comparison with the deterministic results provided by EnergyPlus showed that the median estimated savings error was always lower than 3% of the total reporting period consumption, with similar accuracy retained even when reducing the total training data available.

  Abstract
  Methods to obtain accurate estimations of the savings generated by building energy efficiency interventions are a topic of great importance, and considered to be one of the [...]

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• A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings

  B. Grillone, S. Danov, A. Sumper, J. Cipriano, G. Mor Martinez

  A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings (2020).

  
  

  Abstract

  Increasing the energy efficiency of the built environment has become a priority worldwide and especially in Europe. Because of the relatively low turnover rate of the existing built environment, energy efficiency retrofitting appears to be a fundamental step in reducing its energy consumption. Last experiences have shown that there is a vast energy efficiency potential lying in the building stock, and it is mainly untapped. One of the reasons is a lack of robust methodologies able to evaluate the effect of applied energy efficiency measures and inform about the expected impact of potential retrofitting strategies. Nowadays, dynamic measured data coming from automated metering infrastructure provides valuable information to evaluate the effect of energy conservation strategies. For this reason, energy performance modeling and assessment methods based on this data are starting to play a major role. In this paper, several methodologies for the measurement and verification of energy savings, and for the prediction and recommendation of energy retrofitting strategies, are analysed in detail. Practitioners looking at different options for these two processes, will find in this review a thorough and detailed overview of the different methods that can be used. Guidance is also provided to determine which method could work best depending on the specific case under analysis. The reviewed approaches include statistical learning models, machine learning models, Bayesian methods, deterministic approaches, and hybrid techniques that combine deterministic and data-driven modeling. Existing research gaps are identified and prospects for future investigation are presented within the main conclusions of this research work.

  Abstract
  Increasing the energy efficiency of the built environment has become a priority worldwide and especially in Europe. Because of the relatively low turnover rate of the existing [...]

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• Model Predictive Control applied to thermostatic controlled systems

  F. Lazzari, G. Mor Martinez, J. Cipriano, E. Gabaldon, S. Danov, B. Grillone

  Florencia Lazzari's personal collection (2020). 1

  
  

  Abstract

  A Model Predictive Control (MPC) was developed to optimize the performance of a residential heat pump. To test the MPC, the real system was replaced by a Modelica emulator of the entire house. The building’s thermal behavior model was developed as an Auto-Regressive linear model with eXogenous variables (ARX) and the optimization algorithm was based in a genetic algorithm. The proposed predictive model to characterize the building’s thermal behavior was developed successfully. And the MPC is already implemented and validated, but the total integration with the emulator of the system and the feedback loop has not been yet assembled. In this way, we are looking towards to end this task and complete the further analysis.

  Abstract
  A Model Predictive Control (MPC) was developed to optimize the performance of a residential heat pump. To test the MPC, the real system was replaced by a Modelica emulator [...]

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• L'ús actual de l'energia solar. Aplicacions als edificis

  X. Cipriano, J. Cipriano

  L'Atzavara (2004). Vol. 12, pp. 51-60

  
  

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• Design methodology for low cost tubular digesters

  J. Martí-Herrero, J. Cipriano

  Bioresource Technology (2012). Vol. 108, pp. 21-27

  
  

  Abstract

  The aim of this paper is to present a novel, universal, methodology for the design of low cost tubular digesters. This method improves on the established methodology by avoiding assumptions that tend to reduce the final hydraulic retention time (HRT) of digesters once installed. This work recommends designing the digester using trench cross-sectional area and proposes an optimization of the trench dimensions with respect to the angle of the walls and the relationship between the length of the biogas bell and the top width of the trench. The influence of the biogas pressure is considered. A simple geometrical analysis is presented that, by parameterization, can be applied in a wide range of situations.

  Abstract
  The aim of this paper is to present a novel, universal, methodology for the design of low cost tubular digesters. This method improves on the established methodology by avoiding [...]

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• Evaluation of a multi-stage guided search approach for the calibration of building energy simulation models

  J. Cipriano, G. Mor Martinez, D. Chemisana, D. Pérez, G. Gamboa, X. Cipriano

  Energy and Buildings (2015). Vol. 87, pp. 370-385

  
  

  Abstract

  This paper is focused on increasing the knowledge on methods for calibrating BES models and to get more insights of different approaches for the optimization of the calibration process. The paper will be centred in the evaluation of a multistage guided search approach. It defines an iterative optimization procedure which starts with the assignment of probabilistic density functions to the unknown parameters, followed by a random sampling and running batch of simulations. It then finishes with an iterative uncertainty and sensitivity analysis combined with a re-assignment of the ranges of variation of the strong parameters. The procedure converges when no new influencing parameters are found. This method is applied to a real case study consisting of an unoccupied office building located in Lleida (Spain). The measured indoor temperature has been used to determine the uncertainty and precision of the method. The effect of the size of the sampling, the number of iterations and the parameters of the global sensitivity method are analyzed in detail. The results of this paper exemplify the degree of accuracy of multistage guided search approaches, and illustrate the reasons how these analyses can contribute to the improvement of more refined calibration methods.

  Abstract
  This paper is focused on increasing the knowledge on methods for calibrating BES models and to get more insights of different approaches for the optimization of the [...]

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Articles (Documents not available in Scipedia)

• Assessing the nearly zero-energy building gap in university campuses with a feature extraction methodology applied to a case study in Spain

  M Medrano, JM Martí, L Rincón, G Mor, J Cipriano, M Farid

  International Journal of Energy and Environmental Engineering, 1-21, 2018

• Using matrix factorisation for the prediction of electrical quantities

  F Lecron, Z De Grève, F Vallée, G Mor, D Pérez, S Danov, J Cipriano

  CIRED-Open Access Proceedings Journal 2017 (1), 2568-2571, 2017

• Developing indicators to improve energy action plans in municipalities: An accounting framework based on the fund-flow model

  X Cipriano, G Gamboa, S Danov, G Mor, J Cipriano

  Sustainable cities and society 32, 263-276, 2017

• Comparing time-series clustering approaches for individual electrical load patterns

  Z De Greve, F Lecron, F Vallee, G Mor, D Perez, S Danov, J Cipriano

  CIRED-Open Access Proceedings Journal 2017 (1), 2165-2168, 2017

• ZEBRA 2020-NEARLY ZERO-ENERGY BUILDING STRATEGY 2020. Strategies for a nearly Zero-Energy Building market transition in the European Union

  A Toleikyte, L Kranzl, R Bointner, F Bean, J Cipriano, M De Groote, ...

  ZEBRA 2020, 2016

• ZEBRA 2020-Nearly Zero‐Energy Building Strategy 2020. D6. 2: Strategies for nZEB market transition on national level

  A Toleikyte, J Cipriano, S Schimschar, D Kretschmer, R Guillin, M Klinski, ...

  ZEBRA 2020, 2016

• Development of a dynamic model for natural ventilated photovoltaic components and of a data driven approach to validate and identify the model parameters

  J Cipriano, G Houzeaux, G Mor, U Eicker, J Carbonell, S Danov

  Solar Energy 129, 310-331, 2016

• Hidden Markov Models for indirect classification of occupant behaviour

  J Liisberg, JK Møller, H Bloem, J Cipriano, G Mor, H Madsen

  Sustainable Cities and Society 27, 83-98, 2016

• Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment pr...

  X Cipriano, A Vellido, J Cipriano, J Martí-Herrero, S Danov

  Energy Efficiency, 1-24, 2016

• Dynamic Methodology for the Evaluation of Occupant Behaviour and Residential Energy Consumption

  GM J. Bloem, H. Madsen, J. Kloppenborg, J. Liisberg, J. Cipriano

  Proceedings of the 8th International Conference on Energy Efficiency in …, 2015

• Empowering customer engagement by informative billing: a European approach

  S Danov, J Cipriano, A Meganck, L Vandevelde

  23rd International Conference and Exhibition on Electricity Distribution …, 2015

• Evaluation of a multi-stage guided search approach for the calibration of building energy simulation models

  J Cipriano, G Mor, D Chemisana, D Pérez, G Gamboa, X Cipriano

  Energy and Buildings 87, 370-385, 2015

• Energy characterization and experimental validation of natural ventilated semitransparent double skin PV components

  J Cipriano

  Universitat de Lleida, 2014

• Research activities of the Building Energy and Environment (BEE) group of CIMNE

  J Cipriano, D Pérez

  I Jornada de la recerca i la innovació tecnològica al Campus de la UPC a …, 2013

• Numerical analysis of the most appropriate heat transfer correlations for free ventilated double skin photovoltaic façades

  J Cipriano, G Houzeaux, D Chemisana, C Lodi, J Martí-Herrero

  Applied Thermal Engineering 57 (1-2), 57-68, 2013

• Approaches to evaluate building energy performance from daily consumption data considering dynamic and solar gain effects

  S Danov, J Carbonell, J Cipriano, J Martí-Herrero

  Energy and Buildings 57, 110-118, 2013

• Modelling the heat dynamics of a monitored test reference environment for building integrated photovoltaic systems using stochastic differential equations

  C Lodi, P Bacher, J Cipriano, H Madsen

  Energy and Buildings 50, 273-281, 2012

• An outdoor test reference environment for double skin applications of building integrated photovoltaic systems

  JJ Bloem, C Lodi, J Cipriano, D Chemisana

  Energy and Buildings 50, 63-73, 2012

• Design methodology for low cost tubular digesters

  J Martí-Herrero, J Cipriano

  Bioresource Technology 108, 21-27, 2012

• Design and monitoring of an improved test reference environment for the evaluation of BIPV systems

  C Lodi, J Cipriano, JJ Bloem, D Chemisana

  Proceedings of the 25th European Photovoltaic Solar Energy Conference …, 2010

• Monitoring and modelling energy efficiency of municipal public buildings: case study in Catalonia region

  X Cipriano, J Carbonell, J Cipriano

  International Journal of Sustainable Energy 28 (1-3), 3-18, 2009

• Development and characterization of semitransparent double skin PV façades

  J Cipriano, C Lodi, D Chemisana, G Houzeaux, O Perpinan

  Proceedings of the EuroSun 2008, 8, 2008

• L'ús actual de l'energia solar. Aplicacions als edificis

  X Cipriano, J Cipriano

  Atzavara, L', 51-60, 2004