Validation of calibrated energy models: Common errors

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

Towards a new generation of building envelope calibration

Building energy performance (BEP) is an ongoing point of reflection 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

Probabilistic load forecasting for building energy models

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 with the probability that the load forecast error is less than a certain value. This map can then be applied to the forecast load that is provided by the BEM by applying the prediction intervals with their associated probabilities to its outputs. The methodology was implemented and evaluated in a real school building in Denmark. The results show that the percentage of the real values that are covered by the prediction intervals for the testing month is greater than the confidence level (80%), even when a small amount of data are used for the creation of the uncertainty map; therefore, the proposed method is appropriate for predicting the probabilistic expected error in load forecasting due to the use of weather forecast data

Ground characterization of building energy models

The calibration of building energy models is crucial for their use in some applications that depend on their accuracy for adequate performance, such as demand response and model predictive control (MPC). In general, energy models offer many possibilities/strategies when characterizing a construction system, and such a characterization is key when analyzing both its thermal behavior and its energy impact. This research analyzes the different ways to characterize the thermal interaction of the building energy model (BEM) with the ground, comparing conventional approaches with new approaches based on both optimization of the former and dynamic ground characterizations. Using a model adjusted to a real case study, each of the existing options are analyzed, in which a different control of the ground temperature both in terms of its temporal oscillation and its location in the building (based on thermal zones) is taken into account. Exhaustive monitoring of a real building and measuring the ground and ground floor surface temperatures have made establishing which EnergyPlus components/objects best characterize the ground-slab interaction possible, both in terms of the simplicity of modeling and the cost (economic and technical) required for each of them. As will be seen, there are objects with an excellent cost/effectiveness ratio when characterizing the groun

Programa AQRDATE aplicado en rehabilitación en actividades de la vida diaria en pacientes con daño cerebral adquirido

Versión electrónica de la ponencia presentada en INTERA 2011: International Technology Robotics Applications Congress, celebrado en Mieres en 2011El proyecto que proponemos consiste en la utilización de un dispositivo móvil que facilite la realización de las Actividades de la Vida Diaria (AVD) en personas que han sufrido un daño cerebral adquirido. Estas dejan de realizarlas con autonomía debido a una alteración en las funciones mentales superiores (atención, funciones ejecutivas,…). Para conseguir la funcionalidad propuesta se combinan etiquetas 2D en las cuales se almacena la información (análisis de tareas de las AVD) con un teléfono móvil. Las tareas que se han seleccionado son: hacer un zumo de naranja, preparar un café con leche, preparar dos tostadas y untarlas con mantequilla y mermelada. Estas se han subdivido en subtareas que se irán mostrando en la pantalla del teléfono móvil de forma secuenciada, lo cual permitirá al usuario acceder a la información. El sistema por lo tanto ofrece al usuario la posibilidad de: planificar, organizar, secuenciar y ejecutar la actividad propuest

Model predictive control optimization via genetic algorithm using a detailed building energy model

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

“Pororo Ká”. Flujo diastólico paradójico y aneurisma apical del ventrículo izquierdo. A propósito de un caso

A 71-year-old male with mechanical aortic valve replacement evolves with progressive impairment of functional capacity. Transthoracic echocardiography showed dilatation and moderate systolic dysfunction of the left ventricle. An apical aneurysm with systolic influx to the aneurysmal cavity and diastolic paradoxic flow of the aneurysm to the midventricular region was found. This flow was counterposed to the passive diastolic filling of the left atrium. The identification of this alteration has a prognostic role in relation to the association with increased incidence of sudden death, thromboembolic events and impairment of functional capacity and left ventricular systolic function.Hombre de 71 años con reemplazo mecánico de válvula aórtica que evoluciona con deterioro progresivo de la capacidad funcional. La ecocardiografía transtorácica mostró dilatación y disfunción sistólica moderada del ventrículo izquierdo. Se encontró un aneurisma apical con flujo sistólico hacia la cavidad aneurismática y flujo paradójico diastólico del aneurisma a la región medioventricular. Este flujo se contraponía al llenado diastólico pasivo de la aurícula izquierda. La identificación de esta alteración tiene un papel pronóstico en relación con la asociación de aumento de incidencia de muerte súbita, eventos tromboembólicos y deterioro de la capacidad funcional y la función sistólica ventricular izquierda

Methodology for the quantification of the impact of weather forecasts in predictive simulation models

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..

An active mode of learning: students collaboration in a research project on masonry mortar

During the 2012-2013 academic year, a practical work was proposed to the students of the fourth year of the School of Architecture of the University of Navarre (ETSAUN), in the Building Construction IV subject of the Building Construction, Services and Structures Department (CIE), in the context of implicating students in academic activities, specifically designed to allow them to improve essential capabilities and abilities required for their future professional exercise