Analysis of uncertainty indices used for building envelope calibration

Ruiz, Germán Ramos; Bandera, Carlos Fernández

doi:10.1016/j.apenergy.2016.10.054

Cited by 40 publications

(20 citation statements)

References 27 publications

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“…For the application of this procedure, the BEM used in the optimization must be a calibrated energy model that accurately represents the building's energy performance. Several authors of previous research described the calibration process for detailed energy models [36][37][38][39][40]. In this case, the model is synthetic, which means that it is assumed to fit perfectly to the real building.…”

Section: Building Energy Model (Bem)mentioning

confidence: 99%

Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass

et al. 2020

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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 % .

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Section: Building Energy Model (Bem)mentioning

confidence: 99%

Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass

et al. 2020

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“…For the building envelope parameters' definition, a calibrated model that represents the accurate thermal dynamics of the real building is used. The calibration process is based on the author's previous work [15][16][17]. The resulting calibrated model complies with the international quality standards International Performance Measurement and Verification Protocol (IPMVP) [35], Federal Energy Management Program (FEMP) [36,37] and American Society of Heating, Refrigerating and Air-Conditioning Engineers guidelines (ASHRAE) [38,39].…”

Section: Test Site Descriptionmentioning

confidence: 99%

“…• Simulation model accuracy: Previous work from authors have developed a calibration methodology to get accurate simulation models and predictions [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Methodology for the Quantification of the Impact of Weather Forecasts in Predictive Simulation Models

Segarra

Ruiz

et al. 2019

Energies

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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 mean indoor temperature and energy demand predictions in a building located in Pamplona, Spain. The main novel concepts in this paper are: first, the characterization of the weather forecast error for a specific weather data provider and location and its effect in the building’s load prediction. The error is calculated based on recorded hourly data so the results are provided on an hourly basis, avoiding the cancel out effect when a wider period of time is analyzed. The second is the classification and analysis of the data hour-by-hour to provide an estimate error for each hour of the day generating a map of hourly errors. This application becomes necessary when the building takes part in the day-ahead programs such as demand response or flexibility strategies, where the predicted hourly load must be provided to the grid in advance. The methodology developed in this paper can be extrapolated to any weather forecast provider, location or building.

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“…Because of that, each experiment requires a careful selection of the objective function. The authors have extensive experience on working with different objective functions in the same simulation environment [50,52,53].…”

Section: Simulation and Optimization Toolsmentioning

confidence: 99%

Exergy As a Measure of Sustainable Retrofitting of Buildings

Bandera

Mardones

et al. 2018

Energies

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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 façade, 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.

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Analysis of uncertainty indices used for building envelope calibration

Cited by 40 publications

References 27 publications

Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass

Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass

Methodology for the Quantification of the Impact of Weather Forecasts in Predictive Simulation Models

Exergy As a Measure of Sustainable Retrofitting of Buildings

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