A unified model for the simulation of oil, gas and biomass space heating boilers for energy estimating purposes. Part I: Model development

Haller, Michel Y.; Paavilainen, Janne; Konersmann, Lars; Haberl, Robert; Dröscher, Angela; Frank, Elimar; Bales, Chris; Streicher, Wolfgang

doi:10.1080/19401491003671944

Cited by 23 publications

(14 citation statements)

References 2 publications

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“…In this study the pellet boilers have been simulated by means of the TRNSYS Type 869 boiler model, which is described in detail in [14,30]. The model calculates the mass and energy balance of the boiler under time variable inputs, thus describing the boiler operation in dynamic conditions.…”

Section: Boiler Modelmentioning

confidence: 99%

“…TRNSYS is a software used for the dynamic simulation of systems, in particular for buildings and energy systems [28]. The Nomenclature c p,fg specific heat capacity of the dry flue gases (kJ kg À1 K À1 ) c p,vap specific heat capacity of water vapour (kJ kg À1 K À1 ) c p,w specific heat capacity of water (kJ kg À1 K À1 ) C therm thermal capacitance of the boiler (kJ K À1 ) dT nom , dT hx,wat parameters for the determination of the flue gas temperature (K) fac A,lam, fac B,lam parameters for the determination of the excess air ratio ( [26] and Type 869 [30]. As the latter is the most extensive model, in the present study the two pellet boilers have been simulated by means of Type 869 (version 502), a non-standard TRNSYS Type distributed by SPF Institut fur Solartechnik [31].…”

Section: Introductionmentioning

confidence: 99%

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Experimental validation of a thermodynamic boiler model under steady state and dynamic conditions

et al. 2015

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Section: Boiler Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental validation of a thermodynamic boiler model under steady state and dynamic conditions

et al. 2015

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“…A unified model for the simulation of oil, gas, pellets (Pel) and wood chips (Chp) space heating boilers for energy estimating purposes was presented in Part I of this article (Haller et al 2010), referred to in this article as 'Part I'. In this follow-up article, results from laboratory measurements performed on nine different space heating boiler units (Table 1) are presented.…”

Section: Introductionmentioning

confidence: 99%

A unified model for the simulation of oil, gas and biomass space heating boilers for energy estimating purposes. Part II: Parameterization and comparison with measurements

Haller

Paavilainen

Konersmann

et al. 2011

Journal of Building Performance Simulation

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A semi-physical model for the simulation of oil, gas and biomass space heating boilers has been parameterized based on measurements on nine different boiler units and simulation results have been compared to results obtained from measurements in steady state and transient operation. Although the agreement between simulated and measured boiler efficiencies was within the range of measurement uncertainties in most cases, model improvements are expected to be possible concerning the heat capacitance modelling in cycling on/off operation as well as influences of start and stop behaviour on the overall efficiency. It is found that electricity consumption during cycling on/off operation of small pellets or oil space heating boilers may have a significant influence on the overall energy balance of these units. This influence increases strongly with decreasing heat load and increasing number of on/off cycles.

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“…Windows have been modeled with LBNL Window 6.3 [60] and the linear thermal transmittances of thermal bridges calculated with LBNL THERM 6.3 [61]. TRNSYS "Type 56" has been used for multizone building modeling and "Type 869" [62,63] for the heating systems, together with "Type 2" for the ON-OFF control, "Type 3" for the calculation of the pump power consumption and "Type 31" for the estimation of distribution heat losses of pipes. As regards the climatic solicitations, Reindl et al [64] and Perez et al [65] models have been implemented for the calculation of the solar irradiation on the external surfaces, the fictive sky vault temperature estimated with "Type 69" and the other weather variables read directly from the reference year input.…”

Section: Building Energy Simulation and Optimization Objectivesmentioning

confidence: 99%

Impact of Reference Years on the Outcome of Multi-Objective Optimization for Building Energy Refurbishment

et al. 2017

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Abstract:There are several methods in the literature for the definition of weather data for building energy simulation and the most popular ones, such as typical meteorological years and European test reference years, are based on Finkelstein-Schafer statistics. However, even starting from the same multi-year weather data series, the developed reference years can present different levels of representativeness, which can affect the simulation outcome. In this work, we investigated to which extent the uncertainty in the determination of typical weather conditions can affect the results of building energy refurbishment when cost-optimal approach is implemented for the selection of energy efficiency measures by means of the NSGA-II genetic algorithm coupled with TRNSYS simulations. Six different reference years were determined for two north Italy climates, Trento and Monza, respectively in the Alpine and in the continental temperate regions. Four types of energy efficiency measures, related to both building envelope and HVAC system, were applied to six existing building typologies. Results showed how the choice of reference year can alter the shape of the Pareto fronts, the number of solutions included and the selection among the alternatives of the energy efficiency measures, for the entire front and, in particular, for energy and economic optima.

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A unified model for the simulation of oil, gas and biomass space heating boilers for energy estimating purposes. Part I: Model development

Cited by 23 publications

References 2 publications

Experimental validation of a thermodynamic boiler model under steady state and dynamic conditions

Experimental validation of a thermodynamic boiler model under steady state and dynamic conditions

A unified model for the simulation of oil, gas and biomass space heating boilers for energy estimating purposes. Part II: Parameterization and comparison with measurements

Impact of Reference Years on the Outcome of Multi-Objective Optimization for Building Energy Refurbishment

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