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Due to climate change and hot summers in most of Algeria’s regions, air conditioning has become a thorny issue, resulting in excessive energy consumption. This research focuses on the implementation of dew point evaporative coolers as an alternative to conventional air conditioners. The desirability function approach is used to predict the optimal operating parameters and compare the thermal performance and water consumption of two dew point cooler configurations (counter flow-regenerative cooler and combined parallel–regenerative cooler) under different climatic conditions in Algeria. A numerical model is developed and validated using literature data for regenerative and combined dew point evaporative systems. Parametric analysis and multi- to single-objective optimization simulations were performed with the GenOpt simulation software, identifying the most influential parameters and predicting the optimal conditions for both configurations. The findings suggest that the optimal channel spacing, working air ratio, and primary air velocity are identical for both technologies.However, the cooling capacity and the coefficient of performance of the combined parallel–regenerative cooler are higher in drier climates. When both technologies are compared at nearly equal dew point efficiency, the combined configuration improves cooling capacity by 5%, while increasing water consumption by about 40%. This study provides a useful method for assessing cooling capacity and adapting suitable dew point technology to various climates and cities.

For a positive net building (PNEB), the paper presents its need, and tools to achieve its design. The PNEB should provide the maximum thermal comfort with a minimum of energy, primary energy, and exergy consumption, .and reduction of the use of energy resources, maximizing energy security, as well as the minimum impact on the environment. This very useful knowledge is also needed for identifying energy efficiency, as well as for dictating the right energy management strategies of a country. Then, the paper presents the software for a energy simulation and optimization of PNEB. After that, the paper describes the three examples connected to the PNEB. The first example is a simulation of a residential PNEB in Serbian conditions, second the optimization of photovoltaics panels area at Serbian zero-net energy building, third the description of an the building and optimizing energy performances, by placing the solar collector in the optimum position.

• Performance of PCM building models in ten cities of Algeria was evaluated. • Optimization is based on hypothetical h-T curves derived from a validated model. • The HVAC system operate according to Fanger's PMV model. The use of phase change materials (PCMs) in the building envelope has emerged as an attractive passive design strategy that can be used to improve the energy performance of buildings. This paper discusses the effect of using PCMs on the thermal performance of shaded and unshaded lightweight structures in different Algerian climatic zones. A simulation-based optimization was carried out by coupling EnergyPlus and GenOpt tool, to determine the optimum melting temperature of PCM when integrated into the building envelope. Results show that the shaded building with PCM is a preferred design model in majority of Algerian climates when it is free floating. The annual percentage of thermal comfort ranges between 44.13% and 59.11% in cities where the PCMs showed positive potential. Furthermore, the optimization results show that the PCMs achieved a modest cooling energy saving for mechanically-ventilated buildings in summer, especially in hot-dry climate with optimal melting points equal to or close to 28 °C. The control of solar heat gain by using shading devices is critical to enhance the thermal performance in summer. In winter, the PCMs achieved a noticeable reduction in the heating energy requirements where it reached a maximum of 63.23% in the city of Tamanrasset. The shading device is not recommended during the winter because it hinders the use of solar radiation for passive heating. During this season, the optimal melting points of PCMs are generally bounded between 18.50 °C and 21.25 °C. When considering both periods, the most advantageous design varies from climatic zone to another. [ABSTRACT FROM AUTHOR]

Featured Application: The results of this paper can support the design of nearly zero-energy single-family houses in the Italian context. The provided methodological framework can support the design of nearly zero-energy buildings and be replicated in different contexts. The effective design of nearly zero-energy buildings depends on a large set of interdependent variables, which affect both energy demand and supply. Considering them simultaneously is fundamental when searching for optimal design of nearly zero-energy buildings, as encouraged by the EU in the second recast of the Energy Performance of Building Directive (EPBD). This paper presents the application of the new energy demand and supply simultaneous optimization (EDeSSOpt) methodology to optimize the design of a single-family house in the Italian context. Both primary energy optimization and financial optimization are carried out in the context of European regulations. Robustness of the resulting optimal solution is studied through analysis of optimum neighborhoods. The resulting cost-optimized solution relies on a moderately insulated envelope, a highly efficient system, and 34% of coverage from renewables. The energy-optimized solution requires a higher level of insulation and a higher coverage from renewables, demonstrating that there is still a gap between energy and cost optimums. Beyond the results, integrated optimization by means of EDeSSOpt is demonstrated to better minimize cost functions while improving the robustness of results. [ABSTRACT FROM AUTHOR]

Featured Application: This work could contribute to evidence strengths and weaknesses of manual and automatic calibration of building dynamic simulation models leading at improving the quality of building retrofit solutions investigation. Energy reduction can benefit from the improvement of energy efficiency in buildings. For this purpose, simulation models can be used both as diagnostic and prognostic tools, reproducing the behaviour of the real building as accurately as possible. High modelling accuracy can be achieved only through calibration. Two approaches can be adopted—manual or automatic. Manual calibration consists of an iterative trial and error procedure that requires high skill and expertise of the modeler. Automatic calibration relies on mathematical and statistical methods that mostly use optimization algorithms to minimize the difference between measured and simulated data. This paper aims to compare a manual calibration procedure with an automatic calibration method developed by the authors, coupling dynamic simulation, sensitivity analysis and automatic optimization using IDA ICE, Matlab and GenOpt respectively. Differences, advantages and disadvantages are evidenced applying both methods to a dynamic simulation model of a real office building in Rome, Italy. Although both methods require high expertise from operators and showed good results in terms of accuracy, automatic calibration presents better performance and consistently helps with speeding up the procedure. [ABSTRACT FROM AUTHOR]

Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO2 emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates the energy performance of an individual house integrating a solar Trombe wall containing PCM with respect to heating demand and thermal comfort applications. The thermal energy performance of the design house was simulated using Dymola/Modelica, the thermal building simulation tool, whereby the optimization of objective functions as regards heating demand and thermal comfort was executed using GenOpt, the generic optimization software. Optimization of the solar Trombe wall focuses on the feasibility to find the optimal PCM parameters when running GenOpt, which consist of latent heat, melting temperature, PCM thickness and thermal conductivity, in order to minimize both the annual energy consumption for heating and the number of hours of thermal discomfort. The parametric study was first conducted for each PCM parameter so as to not only observe its effect on the identified energy performance, but also ensure the absence of errors in simulation runs before performing the optimization. The ‘Coordinate Search’ Generalized Pattern Search (GPS) algorithm was applied to minimize the objective function, whereas the ‘Weighted Sum Approach’ was used to solve the multi-objective function problem. Results showed that the higher the latent heat, the lower the heating demand and the greater the thermal comfort. The results of these parametric studies show that for the effect of the parameter on heating, demand is quite limited (1–2 kWh·m−2·year−1) whereas the effect on thermal comfort is more significant. The optimal PCM melting temperature is higher for warmer climates; it is also higher for the studied case applying the optimization method to minimize the objective function by assigning the number of hours of thermal discomfort (from 32.8 ∘C to 35.9 ∘C, depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 ∘C to 32.9 ∘C, again depending on weather).

It is well known that nowadays a significant part of the total energy consumption is related to buildings, so research for improving building energy efficiency is very important. This paper presents our investigations about the dimensioning of horizontal overhangs in order to determine the minimum annual consumption of building primary energy for heating, cooling and lighting. In this investigation, embodied energy for horizontal roof overhangs was taken into account. The annual simulation was carried out for a residential building located in the city of Belgrade (Serbia). Horizontal overhangs (roof and balcony) are positioned to provide shading of all exterior of the building. The building is simulated in the EnergyPlus software environment. The optimization of the overhang size was performed by using the Hooke Jeeves algorithm and plug-in GenOpt program. The objective function minimizes the annual consumption of primary energy for heating, cooling and lighting of the building and energy spent to build overhangs. The simulation results show that the building with optimally sized roof and balcony overhangs consumed 7.12% lessprimary energy for heating, cooling and lighting, compared to the house without overhangs. A 44.15% reduction in cooling energy consumption is also achieved.

Increasing the insulation thickness in residential buildings leads to the reduction of operational CO2 emissions but simultaneously increases the embodied CO2 due to the insulation material. The environmentally optimum insulation thickness exists at a point where the total CO2 emissions are minimum. This work presents the optimum insulation thickness for external walls of different composition and orientation, for both the heating and the cooling period. Three different wall types and insulation materials are being presented. The dynamic thermal behavior of the external walls simulation is based on the heat conduction transfer functions method and using the hourly climatic data available for the city of Athens, Greece. The optimization methodology uses a single objective function approach, combining the simulation of the thermal behavior of external walls with an optimization algorithm. The results indicate that the optimum insulation thickness varies from 11.2 to 23.4 cm and is different for each orientation, wall type, and insulation material. In addition, the total annual CO2 emissions per unit area of the wall can be reduced by 63.2%–72.2%, depending on the insulation material and its position on the wall. [ABSTRACT FROM AUTHOR]

Hospitals present a widely recognized margin for energy conservation due to their elevated final energy use intensity. Specifically, operating rooms are among the functional areas with greatest energy demand in hospitals, given the stringent indoor conditions for patients and surgical staff. However, energy efficiency in surgical facilities has traditionally been overlooked by the scientific literature in favor of guaranteeing adequate air quality conditions. This paper assesses the potential energy savings that could be achieved in a surgical suite in a Spanish hospital by lowering the current ventilation rates to the lowest energy-demanding values recommended by the proper Spanish standard and other international codes. Likewise, the paper assesses the actual hygrothermal and ventilation conditions in the suite based on the results of a continuous monitoring campaign performed for a period of 12 days. Simulations undertaken with a dynamic energy model specifically developed and calibrated for this work revealed that the average energy intensity of the suite is 1021 kWh/m 2 /year (1685 kWh/m 2 /year for operating rooms), with 80% of the total annual thermal demand corresponding to periods of inactivity. In addition, energy savings between 40% and 80% are possible while complying with both national and international standards. [ABSTRACT FROM AUTHOR]

Nowadays, the design of energy efficient and comfortable building results as the solution to a complex optimization that involves a great number of interdependent variables. In such a complex system that is characterized by many requirements, sometimes conflicting, the use of an integrated design approach can speed up the design process, allow evaluating and comparing a great number of design options and lead to optimized performance at multiple levels. We present the conception of a replicable methodology, including the integrated tools and metrics, for supporting the integrated design of the building envelope, aiming at minimizing the building total energy demand (resulting from the sum of heating, cooling and lighting energy needs) in a thermal and visual comfort context. The methodology relies on a simulation-based optimization process. For each of the two thousand of design solutions that are analyzed within the design space of the problem, the thermal and visual comfort conditions are evaluated at the same time. A “filter” approach is used for combining the different objectives. The methodology is applied to the design of a school classroom as a reference case study. Results are compared for four different building orientations and two different climatic conditions. The differences in design between the optimized building configurations in the different location and orientation emerge from the study, however resulting in similar energy performance (total primary energy demands in the range 78.6–82.8 kWh/m 2 y for Turin and 57.7–60.1 for Palermo). In all cases, energy-optimal solutions result as nearly optimal also from the comfort point of view, which demonstrate the validity of the implemented total energy approach. Beyond the numerical results, we provide an effective integrated methodology that is able to support designers in defining a unique energy and comfort optimized solution to be implemented in the real design analyzing the design space and determining the optimal set of passive solutions to minimize the total energy needs of a building in a context of good comfort conditions, going beyond the Pareto optimality concept and without dealing through complex multi-objective optimization processes. [ABSTRACT FROM AUTHOR]

Optimizing efficiency in the operation of the HVAC system of existing buildings requires the construction of a thermal dynamic model of the building, which may be challenging because architectural metadata may be missing or obsolete. Based on a suitable set of measured data, this paper presents a novel practical methodology to create and automatically derive thermal models of existing buildings in high-fidelity simulators for energy management. To this end, the philosophy of grey-box strategies is followed to simplify the modeling and avoid the requirement of architectural metadata, facilitating and expediting the process. First, a building model with a highly reduced number of parameters is constructed by exploiting the existing similarities in the materials of the buildings and simplifying their elements to a simple one-layer parameterization. Then, the parameters of the derived model are iteratively updated while minimizing the error between the real temperature evolution and that generated by the model being identified. For this purpose, data of the room air temperature, estimated occupancy, weather conditions, and variables of the HVAC system are assumed to be available in suitable zones of the building to apply the creation and identification processes of the model, allowing that a whole digital twin of the building is constructed. The methodology is presented by its application to a real case study: the Nimbus Research Centre building at Munster Technological University, located in Cork (Ireland). The high-fidelity simulator software TRNSYS is used for the modeling task, together with the GenOpt optimization program. The results demonstrate that the proposed methodology yields a highly accurate model of the building, capable of representing reality with RMSE values consistently below 0.6 C ∘ during open-loop validation periods of up to four days. The findings suggest that this methodology may outperform other modeling techniques reported in the literature. Importantly, the proposed technique is less complex and time-consuming to implement than many of the alternatives. • Thermal modeling of existing buildings avoiding the use of architectural metadata. • Novel integration of grey-box modeling methods with high-fidelity simulators. • The proposed method copes with the drawbacks of the models found in the literature. • Methodology validated with experimental data from the Nimbus Centre (Ireland). • Results show high accuracy of greatly simplified models—RMSE<0.6 °C in 4-day horizons. [ABSTRACT FROM AUTHOR]

Street lighting plays an important role in the comfort and safety of drivers and pedestrians, so the control and management of the lighting systems operation and consumption is an essential service for a city. In this document, a methodology is presented to calibrate lighting models in order to assess the lighting performance through simulation techniques. The objective of this calibration is to identify the maintenance factor of the street lamps, determine the real average luminance coefficient of the road pavement and adapt the reflection properties of the road material. The method is applied in three stages and is based on the use of Radiance and GenOpt software suits for the modeling, simulation, and calibration of lighting scenes. The proposed methodology achieves errors as low as 13% for the calculation of illuminance and luminance, evincing its potential to assess the actual lighting conditions of a road.

Operating rooms are stringent controlled environments. All influential factors, in particular, airborne particles, must be within the limits established by regulations. Therefore, energy efficiency stays in the background, prioritizing safety and comfort in surgical areas. However, the potential of improvement in energy savings without compromising this safety is broad. This work presents a new procedure, based on calibrated simulations, that allows the identification of potential energy savings in an operating room, complying with current airborne particle standards. Dynamic energy and airborne particle models are developed and then simulated in TRNSYS and calibrated with GenOpt. The methodology is validated through experimental contrast with a real operating room of a hospital in Spain. A calibrated model with around 2% of error is achieved. The procedure determines the variation in particle concentration according to the flow rate of ventilation supplied and the occupancy of the operating room. In conclusion, energy savings up to 51% are possible, reducing ventilation by 50% while complying with airborne particles standards.

The effective design of nearly zero-energy buildings depends on a large set of interdependent variables, which affect both energy demand and supply. Considering them simultaneously is fundamental when searching for optimal design of nearly zero-energy buildings, as encouraged by the EU in the second recast of the Energy Performance of Building Directive (EPBD). This paper presents the application of the new energy demand and supply simultaneous optimization (EDeSSOpt) methodology to optimize the design of a single-family house in the Italian context. Both primary energy optimization and financial optimization are carried out in the context of European regulations. Robustness of the resulting optimal solution is studied through analysis of optimum neighborhoods. The resulting cost-optimized solution relies on a moderately insulated envelope, a highly efficient system, and 34% of coverage from renewables. The energy-optimized solution requires a higher level of insulation and a higher coverage from renewables, demonstrating that there is still a gap between energy and cost optimums. Beyond the results, integrated optimization by means of EDeSSOpt is demonstrated to better minimize cost functions while improving the robustness of results.

Energy reduction can benefit from the improvement of energy efficiency in buildings. For this purpose, simulation models can be used both as diagnostic and prognostic tools, reproducing the behaviour of the real building as accurately as possible. High modelling accuracy can be achieved only through calibration. Two approaches can be adopted—manual or automatic. Manual calibration consists of an iterative trial and error procedure that requires high skill and expertise of the modeler. Automatic calibration relies on mathematical and statistical methods that mostly use optimization algorithms to minimize the difference between measured and simulated data. This paper aims to compare a manual calibration procedure with an automatic calibration method developed by the authors, coupling dynamic simulation, sensitivity analysis and automatic optimization using IDA ICE, Matlab and GenOpt respectively. Differences, advantages and disadvantages are evidenced applying both methods to a dynamic simulation model of a real office building in Rome, Italy. Although both methods require high expertise from operators and showed good results in terms of accuracy, automatic calibration presents better performance and consistently helps with speeding up the procedure.

The duct storage (DST) model is one of the most widely used borehole heat exchanger (BHE) models owing to its fast calculation scheme and usability. However, the DST model can simulate only regularly placed BHEs, particularly in cylindrical borefield configurations. As a possibility to describe irregular borefield configurations by adjusting BHE spacing has been reported, we propose optimal values of BHE spacing for typical irregular BHE cases using the GenOpt optimization tool. A regression model based on a set of results obtained from the optimization is proposed to calculate the modified spacing for the DST model directly without optimization simulations. The proposed regression model fits to the datasets of the optimization with an accuracy of 96.5% in predicting the modified BHE spacing. The differences in time-averaged EWTs between the DST model with the proposed modified spacing and a reference model are close to zero, and they are less than 0.5 °C. However, other borefield configurations that have not been used for the model development can result in higher errors. [ABSTRACT FROM AUTHOR]

Until now, design of new high performance buildings has been focused on the energy performance but lacks to be addressed as a holistic problem taking into account all the aspects of a performance of a building. This work strives to study and optimize at once, the energy performance of a building and the sound insulation performance of its facades. In particular, energy and acoustic performances of different building facades, made of two different wall types, were compared taking in account the cost-optimized design of a building. The proposed methodology couples a cost-optimization of the building energy model made though TRNSYS® and GenOpt, with an evaluation of the sound insulation indexes with Matlab®, and it was applied to a French single-family case study. The results show that the cost optimal energy performance level of such case study is somewhere between 40 and 47 kWh/m2.year, while the sound insulation efficiency of the façade can reach a wide range of values. However, the proposed methodology allowed to highlight several design solutions fulfilling the requirements in term of energy, cost and acoustics performances. [ABSTRACT FROM AUTHOR]

This paper implements a sensitivity analysis of a vertical Geothermal Heat Exchanger model from a Ground Coupled Heat Pump system, simulated with the software TRNSYS. Afterward, the optimization software GenOpt is applied in an iterative calibration process, calibrating those factors that were proven to be the most important in the sensitivity analyses. A comparison is made between the calibrated simulation and the experimental data collected from the system, obtaining a significant reduction in the error. The results demonstrate that the methodology used is effective, which indicates that a sensitivity analysis is an appropriate method to determine which parameters should be calibrated, while avoiding biases of the modeler and decreasing the number of iterations required in the calibration by approximately 89%. [ABSTRACT FROM AUTHOR]

Cool roofs have been widely proved to represent an effective strategy for building thermal-energy performance improvement during the cooling season. However, their effectiveness along the whole year can be affected by building features and other boundary conditions. The present work aims at assessing the energy performance of high solar reflectance roof solutions in different climate zones, when implemented in a variety of building typologies. Therefore, an optimization study was carried out to select the optimum roof solar reflectance able to minimize building annual HVAC energy consumption. In this work, Italian climate zones were considered as case study conditions. The analysis was performed through dynamic simulation of validated standard ASHRAE building reference models. Moreover, the role of (i) type of HVAC system operating, (ii) presence and intensity of internal gains, and (iii) roof thermal insulation level was evaluated on the resulting optimum roof reflectance capability. Results show that the optimum roof solar reflectance varies under different climate conditions, mainly depending on heating or cooling dominated conditions. However, all further analyzed boundary conditions, i.e. building typology, HVAC system, internal gains, and roof insulation level, affect building energy performance and, therefore, the optimum roof reflectance identification. In the hottest climate, the optimum roof solar reflectance resulted to be consistently equal to the maximum considered, i.e. 0.8, also with varying the other parameters. Moreover, the annual HVAC energy need is more sensitive to roof reflectance in the apartment building, showing 17% of energy savings with standard model characteristics. On the other hand, in heating dominated climates, the optimum roof solar reflectance is more variable, ranging over all the considered values, because it is affected by the additional boundary conditions. On the contrary, the variability of HVAC need due to roof solar reflectance variation is generally lower. [ABSTRACT FROM AUTHOR]

Globally, a considerable amount of energy is consumed by the building sector. The building envelope can highly influence the energy consumption in buildings. In this regard, innovative technologies such as thermal energy storage (TES) can help to boost the energy efficiency and to reduce the CO 2 emissions in this sector. The use of phase change materials (PCM), due to its high heat capacity, has been the centre of attention of many researchers. A considerable number of papers have been published on the application of PCM as passive system in building envelopes. Researches have shown that choosing the PCM melting temperature in different climate conditions is a key factor to improve the energy performance in buildings. In the present paper, a simulation-based optimization methodology will be presented by coupling EnergyPlus and GenOpt with an innovative enthalpy-temperature (h-T) function to define the optimum PCM peak melting temperature to enhance the cooling, heating, and the annual total heating and cooling energy performance of a residential building in various climate conditions based on Köppen-Geiger classification. Results show that in a cooling dominant climate the best PCM melting temperature to reduce the annual energy consumption is close to the maximum of 26 °C (melting range of 24–28 °C), whereas in heating dominant climates PCM with lower melting temperature of 20 °C (melting range of 18–22 °C) yields higher annual energy benefits. Moreover, it was found that the proper selection of PCM melting temperature in each climate zone can lead to notable energy savings for cooling energy consumption, heating energy consumption, and total annual energy consumption. [ABSTRACT FROM AUTHOR]

Calibration of a Building Energy Model (BEM) is necessary to reduce the discrepancies between the simulation results and real data. This research work proposes a novel ground-breaking calibration methodology that divides the entire building into different sub-models and calibrates them separately to obtain an accurate model. To validate this new procedure, a public library Heating, Ventilation and Air Conditioning (HVAC) system with a Ground-Source Heat Pump (GSHP) and a Radiant Floor (RF) was simulated and calibrated using TRNSYS and GenOpt. The results demonstrated that this new multi-stage procedure met the ASHRAE standards and achieved better results than those obtained with a global calibration. The Mean Bias Error (MBE) and the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) of the hourly temperature data were reduced below −3.74% and 6.03% respectively, involving an improvement of approximately 50% over typical global calibration methods. [ABSTRACT FROM AUTHOR]

In the present paper, the energy performance of buildings forming a school centre in the northwest of Spain was analyzed using a transient simulation of the energy model of the school, which was developed with TRNSYS, a software of proven reliability in the field of thermal simulations. A deterministic calibration approach was applied to the initial building model to adjust the predictions to the actual performance of the school, data acquired during the temperature measurement campaign. The buildings under study were in deteriorated conditions due to poor maintenance over the years, presenting a big challenge for modelling and simulating it in a reliable way. The results showed that the proposed methodology is successful for obtaining calibrated thermal models of these types of damaged buildings, as the metrics employed to verify the final error showed a reduced normalized mean bias error (NMBE) of 2.73%. It was verified that a decrease of approximately 60% in NMBE and 17% in the coefficient of variation of the root mean square error (CV(RMSE)) was achieved due to the calibration process. Subsequent steps were performed with the aid of new software, which was developed under a European project that enabled the automated calibration of the simulations. [ABSTRACT FROM AUTHOR]

In Europe, the recast of the Directive on the Energy Performance of Building and the consequent Zero Energy Buildings objective that has to be reached for all new buildings by 2020, lead designers to re-think building design as a complex optimization problem aimed at identifying the most effective strategies to improve building performance.These strategies can help reducing not only the climate change effect, but also the risk of energy poverty for low-income households. This work is intended to apply a simulation-based optimization methodology for optimizingthe energy performance of a multi-family building for social housing. The method combines the use of TRNSYS ® withGenOpt ® . A typical floor of a real case study was modeled and the impacts of the variation of several design parameters on the heating and cooling demand wereassessed.The optimization lead to reduce the primary energy demand of a floor by 36%. The resulted differences in performance and energy rating between flats were analyzed. [ABSTRACT FROM AUTHOR]

This paper presents the simultaneous optimization of the depths of the horizontal roof overhangs for the design of a residential summer house for house operation during summer season in Belgrade, Serbia. The overhangs facing south, east, and west are made by using reinforced concrete. The two objective functions are used such as (1) minimizing the sum of the primary operative energy consumption during the overhang life cycle and the embodied energy in the roof overhangs and (2) maximizing the ratio of the annual primary operating energy saving and the annualized embodied energy of the applied roof overhangs. For the optimization, the Hooke-Jeeves method is used, and the EnergyPlus software is used to simulate energy behavior of the house. The research showed that two different optimizations gave different results. However, if the house is not used during the same time for which the overhangs are optimized, there is a slight increase in primary energy consumption, although the operative energy consumption may be lower. [ABSTRACT FROM AUTHOR]

This document addresses the development of a novel methodology to identify the actual maintenance factor of the luminaires of an outdoor lighting installation in order to assess their lighting performance. The method is based on the combined use of Radiance, a free and open-source tool, for the modeling and simulation of lighting scenes, and GenOpt, a generic optimization program, for the calibration of the model. The application of this methodology allows the quantification of the deterioration of the road lighting system and the identification of luminaires that show irregularities in their operation. Values lower than 9% for the error confirm that this research can contribute to the management of street lighting by assessing real road conditions.

The international efforts for improving energy efficiency in buildings and reducing their environmental impact also constitute a challenge for working against the risk of energy poverty. The work aims to test a methodology for optimizing the operational costs of the different flats of a multi-family building for social housing. The method combines the use of TRNSYS building energy simulation program with GenOpt Generic Optimization program in a so-called simulation-based optimization method. A typical floor of a real case study building was modeled and the energy costs for heating and cooling due to the variation of design variables related to the building envelope was studied. The optimization led to reduce the total operational costs of the flats by the range 17%-23%. The different share of heating, cooling, ventilation and DHW in the total operational costs was studied and resulted differences in energy rating and costs between flats were analyzed. [ABSTRACT FROM AUTHOR]

The effective design of sustainable buildings results from an accurate optimization process of all the interrelated variables. The authors developed a replicable methodology for the optimization of the building envelope design. Following a previous work, where in the pre-processing and the optimization phases the minimization of the total energy demand is performed by coupling TRNSYS ® with GenOpt ® , this paper is focused on the post-processing phase of the methodology, in which the results are validated and the comfort filters are applied. As an explanatory example, the application of the methodology to a school classroom located in two different climates is presented. [ABSTRACT FROM AUTHOR]

The goals of the EU2030 energy policy should be achieved cost-effectively by employing the optimal mix of supply and demand side technical measures, including energy efficiency, renewable energy and structural measures. In this paper, the achievement of these goals is modeled by introducing an innovative method of soft-linking of EnergyPLAN with the generic optimization program (GenOpt). This soft-link enables simulation-based optimization, guided with the chosen optimization algorithm, rather than manual adjustments of the decision vectors. In order to obtain EnergyPLAN simulations within the optimization loop of GenOpt, the decision vectors should be chosen and explained in GenOpt for scenarios created in EnergyPLAN. The result of the optimization loop is an optimal national energy master plan (as a case study, energy policy in Serbia was taken), followed with sensitivity analysis of the exogenous assumptions and with focus on the contribution of the smart electricity grid to the achievement of EU2030 goals. It is shown that the increase in the policy-induced total costs of less than 3% is not significant. This general method could be further improved and used worldwide in the optimal planning of sustainable national energy systems. [ABSTRACT FROM AUTHOR]

The ocean thermal energy conversion (OTEC) process uses the difference in temperature between the warm seawater on the ocean surface and the deep cold seawater to operate a Rankine cycle system for producing electrical power without consuming fossil fuel. This thermodynamic cycle uses a very low temperature gradient that limits its efficiency at 3–5%. Consequently every consumptions and losses of the system have to be optimized to increase the cost-effectiveness of this technology. This paper presents a thermodynamic analysis of a closed OTEC Rankine cycle. The model used in this paper is based on the work of Martins, using the concept of equivalent Gibbs systems. In an equivalent system, mass, energy and entropy are linked through the Gibbs equation, and the entropy production can easily be expressed in terms of fluxes and their related forces. Assuming linear phenomenological laws, the phenomenological coefficients are assessed from technical data. This method permits the study or design of a lot of process engineering. Moreover, a reliable analysis of the second principle can be realized, in order to compare several processes. This method will be used to analyze the cycle, to determine which components need to be optimized. Based on these results, sensitivity analysis are made on these components and the generic optimization program GenOpt is used to determine the optimized parameters of a 10 MW OTEC plant that could be installed on Reunion Island. [ABSTRACT FROM AUTHOR]

Radiant panels are known to be energy efficient sensible heating systems and a suitable fit for low-energy buildings. The main goal of this paper is to optimize the thermal insulation layers of house heated by using the radiant heating systems. This work is conducted to study four radiant systems: floor-heating system, wall-heating system, ceiling-heating system and newly developed floor-ceiling heating system located in a net-zero-energy house in Kragujevac, Serbia. The operation of these panels is simulated by software EnergyPlus. For the optimization of the optimal length of the thermal insulation software GenOpt is used. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper investigated the energy impact of DSF design regarding window glazing type and cavity depth. [•] Parametric and optimization studies were conducted based on a validated DSF model. [•] Energy consumption decreased when the cavity depth of the DSF decreased. [•] Results show the significance of the initial DSF design on the thermal load of the adjacent conditioned zones. [Copyright &y& Elsevier]

Abstract: This article deals with the optimization and validation of a thermal model of photovoltaic panels integrated to buildings. The PV thermal model is implemented in the building simulation code ISOLAB and have already been the subject of previous works. The optimization is made by using the generic optimization program GenOpt. First, these two programs are presented. Secondly, the case study is presented both experimental and modeling way, and main results of previous work are given. Thirdly, the validation methodology is described. Fourthly, the coupling between ISOLAB and GenOpt is presented, and optimization and validation criteria are given. Finally, results of the experimental optimization are presented and the model is validated. [Copyright &y& Elsevier]

Abstract: Since naturally ventilated buildings respond to site conditions and microclimate, we cannot establish a “one set of criteria” for every naturally ventilated building. So natural ventilation should be optimized to deal with thermal comfort in passive buildings during summer. A survey of existing tools for natural ventilation simulation shows the dominance of so-called “analysis” tools over “design” tools. In this present work, we will propose a new method to size natural ventilation openings based on inverse calculation, reduction of the number of independent parameters and optimization of occupants thermal comfort. [Copyright &y& Elsevier]

Abstract: A new lighting and daylighting control strategy is modeled and evaluated against conventional lighting and daylighting controls. The new lighting and daylighting control strategy can be incorporated in an energy management and control system (EMCS) to operate and control lighting fixtures in any indoor space. The new daylighting control can also be modeled and integrated in detailed building energy simulation tools. Through a validation analysis, it was found that the new control strategy provides more energy savings than conventional daylighting controls. Moreover, the validation analysis has indicated that existing daylighting control simulation analysis tools could overestimate lighting energy savings associated with daylighting controls. Moreover, it was also found that if calculated solar and illuminance data are used instead of measured solar radiation data, the errors in predicting lighting energy use when daylighting controls are utilized can be significant. [ABSTRACT FROM AUTHOR]

Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO2 emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates the energy performance of an individual house integrating a solar Trombe wall containing PCM with respect to heating demand and thermal comfort applications. The thermal energy performance of the design house was simulated using Dymola/Modelica, the thermal building simulation tool, whereby the optimization of objective functions as regards heating demand and thermal comfort was executed using GenOpt, the generic optimization software. Optimization of the solar Trombe wall focuses on the feasibility to find the optimal PCM parameters when running GenOpt, which consist of latent heat, melting temperature, PCM thickness and thermal conductivity, in order to minimize both the annual energy consumption for heating and the number of hours of thermal discomfort. The parametric study was first conducted for each PCM parameter so as to not only observe its effect on the identified energy performance, but also ensure the absence of errors in simulation runs before performing the optimization. The 'Coordinate Search' Generalized Pattern Search (GPS) algorithm was applied to minimize the objective function, whereas the 'Weighted Sum Approach' was used to solve the multi-objective function problem. Results showed that the higher the latent heat, the lower the heating demand and the greater the thermal comfort. The results of these parametric studies show that for the effect of the parameter on heating, demand is quite limited (1–2 kWh·m − 2 ·year − 1 ) whereas the effect on thermal comfort is more significant. The optimal PCM melting temperature is higher for warmer climates; it is also higher for the studied case applying the optimization method to minimize the objective function by assigning the number of hours of thermal discomfort (from 32.8 ∘ C to 35.9 ∘ C , depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 ∘ C to 32.9 ∘ C , again depending on weather). [ABSTRACT FROM AUTHOR]