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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.

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/m2y 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.

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 facade 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.

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. Ministerio de Ciencia, Innovación y Universidades | Ref. FPU17/01834

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.

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.

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.

Dynamic testing of solar thermal systems is presently defined by ISO 9459-5:2007. The testing methodology is clearly defined in the standard. Presently, laboratories that use Dynamic System Testing methodology only have available for identification of parameters, a closed source program, which is based on a model described by Spirkl and Muschawek (1992). The present paper describes the work done following a different approach for the identification of parameters – use of TRNSYS to simulate the system and use of GENOPT® for optimization. Results are presented, both for thermosyphon and forced circulation systems, and show, in most cases, good agreement (differences lower then ±5%) when compared with the results using ISS, v2.7 (from In Situ Scientific Software). Comparison of system energy yield, calculated using TRNSYS for periods higher than one month, with measured energy yield for these periods, was also done for a thermosyphon system showing very good agreement (differences lower than ±3%).

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&mdash, 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.

One of the challenges in global optimization is to use heuristic techniques to improve the behaviour of the algorithms on a wide spectrum of problems. With the aim of reducing the probabilistic component and performing a broader and orderly search in the feasible domain, this paper presents how discretization techniques can enhance significantly the behaviour of a genetic algorithm (GA). Moreover, hybridizing GA with local searches has shown how the convergence toward better values of the objective function can be improved. The resulting algorithm performance has been evaluated during the Generalization-based Contest in Global Optimization (GENOPT 2017), on a test suite of 1800 multidimensional problems.

International audience; A simple model for a detached house in Beirut is optimized using a building energy simulation program to minimize two objective functions: the annual thermal demand; and the difference between the total electrical load and the on-site electricity generated from the renewable energy system. The optimization variables are: insulation thickness of external walls and roof, thickness of roof reinforced concrete, size of windows on each façade, number of solar collectors of the domestic hot water system (SDHW), SDHW circulating pump flow rate, and number of panels of the Photovoltaic system (PV). The main optimization constraint adopted is the thermal comfort criterion. Results of the optimization shows that the exclusion of cost parameter may lead to unfeasible solutions even if the net zero balance is theoretically achieved.