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• HVAC system stock is heterogeneous and changes over time. • A HVAC stock modeling and an archetype building energy modeling were integrated. • Disregard of the heterogeneity and its change can cause error in energy modeling. • Energy reduction by technological innovation relies on the share of the HVAC stock. Urban building energy model (UBEM) is an important tool in coping with energy issues of building sector. This paper focuses on an issue that the stock of heating, ventilation, and air-conditioning (HVAC) systems has been oversimplified in UBEM without considering its heterogeneity. It has been observed that this oversimplification may incur a significant error in the result. To address this issue, this paper proposes a framework that integrates a logistic regression based HVAC system stock modeling method and the bottom-up type engineering modeling method using building archetypes considering HVAC system configurations. A case study with Japanese office building stock revealed that (1) the disregard of the heterogeneity resulted in an error of 15% in the annual primary energy consumption, (2) the historical change in the HVAC system stock could decrease the consumption up to 5%, and (3) its composition has a significant influence on the energy saving due to energy efficiency increase in heat source machines used in HVAC systems. The presented method would contribute not only to improving the reliability of UBEM but also to providing an analytical capability of considering energy efficiency technologies related to HVAC systems along with the alternation of technology selection in the building stock. [ABSTRACT FROM AUTHOR]

Abstract: The investigation presented in this paper has three main objectives. The first one is to study, through a case study, if it is possible to acceptably predict the energy consumption of a massive residential free-running building, when the exact behavior of the occupants is unknown or actual indoor conditions are not monitored, assuming standard use and occupation schedules, for the dry climate of the Argentinean Northwest. The second objective of the paper is to detect the possible causes of differences between actual and predicted energy consumption through an exhaustive thermal monitoring and occupant''s behavior, in order to obtain an improved model of the building giving more accurate predictions of the energy consumption. The third objective is to analyze the effect on the annual energy consumption of changing the massive envelope by a lightweight one. The comparison of real and simulated consumptions under comfort conditions defined by ASHRAE Standard 55 shows that simulations overestimated the energy consumption for heating and cooling. The main causes were detected from the experimental monitoring, indicating a lower use of the air conditioning equipment than the supposed initially. Simulations were improved to consider actual use and occupation conditions. Finally, an annual simulation of the improved model performed by changing the envelope material to a lightweight one showed that energy consumption for heating was increased, while energy consumption for cooling was decreased. In an annual balance, the massive walls are preferable over lightweight ones in arid sunny climates as in the Argentinean Northwest, giving energy savings of around 25%. [Copyright &y& Elsevier]

Abstract: This paper demonstrates a systematic, evidence-based methodology for calibrating whole building energy models. The methodology uses version control software to store a complete history of the calibration process, including the evidence on which decisions were made. This paper details the calibration of a whole building energy model to hourly energy consumption data using the methodology. The case study building was a 30,000m2, four-floor office building located on Intel''s campus in Ireland. The final calibrated model represents the building to a high level of detail using a large number of zones and uses measured lighting and plug load data in the simulation at hourly intervals. The results show excellent correlation with the measured HVAC consumption data for the analysed year (2007), demonstrating the effectiveness of the methodology. Mean Bias Error (MBE) and Cumulative Variation of Root Mean Squared Error (CVRMSE(hourly)) for HVAC electrical consumption were −4.16% and 7.8%, respectively for the final model. This model was then used to investigate Energy Conservation Measures (ECMs) for feasibility. The paper concludes with a discussion of discrepancies remaining in the model, the issues encountered related to the criteria used for determining when a model is calibrated, and recommendations for future calibration case studies. [Copyright &y& Elsevier]

• Provided a platform to test various residential building control systems. • Used probability of occupancy to determine setback temperature when unoccupied. • Integrated optimizer with adaptive and occupancy control. • Generated dynamic electricity tariff based on wholesale electricity pricing. • Evaluated the peak load shaving potential with dynamic pricing and optimization. Energy consumption in buildings continues to rise with increased deployment of energy-consuming equipment such as Heating, Ventilation, and Air Conditioning (HVAC) amid a growing world economy. Renewable energy is projected to comprise a majority of the future electricity supply, but the intermittent nature of renewables means that consumption must respond to dynamic supply for optimal utilization. This paper proposes a novel HVAC control strategy for residential buildings using the adaptive comfort model, considering occupancy through probability and real-time information, and optimizing the HVAC schedule to reduce cost, maintain thermal comfort, and respond to the dynamic availability of renewable energy while being generalizable to different situations. To validate this approach, the Universal CPS Environment for Federation (UCEF) co-simulation platform is used to connect advanced building controls with the building energy simulation software EnergyPlus. Simulations are performed for a residential building in Sacramento, CA during a typical summer week. Economic impacts, energy consumption, and thermal comfort are analyzed for traditional, adaptive, and occupancy-based control strategies under demand-based, tiered, and fixed electric tariff systems. Simulation results show that occupancy consideration, adaptive thermal comfort, and optimization can reduce cost by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 % compared to traditional fixed setpoints. The ability of the proposed HVAC control strategy to shift energy consumption away from peak times under a demand-based tariff system is qualitatively analyzed and findings suggest that maximum load-shifting on a grid-scale is attained using occupancy consideration with optimized control and demand-based pricing. For individual residential buildings, similar economic benefits can be gained using the less-complex adaptive HVAC control strategy with existing tiered or simple electric tariff systems. [ABSTRACT FROM AUTHOR]

• A new urban building energy modeling tool-AutoBPS was developed. • AutoBPS calculated urban building energy demands, analyzed energy retrofit and rooftop PV potential via EnergyPlus. • AutoBPS automatically generated multi-zone models, considering shading from surrounding buildings. • A downtown district of 3633 buildings in Changsha, China, was simulated to demonstrate the tool's features. • All three energy conservation measures and PV installation could save 38.6% of total energy demand. China has promised to peak carbon emissions by 2030 and become carbon neutral before 2060. Achieving this target requires actions from all sectors, especially the building sector, which accounts for 33 % of the total energy consumption in China. Within this scenario, this paper introduces a new urban building energy modeling tool, Automated Building Performance Simulation (AutoBPS), to calculate urban building energy demands and to analyze energy retrofit and rooftop photovoltaic (PV) potential. AutoBPS uses a building-by-building approach to automatically generate multi-zone (one zone per floor) models based on the city building dataset, considering the shading effect by surrounding buildings. The tool simulates building energy use and PV generation via EnergyPlus. A downtown district of 3633 buildings in Changsha, China, was selected as a case study to demonstrate the features of the tool. Firstly, annual baseline energy uses of 1793 GWh were simulated by inputting Geographic Information System (GIS) data. Then, different energy conservation measures (covering envelope, lighting, cooling system upgrade, etc.) and roof PV generation systems were adopted to explore energy saving potential. The results showed that the window upgrade was the most energy-efficient individual measure for residential buildings, while the lighting upgrade was that one for commercial buildings. Altogether three measures could save 2.7 ∼ 30.7 % of annual site energy use intensity per building. The total energy demand could be reduced by 18.5 % by combining all measures and saved by 38.6 % when PV installation was added. AutoBPS can be easily applied to other cities, supporting urban energy efficiency plans for carbon reduction goal implementation. [ABSTRACT FROM AUTHOR]

This paper details a manual calibration of a 132 zones, highly monitored 5 434 m2 office building located in France. The calibration is conducted over one year of simulation at a five minute time-step. The model is mostly fed with input files containing measured data for each simulation time-step. First simulation results show that the model cannot be considered as being calibrated considering usual guidelines based on statistical indicators calculated on monthly energy consumption. Instead of going through a classical tuning process to match measured and simulated monthly energy consumption data, the choice was made to focus on explaining those discrepancies using available building information and monitoring data. A first dynamical heating and cooling powers analysis has been made, resulting in good correlation with measured values and explaining most of the discrepancies previously noticed, followed by a dynamical temperature analysis performed at the zone scale, and completed by a global statistical analysis at the building scale for the 132 zones of the building. Results showed very good agreement between measured and simulated temperature values with 90% of data points ranging between −1.72 °C and 2.02 °C of error. This demonstrate that a model that at first glance does not perform well considering particular statistical indicators can show an accurate dynamical behavior and a good performance when other variables and performance criteria are considered. This is followed by a discussion of the possible model improvements along with the limitations of statistical analysis compared to dynamic physical analysis for calibration performance assessment. The paper concludes with several proposals to improve the guidelines for calibration procedures involving the use of detailed monitoring data. [ABSTRACT FROM AUTHOR]

The variable air volume (VAV) system is the most popular form of heating, ventilation, and air-conditioning (HVAC) system used in commercial buildings. Researchers and engineers often use VAV systems as a reference when evaluating new technologies and systems or comparing design options. However, VAV system performance varies significantly, in part because of variations among VAV system controls, so, when analyzing use cases, it is critical to accurately represent system controls in order to accurately define system performance. Unfortunately, no existing literature documents standard VAV system controls for this purpose. This paper aims to remedy this omission by characterizing the variations in VAV system controls and proposing an approach to representing VAV system baseline performance. We used EnergyPlus to model variation among VAV system controls. We use the medium-size office reference-building model developed by the U.S. Department of Energy to demonstrate the impact of variations among controls in two U.S. climate zones and sort system performance into “good,” “average,” and “poor” categories. [ABSTRACT FROM AUTHOR]

The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation. Finally, we solved an optimisation problem using genetic algorithms in order to find the optimal set of design variables for the considered house. The results highlighted the efficiency and the effectiveness of the proposed methodology to redesign a typical house in the Argentine Littoral region, improving hugely its thermal and energy performance. [ABSTRACT FROM AUTHOR]

• HVAC system stock is heterogeneous and changes over time. • A HVAC stock modeling and an archetype building energy modeling were integrated. • Disregard of the heterogeneity and its change can cause error in energy modeling. • Energy reduction by technological innovation relies on the share of the HVAC stock. Urban building energy model (UBEM) is an important tool in coping with energy issues of building sector. This paper focuses on an issue that the stock of heating, ventilation, and air-conditioning (HVAC) systems has been oversimplified in UBEM without considering its heterogeneity. It has been observed that this oversimplification may incur a significant error in the result. To address this issue, this paper proposes a framework that integrates a logistic regression based HVAC system stock modeling method and the bottom-up type engineering modeling method using building archetypes considering HVAC system configurations. A case study with Japanese office building stock revealed that (1) the disregard of the heterogeneity resulted in an error of 15% in the annual primary energy consumption, (2) the historical change in the HVAC system stock could decrease the consumption up to 5%, and (3) its composition has a significant influence on the energy saving due to energy efficiency increase in heat source machines used in HVAC systems. The presented method would contribute not only to improving the reliability of UBEM but also to providing an analytical capability of considering energy efficiency technologies related to HVAC systems along with the alternation of technology selection in the building stock. [ABSTRACT FROM AUTHOR]

These days, many studies are about the performance of some shading devices. Many engineers think the performance of internal shading systems is inferior to external systems. Because when using internal shades, the solar heat has already entered the internal spaces and has become trapped. However, in real applications, external shading is difficult to use, easily damaged and prone to dirt buildup. Internal shading is more flexible, cheaper and easier to repair. Some engineers doubt the validity of this traditional thinking and believe internal shading may be effective and useful to some extent because many occupants use internal blinds to minimize air conditioning costs. In this paper, the possibility of substituting the external shades with an internal ones using high reflectivity materials was studied through experimental tests and simulation validations. The results indicate that an internal shading system may be as effective as an external system if proper materials are used. Such substitution can reduce the overall cost of a shading system and can provide flexibility to the design of building facades. A grey relational analysis of the internal shade optimization is further presented so that the significant factors influencing the internal shading device performance are better understood. These factors should be taken into consideration during the design. [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]

In recent years, a large number of building energy consumption prediction models, with various intended uses, have been proposed. The majority of these models have either taken a data-driven or a physical modeling approach, with each approach having its own strengths and limitations. Towards leveraging the strengths and reducing the limitations of each approach for improved prediction performance, this paper presents a hybrid machine-learning approach for occupant-behavior-sensitive energy consumption prediction. The proposed approach is composed of three constituent models: (1) a machine-learning model that learns the impact of outdoor weather conditions from simulation-generated data, (2) a machine-learning model that learns the impact of occupant behavior from real data, and (3) an ensemble model that predicts cooling energy consumption based on the outputs of the first two models. The simulation-generated data were created through simulating a set of reference buildings in EnergyPlus. The real data were collected from an office building in Pennsylvania. The proposed hybrid model was validated on an unseen real dataset. It achieved 0.73 kWh RMSE and 9.07% CV in hourly cooling energy consumption prediction, which indicates that the proposed approach is promising. [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 paper presents the results of the thermal and airflow simulation of an existing naturally ventilated shopping mall located near Lisbon, Portugal. Thermal and airflow simulation is used to improve the original natural ventilation system design in order to address winter thermal comfort problems that were due to excessive cold airflow in the mall corridors. In the first part of the simulation work, computational fluid dynamics (CFD) is used to predict indoor airflow velocities for different levels of building envelop airflow permeability. In the second part, a coupled thermal and airflow simulation model is used to investigate whether the more closed envelope generates a summer overheating problem. The simulation results for the optimized natural ventilation opening geometry show that it successfully addresses the mall winter discomfort problem while resulting in limited corridor temperature increase in the warm season. The third and final part of this study compares the energy consumption of a naturally ventilated mall with a conventional mechanically ventilated mall. [Copyright &y& Elsevier]

Abstract: The concern on climate change leads to growing demand for minimization of energy use. As building is one of the largest energy consuming sectors, it is essential to study the impact of climate change on building energy performance. In this regard, building energy simulation software is a useful tool. A set of appropriate typical weather files is one of the key factors towards successful building energy simulation. This paper reports the work of developing a set of weather data files for subtropical Hong Kong, taking into the effect of future climate change. Projected monthly mean climate changes from a selected General Circulation Model for three future periods under two emission scenarios were integrated into an existing typical meteorological year weather file by a morphing method. Through this work, six sets of future weather files for subtropical Hong Kong were produced. A typical office building and a residential flat were modeled using building simulation program EnergyPlus. Hourly building energy simulations were carried out. The simulated results indicate that there will be substantial increase in A/C energy consumption under the impact of future climate change, ranging from 2.6% to 14.3% and from 3.7% to 24% for office building and residential flat, respectively. [Copyright &y& Elsevier]

Abstract: The evaluation of building energy consumption under typical meteorological conditions requires building energy profiles on an hourly basis. Computer simulations can be used to obtain this information, but generating simulations requires a significant amount of experience, time, and effort to enter detailed building parameters. This paper considers a simple methodology for using existing EnergyPlus benchmark building energy profiles to estimate the energy profiles of buildings with similar characteristics to a given benchmark model. The method utilizes the building monthly energy bills to scale a given benchmark building energy profile to approximate the real building energy profile. In particular, this study examines the robustness of the methodology considered with respect to the parameter discrepancies between a given building and the corresponding EnergyPlus benchmark model used to estimate its profile. Test buildings are defined by perturbing several combinations of the parameters defined in the benchmark building model. The test buildings examined are similar to the EnergyPlus, medium sized office, benchmark building in Baltimore, MD, and a total of 72 distinct test building configurations are examined. The analysis reveals that the methodology can significantly reduce the errors introduced by discrepancies from the EnergyPlus benchmark model. [Copyright &y& Elsevier]

Abstract: The evaluation of building energy consumption usually requires building energy profiles on an hourly basis. Computer simulations can be used to obtain this information but generating simulations requires a significant amount of experience, time, and effort to enter detailed building parameters. This paper presents a simple methodology to estimate hourly electrical and fuel energy consumption of a building by applying a series of predetermined coefficients to the monthly energy consumption data from electrical and fuel utility bills. The advantage of having predetermined coefficients is that it relieves the user from the burden of performing a detailed dynamic simulation of the building. The coefficients provided to the user are obtained by running EnergyPlus Benchmark Models simulations; thus, the simulation process is transparent to the user. The methodology has been applied to a hypothetical building placed both in Atlanta, GA, and in Meridian, MS, and in both cases, errors obtained for the estimated hourly energy consumption are mainly within 10%. [ABSTRACT FROM AUTHOR]

Abstract: Possible solutions for zero energy building design in UK are discussed in this paper. Simulation software (EnergyPlus and TRNSYS 16) are employed in this study, where EnergyPlus simulations are applied to enable facade design studies considering building materials, window sizes and orientations and TRNSYS is used for the investigation of the feasibility of zero energy houses with renewable electricity, solar hot water system and energy efficient heating systems under Cardiff weather conditions. Various design methods are compared and optimal design strategies for typical homes and energy systems are provided. [Copyright &y& Elsevier]

Abstract: A new module was developed for and implemented in the EnergyPlus program for the simulation and determination of the energy impact of thermal chimneys. This paper describes the basic concepts, assumptions, and algorithms implemented into the EnergyPlus program to predict the performance of a thermal chimney. Using the new module, the effects of the chimney height, solar absorptance of the absorber wall, solar transmittance of the glass cover and the air gap width are investigated under various conditions. Chimney height, solar absorptance and solar transmittance turned out to have more influence on the ventilation enhancement than the air gap width. The potential energy impacts of a thermal chimney under three different climate conditions are also investigated. It turned out that significant building cooling energy saving can be achieved by properly employing thermal chimneys and that they have more potential for cooling than for heating. In addition, the performance of a thermal chimney was heavily dependent on the climate of the location. [Copyright &y& Elsevier]

Abstract: A great amount of world energy demand is connected to the built environment. Electricity use in the commercial buildings, accounts for about one-third of the total energy consumption in Turkey and fully air-conditioned office buildings are important commercial electricity end-users since the mid-1990s. In the presented paper, the interactions between different conditions, control strategies and heating/cooling loads in office buildings in the four major climatic zones in Turkey – hot summer and cold winter, mild, hot summer and warm winter, hot and humid summer and warm winter – through building energy simulation program has been evaluated. The simulation results are compared with the values obtained from site measurements done in an office building located in Istanbul. The site-recorded data and simulation results are compared and analyzed. This verified model was used as a means to examine some energy conservation opportunities on annual cooling, heating and total building load at four major cities which were selected as a representative of the four climatic regions in Turkey. The effect of the parameters like the climatic conditions (location), insulation and thermal mass, aspect ratio, color of external surfaces, shading, window systems including window area and glazing system, ventilation rates and different outdoor air control strategies on annual building energy requirements is examined and the results are presented for each city. [Copyright &y& Elsevier]

• The impact of people's behavior during COVID 19 quarantine on energy consumption. • The study was conducted numerically (using EnergyPlus software) during March 2020. • The energy and water consumption, CO2 emissions and economic was analysed. • Protection measures adopted by the Government of the Republic Serbia were considered. • The energy and environmental indicators were presented for the last three years. Humanity is currently confronted with a new, unknown, highly contagious virus, where social isolation and increased personal hygiene seem to be the main means in preventing its spread. The world economy is very threatened by the new situation, which has not bypassed the energy sector either. The mortality rate is relatively high, people are not leaving their homes, which is directly reflected in the increase of the energy consumption in the residential sector. The same is valid for water consumption. For a household located in Kragujevac (Central Serbia), 4 simulation scenarios were analyzed (S1 – reference case, S2 – mild protection measures, S3 – semi-quarantine measures, S4 – complete quarantine) to assess the link between people's behavior (on the one hand) and the consumption of natural gas, electricity and water (on the other hand), in the residential sector, in unforeseen circumstances, such as the COVID-19 virus pandemic. The analysis was conducted numerically for the month of March 2020, using EnergyPlus software packages. In defining the above scenarios, a one-minute time step schedule of people's behavior was used, taking into account the number of family members in the household, their age, occupation, lifestyle, habits (all in accordance with cultural and socio-economic circumstances), as well as the measures taken by the Government of the Republic of Serbia to fight the pandemic. Also, an analysis of energy consumption at the level of the city of Kragujevac for the past three years was made, based on data obtained from public companies – distributors (thermal energy, natural gas, electricity, water). In this paper, an analysis of air quality for the same time period was conducted, which is closely related to energy consumption and limited population movement. The simulatinos show that the consumption of natural gas can increase by 21.26% (S2), electricity by 58.39% (S4), and the consumption of water from the city water supply network by 25.45% (S3) compared to the reference case (S1). On the other hand, based on the invoice for payment of services to distributors, the actual energy consumption that was made on the analyzed house during the month of March 2020 was: natural gas (260.36 Sm3), electricity (1418 kWh), and water (22.5 m3). The conducted economic analysis showed that the largest funds at the level of the entire facility were allocated in S3 (27.33% more than in S1), and that the actual costs were 15.09% higher than in S1, and 16.41% lower than in S2. [ABSTRACT FROM AUTHOR]

• A local sensitivity analysis of double skin facades' (DSFs) features is presented. • Simulations are carried out with two building energy simulation tools and compared. • In-built models for DSF (climate façade) are compared with experimental data. • The ranking and magnitude of sensitivity indices are similar for the two tools. • Glazing thermal and optical transmittance are the most relevant variable in DSF design. Double skin façades (DSFs) are considered façade technologies that can reduce energy use and improve occupant comfort due to their advanced features. Their design requires reliable simulations due to their complex thermophysical behaviour, which are often carried out by practitioners using building energy software (BES) tools. Using an exhaust-air façade (also called climate façade) case study, the paper analyses the sensitivity of in-built DSF models in two popular BES tools (EnergyPlus and IDA ICE) for different orientations and climates. Small variations in input variables were considered to identify the parameters that the designer should pay most attention to during the design of the DSF according to different performance indicators. The results show that, regardless of the climate or orientation, the optical properties of the system (glazing and shading) were the most important in determining its performance, followed by the thermal properties of the glazing, while the geometrical, airflow and frame characteristics were less relevant. The model validation process also showed how differences in the in-built models (i.e. the use of a capacitance node for the glazed layers) lead to a difference in the reliability of the two BES tools. [ABSTRACT FROM AUTHOR]

• Future-TMY (F-TMY) and Morphing methodologies are compared in 14 Iberian cities. • Morphing sensitive analysis using 3 different files is performed. • High-quality Morphing and F-TMY have similar climate and BES performances (7%−8%). • F-TMY is representative of the multi-year simulation for BES applications. • Low-quality Morphing leads to average errors between 16% to 20%. In the last decade, building energy simulation (BES) became a central component in building energy systems' design and optimization. For each building location, BES requires one year of hourly weather data. Most buildings are designed to last 50+ years, consequently, the building design phase should include BES with future weather files considering climate change. This paper presents a comparative study of two methods to produce future climate hourly data files for BES: Morphing and typical meteorological year of future climate (F-TMY). The study uses data from a high-resolution (9 km) regional climate atmospheric model simulation of Iberia, spanning 10 years of historical and future hourly data. This study compares both methods by analyzing anomalies in air temperature, and the impact in BES predictions of annual and peak energy consumption for space heating, cooling and ventilation in 4 buildings. Additionally, this study performs a sensitivity analysis of morphing method. The analysis shows that F-TMY is representative of the multi-year simulation for BES applications. A high-quality Morphed TMY weather file has a similar performance compared to F-TMY (average difference: 8% versus 7%). Morphing based on different baseline climates, low-grid resolution and/or outdated climate projections leads to BES average differences of 16%-20%. [ABSTRACT FROM AUTHOR]