Search Results (48)

In recent years, solar energy has emerged as one of the most advanced renewable energy sources, with its production capacity steadily growing. To maximize output and efficiency, choosing the right configuration for a specific location for these installations is crucial. This study uniquely integrates detailed multi-variant fixed-tilt PV system simulations with comprehensive economic evaluation under temperate climate conditions, addressing site-specific spatial constraints and grid integration considerations that have rarely been combined in previous works. In this paper, an energy and economic efficiency analysis for a photovoltaic power plant, located in central Poland, designed in eight variants (10°, 15°, 20°, 25°, 30° PV module inclination angle for a south orientation and 10°, 20°, 30° for an east–west orientation) for a limited building area of approximately 300,000 m² was conducted. In PVSyst computer simulations, PVGIS-SARAH2 solar radiation data were used together with the most common data for describing the Polish local solar climate, called Typical Meteorological Year data (TMY). The most energy-efficient variants were found to be 20° S and 30° S, configurations with the highest surface production coefficient (249.49 and 272.68 kWh/m²) and unit production efficiency values (1123 and 1132 kWh/kW, respectively). These findings highlight potential efficiency gains of up to approximately 9% in surface production coefficient and financial returns exceeding 450% ROI, demonstrating significant economic benefits. In economic terms, the 15° S variant achieved the highest values of financial parameters, such as the return on investment (ROI) (453.2%), the value of the average annual share of profits in total revenues (56.93%), the shortest expected payback period (8.7 years), the value of the levelized cost of energy production (LCOE) (0.1 EUR/kWh), and one of the lowest costs of building 1 MWp of a photovoltaic farm (664,272.7 EUR/MWp). Among the tested variants of photovoltaic farms with an east–west geographical orientation, the most advantageous choice is the 10° EW arrangement. The results provide valuable insights for policymakers and investors aiming to optimize photovoltaic deployment in temperate climates, supporting the broader transition to renewable energy and alignment with national energy policy goals. Full article

Thermal simulations of buildings play a critical role in optimizing energy efficiency, thermal comfort, and heating, ventilation and air conditioning (HVAC) systems design. Accurate weather data is essential for reliable simulations, as local weather and climate have a significant impact on energy requirements for space heating and cooling and thermal comfort. This study conducted a literature review regarding the sources, types, and uncertainties of weather data used for thermal simulations of buildings, including typical meteorological years (TMYs) and extreme weather files under current and future climates. Additionally, this paper evaluates methods for weather data processing, including interpolation, downscaling, and synthetic generation, to improve simulation accuracy. Finally, approaches are proposed for constructing weather files for the future and extreme conditions under a changing climate. This review aims to provide a guide for researchers and practitioners to enhance the reliability of thermal modeling through informed construction, selection, and application of weather data. Full article

This study investigates the long-term impact of insulation degradation on building heating energy consumption, with a focus on extruded polystyrene (XPS) insulation. Year-by-year degradation in thermal transmittance was derived from long-term experimental data and applied to prototypical energy models of multifamily apartment buildings and office buildings. Simulations were performed using both Actual Meteorological Year (AMY) and Typical Meteorological Year (TMY) data for six cities representing Korea’s major climate zones. The results showed that insulation degradation led to a significant increase in heating energy consumption from 23.2% to 34.9% in AMY simulations and 23.5% to 36.2% in TMY simulations for multifamily apartment buildings over 15 years. The difference between the AMY and TMY estimates was within 4%, demonstrating the reliability of TMY for long-term performance assessments. Notably, the southern and Jeju zones exhibited higher sensitivity to degradation due to their relaxed insulation standards and lower initial thermal performance. Office buildings were less affected, with increases below 8%, attributed to smaller envelope areas and higher internal heat gains. These findings highlight the need for zone-specific insulation standards and differentiated energy-saving design strategies by building type to ensure long-term energy efficiency. Full article

This study presents a preliminary analysis of an innovative system that combines indoor air conditioning with water recovery and storage. The device integrates Peltier cells with a horizontal Earth-to-Air Heat Exchanger (EAHX), exploiting the ground stable temperature to enhance cooling and promote condensation. Warm, humid air is pre-cooled via the geothermal pipe, then split by a fan into two streams: one passes over the cold side of the Peltier cells for cooling and dehumidification, while the other flows over the hot side and heats up. The two airstreams are then mixed in a water storage tank, which also serves as a thermal mixing chamber to regulate the final air temperature. The analysis investigates the influence of soil thermal conditions on condensation within the horizontal pipe and the resulting cooling effect in indoor spaces. A hybrid simulation approach was adopted, coupling a 3D model implemented in COMSOL Multiphysics^® with a 1D analytical model. Boundary conditions and meteorological data were based on the Typical Meteorological Year (TMY) for Palermo. Two scenarios were considered. In Case A, during the hours when air conditioning is not operating (between 11 p.m. and 9 a.m.), air is circulated in the exchanger to pre-cool the ground and the air leaving the exchanger is rejected into the environment. In Case B, the no air is not circulated in the heat exchanger during non-conditioning periods. Results from the June–August period show that the EAHXs reduced the average outdoor air temperature from 27.81 °C to 25.45 °C, with relative humidity rising from 58.2% to 66.66%, while maintaining nearly constant specific humidity. The system exchanged average powers of 102 W (Case A) and 96 W (Case B), corresponding to energy removals of 225 kWh and 212 kWh, respectively. Case A, which included nighttime soil pre-cooling, showed a 6% increase in efficiency. Condensation water production values range from around 0.005 g/s with one Peltier cell to almost 0.5 g/s with seven Peltier cells. As the number of Peltier cells increases, the cooling effect becomes more pronounced, reducing the output temperature considerably. This solution is scalable and well-suited for implementation in developing countries, where it can be efficiently powered by stand-alone photovoltaic systems. Full article

Typical Meteorological Year (TMY) datasets, widely used in building energy modeling, overlook Urban Heat Island (UHI) effects and future climate trends by relying on long-term data from rural stations such as airports. This study addresses this limitation by integrating Urban Weather Generator (UWG) simulations with CCWorldWeatherGen projections to produce microclimate-adjusted and future weather scenarios. These datasets were then incorporated into an Urban Building Energy Modeling (UBEM) framework using Urban Modeling Interface (UMI) to evaluate energy performance across a low-income residential neighborhood in Des Moines, Iowa. Results show that UHI intensity will rise from an annual average of 0.55 °C under current conditions to 0.60 °C by 2050 and 0.63 °C by 2080, with peak intensities in summer. The UHI elevates cooling Energy Use Intensity (EUI) by 7% today, with projections indicating a sharp increase—91% by 2050 and 154% by 2080. The UHI will further amplify cooling demand by 2.3% and 6.2% in 2050 and 2080, respectively. Conversely, heating EUI will decline by 20.0% by 2050 and 40.1% by 2080, with the UHI slightly reducing heating demand. Insulation mitigates cooling loads but becomes less effective for heating demand over time. These findings highlight the need for climate-adaptive policies, building retrofits, and UHI mitigation to manage future cooling demand. Full article

Global climate change is significantly altering the energy consumption patterns and outdoor environments of buildings. The current meteorological data utilized for building design exhibit numerous deficiencies. To effectively address the needs of future building usage in design, it is crucial to establish more refined meteorological parameters that accurately reflect the climate of specific geographical locations. Utilizing 60 years of meteorological data from Guangzhou, this study employs the cumulative distribution functions (CDFs) method to define four archetypal meteorological years, providing a robust foundation for subsequent analysis. The findings indicate a significant increase in the frequency of high temperatures and temperature values during the summer months, with an increase of nearly 20% in the cumulative degree hours (CDHs) used for calculating a typical meteorological year (TMY4) over the past 30 years. Additionally, there has been an increase of 0.4–0.7 °C in the air conditioning design daily temperature. The statistics on outdoor calculation parameters for different geographical locations, as well as outdoor design parameters for varying guaranteed rate levels in the Pearl River Delta, reveal a substantial impact on outdoor calculation parameters. The maximum difference in cooling load is approximately 9.3%, with a generally high cooling demand in summer and a relatively low heating demand in winter. Furthermore, the calculation values for different non-guaranteed rates can be applied flexibly to meet the needs of engineering applications. This study provides a valuable reference for updating meteorological parameters in building design. By refining meteorological parameters, this study enables more accurate predictions of energy needs, leading to optimized building designs that reduce energy consumption and greenhouse gas emissions. It supports the development of resilient buildings capable of adapting to changing climatic conditions, thus contributing to long-term environmental sustainability. Full article

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%. Full article

The National Standard of China has recommended the typical meteorological year (TMY) method for assessing solar energy resources. Compared with the widely adopted multi-year averaging (MYA) methods, the TMY method can consider the year-to-year variations of weather conditions and characterize solar radiation under climatological weather conditions. However, there are very few TMY-based solar energy assessments on the scale of China. On the national scale, the difference between the TMY and MYA methods, the requirement of the data record length, and the impacts of the selection of meteorological variables on the TMY-based assessment are still unclear. This study aims to fill these gaps by assessing mainland China’s solar energy resources using the TMY method and China Meteorological Forcing Dataset. The results show that the data record length could significantly influence annual total solar radiation estimation when the record length is shorter than 30 years. Whereas, the estimation becomes stable when the length is greater or equal to 30 years, suggesting a thirty-year data record is preferred. The difference between the MYA and TMY methods is exhibited primarily in places with modest or low abundance of solar radiation. The difference is nearly independent of the examined data record lengths, hinting at the role of regional-specific weather characteristics. The TMY and MYA methods differ more pronounced when assessing the seasonal stability grade. A total of 7.4% of the area of China experiences a downgrade from the TMY relative to the MYA methods, while a 3.15% area experiences an upgrade. The selection of the meteorological variables has a notable impact on the TMY-based assessment. Among the three meteorological variables examined, wind speed has the most considerable impact on both the annual total and seasonal stability, dew point has the second most significant impact, and air temperature has the least. The results are useful for guiding future research on solar energy assessment in China and could be helpful for solar energy development planning. Full article

The Photovoltaic Geographical Information System (PVGIS) is a web application that provides free access to solar radiation and temperature data, typical meteorological year (TMY) data, and to photovoltaic performance assessment tools for any place in most parts of the world. The PVGIS was originally developed over 20 years ago, and since then, it has been under continuous development. At present, there are two versions of the PVGIS online—the older version 5.1 and the newest version 5.2. PVGIS 5.2 includes substantial improvements compared to the previous version, e.g., the update of the underlying data sets both in terms of quality, resolution, and geographical coverage and the extension of the time period used. This paper focuses on comparing the TMYs (and more specifically the TMY time series of air temperature), coming from both PVGIS 5.1 and 5.2, with the TMY produced on the basis of ground station meteorological data and with the ground station data itself. The results show that whereas overall the errors and biases for most locations are within the expected range (mean stationRMSE 4.27), these differences increase in places with complicated topography, e.g., in the Alps (maximum stationRMSE 9.50). Full article

Amid the ongoing climate crisis, the international community is enacting policies to promote low-carbon energy-sharing communities. The primary objective of such communities is to enhance community-level energy self-sufficiency. Accurate energy self-sufficiency assessments are paramount in planning energy-efficient architectural designs, urban landscapes, and communal environments. In this study, the energy self-sufficiency rate of an energy-sharing community was estimated at the design stage and compared with the actual energy self-sufficiency rate calculated based on data collected over the following year (April 2022 to March 2023). The outcomes reveal that the estimated energy self-sufficiency rate is 171%, whereas the realized rate is 133%, underscoring the disparity between the projections and outcomes. An analysis of the seasonal variations in these discrepancies elucidated a correlation between the differences in the insolation levels between standard typical meteorological year (TMY) data that are conventionally used for energy generation projections and the actual meteorological conditions. Moreover, a notable incongruity surface exists between the monthly average electricity consumption of a standard four-person household, as stipulated by the Korean Electric Power Corporation (KEPCO) at 273 kWh, and the empirical power consumption at 430 kWh, resulting in a variance of approximately 157 kWh. This study illuminates the complex relationship between variables affecting energy self-sufficiency in energy-sharing communities. It serves as a crucial step towards informed decision making and precision in sustainable urban energy solutions. Full article

As a common engineering practice, the buildings are usually evaluated under the Typical Meteorological Year (TMY), which represents the common weather situation. The warm and cool conditions, however, can affect the building performance considerably, yet building performances under such conditions cannot fully be given by the conventional TMY. This paper gives approaches to constructing the weather data that represents several warm and cool conditions and compares their differences by studying the cumulative cooling demands of a typical building in a hot and humid climate. Apart from the Extreme Weather Year (EWY), the Near-Extreme Weather Year (NEWY) and Common warm/cool Years (CY) data are proposed according to the occurrence distributions of the weather over the long term. It was found that the cooling demands of NEWY and EWY differ by 4.8% from the cooling needs of TMY. The difference between the cooling demands of NEWY and CY for most calendar months can be 20% and 15%, respectively. For the hot months, the cooling demands under NEWY and CY take 7.4–11.6% and 2.3–5.6% differences from those under TMY. The uncertainties of building performance due to the ever-changing weather conditions can be essential to the robustness of building performance evaluations. Full article

The establishment of the typical weather conditions of a given locality is of fundamental importance to determine the optimal configurations for solar thermal power plants and to calculate feasibility indicators in the power plant design phase. Therefore, this work proposes a summarization method to statistically represent historical weather data using typical meteorological days (TMDs) based on the cumulative distribution function (CDF) and hourly normalized root mean square difference (nRMSD). The proposed approach is compared with regular Sandia selection in forecasting the electricity produced by a solar thermal power plant in ten different Brazilian cities. Considering the determination of the annual generation of electricity, the results obtained show that when considering an overall average of weather characteristics, commonly used for analyzing solar thermal power plant designs, the normalized mean average error (nMAE) is 20.8 ± 4.8% relative to the use of historical data of 20 years established at hourly intervals. On the other hand, a typical meteorological year (TMY) is the most accurate approach (nMAE = 1.0 ± 1.1%), but the costliest in computational time (CT = 381.6 ± 56.3 s). Some TMD cases, in turn, present a reasonable trade-off between computational time and accuracy. The case using 4 TMD, for example, increased the error by about 11 percentual points while the computational time was reduced by about 81 times, which is quite significant for the simulation and optimization of complex heliothermic systems. Full article

The natatorium’s ventilation problem receives much concern because of its large wet load. The outdoor humidity ratio in transition season is the basic design parameter of the ventilation calculation, directly affecting the rationality of architectural design. At present, the ventilation-curve (V-C) method is the most widely used method to determine the outdoor humidity ratio in the transition season in China. However, due to failing to reflect non-guaranteed hours, the rationality of this value is difficult to assess by employing this approach. This paper presents a new method, the typical transition season method (TTS), for determining the outdoor humidity ratio in the transition season of a natatorium. The TTS method selects the transition season based on the typical meteorological year (TMY) data and calculates the outdoor humidity ratio with multiple non-guaranteed hours. This can well-represent the local perennial climate characteristics and clearly reflect the non-guaranteed hours. In this study, through selecting six typical representative cities in China, the evaluation of the outdoor humidity ratio is achieved through calculating ventilation volume and air change rate, verifying the rationality of this method. The results show that the humidity ratio obtained by the V-C method is lower than that obtained by the TTS method at about 2 g/kg without guarantee of 200 h humidity ratio, and even that the maximum difference is 6.64 g/kg. Meanwhile, the validation results of the ventilation calculation show that the humidity ratio determined by the V-C method cannot meet the minimum design requirements in five cities, while the humidity ratio obtained by the TTS method cannot meet the requirements in only one city. Full article

Solar energy technology is now a mature and environmentally friendly solution. Long-term and credible solar radiation data are required for energy assessments of solar applications. Due to the lack of a typical year and accurate, long-term global solar radiation data for Taiwan, data for the typical meteorological year (TMY) of global solar radiation from 30 weather stations across Taiwan of the Central Weather Bureau were gathered for this study. The database for solar radiation contains data for the 15 years between 2004 and 2018, except for one (Chigu) weather station which provides data for the 12 years between 2004 and 2015, which possesses credible data quality and meets the requirements of the TMY method. The minimum and maximum TMY global radiation observed from the 30 weather stations are 3421.8 and 5479.9 MJ/$m^2$ at the Zhuzihu (Station 2) and Tainan (Station 16) weather stations, respectively. The effects of topography, geography, and latitude on the global radiation distribution in Taiwan are discussed. A trend of increasing annual global radiation from the northeast to the southwest in the Taiwanese mainland, which is attributed to the combined effects of topography and latitude, is observed. This credible, long-term database for global solar radiation is a prerequisite reference for solar information for use in determining the performance of solar energy applications in Taiwan. Full article

In this study, a lumped parameter model, developed and extensively validated by the authors, is used to simulate the impact of three different dehumidification technologies (mechanical refrigeration dehumidifier, liquid desiccant dehumidifier, and a heat recovery ventilation unit), at a commercial greenhouse growing potted roses in southwestern Ontario, Canada. Typical meteorological year (TMY) data from nearby Vineland, Ontario was used to provide the external weather data used in the model. Each greenhouse bay containing a dehumidification unit was simulated for spring, fall, and winter conditions. The potential reductions in energy use (kWh), greenhouse gas emissions (kg CO_2e), and operating cost were estimated for each test case. The potential energy savings from switching from high-pressure sodium (HPS) to light-emitting diode (LED) lights were also examined. The simulation results showed that switching to LED lamps could reduce the electrical energy usage by up to 60% but would increase the space heating requirements. The expected energy-savings from using dehumidification equipment and switching from HPS to LED lighting in Canadian greenhouses is underrepresented in the literature. With the industry growing in the region, this study provides insight into the expected impact that these systems will have on the energy use in commercial greenhouses. Full article