Search Results (342)

The output of vehicle-integrated photovoltaics (VIPVs) varies due to complex surface interactions, shading, weather conditions, module temperature, and module configuration, making accurate predictions of power generation challenging. This study examines the characteristics of incident light on VIPVs, focusing on installations on automobile roofs and hoods. Surface element data were collected from areas near the target locations (hood and roof), with shading effects taken into account. The calculations evaluated how the angle of incoming light impacts the intensity on specific parts of the vehicle, identifying which surfaces are most likely to receive maximum illumination. For example, the hood exhibited the highest incident light intensity when sunlight approached directly from the front at a solar altitude of 71°, reaching approximately 98% of the light intensity. These calculations enable the assessment of incident light intensity characteristics for various vehicle parts, including the hood and roof. Additionally, by utilizing database information, it is possible to calculate the incident light on vehicle surfaces at any given time and location. Full article

The global climate crisis has driven unprecedented agreements among nations on carbon mitigation. With China’s commitment to carbon peaking and carbon neutrality targets, the building sector has emerged as a critical focus for emission reduction, particularly because office buildings account for over 30% of building energy consumption. However, a systematic and regionally adaptive low-carbon technology evaluation framework is lacking. To address this gap, this study develops a multidimensional decision-making system to quantify and rank low-carbon technologies for office buildings in Beijing. The method includes four core components: (1) establishing three archetypal models—low-rise (H ≤ 24 m), mid-rise (24 m < H ≤ 50 m), and high-rise (50 m < H ≤ 100 m) office buildings—based on 99 office buildings in Beijing; (2) classifying 19 key technologies into three clusters—Envelope Structure Optimization, Equipment Efficiency Enhancement, and Renewable Energy Utilization—using bibliometric analysis and policy norm screening; (3) developing a four-dimensional evaluation framework encompassing Carbon Reduction Degree (CRD), Economic Viability Degree (EVD), Technical Applicability Degree (TAD), and Carbon Intensity Degree (CID); and (4) conducting a comprehensive quantitative evaluation using the AHP-entropy-TOPSIS algorithm. The results indicate distinct priority patterns across the building types: low-rise buildings prioritize roof-mounted photovoltaic (PV) systems, LED lighting, and thermal-break aluminum frames with low-E double-glazed laminated glass. Mid- and high-rise buildings emphasize integrated PV-LED-T8 lighting solutions and optimized building envelope structures. Ranking analysis further highlights LED lighting, T8 high-efficiency fluorescent lamps, and rooftop PV systems as the top-recommended technologies for Beijing. Additionally, four policy recommendations are proposed to facilitate the large-scale implementation of the program. This study presents a holistic technical integration strategy that simultaneously enhances the technological performance, economic viability, and carbon reduction outcomes of architectural design and renovation. It also establishes a replicable decision-support framework for decarbonizing office and public buildings in cities, thereby supporting China’s “dual carbon” goals and contributing to global carbon mitigation efforts in the building sector. Full article

Renewable Energy Communities (RECs) are voluntary coalitions of citizens, small and medium-sized enterprises and local authorities, which cooperate to share locally produced renewable energy, providing environmental, economic, and social benefits rather than profits. Despite a favorable European and Italian regulatory framework, their development is still limited in the Member States. To this end, this paper proposes a methodology to identify optimal spatial configurations of RECs, based on proximity criteria and maximization of energy self-sufficiency. This result is achieved through the mapping of the demand, expressive of the energy consumption of residential buildings; the suitable areas for installing photovoltaic panels on the roofs of existing buildings; the supply; the supply–demand balance, from which it is possible to identify Positive Energy Districts (PEDs) and Negative Energy Districts (NEDs). Through an iterative process, the optimal configuration is then sought, aggregating only PEDs and NEDs that meet the chosen criteria. This method is applied to the case study of the Avellino Province in the Campania Region (Italy). The maps obtained allow local authorities to inform citizens about the areas where it is convenient to aggregate with their neighbors in a REC to have benefits in terms of energy self-sufficiency, savings on bills or incentives at the local level, including those deriving from urban plans. The latter can encourage private initiative in order to speed up the RECs’ deployment. The presented model is being implemented in the framework of an ongoing research and development project, titled Renewable Energy Communities Monitoring, Optimization, and Planning (RECMOP). Full article

As a densely populated area, college student dormitories consume a large amount of electricity every year to heat the domestic hot water used by students. Applying solar energy to hot water systems can effectively alleviate this situation. This paper first conducts a simulation of the hot water load and the calculation of the available area of the solar roof in a dormitory building of a certain university. Then, different solar-coupled air source heat pump systems were designed, and simulation models of the two systems were established. The thermal performance parameters and solar energy utilization of the two systems were discussed, and the energy efficiency, economy, and environmental protection of the two systems were analyzed. The results show that after coupling with the solar collector, the system operation time is shortened by 26.2%, the annual performance coefficient is 3.4, which is 0.8 higher than that of the original system, and the annual heating energy consumption is reduced by 24.4%. In contrast, the annual energy self-sufficiency rate of the photovoltaic coupled with air source heat pump system is 94.6%, achieving nearly zero energy consumption for heating. Full article

This study combines convolutional neural network (CNN) recognition technology, Greenwich engineering software, and statistical yearbook methods to evaluate rural solar, wind, and biomass energy resources in pilot cities in China, respectively. The CNN method enables the rapid identification of the available roof area, and Greenwich software provides wind resource simulation with local terrain adaptability. The results show that the capacity of photovoltaic power generation reaches approximately 15.63 GW, the potential of wind power is 458.3 MW, and the equivalent of agricultural waste is 433,900 tons of standard coal. The city is rich in wind, solar, and biomass resources. By optimizing the hybrid power generation system through genetic algorithms, wind energy, solar energy, biomass energy, and coal power are combined to balance the annual electricity demand in rural areas. The energy trends under different demand growth rates were predicted through the LEAP model, revealing that in the clean coal scenario of carbon capture (WSBC-CCS), clean coal power and renewable energy will dominate by 2030. Carbon dioxide emissions will peak in 2024 and return to the 2020 level between 2028 and 2029. Under the scenario of pure renewable energy (H_WSB), SO₂/NO_x will be reduced by 23–25%, and carbon dioxide emissions will approach zero. This study evaluates the renewable energy potential, power system capacity optimization, and carbon emission characteristics of pilot cities at a macro scale. Future work should further analyze the impact mechanisms of data sensitivity on these assessment results. Full article

China’s urban residential building stock is extensive and spans a wide range of construction periods. With the continuous enhancement of building energy efficiency standards, the chronological characteristics and variability of residential building envelopes are evident. Through field research and typological analysis of residential buildings in Jinan, a cold region of China, three construction eras were classified: Period I (1980–1985), Period II (1986–1995), and Period III (1996–2005). Building performance and economic benefits across these periods are modeled using Rhino 7.3 and Grasshopper. The NSGA-II algorithm, as the core of Wallacei2.7, is employed for multi-objective optimization. Through K-means clustering, TOPSIS comprehensive ranking, and Pearson correlation analysis, the optimized processes and solutions are provided for urban residential renovation decisions in different periods and target preferences. The results show that the optimal comprehensive performance solutions for Period I, Period II, and Period III achieve energy savings of 40.92%, 29.62%, and 15.81%, respectively, and increase annual indoor comfort hours by 872.64 h/year, 633.57 h/year, and 564.11 h/year. For Period I and II residential buildings, the most effective energy efficiency retrofit measures include increasing exterior wall and roof insulation, replacing exterior window types, and reducing exterior window k-value. The overall trend in energy savings rates and economic benefits across the three periods shows a decline. For Period III residential buildings, systematic strategies, such as solar thermal collector systems and photovoltaic technology, are required to enhance energy efficiency. Full article

With the development of alternative energy technologies, energy production from renewable sources is gaining wide application. One of the types of renewable energy sources is solar power. In the past 5 years, solar cells have become very popular for both private electricity microgeneration and large power plants. There are two main options for installing solar photovoltaic panels: on the roof of a house or the ground; on specially made frames. When installing solar cells on the roof, it is not always possible to choose a tilt angle that is appropriate for all seasons, since the angle is mainly adjusted to the plane of the roof. When installing solar cells on the ground, it is usually possible to choose both the orientation relative to the cardinal points and the tilt angle relative to the ground. There are various theories about the best tilt angle of solar cells for producing the most amount of energy during the year. Therefore, the aim of the present research study is to develop an original research methodology for determining an optimal tilt angle for solar cells. The research study examined six different tilt angles of solar cells, 0°, 30°, 35° 40° 45° and 50°, orienting the cells towards the south. The research study used 18 identical monocrystalline solar panels with a power of 20 W. Three solar panels were set at each angle. This way, the experiment had three replications at each angle of the solar cells. The measurements were recorded by a GWL840 data logger with an interval of 10 s. The experiment was conducted by placing all solar cell modules on the roof of the building at Lat. 56.66181° and Long. 23.75238°. During the experimental period, the highest efficiency was found for the solar panels set at 50° and 40°, reaching the total solar irradiation of 266.61 Wm⁻² and 266.27 Wm⁻², respectively. Full article

Rooftop photovoltaic (PV) panel systems have become a key component in green building design, driven by new building sustainability measures advocated worldwide. The shading generated by the rooftop PV panel arrays can impact their annual heating and cooling load, as well as their overall thermal performance. This paper presents a long-term experimental investigation into the changes in roof temperature caused by PV panels. The experiment was conducted over the course of a year, with measurements taken on four sample days each month. The study is based on measurements of the covered roof temperature, the uncovered roof temperature, PV surface temperature, ambient air temperature, as well as solar irradiation, wind speed, and rainfall. The results reveal that the annual energy savings (MJ/m²) in the cooling load due to the covered roof are about 26% higher than the energy loss from the heating load due to shading. The study shows that the effect of the rooftop PV panels on the house’s total heating and cooling load savings is between 5.3 to 6.1%. This difference is significant in thermal performance analyses, especially if most of the roof is covered by PV panels. Full article

The integration of tilted photovoltaic strings on large, flat roofs, typical of industrial and commercial buildings, raises complex design challenges, particularly regarding wind-induced loads. This study presents a comprehensive wind tunnel investigation aimed at evaluating the aerodynamic effects on rooftop PV strings under various representative configurations and the correlation between characteristic geometric parameters such as tilt angle, bottom clearance, row spacing, and wind direction. Following a literature review, a detailed 1:10 scaled model with geometric adjustment capabilities was developed and eventually tested in a boundary-layer wind tunnel. High-resolution pressure measurements were processed to derive force and moment resultants normalised by reference wind pressure. Envelopes of force/moment resultants are presented for each representative geometric configuration and for each wind exposure angle. The results present severe variations in local wind actions, particularly significant at the strings’ free ends and for oblique wind angles. The severe underestimation of local wind loads by standard codes is discussed. The findings underline the importance of detailed wind-load assessment for both new constructions and retrofits, suggesting that reliance solely on code provisions might result in unsafe designs. Full article

With the rapid development of science and technology, the global demand for renewable energy is increasing. In the urban context, solar energy has become one of the key ways to increase urban energy self-sufficiency and reduce carbon emissions due to its flexibility in installation and ease of expansion of applications. Therefore, based on Geographic Information System (GIS) and deep learning modeling, this paper proposes a method to efficiently assess the potential of urban rooftop solar photovoltaic (PV), which is analyzed in a typical area of Lanzhou New District, which is divided into 8774 units with an area of 87.74 km². The results show that the method has a high accuracy for the identification of the roof area, with a maximum maxF_β of 0.889. The annual solar PV potential of industrial and residential buildings reached 293.602 GWh and 223.198 GWh, respectively, by using the PV panel simulation filling method for the calculation of the area of roofs where the PV panels can be installed. Furthermore, the rooftop PV potential of the industrial buildings in the research area provided can cover 75.17% of the industrial electricity consumption. This approach can provide scientific guidance and data support for regional solar PV planning, which should prioritize the development of solar potential of industrial buildings in the actual consideration of rooftop PV deployment planning. Full article

The transition to renewable energy is critical to enhance Puerto Rico’s energy resilience and reduce dependence on imported fossil fuels. Rooftop photovoltaic (PV) systems provide a scalable opportunity to meet these objectives. This study evaluates the potential of rooftop PV systems across Puerto Rico using the National Renewable Energy Laboratory’s (NREL) PV Rooftop Database, processing detailed roof surface data to estimate installed capacity, energy generation, Levelized Cost of Electricity (LCOE), and solar resource potential at municipal and barrio levels. Findings reveal high solar rooftop capacity in urban neighborhoods, with areas like Sabana Abajo and Hato Tejas each exceeding 450 GWh/year in potential generation. Solar rooftop resource values peak at 3.67 kWh/kW in coastal areas, with LCOE values (0.071–0.215 USD/kWh) below current electricity rates. All municipalities demonstrate technical potential to meet their electricity demand with rooftop PV system alone. This research contributes through (1) developing Puerto Rico’s first comprehensive solar rooftop potential map; (2) providing unprecedented barrio-level analysis; (3) introducing a methodology for estimating missing post-disaster consumption data; and (4) integrating technical, economic, and equity indicators to inform energy policy. These findings demonstrate the importance of rooftop solar in achieving renewable energy goals and provide an understanding of spatial energy inequalities. Full article

Agrivoltaic greenhouses in southern Spain offer a sustainable way to manage excessive irradiance levels by generating renewable energy. This study presents a shading experiment on tomato cultivation in a raspa-y-amagado greenhouse in Almeria, southern Spain, during the 2023–2024 growing season. Photovoltaic modules were mimicked by opaque plastic sheets that were arranged in a checkerboard pattern on the roof of the greenhouse. Two shading zones (30% and 50% roof cover ratio) were compared against an unshaded control zone. Microclimate, plant physiology, yield and quality were monitored during the study. The results show that shading influenced the microclimate, which directly impacted crop yield. The 30% and 50% shading zones resulted in 15% and 26% crop yield reductions, respectively. A preliminary, theoretical analysis of potential revenues of the photovoltaic yield showed that reductions in crop yield can be overcompensated by the energy generated by the PV system. For the summer crop cycle, a higher PV production and lower crop yield reductions can be expected. The economic advantage demonstrates the potential of agrivoltaic greenhouses in southern Spain. Full article

The traditional carrying capacity assessment method fails to effectively quantify the difference in spatial distribution of rooftop photovoltaic (PV) resources and ignores the temporal fluctuation of PV output and load demand, as well as the temporal and spatial matching characteristics of sources and loads. This leads to problems such as a disconnect between the assessment and the actual grid acceptance capacity and insufficient dynamic adaptability. In response to the above issues, this paper proposes a dynamic assessment model for distributed photovoltaic carrying capacity based on the combination of improved DeepLabv3+ and game-theoretic weighted assignment. First, the DeepLabv3+ model was improved by integrating the Efficient Channel Attention (ECA) mechanism and the strip pooling (SP) module to enhance roof recognition accuracy. Ablation experiments showed that the mIoU increased to 77.53%, 6.29% higher than the original model. The simulation results in the summer scenario demonstrated that, with the optimal coordination of STMF and scene scoring, the comprehensive carrying coefficient reached 0.73. Next, a photovoltaic carrying capacity evaluation system was established, considering the source, grid, and load perspectives, with dynamic evaluation using a game-theory-based weighting method. Finally, a comprehensive carrying coefficient was introduced, accounting for the spatiotemporal match between photovoltaic output and load, leading to the development of a distributed photovoltaic carrying capacity model. The case study results show that, in summer, due to the optimal coordination of STMF and scene scoring, the comprehensive carrying coefficient reaches 0.73. With a total PV access capacity of 6.48 MW, all node voltages remain within limits, verifying the model’s effectiveness in grid adaptability. Full article

This study develops a calibrated multiscale simulation of three lightweight industrial warehouses located in Tecámac, Mexico, to evaluate the dual role of rooftop photovoltaic (PV) arrays as renewable energy generators and passive thermal modifiers. Dynamic energy models were developed using EnergyPlus via Ladybug Tools v. 1.8.0 and calibrated against 2021 real-world electricity billing data, following ASHRAE Guideline 14. Statistical analyses conducted in RStudio v2024.12.1 Build 563 confirmed significant passive cooling effects induced by PV integration, achieving up to 15.3 °C reductions in peak indoor operative temperatures and improving thermal comfort rates by approximately 10 percentage points. While operational energy savings were evident, the primary focus of this research was on the multiscale modeling of thermal performance enhancement in composite metallic-PV roofing systems under semi-arid climatic conditions. These results provide new insights into computational approaches for optimizing passive thermal performance in lightweight industrial envelopes. Full article

The search for sustainable energy alternatives is urgent in the face of climate change and resource scarcity. In this context, increasing energy efficiency in buildings through distributed energy resources (DERs) is crucial for sustainability and self-sufficiency. This article aims to analyze the impact of several energy efficiency actions, in addition to the installation of a photovoltaic solar energy system in a public building in a semi-arid region, determining the necessary aspects for such buildings to become positive energy buildings (PEBs) and/or net zero energy buildings (NZEBs). As a basis for the methodology, a case study was carried out in a university restaurant in a semi-arid region in Brazil. Several pieces of data were collected, such as the air temperature, solar radiation, active energy and the number of users in the building. The relevance of each variable in relation to electricity consumption was identified through statistical correlation analysis, resulting in an energy consumption per square meter per year of 80.78 kWh/m²/year and an active energy consumption per user per year of 0.88 kWh/m²/year. Three energy efficiency actions were evaluated and compared technically and economically against the investment in a grid-connected photovoltaic system (GCPVS) for the same building, simulating before and after the entry into force of Law 14.300/2022, which regulates distributed generation in Brazil. The installation of thermal insulation on the building’s roof showed good technical, economic and environmental performance, compared to GCPVS, and proved to be attractive and competitive among the other scenarios. All simulated actions resulted in an annual emission reduction of 14.8 tCO₂e. When calculating the building’s generation potential, it was found that it could be considered an NZEB and PEB. Full article