Search Results (482)

This study analyses household energy consumption patterns and the main energy-related challenges in the rural communities of San Sebastián de Yuluc and Sumaypamba, Ecuador, within the framework of sustainable community energy planning. A quantitative descriptive approach was adopted, based on structured household surveys and statistical analyses using descriptive statistics, nonparametric correlations, and mean comparisons. The results show that electricity consumption in both communities remains below the national household average, while liquefied petroleum gas remains the dominant cooking energy source. Firewood is still used by a portion of households, whereas the adoption of active solar energy systems is practically non-existent. Significant differences in electricity consumption were identified across communities, as were heterogeneous consumption patterns associated with household equipment and living conditions. In Sumaypamba, a strong positive correlation was found between electricity and gas consumption, suggesting complementary rather than substitutive energy use. The findings reveal limited infrastructure, unequal access to modern energy technologies, and a persistent dependence on non-renewable fuels. These results provide evidence to inform local energy transition strategies focused on rural electrification, energy efficiency, and renewable microgeneration to improve energy access, sustainability, and community resilience. Full article

Concentrated Solar Power (CSP) is a strategic clean-energy technology for India, combining high-efficiency electricity generation with thermal storage to enable power supply beyond daylight hours. This review maps CSP potential across India by analysing solar resource distribution, the suitability of different CSP technologies (e.g., parabolic troughs and solar towers), and economic feasibility under current cost and policy conditions. It evaluates recent developments in deployment, technology maturity and financing mechanisms, while identifying key barriers such as land availability, grid integration and investment risk. In addition, the study identifies research gaps related to large-scale deployment, cost-reduction strategies, and long-term performance under Indian climatic conditions, and outlines future research directions and policy pathways to accelerate CSP adoption in India. By drawing on recent data and trends, the paper offers insight into how CSP can complement the ongoing expansion of renewable electricity and contribute to India’s goal of achieving 500 GW of non-fossil installed capacity by 2030 and net-zero by 2070. The analysis aims to support researchers, policymakers and industry stakeholders in making informed decisions to scale CSP deployment. Full article

Precision agriculture and sustainable farming practices require autonomous environmental monitoring systems capable of operating in remote areas with limited energy and connectivity. However, the high cost of existing professional technology remains a significant barrier to widespread adoption. This study presents the development of a solar-powered smart sensing node designed for autonomous operation that integrates TinyML and dual-mode wireless connectivity via LoRaWAN and Wi-Fi for intelligent monitoring. The system features a custom-designed cup anemometer and multispectral sensing capabilities integrated into a compact single-tower architecture. All structural components, including radiation shields and a modular PVC frame, were designed for low-cost manufacturing and mass production. A single hermetic housing protects the core control electronics and is designed to improve durability in harsh outdoor environments. A Multi-Layer Perceptron model was implemented on the edge to enable intelligent data fusion and compensation, while a dynamic sampling strategy optimized power consumption. Experimental results demonstrate the feasibility of the proposed architecture through adaptive spectral acquisition over a daily illumination cycle, embedded MLP-based sensor fusion, and telemetry-oriented data compression that substantially reduces the number of transmitted samples. The main contribution of this work is a system-level architecture that integrates sensing, embedded intelligence, solar-energy harvesting, hybrid wireless communication, and telemetry optimization into a compact, low-cost, and field-deployable prototype IoT platform for sustainable precision agriculture. Full article

Composite vortex beams (CVBs) with multiple spatial singularities and orbital angular momentum (OAM) are widely used in various applications including multiple optical traps and optical communication. Here, based on the equal-angle segmentation and radial displacement modulation approach, we propose an innovative scheme for generating CVBs with controllable OAM spectrum by proposing a simple and compact optical element termed as single-helicity annulus-sector spiral zone plates (SASZPs). Theoretical analysis reveals that by modulating the structural parameters of the SASZPs, such as the topological charge, the radial misalignment parameter and the number of annulus-sector primitives, an attractive intensity pattern consisting of petal-like structures can not only be produced but also the mode purity of CVBs can also be flexibly controlled. In addition, by adopting the high-quality and low-defect diamond substrate we have synthesized, based on the electron beam lithography technology and dry etching technology, the SASZP samples with different parameters have been fabricated and the focusing properties of such optics in the visible light region have been carried out and verified. These findings direct a new avenue for improving the performance of ultra-compact solar-blind UV imaging, optical communication and integrated optics. Full article

Decarbonisation targets are now widely adopted. However, the speed at which renewables are built depends on many factors, including technology, cost, regulation, and the decisions of investors, developers, and governments. Public acceptance is one of these factors, but it is not the decisive one. This article examines public acceptance specifically: the attitudes, perceptions, and preferences of citizens and consumers, which form only one part of the wider social acceptance of renewable energy that also involves policy-makers, intermediaries, and market actors. We ask how public acceptance of renewable energy varies across countries, what drives that variation, and which policy instruments most reliably turn public approval into built capacity. Using a structured narrative synthesis across 21 countries, we integrate major cross-national opinion surveys (Eurobarometer 555, the UNDP–Oxford Peoples’ Climate Vote 2024, Pew, DESNZ, CSIRO, KfW, Ipsos), peer-reviewed work on local community acceptance, and capacity data from IRENA and the IEA. Three findings stand out. Headline support is high almost everywhere—a median of 76% across 77 countries and 85% in the EU—but increasingly masks polarisation, most sharply in the United States, where the partisan gap on prioritising renewables widened from 26 to 49 points between 2020 and 2024. Technology-specific acceptance follows a broadly consistent order, from rooftop solar down through wind, geothermal, hydropower, and biomass to carbon capture and nuclear. And community acceptance turns less on physical proximity to infrastructure than on procedural fairness, place attachment, and meaningful financial participation. Our contribution is integrative: we propose operational indicators of public acceptance that travel across national contexts, a country typology linking acceptance institutions to renewable outcomes, and a five-element policy architecture—early participation, benefit sharing, procedural transparency, place-sensitive siting, and credible information—each mapped to the acceptance dimension it addresses. Full article

Public building retrofit is an important pathway for reducing operational carbon emissions, but evidence-based technology prioritisation remains limited under real-world multi-technology retrofit conditions. This study develops an interpretable data-driven framework to identify priority technologies and technology co-adoption patterns for public buildings in China’s Hot Summer and Cold Winter (HSCW) region. Based on 218 completed retrofit projects, the carbon reduction rate (CRR) was used as the performance indicator, and 15 retrofit technologies were analysed using FDR-adjusted Mann–Whitney U tests, repeated-validation XGBoost–SHAP analysis, and Apriori association-rule mining. The projects showed substantial variation in CRR, with a mean of 24.98% and a median of 21.70%. Across five repeated 5-fold cross-validations, the predictive XGBoost model achieved a mean R² of 0.417 and a mean RMSE of 0.127. Roof insulation, external wall insulation, and ventilation system retrofit showed the strongest combined evidence and were classified as core technologies. Apriori analysis further revealed three empirical co-adoption patterns: integrated passive-envelope retrofit, solar-control and renewable-energy integration, and operational-management improvement. The findings suggest that retrofit planning in the HSCW region should prioritise envelope insulation and ventilation performance, while selecting shading, system, renewable-energy, and operational-control measures according to project-specific conditions. Full article

Contemporary built environments are increasingly constrained by limited spatial resources, rising density, and evolving functional requirements, demanding more adaptive and sustainable design strategies. Although multifunctional interior design is widely recognized for improving spatial efficiency, material reduction, and long-term adaptability, there remains a need for practice-based studies that examine how multifunctionality can be analyzed consistently across professional practice and design education in relation to sustainability. This practice-based qualitative study investigates how multifunctionality contributes to sustainability across the author’s professional practice and design education through a comparative analysis of professional projects and educational design experiments. The research adopts a qualitative, practice-based methodology combining the analysis of six professional projects from the author’s architectural practice with ninety educational design projects developed within an integrative architectural curriculum. These include multifunctional interior interventions, adaptive furniture systems, and digitally fabricated prototypes exploring small-scale renewable energy integration through solar-powered lighting and bio-inspired micro-structures developed within studio-based learning and digital fabrication courses. The comparative analysis identified recurring multifunctional design mechanisms operating across multiple scales, from furniture objects and interior systems to architectural interventions and concept-driven spatial identities. Beyond functional optimization, it acts as a generative design framework capable of integrating spatial organization, material efficiency, social interaction, and environmental responsiveness. The educational projects further suggest that multifunctionality can be effectively introduced as a pedagogical tool, supporting the development of spatial thinking and design adaptability. The main scientific contribution of this study is the development of a practice-based analytical framework that connects professional practice, project-based learning, and digital fabrication through multifunctionality as a common design strategy. This framework is characterized by a highly integrated cross-disciplinary structure, in which multiple subjects converge within the core Design Studio, enabling a continuous exchange between theory, practice, and experimentation. This approach strengthens the connection between academic learning and professional application. The results suggest that multifunctional interior design contributes to sustainability by reducing spatial redundancy, integrating multiple functions within single systems, supporting long-term adaptability, and encouraging more efficient use of material and spatial resources. These findings support the interpretation of multifunctionality as a transferable sustainability-oriented design strategy that connects professional practice, architectural education and emerging design technologies through recurring mechanisms of spatial optimization, resource efficiency, and long-term adaptability. Full article

The integration of Concentrated Solar Power (CSP) and Photovoltaic (PV) technologies represents a promising strategy to enhance the reliability, flexibility, and dispatchability of solar-based electricity generation. The novelty of this work lies in the development and assessment of an integrated PV–CSP hybrid power plant in a series configuration, where the two technologies are energetically coupled and coordinated with thermal energy storage and an electrolyzer under a grid-minimization operating strategy. Unlike most previous studies, which investigate PV and CSP systems as standalone or loosely coupled technologies, the proposed approach simultaneously optimizes renewable electricity utilization, dispatchable operation, and green hydrogen production. A comprehensive simulation framework was developed using site-specific solar irradiance data, component performance models, thermal energy storage characteristics, and electrolyzer operating constraints. A seasonal operating strategy was adopted, with the CSP plant and the electrolyzer operating from 15 April to 15 October, while the PV system generated electricity throughout the entire year. Under these conditions, the electrolyzer operated for 4416 h·year⁻¹, producing 1000 t·year⁻¹ of green hydrogen and requiring an annual electricity demand of 52.4 GWh. The hybrid renewable system supplied 37.2 GWh of this demand, corresponding to a renewable penetration of approximately 71%, while the remaining 29% was covered by grid electricity purchases. Results show that the series hybridization of CSP and PV technologies improves overall plant performance compared with standalone solar systems. In particular, the integration of thermal energy storage within the CSP subsystem enabled dispatchable generation and more stable electrolyzer operation. All the electricity generated by the CSP plant was directly utilized by the electrolyzer, and approximately 17% of the renewable electricity supplied to the electrolyzer was delivered during periods when PV production was unavailable, corresponding to 12.2% of the total annual electricity demand of the electrolyzer. Furthermore, of the total annual PV generation of 33.6 GWh, 15.1 GWh were directly used for hydrogen production, while 18.5 GWh were exported to the electrical grid, resulting in a positive annual electricity balance. The analysis provides design and operational guidelines for optimizing integrated PV–CSP plants coupled with hydrogen production systems under a grid-minimization strategy. The findings confirm that hybrid solar systems integrating dispatchable CSP generation, thermal energy storage, and PV technologies can significantly increase renewable penetration, support stable, low-carbon power generation, and enable large-scale green hydrogen production with reduced dependence on grid-supplied electricity. Full article

IoT cloud platforms support the monitoring and management of distributed renewable-energy systems, but sustaining them can be challenging in academic and community initiatives with limited resources. Recurring cloud-service fees, dependence on proprietary platforms, and limited local control may become major obstacles, particularly when long-term service operation must be combined with technical capacity-building within local institutions and surrounding communities. This paper presents an open-source, multi-tenant IoT cloud architecture developed within the GREATER Erasmus+ framework and deployed in renewable-energy Living Labs in Rwanda. The architecture is built using widely adopted open-source tools, including Docker, Node-RED, MySQL, Nginx, MQTT, and HTTPS APIs. The main novelty is an open-source middleware layer that transforms standard components into a shared, tenant-aware platform by coordinating authentication, role-based access, tenant-aware routing, controlled database access, separate Node-RED workspaces, and dashboard visibility for different Living Labs and user roles. The platform has been deployed in real settings, supporting photovoltaic monitoring, solar-powered irrigation, community energy services, domestic energy monitoring, and educational activities. The platform is evaluated in terms of cost, resource usage, communication delay, reliability mechanisms, and access-control behavior. The results show that heterogeneous IoT services can be hosted on modest local infrastructure while maintaining logical separation between Living Lab data and services. By combining open-source technologies, multi-tenant management, and field deployment, the proposed architecture offers a practical model for higher-education institutions and community-oriented renewable-energy initiatives in resource-constrained environments. Full article

The rise in energy demand in Thailand due to constant economic growth coupled with reliance on limited natural gas and oil resources has led to an increased demand for alternative sources of energy. Therefore, this study aims at examining factors that influence the intention of adopting solar rooftop energy among households in Thailand through the integration of the theory of planned behavior (TPB) and the technology acceptance model (TAM). A quantitative research approach was adopted whereby data were obtained from 255 households in all parts of Thailand through questionnaires. The results reveal that attitude (β = 0.484, p < 0.001), perceived usefulness (β = 0.271, p < 0.05), and subjective norms (β = 0.257, p < 0.001) positively and significantly influence intention to use solar rooftop energy, collectively explaining 61% of the variance (R² = 0.61). Attitude proved to be the most significant predictor in this regard, underscoring the significance of the evaluative process of cognition and emotion for adopting certain behavior. This research makes a valuable contribution to the body of knowledge on renewable energy in that the TPB-TAM model has been empirically validated in a Thai household setting. In addition, the findings provide suggestive evidence of a mediating role of attitude in the link between perceived usefulness and intention, although this mediation finding should be interpreted with caution due to the conceptual overlap between these constructs and the absence of bootstrap confidence intervals. Future research is recommended to confirm this mediation pathway using formal bootstrap procedures. Full article

This exploratory pilot study analyzes the organizational and environmental determinants associated with stated intention to adopt biogas-solar microgrids within a circular bioeconomy framework. A quantitative, applied, cross-sectional design was used with 71 valid individual responses from participants linked to productive, agro-industrial, livestock, energy, and waste management organizations or projects, selected through nonprobabilistic convenience sampling. The analysis does not measure actual investment, implementation, or use; therefore, the results refer only to declared adoption intention and should not be generalized beyond the sample. The questionnaire measured perceived benefits, barriers, institutional conditions, financial feasibility, environmental value, organizational capabilities, and adoption intention. Content validity was supported by expert judgment, and psychometric reliability was assessed using Cronbach’s alpha and McDonald’s omega. Predictive modeling compared supervised classification, regression, and unsupervised segmentation techniques using train-test validation, cross-validation, and interpretability analyses. ExtraTrees achieved the best exploratory classification performance, with a test ROC-AUC of 0.889, while RandomForestRegressor showed the best regression performance; however, these values should be interpreted as sample-specific evidence rather than as a validated predictive tool. Organizational capabilities and environmental criteria emerged as the most influential predictors, and K-Means suggested two tentative readiness profiles with weak separation. The findings suggest that stated adoption intention is associated with a systemic configuration of organizational maturity, environmental legitimacy, financial feasibility, and institutional support, providing preliminary evidence for future larger sample validation and for decision-support discussions in sustainable energy transitions. Full article

While total solar PV capacity in Hungary was only 1 MW in 2010, this figure had grown to 7551 MW by 2024 as a result of the favorable settlement system, subsidies, and the uncertainty caused by the Russo-Ukrainian war. At that time, more than 6.4% of households were already prosumers. In our study, we focus on Hungarian districts, examining the spatial patterns of household-scale solar PV systems and the main drivers of technology adoption in 2024. We use the Theil T index to examine spatial heterogeneity and the Moran’s I statistic to test for spatial dependence. Spatial autocorrelation is further explored using maps based on Local Moran’s I and Local Geary statistics. Finally, a spatial error model is applied to identify the factors influencing the share of household-scale solar PV systems per 100 households. Our results show that the spatial error variable has the largest effect, with household education, the age and size of the building stock, population growth, and built-up area also having significant effects. This confirms the need for a spatially sensitive policy approach and for incorporating space and spatial relations in energy economic studies. Full article

Institutional shuttle fleets with fixed routes and predictable terminal parking are well-suited to charging photovoltaic–battery energy storage system (PV–BESS) charging for sustainable campus mobility. However, siting and sizing are often solved numerically without identifying the physical constraints that determine the optimum. This study develops a sustainability-oriented framework for converting a 10-van diesel shuttle fleet at Rajamangala University of Technology Lanna into an electric fleet supported by distributed PV–BESS charging stations. A centralized one-station layout is compared with a distributed two-station layout, and a closed-form active-constraint sizing rule is derived using Karush–Kuhn–Tucker (KKT) analysis. Results show that the distributed configuration eliminates dead-run travel and provides higher lifecycle value than the centralized case. KKT analysis identifies two binding constraints: the PV rooftop-area limit and the BESS one-day autonomy requirement. Under base-case assumptions, the transition achieves positive lifecycle value and substantial CO₂ reduction relative to the diesel baseline. Monte Carlo analysis confirms financial robustness within the uncertainty ranges, while deterministic stress tests show sensitivity to diesel prices, PV electricity credit values, discount rate, and fleet utilization. The framework provides an interpretable decision-support method for institutional fleet electrification in solar-rich campus settings, contributing to SDGs 7, 11, and 13 through clean-energy adoption, sustainable transportation, and CO₂-emission reduction. Full article

One to four million annual premature deaths are associated with household air pollution. This indoor pollution is mainly generated by traditional biomass cookstoves. Thus, solar cooking can significantly reduce this toll. Its proliferation would also mitigate deforestation pressures. Additionally, for developing countries, it would alleviate the fuel collection workload, mainly borne by women responsible for fuel collection. Electric cooking provides a clean and controllable alternative to thermal cookers for indoor food preparation, sterilization and heating. This study presents a minimal, off-grid photovoltaic solar cooker that operates without batteries and power electronics. Such a cooker constitutes a low-cost and high-reliability solution for electrically decentralized locations. The system encompassing the cooker is conceived as an accessible entry point for household-level photovoltaic (PV) adoption. So, it offers the potential to catalyze the uptake of clean-energy technologies and to support sustainable development. The proposed design dissipates PV power into heat using commercial positive temperature coefficient (PTC) resistors operating near their Curie temperature. A simplified theoretical model is formulated to easily estimate the thermal power and heat-transfer conductances required for achieving cooking temperatures. An instrumented prototype allows for characterizing the transient temperature evolution during controlled heating and cooling experiments in the laboratory, facilitating development in an initial step avoiding the PV panel. The results demonstrate that the minimal PV configuration is technically feasible, robust, and compatible with low-resource settings. This encourages its adoption in communities experiencing energy poverty. Full article

The increased deployment of photovoltaic (PV) technology has led to an increased demand for grid-balancing capacity owing to growing short-term variability and forecast uncertainty. Simultaneously, higher PV penetration can lead to daytime energy market oversupply, pushing day-ahead prices toward zero and undermining PV revenues. Against this backdrop, this study investigated a market participation paradigm in which PV power plants supply reserve power themselves while actively absorbing their own uncertainty, rather than merely relying on balancing the services provided by external resources. We propose a risk-aware framework that classifies solar irradiance prediction errors into four risk categories using GPV-GSM numerical weather forecast data, translating the inferred risk level into practical bidding rules for balancing market participation. We adopted a hierarchical classification pipeline consisting of sign determination (stage 1, under- vs. overprediction), followed by degree determination (Stages 2 and 3), implemented with a multi-layer perceptron. To enhance class separability and reduce features, we introduced a stage-wise area under the curve (AUC)-based feature selection and compared AUC-selected and all-features settings under identical training conditions. The proposed strategies substantially reduce shortage events compared with directly using the original predictions as bids, although they increase surplus energy. The AUC-based model achieves comparable imbalance evaluation results, indicating that the selected features are sufficient for practical bidding support. Full article