Search Results (212)

Distributed generation offers a critical pathway to sustainable urban energy; however, incomplete regulatory frameworks in emerging economies frequently force residential photovoltaic (PV) systems into export-restricted operation. This study quantifies the empirical performance and opportunity costs of a demand-matched, zero-export PV system paired with an Internet of Things (IoT)-managed backup tier. A 54-month longitudinal single-case evaluation was conducted in Arequipa, Peru, utilizing a 1.36 kWp grid-tied array and a 0.6 kWh/day decoupled backup subsystem. Performance was benchmarked against a fully metered pre-PV counterfactual. The zero-export constraint mandated a 96.3% self-consumption index (SCI), capping the self-sufficiency index (SSI) at 37.9% and yielding a utilization ratio (U) of only 24.1% against the site’s technical potential. Economically, a full lifecycle appraisal of the status quo produced a negative net present value (NPV) of −USD 1738. Scenario modeling reversed that outcome under net metering (+USD 862). Net billing at the generation price currently contemplated left the investment short of break-even (−USD 202): the break-even price is PEN 0.317/kWh, some 13% above that reference. The decisive variable is therefore not the remuneration mechanism alone but the price set within it. Furthermore, the decoupled backup architecture mitigated 97.7% of 43 recorded grid outages at a resilience cost of USD 3.2 per protected hour. The headline findings are therefore institutional, not technological: identical hardware shifts from value-destroying to value-creating through the regulatory treatment of surplus energy alone, provided that surplus is priced above the break-even threshold quantified here. We present two replicable sizing rules and propose the U metric to translate regulatory impasse into an internationally standardized reporting parameter, providing an evidence-based roadmap for accelerating decentralized renewable energy in resource-constrained grids (SDG 7, SDG 11). Full article

As a distinctive type of historic urban area shaped by complex topography, historic urban areas in mountainous cities have undergone multiple rounds of urban regeneration and social–spatial restructuring amid the continuous influx of capital and the development of the industrial economy. Under these multifaceted influences, the spatial form of historic urban areas in mountainous cities has undergone a series of transformations. To reveal the characteristics and underlying mechanisms of spatial evolution in historic urban areas in mountainous cities, this study has established a research framework tailored to such areas. Selecting the Yuzhong Peninsula Historic District in Chongqing—a typical example of historic urban areas in mountainous cities in China—as the study area, the research employs land transfer matrices, spatial design network analysis (sDNA), spatial overlay and statistical methods to analyse its spatial evolution characteristics across three dimensions: land-use evolution, road network evolution and building renewal. Seven key indicators were selected for historic urban areas in mountainous cities, and the GeoDetector was utilised to investigate the driving forces and interactions among these factors. The results indicate that in the Yuzhong Peninsula Historic District, residential and special-purpose land use has decreased whilst commercial land use has increased; the road network has been continuously improved, leading to increased choice and accessibility; and the proportion of small-scale buildings has decreased whilst that of large-scale buildings has increased. The primary factors influencing spatial evolution are elevation, social and location factors, with the combined interaction of these factors exerting a greater influence than any single factor alone, indicating that topography acts as a significant persistent spatial constraint guiding the spatial evolution of historic urban areas in mountainous cities. Finally, based on the above findings, recommendations are put forward for the sustainable conservation and utilisation of historic urban areas in mountainous cities, covering land-use management, traffic guidance and the typological control of urban architectural fabric. Full article

Autonomous robotic systems operating in residential environments must maintain safe, reliable, and adaptive performance under heterogeneous conditions characterized by environmental uncertainty. Achieving this performance is difficult because such systems must simultaneously cope with variable contact states and complex subsystem interactions. Conventional component-oriented engineering approaches often fail to capture how internal faults, external disturbances, and architectural decisions interact to generate system-level instabilities and hazards. This paper proposes a Systems Thinking-based Safety-by-Design framework to support the sustainable early-stage design of autonomous residential robotic systems. The methodology formalizes the relationships among internal faults (F), environmental variability (E), system behaviour (S), architecture (A), instabilities (I), hazards (H), and safety barriers (B) through the dependencies S = f(F,E), I = g(S,A), and H = h(I,B). Environmental variability is treated as an active design driver influencing system behaviour, architectural decisions, and safety requirements. The framework is evaluated as a proof-of-concept, semi-quantitative analytical demonstration, rather than an experimentally validated result, using an autonomous window-cleaning robot: its functional subsystems are mapped to the conceptual model and fault-dominated, environment-dominated, and coupled degradation scenarios are assessed through a semi-quantitative index. The results show that risk emerges from subsystem interactions rather than isolated component failures and that adaptive architectures reduce instability propagation under uncertain operating conditions. The proposed framework supports early engineering decisions that improve robustness, resilience, safety, maintainability, and sustainability. Full article

Non-intrusive load monitoring (NILM) provides a cost-effective way to obtain appliance-level electricity information from aggregate smart-meter measurements and is therefore important for energy management, demand-side response, and sustainable operation in smart buildings. However, accurate appliance-level power disaggregation remains challenging because residential load signals usually involve overlapping appliance signatures, sparse activations, heterogeneous temporal patterns, and transient switching events. To address these challenges, this paper proposes a State-Event-Guided Multi-Scale Gated Network (SEMG-Net) for NILM. The proposed framework integrates a residual temporal encoder, multi-scale dilated convolutional blocks, and a state-event-guided gating mechanism within a unified multi-task learning architecture. The shared encoder extracts hierarchical temporal representations from aggregate mains windows, while task-specific branches jointly estimate appliance power, on/off state, and switching event type. The predicted state probability, three-class event probability distribution, and shared temporal representation are jointly used to construct a continuous gate that modulates the raw power estimate, thereby directly incorporating behavioral predictions into final power estimation. Experimental results on public datasets show that SEMG-Net achieves competitive overall performance, with clear advantages in power estimation, energy consistency, and state identification, particularly for appliances with complex operating stages or transient switching behavior. The ablation results further demonstrate the benefits of multi-scale feature extraction and auxiliary supervision, as well as the effectiveness of the proposed state-event-guided power modulation mechanism. Full article

In this technological era, electrical energy is the bloodstream for the economic and social development of any country. It is the need of the time that developing countries like Pakistan have strategic planning for efficient generation and utilisation of electricity and have as much cheap electricity as possible at their disposal while respecting environmental constraints. The overloaded and ageing infrastructure of an electrical power network can impact system reliability and the sustainability of power generation, transmission and distribution mechanisms. The initiation of the planning process depends upon accurate load estimation to optimally fulfil consumers’ power needs. This paper compares statistical, hybrid and deep learning (DL) mechanisms, including SARIMAX, SARIMA with gradient boosting (SARIMA-GB), long short-term memory (LSTM) network, STL decomposition with LSTM, and CWT-LeNet-5-LSTM, for the prediction of residential electricity demand in the LESCO region of central Pakistan. The study uses 7670 daily feeder observations recorded between 1 January 2002 and 31 December 2022. The series is modelled at its native daily resolution and partitioned chronologically into a fitting span of 5216 days, a validation span of 920 days and a test span of 1534 days beginning 20 October 2018. All models receive the same block of 14 exogenous calendar variables, four annual Fourier harmonic pairs, day-of-week and month sine and cosine terms, a weekend indicator and a linear trend, and all neural models are trained with a validation split, early stopping and restoration of the best weights rather than for a fixed number of epochs. Accuracy is assessed with MAE, RMSE, MAPE and peak normalized RMSE under one recursive protocol at forecast leads of 1, 7, 14 and 30 days, because the ranking of the frameworks depends on the lead. Averaged over three random initialisations, the proposed CWT-LeNet-5-LSTM attains the lowest error at every multi-step lead, reaching an MAPE of 2.35 ± 0.28% at lead 30 against 3.32% for the multivariate LSTM, 3.89% for SARIMA-GB and 4.47% for SARIMAX. At lead 1, SARIMA-GB is the more accurate model (0.76% against 1.20 ± 0.17%) because the previous day’s observed load dominates one-step prediction for a series whose lag-one autocorrelation is 0.978. An architecture ablation isolates the contribution of the wavelet stage, the convolutional stage, the anisotropic pooling and the calendar fusion. A stratified analysis across seasons, weekdays, weekends and high-, medium- and low-load days shows where the advantage is concentrated. Additionally, Diebold–Mariano tests identify the statistical significance of the differences. Full article

Growing urbanization, housing affordability pressures, and increasing sustainability demands have positioned modular and flexible design strategies as central approaches in contemporary residential architecture. Modularity enhances construction efficiency, reduces material waste, and accelerates delivery through the use of prefabricated, standardized components. Flexibility, in turn, enables spaces to adapt in configuration and function over time, responding to the evolving needs of occupants and communities. Following PRISMA 2020 guidance, a systematic search was conducted across Web of Science, Scopus, and ScienceDirect academic databases resulting in 2140 records. After duplicate removal and sequential screening, 98 studies were included in the final review. The selected literature spans peer-reviewed journal articles and documented case studies, with emphasis on publications from 2015 onwards. The review identifies key advantages of modular and flexible residential systems, including cost-effectiveness, reduced environmental impact, and improved user satisfaction, while also highlighting persistent challenges such as regulatory barriers, standardization constraints, and limited interdisciplinary integration. The review contributes three synthesis outputs: a typology of modular residential systems, a critical comparison of modular–flexible strategies, and a cross-scale conceptual framework linking production logic, occupant adaptation, and sustainability outcomes. The findings underscore the potential of hybrid strategies that combine modular construction with flexible design principles to produce residential environments that are resilient, adaptable, and sustainable. The review provides structured insights and evidence-based recommendations for architects, planners, and policymakers involved in the development of future housing systems. Full article

Architectural heritage conservation and development (AHCD) increasingly require social approaches that connect material remains with emotions, memories, and meanings. Sense of place offers a theoretical lens for understanding these connections, yet its operational role in AHCD remains unclear. This study draws on a bibliometric analysis and narrative synthesis of 79 publications to classify these publications into four architectural heritage contexts: urban residential, rural residential, public, and religious and ritual. The results show that the physical form of architectural heritage fundamentally shapes sense of place, while the pathways through which sense of place supports conservation and development vary across heritage types. The review further identifies emerging research trends, conceptual gaps, and practical limitations in applying sense of place to AHCD. This study proposes an implementation framework for integrating sense of place into AHCD. The framework connects heritage attributes and place meanings with stakeholder engagement and strategies for conservation and development. The framework offers a reference for research, policy-making, and practice in architectural heritage conservation and sustainable development from a social perspective. Full article

The purpose of this study is to examine the importance of architectural details and artefacts as cultural markers within the interior spaces of adaptively reused heritage buildings in Sofia’s historic urban centre. A comparative study was performed on three significant early twentieth-century residential buildings: the house linked to the former ‘Excelsior’/‘Asen Zlatarov’ cinema complex at Blvd ‘Christo Botev’ N85, the former residence at Blvd ‘Christo Botev’ N75, and the building at Blvd ‘Stamboliyski’ N36—the latter two have both been transformed into hotels. The research employs an interdisciplinary methodology combining archival research, field surveys, photographic documentation, 3D laser scanning, and comparative stylistic analysis. The study’s principal contribution is the development of a transferable analytical framework for classifying interior details by function (constructive or decorative), location (enclosing surfaces, fixed furnishings, vertical circulation), and material—a framework not previously applied to this building stock in the Bulgarian context. The findings confirm that authentic interior details—including stair railings, flooring patterns, gypsum cornices, ornamental plasterwork, heating appliances, and joinery—function as reliable cultural artefacts and markers of historical period and stylistic identity. These details serve as evidence for dating, authenticating, and analysing the evolution of architectural style elements. Preserving and integrating these elements into adapted interiors strengthens architectural identity and supports the sustainable reuse of cultural heritage for contemporary purposes. Full article

Dwellings built from rammed earth in historical contexts represent not only a heritage to be preserved but also buildings with a long service life that are still in use by the local population. Changes in urban dynamics and the revitalization of historic downtown areas have led to an increase in renovations of these buildings. However, in many cases, these projects are carried out using materials and techniques that are structurally incompatible and detrimental to sustainability. The aim of this study is to examine earthen residential architecture in the historical context of the Region of Northwest Murcia (Spain), the resources used in their construction, their building systems and their current condition. To this end, an analysis is proposed based on historical documentation, including an assessment of the costs and energy required for their construction, a visual inspection of the current condition of these buildings, and a study of the relevant building regulations. The study of their cladding, eaves, floor structures and partitions in their current state allows for an assessment of the extent of transformation they have undergone and their state of conservation, whilst the study of the regulations provides insight into recent interventions on these buildings. The results point to rammed earth as a technique that, in historic dwellings of various kinds, combined low economic and energy costs with acceptable durability, allowing them to remain in use several centuries later, albeit under the recent threat of interventions using incompatible materials that are shortening their lifespan. Full article

Façades play a decisive role in shaping the visual and symbolic character of historic urban environments. Recent European funding schemes promoting energy-efficient retrofitting have accelerated interventions on building envelopes. Although aligned with decarbonization objectives, these processes are generating significant chromatic and material transformations that risk eroding the visual coherence and cultural sustainability of consolidated urban areas. In the historic Ensanches of San Sebastián, the replacement of traditional envelope systems with new cladding solutions is leading to the loss of the architectural style of some facades and altering their materials, textures, and colors. A progressive “contagion effect” has been identified, whereby dissonant chromatic schemes—often associated with the proliferation of so-called “zebra blocks”, residential buildings with façades clad in alternating black and white stripes that have proliferated in recent urban developments—are replicated across adjacent buildings, gradually weakening spatial continuity and the genius loci of the neighborhood. In response to this phenomenon, this research develops a systematic methodology to analyze, quantify, and anticipate chromatic transformation in consolidated urban fabrics. The study combines historical morphological analysis, classification of architectural periods, and chromatic mapping of recent façade interventions. Based on this framework, a CARI, Chromatic Alteration Risk Index is proposed to evaluate the potential impact of façade alterations on urban chromatic coherence. Drawing on an epidemiological framework, the methodology enables the identification of critical transformation clusters, the assessment of contagion dynamics, and the definition of regulatory thresholds for color and material interventions. By integrating perceptual criteria, urban morphology, and spatial distribution patterns, the study moves beyond descriptive diagnosis and offers a transferable tool for municipal planning. The proposed approach supports the proactive regulation of façade rehabilitation processes, balancing energy efficiency objectives with the preservation of collective memory, material identity, and urban sensory quality. This study proposes a quantitative model of “urban chromatic contagion” to assess how façade color interventions propagate within a neighborhood. We define the Chromatic Integration Percentage (CIP) and the Chromatic Alteration Risk Index (CARI) of the analyzed area. Results indicate that poorly regulated façades show higher chromatic dissonance (low CIP) and act as contagion hotspots, while a clear risk gradient emerges: highly protected buildings present lower risk, whereas mixed typologies and recent rehabilitations concentrate higher CARI values. The model supports preventive urban color management by identifying areas at risk before visible alteration. Full article

Monitoring urban biodiversity is essential for designing resilient and sustainable cities. Urban trees provide a wide range of ecosystem services (ESs), including air pollution reduction, urban heat island mitigation, and psychological benefits for citizens. Accurate and updated tree inventories are therefore essential tools for urban environmental monitoring. However, existing urban tree inventories are often incomplete or outdated, especially in private areas, limiting accurate ES assessment and urban planning. Earth observation satellite missions, particularly very-high-resolution multispectral (VHR-MS) imagery, offer a valuable alternative to field surveys for gathering information on urban environments. This work proposes a deep learning (DL) framework based on VHR-MS satellite imagery for the automatic generation of accurate urban tree inventories. DL models reduce human effort and save operational time by automatically learning complex representations and patterns from satellite imagery. The proposed encoder–decoder architecture extends prior point-based detection approaches by integrating a ResNet-50 backbone and a percentile-based threshold calibration procedure. Given the lack of suitable training data covering heterogeneous and densely vegetated urban environments, a dedicated dataset was constructed from VHR-MS satellite imagery acquired over the Lombardy region (Italy). The dataset encompasses a wide range of land uses and land covers, including residential and industrial zones, public parks, private gardens, and agricultural areas. Through the photointerpretation of more than 2800 images, precise coordinates for more than 50,000 manually annotated trees were obtained. The DL model is trained with point-level annotations, enabling precise localization of individual trees while reducing annotation ambiguity in dense urban contexts. On the Lombardy dataset at 30 cm/px resolution, the proposed framework achieves 86.72% Precision, 66.92% Recall, an F1-score of 75.54%, and a localization error of 1.473 m. Full article

The escalating energy consumption in China’s rural residences necessitates the adoption of targeted energy-efficient design strategies. However, existing studies have mainly focused on urban buildings or cold-climate rural residences, and insufficient attention has been given to form-based energy optimization for rural housing in hot summer and cold winter regions. Hangzhou was selected because it is a representative city in this climate zone, where rural residences face both summer cooling and winter heating demands. This study systematically investigates passive design pathways for rural residential buildings by optimizing architectural forms. We conducted in-depth field surveys and data analysis on 76 diverse samples, including both self-built and unified construction types, to establish three representative typical residential models (rectangular, L-shaped, U-shaped) for the Hangzhou region. DesignBuilder was employed to simulate the impacts of eight morphological elements—Shape Coefficient, building area, aspect ratio, orientation, number of floors, floor height, floor height ratio, and roof slope—on building energy consumption. The Gradient Boosting Decision Tree (GBDT) method was then used to quantify the nonlinear effects and relative importance of these elements. The results indicate clear nonlinear relationships between elements and the energy-saving rate. Floor height is identified as the most critical factor affecting energy consumption, followed by roof slope, with building area and other elements also showing significant influence. Based on the quantitative analysis, this study proposes energy-efficient design optimization strategies for rural housing in Hangzhou, offering a validated methodological framework and practical design references for the sustainable development of rural residences in hot summer and cold winter regions. Full article

Building energy performance is largely determined during the early conceptual design stages. However, energy evaluation is often postponed until after key architectural decisions—such as massing and façade configuration—have been finalized, limiting opportunities for meaningful optimization. This study addresses this gap by demonstrating a Building Information Modeling (BIM)-based comparative approach for integrating energy analysis into early design stages. Focusing on residential villas in Abu Dhabi, UAE, three residential forms were selected for testing: compact, L-shaped, and U-shaped designs. Each form included multiple iterations representing the design progression process, namely the base building form, façade refinement (glazing and shading adjustments), and spatial layout and/or orientation adjustments. The analysis incorporated variations in glazing ratio and building orientation to evaluate their combined impact on Energy Use Intensity (EUI). Among the tested options, the L-shaped configuration achieved the lowest EUI (79 kWh/m²), representing the best-performing option, followed by the compact (81 kWh/m²) and U-shaped (82 kWh/m²) configurations. The results also confirm that orientation remains an important factor even after façade refinement. Overall, the findings suggest that BIM-based energy analysis is most effective when applied early as a comparative and iterative design-support tool. Full article

The built environment in Saudi Arabia accounts for approximately 78% of the country’s total electricity consumption, positioning building energy performance as one of the most consequential levers available to policymakers pursuing the kingdom’s net-zero greenhouse gas emissions target for 2060 and Vision 2030’s sustainability agenda. Despite the progressive introduction of the Saudi Building Code (SBC) energy chapters SBC 601, SBC 602, and the Saudi Green Building Code (SgBC 1001), a persistent gap remains between regulatory intent and measurable outcomes across Saudi Arabia’s five distinct climatic zones. Building codes are, by design, generic policy instruments encompassing structural, fire, accessibility, and energy provisions; this paper focuses specifically on the energy and sustainability dimensions and critically examines how the SBC’s update cycle and prescriptive compliance architecture shape actual performance outcomes. This study presents three explicit research questions: (RQ1) What zone-differentiated energy savings does SBC implementation deliver across residential typologies? (RQ2) How does the Mostadam national rating system compare with international benchmarks in the Saudi context, and what caveats govern that comparison? (RQ3) What evidence-based policy interventions are needed to transition from compliance-led to performance-led building energy governance? Drawing on a systematic synthesis of 53 building energy simulation models (2018–2025), official programme data, and a structured comparative analysis of Mostadam against LEED v4.1 and BREEAM, the study finds EUI reductions of 5–25% from SBC compliance, with the largest savings in the hot–humid coastal zone. Seven prioritised policy recommendations are proposed, addressing code revision, financial incentives, digital monitoring, renewable energy thresholds, and capacity building. Full article

The evaluation of intervention strategies for the existing building stock, within the context of energy transition and increasing attention being given to sustainability, requires approaches capable of systematically integrating economic and environmental dimensions over the entire building life cycle. From this perspective, the present study develops and applies an integrated Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) model aimed at comparing two alternative intervention strategies for traditional residential buildings: conservative retrofit of the existing structure and demolition with reconstruction according to Nearly Zero Energy Building (NZEB) criteria. The methodological framework, compliant with ISO 15686-5 and based on a simplified LCA-oriented approach inspired by EN 15978 principles, is applied to a representative case study of Swedish vernacular wooden architecture (röd stuga) located in the municipality of Falun. The assessments are carried out over 50- and 100-year time horizons, adopting Net Present Value (NPV) as the primary economic indicator and Global Warming Potential over 100 years (GWP100) and Cumulative Energy Demand (CED) as environmental indicators. The results show that the NZEB scenario, despite higher initial investment costs, achieves a significant reduction in life-cycle environmental impacts, with a decrease of approximately 20–25% in terms of GWP100 and about 45–50% in terms of CED compared to the retrofit scenario. The analysis also highlights a differentiated behavior of environmental indicators—while operational energy use remains dominant in cumulative energy demand, embodied impacts become increasingly significant in the GWP balance, particularly in high-performance scenarios. From an economic perspective, conservative retrofit results in lower global costs over the considered time horizons, although the economic gap tends to narrow in the long term. The integrated LCC–environmental assessment approach highlights the economic–environmental trade-offs and provides a replicable decision-support framework for sustainable regeneration policies targeting the existing residential building stock. Full article