Impact of Power Interruption on Buildings and Neighborhoods and Potential Technical and Design Adaptation Methods
Bibliographic record
Abstract
This paper presents a state-of-the-art review of the impact of energy interruptions on people, buildings, and neighborhoods and discusses some technological and design strategies to mitigate some of these impacts. An exhaustive literature review was carried out employing keyword searches in the ScienceDirect and Scopus databases. The literature focuses mainly on 37 keywords, which occurred in more than two sources. Based on this literature survey, the paper highlights that, depending on their duration, power outages can have a severe impact on people, buildings, and neighborhoods. The lives of vulnerable individuals dependent on electrical medical devices can be threatened even in short-term power interruption scenarios. Longer-term power outages affect multiple aspects of daily life, such as communication, thermal comfort, life quality, transportation, health, and security, in addition to potential damage to buildings and their contents. The paper identifies and discusses various methods that can be implemented to reduce vulnerability and improve adaptation to climate-related power interruptions. These methods range from simple, low-tech solutions that enable users to temporarily cope with hours of interruption to more sophisticated methods requiring advanced planning. These adaptation and coping methods are classified according to various criteria, including their ease of implementation, accessibility, potential cost, ease of use by occupants, and their potential to address various needs. The paper finally discusses the impact of building and neighborhood design on improving adaptation to energy interruptions. High-performance building design can extend the time that a building can passively operate without reliance on mechanical systems for heating and for cooling. Building shape and geometry, as well as the spatial design of the neighborhood, can maximize solar access and therefore facilitate the implementation of PV and solar technologies. In addition, the design of mixed-use neighborhoods with access to various facilities and basic amenities assists in prolonging the self-reliance of the community as a whole. This work aligns with the vision of the Sustainable Development Goals: by identifying methods and technologies to reduce the impact of power interruptions and improve the energy resilience of urban areas around the globe, this work can contribute to the direct and indirect fulfillment of several Sustainable Development Goals (e.g., SDGs 7, 11, 13, and others). Although the work is performed in a North American context and specifically refers to the Canadian climate, the methodology can be implemented in other climatic and regional conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".