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Record W6987686881

Transforming electrical energy systems towards sustainability in a complex world: the cases of Ontario and Costa Rica

2023· dissertation· en· W6987686881 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityElectric potential energyEnergy (signal processing)Transformative learningClimate changeEnergy management
DOInot available

Abstract

fetched live from OpenAlex

Electrical energy systems have been major contributors to sustainability-associated effects, positive and negative, and therefore are considered as key components in pursuing overall sustainability objectives. Conventional electrical energy systems have delivered essential services for human well-being and can play a key role in tackling ongoing threats including growing poverty, climate change effects, and the long-term impacts of the COVID-19 pandemic. At the same time, some participants in electrical energy systems at national and local scales have stressed that the conventional design of electrical energy systems requires change to ensure the positive contributions and to reduce socioeconomic and environmental risks. Continuing negative trends including significant contributions to climate change, rising energy costs, deepening inequities, and long-term environmental degradation, have raised concerns and prompted calls for transforming conventional electrical energy systems rapidly and safely. However, due in part to the complexity of electrical energy systems, national and local authorities have struggled to steer their systems towards delivering more consistently positive sustainability-associated effects. 
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\nUsual approaches to electrical energy system management have sought to improve efficiency, reliability and capacity to meet anticipated demand. They have seldom treated electrical energy systems as potentially important contributors to overall sustainability in principle and in practice. Doing so would entail recognizing electrical energy systems as complex systems with interlinked effects and aiming to maximize the systems’ positive and transformative effects to deliver multiple, mutually reinforcing and overall sustainability gains. The research reported here considered whether and how sustainability-based assessments can be useful tools to fill this gap and advance sustainability objectives in particular plans, projects, and initiatives carried out in electrical energy systems.
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\nTo aid in responding the main research questions, this dissertation builds and proposes a sustainability-based assessment framework for electrical energy systems that is suitable for application with further specification to the context of different jurisdictions. Use of the framework is illustrated and tested through two case applications – to the electrical energy systems of Ontario and Costa Rica. Building the proposed framework involved a literature review and synthesis of three foundational bodies of knowledge: sustainability in complexity, electrical energy systems and sustainability, and transformations towards sustainability. Further specifying and applying the framework to the context of the two case studies involved carrying out document research and semi-structured interviews with key participants in the electrical energy systems of the two jurisdictions. The resulting sustainability-based assessment framework from this dissertation proposes six main criteria categories that are mutually reinforcing and emphasize minimizing trade-offs scenarios. These are divided into a set of criteria for specification and application to electrical energy system-related projects, plans, and initiatives in different regions. The proposed criteria categories are 1) Climate safety and social-ecological integrity; 2) Intra- and inter-generational equity, accessibility, reliability, and affordability; 3) Cost-effectiveness, resource efficiency and conservation; 4) Democratic and participatory governance; 5) Precaution, modularity and resiliency; and 6) Transformation, integration of multiple positive effects, and minimization of adverse effects.
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\nOntario’s electrical energy system has significant sustainability-related challenges to overcome. The case study has shown that there is little provincial interest in following national net-zero commitments and authorities have removed official requirements for long-term energy planning to pursue climate goals and related sustainability objectives. Rising electricity prices have also raised concerns for many years and have been accompanied by limited willingness to engage in democratic and participatory processes for public review of electrical energy system undertakings. Additionally, recent commitments to highly expensive and risky options can further aggravate long-term socioeconomic and environmental negative impacts. In the Costa Rica case, adopting technocentric approaches to electrical energy system management led to a path dependency on large hydroelectricity development. This background of development of large hydroelectricity projects, without public consultation, has also created a sustained context of tension between governments, Indigenous groups and local communities, and private actors. Since the country is expected to experience changes in natural systems’ patterns including intensified periods of hurricane, storm, flood, and drought, the strong reliance on hydroelectricity has at the same time raised concerns regarding the reliability of the national electrical energy system.
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\nBoth Ontario and Costa Rica have electrical energy systems that require rapid responses to contribute more positively to sustainability, and to help to reduce and reverse ongoing social and environmental crises. The two cases are also suitably contrasting venues for specification and application of the sustainability-based assessment framework developed in this work. The findings showed that while Ontario and Costa Rica have different contextual characteristics (e.g., geographical, socioeconomic, and political), overall lessons can be learned for best designing electrical energy systems in different jurisdictions. The findings also revealed that context-specific sustainability approaches do not necessarily undermine the viability for comparing multiple cases. In fact, specification to context can support comparisons by facilitating the identification of similarities and differences that are closely tied to contextual characteristics. Overall, the study of the two cases indicates significant potential for future works that focus on the specification to context and application of sustainability-based assessments specified to electrical energy systems that seek for barriers and opportunities for unlocking transformative effects.
\nThree key learnings were revealed by building, specifying to context, and applying the sustainability-based assessment framework in a comparative analysis of the electrical energy systems of Ontario and Costa Rica. First, the two jurisdictions require implementation of more effective options to minimize costs in electrical energy system operations and avoid economic risks that undermine the capacity of the system to provide affordable electricity for all. Second, efforts to meet democratic and participatory governance requirements have been insufficient in Ontario and Costa Rica. Both jurisdictions need to demonstrate the capacity to respect official processes for public approval and to ensure adequate representation of different actors’ interests. Particularly, Indigenous people, local communities, and other groups with limited influence need more meaningful inclusion in official decision-making. Third, the two jurisdictions would benefit from implementing strategies to identify and assess possible combinations of policy and technical pathways that could help to unlock an existing dependency on options that support system rigidity. 
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\nThe core overall conclusion is that application of the proposed sustainability-based assessment framework can inform better design electrical energy systems to deliver broader sustainability-related effects and advance transformations towards sustainability. However, the framework could be further developed by including insights from more key participants in electrical energy systems. The criteria set can be honed with specification to context and application to different jurisdictions, and to more particular initiatives that reflect evolving energy scenarios. Inclusion of transformation, integration of multiple positive effects, and minimization of adverse effects as a criteria category has been helpful to recognize political contexts, promote just transitions, and emphasize the interlinked effects of applying the rest of the criteria. Since this is a new component in sustainability-based assessment frameworks, the transformation criteria category will require particular attention in future applications. Among other matters, further work in the field of electrical energy systems transformation towards sustainability should also address continuing and emerging phenomena, including adverse political trends such as right-wing populism and post-truth politics, that would maintain gaps between current practices and the steps needed for progress towards sustainability. 
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\nGenerally, however, while there are many needs and opportunities for more applications of the framework and additional research into the barriers to and openings for energy system transition and transformation, the sustainability-based assessment framework proposed and tested in this dissertation research should be a useful tool for directing change in complex electrical energy systems towards broader contributions to sustainability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.376

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.006
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.018
GPT teacher head0.228
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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