Wind Energy emissions displacement in Alberta, Canada
Bibliographic record
Abstract
In this paper we will explore one of the most problematic pollution aspects along transport, that is the electrical sector. It causes 40% of greenhouse gases emissions in the world [5], and reports say that if we achieve the goal of cutting those down to 90% and use renewable sources, the Paris Agreement goals can be achieved [2]. The electric system is based on all the power plants which run to introduce electricity in the system and those power plants generates a lot of well-paid jobs. That means economies around the world need to move toward a greener employment system to replace that amount of jobs [6]. Therefore, the aim of this paper is to establish the dependency of Canada on greenhouse gas sources and if the procedures that are applied right now are appropriate, or if some changes must be carried out. That dependency of Alberta and Canada as a whole will be compared. In order to do so, the electrical market in Alberta will be studied in order to know the source of the electricity, to establish the amount of renewable and non-renewable energy usage in Alberta. We will focus mainly on wind energy, as it is the most important renewable energy source in this province, although not in Canada. The goal of this paper and research is to see the effects that wind energy generation has on the electrical market and what would happen if this important renewable source wasn’t available. The results we expect to encounter are reduction in emissions caused by the contribution of wind energy, how the pool price of every hour in the market is affected and what are the next steps so that we can reduce as much as possible coal usage and other greenhouse gas emissions. This will help us to know which kind of power plants are displaced from the market because of wind. The data used in this project is AESO’s market data [7]. Alberta Electric System Operator is an entity who manages the planning and operations of the interconnected electrical system. In this data can be found the type of plant that is introducing energy into the system, the pool price of every hour, and how much power is dispatched by each of those plants. Alberta is in a unique position as it is the only province in Canada where the electrical market data is public, therefore it is possible to study the connections between all private investors which generate electricity. The effects of every hour over and eight-year time period will be studied, from 2012 to 2019, and the results of a hypothetical situation in which wind wouldn’t be an energy source observed. This is of interest, because one of the main difficulties for investors to get involved with renewable energies is because it is said renewables are not a reliable source of income as they are too dependent on the weather. Differences between Canadian and Albertan electrical markets is explored, and data is analyzed to know how dependent Alberta is on coal and locate the wind power plants in order to know what to expect of those power plants in the near future
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".