Essays in environmental and energy economics
Abstract/Contents
- Abstract
- In recent years, regulating emissions from big greenhouse gases polluters like the electricity generation sector has become an important climate change mitigation strategy worldwide. Since the electricity generation process is tightly linked to the environmental quality, emissions abatement in this sector can be achieved through several means. This dissertation shows that greenhouse gases emissions can be cut back directly through regulating emissions from power plants, and indirectly through improving the operational efficiency of an electric grid. In the first two chapters of the dissertation, I construct an computable economics model of an electricity market based on the Texas market structure. I then use this model to evaluate welfare performance of different emissions abatement regulations. Among these, renewable energy subsidies have been popular policy instruments to combat climate change. The chapter studies the long-run welfare benefits of optimizing design of the existing renewable energy subsidy (the status quo) to coordinate efficient patterns of renewable investment in the presence of heterogeneity in the offset emissions. I consider two improvements to the status quo subsidy: (i) optimizing the subsidy rates to reflect the average benefits of offseting emissions, and (ii) differentiating the subsidy rates to reflect the location- and time-specific costs of the offset emissions. I find relatively small welfare gains from optimizing rates and designs of the status quo subsidy. In contrast, shifting to the optimal emissions tax or equivalent policies yields much larger welfare gains because these policies engage in additional low-cost emissions abatement channels that renewable energy subsidies cannot: namely, the channel of demand conservation and cross-plant fuel substitution. In the last chapter of the regulation, I use a major structural change in the Texas electricity market as a natural experiment to quantify production and emissions cost savings that result from improving grid efficiency. In December 2010, the Electric Reliability Council of Texas (ERCOT) changed its market structure from a simple 4-zone structure to a full nodal structure. The nodal market structure encompasses a more efficient generation and congestion management as well as a more refined pricing granularity. Efficient generation and congestion management allows the grid to procure more energy from lower-cost, online generation resources. This study quantifies such supply-side cost saving. I find that the nodal market structure leads to a 2-3\% reduction in fuel consumption for all natural gas plants. CO2, SO2, and NOx emissions are also reduced by 1.6-2.5%, 6.5-9%, and 8.6-12%, respectively. In addition to fuel consumption and emissions, the nodal market structure leads to a 1-2.5% reduction in the online capacity required to produce the same amount of energy. Overall, the new market structure leads to a substantial cost saving of at least $185 to $230 million per year.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2014 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Wibulpolprasert, Wichsinee |
|---|---|
| Associated with | Stanford University, Department of Economics. |
| Primary advisor | Goulder, Lawrence H. (Lawrence Herbert) |
| Thesis advisor | Goulder, Lawrence H. (Lawrence Herbert) |
| Thesis advisor | Hoxby, Caroline Minter |
| Thesis advisor | Wolak, Frank A |
| Advisor | Hoxby, Caroline Minter |
| Advisor | Wolak, Frank A |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Wichsinee Wibulpolprasert. |
|---|---|
| Note | Submitted to the Department of Economics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2014. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2014 by Wichsinee Wibulpolprasert
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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