Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage
Thesis: S.M., Massachusetts Institute of Technology, Department of Chemical Engineering, 2019
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2020
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| Online Access: | https://hdl.handle.net/1721.1/123729 |
| _version_ | 1826204478773133312 |
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| author | Miller, Ian(Ian Graham) |
| author2 | Robert Armstrong. |
| author_facet | Robert Armstrong. Miller, Ian(Ian Graham) |
| author_sort | Miller, Ian(Ian Graham) |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Chemical Engineering, 2019 |
| first_indexed | 2024-09-23T12:56:14Z |
| format | Thesis |
| id | mit-1721.1/123729 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:56:14Z |
| publishDate | 2020 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1237292020-02-11T03:17:01Z Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage Miller, Ian(Ian Graham) Robert Armstrong. Massachusetts Institute of Technology. Department of Chemical Engineering. Massachusetts Institute of Technology. Department of Chemical Engineering Chemical Engineering. Thesis: S.M., Massachusetts Institute of Technology, Department of Chemical Engineering, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (page 63). Several approximate findings are made on the carbon intensity of PV power. (1) Reversible temperature effects raise the carbon intensity of silicon PV power installed in warm regions, including by -10% in the southwestern US and ~13% in western India. (2) All temperature effects raise silicon PV carbon intensity by ~23% in southern India (from 35 to 43 gc/kWh). (3) Chinese manufacturing of multi-crystalline silicon (mc-Si) modules emits ~25% more GHGs than European manufacturing, due not only to higher carbon intensity of upstream electricity, as previously reported, but also to more energy input per module produced. (4) Relative to stationary mounting, tracking decreases the carbon intensity of mc-Si PV in most regions analyzed (by 0 to ~12%, or 0 to ~4 gc/kWh), and increases the carbon intensity of cadmium telluride PV in most regions analyzed (by 0 to ~12%, or 0 to ~4 gc/kWh). This dependence on cell type is explained by the interaction of tracking energy gain, tracker production emissions, and module production emissions. (5) Inverter overloading slightly diminishes PV carbon intensity, by less than 2 gc/kWh. This thesis also presents a simple model for estimating emissions from integrated power generation and energy storage. The model applies to emissions of all pollutants, not only GHGs, and to all storage technologies, including pumped hydroelectric. Our case study applies the model to systems that couple PV and wind generation with lithium-ion batteries (LBs) and vanadium redox flow batteries (VFBs). We find that, even when coupled with large amounts of LBs or VFBs, PV and wind power remain much less carbon intensive than fossil-based generation. The most carbon intensive renewable power analyzed (sc-Si PV produced in China, installed in Berlin, and coupled with sufficient VFBs to store 50% of generation) still emits only ~25% of the GHGs of the least carbon intensive mainstream fossil power (combined cycle gas turbine with no storage). Lastly, we find that the pathway to minimize GHG emissions of power from a coupled system depends upon the generator: given low-emission generation (<50 gc/kWh), the minimizing pathway is the storage technology with lowest production emissions (VFBs over LBs for our case study); given high-emission generation (>200 gc/kWh), the minimizing pathway is the storage technology with highest round-trip efficiency (LBs over VFBs). The latter case applies to a majority of the world's power generation today. by Ian Miller. S.M. S.M. Massachusetts Institute of Technology, Department of Chemical Engineering 2020-02-10T21:39:10Z 2020-02-10T21:39:10Z 2019 2019 Thesis https://hdl.handle.net/1721.1/123729 1138469568 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 63 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Chemical Engineering. Miller, Ian(Ian Graham) Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage |
| title | Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage |
| title_full | Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage |
| title_fullStr | Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage |
| title_full_unstemmed | Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage |
| title_short | Modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation, with and without energy storage |
| title_sort | modeling life cycle greenhouse gas emissions from photovoltaic and wind power generation with and without energy storage |
| topic | Chemical Engineering. |
| url | https://hdl.handle.net/1721.1/123729 |
| work_keys_str_mv | AT millerianiangraham modelinglifecyclegreenhousegasemissionsfromphotovoltaicandwindpowergenerationwithandwithoutenergystorage |