The solar industry has grown considerably in the last few years. This larger scale has introduced more problems as well as possibilities. One of those possibilities is analyzing the data coming from the sites that are now being monitored, and using the information to answer a variety of questions.
We have four questions which are of prime importance identified in this thesis:
1. Can data from customers be trusted?
2. Can we use data from existing sites to determine which sites need the most improvement?
3. Can we implement a location-based algorithm to reduce the amount of false positives for performance, or other alarms?
4. Can we improve upon the current predicted power algorithm?
We find that not only can we answer these questions definitively, but the improvements found are of significant value. Each of these items represents an important question that either directly or indirectly translates into increased revenue and engineering improvements for the solar industry as a whole.
| Identifer | oai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-2077 |
| Date | 24 July 2013 |
| Creators | Ray, Mike C. T. |
| Publisher | PDXScholar |
| Source Sets | Portland State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations and Theses |
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