- Title
- Statistical model for risk diversification in renewable energy
- Creator
- Ahame, Edmund
- Subject
- Renewable energy sources -- Statistics
- Subject
- Diversification in industry
- Date Issued
- 2013
- Date
- 2013
- Type
- Thesis
- Type
- Masters
- Type
- MSc
- Identifier
- vital:10564
- Identifier
- http://hdl.handle.net/10948/d1008399
- Identifier
- Renewable energy sources -- Statistics
- Identifier
- Diversification in industry
- Description
- The growth of the industry and population of South Africa urges to seek new sources of electric power, hence the need to look at alternative power sources. Power output from some renewable energy sources is highly volatile. For instance power output from wind turbines or photovoltaic solar panels fluctuates between zero and the maximum rated power out. To optimize the overall power output a model was designed to determine the best trade-off between production from two or more renewable energy sources putting emphasis on wind and solar. Different measures of risk, such as coefficient of variation (CV) and value at risk (VAR), were used to determine the best hybrid renewable energy system (HRES) configuration. Depending on the investors’ expected returns (demand) and risk averseness, they will be able to use the model to choose the best configuration that suites their needs. In general it was found that investing in a diversified HRES is better than investing in individual power sources.
- Format
- ix, 69, 5, 12 leaves
- Format
- Publisher
- Nelson Mandela Metropolitan University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela Metropolitan University
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Collections
NMMU School of Computer Science, Mathematics, Physics and Statistics
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