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|Title:||Assessment of energy reserves and costs of geothermal resources in Hawaii|
|Citation:||2005. Assessment of energy reserves and costs of geothermal resources in Hawaii. Richmond (CA): GeothermEx, Inc.|
|Abstract:||On behalf of the Department of Business, Economic Development and Tourism (DBEDT), GeothermEx has assessed the capacity for electrical generation of seven geothermal resource areas in Hawaii (five on the Island of Hawaii and two on the Island of Maui). We have also estimated a realistic range of costs for future geothermal power plants in Hawaii, based on published sources and industry experience, including estimates of capital cost (dollars per installed kilowatt) and operations and maintenance (O&M) costs (cents per kilowatt-hour). Moreover, we have reviewed the probability of occurrence of geothermal resources throughout the state of Hawaii, and we have found no change in the probability values since the statewide assessment five years ago (GeothermEx, 2000). The probabilities of occurrence are summarized in Table 1.1, and the potential resource areas indicated in Figure 1.1. |
The seven geothermal resource areas with significant potential for electrical generation are
• the East Rift Zone of Kilauea volcano (KERZ);
• the Kilauea Southwest Rift Zone
• the Mauna Loa Southwest Rift Zone;
• the Mauna Loa Northeast Rift Zone;
• the Haleakala Southwest Rift Zone; and
• the Haleakala East Rift Zone.
In assessing the MW capacity of these areas, we have used a probabilistic technique (Monte Carlo simulation) to account for uncertainties of key resource parameters. This results in a probability distribution curve for each area, which allows one to estimate the likelihood that recoverable energy reserves of a given area will exceed a specified level. For the purposes of this report, we have considered the 10th percentile MW value to be a minimum; there is a 90% probability that geothermal energy reserves will exceed this level for the area being evaluated.
Because of the uncertainty in reservoir characteristics, the most likely values of MW capacity for the various areas are not known with precision. For each area, this study assumes the mean value of the MW capacities from Monte Carlo simulation to be the most likely.
|Description:||Prepared for the Department of Business Economic Development & Tourism, Honolulu, Hawaii|
|Sponsor:||United States Department of Energy under Cooperative Agreement No. DE-FG51-03R021488|
|Appears in Collections:||Department of Business, Economic Development and Tourism|
The Geothermal Collection
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