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Performance assessment of a binary cycle geothermal power plant

dc.contributor.advisor Çelik, Hüseyin Murat en
dc.contributor.author Karadaş, Murat
dc.date.accessioned 2023-11-13T09:33:41Z
dc.date.available 2023-11-13T09:33:41Z
dc.date.issued 2013 en
dc.description Thesis (Master)--Izmir Institute of Technology, Energy Engineering, Izmir, 2013 en
dc.description Includes bibliographical references (leaves: 97-99) en
dc.description Text in English; Abstract: Turkish and English en
dc.description xii, 75 leaves en
dc.description Full text release delayed at author's request until 2016.09.01 en
dc.description.abstract An air cooled binary cycle GPP is thermodynamically modeled by using the design data of an actual plant. Effects of design parameters are investigated to plant performance. The modeling binary cycle power plant is produced 6514 kWe by using 542.65 ton/hour brine, 22.45 ton/hour steam and 33.4% NCGs content of steam at 157.9 °C geothermal resource temperature and 17.1 °C average ambient air conditions. The thermal efficiency of the model plant is found 11.32 %. The performance equations and the theoretical net power correction factors of the plant are created by using the thermodynamic model. According to this model, the net power generation of the plant increases with an increase in brine temperature, and mass flow rates of brine and steam; decreases with an increase of ambient air temperature and NCGs content of the steam. Furthermore, regression analysis of DORA-1 GPP is conducted using actual plant data to assess the plant performance. The annual multiple linear regression models are developed from 2006 to 2012 to estimate the performance of a geothermal power plant by using three measured dependent variables: the ambient air temperature, the brine flow rate and temperature. These models are tested by using classical assumptions of linear regressions, positive serial autocorrelation is found in all models. Autocorrelations are eliminated by using Orcutt-Cochran method. Although the performance model trends from 2006 to 2008 are found to be close, the performance status of the plant is generally variable from year to year. According to perennial regression models, the plant performance has started to decline with 270 kWe electricity generation capacity since 2009. The total degradation of the plant performance reached to 760 kWe capacity by 2012. Additionally, the statistical net power correction factors are calculated using regression model of 2008. Consequently, the net power correction factors for thermodynamic model and regression analysis are compared with DORA-1’s manufacturer, Ormat, correction factors. Although there are some minor differences, all of the net power correction factors have similar trends. The comparison shows that Ormat’s correction factors don’t exactly express the performance status of the DORA-1 GPP. en
dc.identifier.uri http://standard-demo.gcris.com/handle/123456789/4636
dc.language.iso en en_US
dc.publisher Izmir Institute of Technology en
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Multiple regression analysis en
dc.subject Energy performance analysis en
dc.subject.lcsh Geothermal power plants en
dc.title Performance assessment of a binary cycle geothermal power plant en_US
dc.type Master Thesis en_US
dspace.entity.type Publication
gdc.author.institutional Karadaş, Murat
gdc.description.department Energy Systems Engineering en_US
gdc.description.publicationcategory Tez en_US
gdc.oaire.accepatencedate 2013-01-01
gdc.oaire.diamondjournal false
gdc.oaire.impulse 0
gdc.oaire.influence 2.9837197E-9
gdc.oaire.influencealt 0
gdc.oaire.isgreen false
gdc.oaire.keywords Energy
gdc.oaire.keywords İstatistik
gdc.oaire.keywords Mechanical Engineering
gdc.oaire.keywords Multivariate statistic
gdc.oaire.keywords Statistics
gdc.oaire.keywords Makine Mühendisliği
gdc.oaire.keywords Multiple linear regression analysis
gdc.oaire.keywords Enerji
gdc.oaire.popularity 9.2213404E-10
gdc.oaire.popularityalt 0.0
gdc.oaire.publicfunded false

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