This is a Demo Server. Data inside this system is only for test purpose.
 

Performance assessment of a binary cycle geothermal power plant

Loading...
Publication Logo

Date

2013

Journal Title

Journal ISSN

Volume Title

Publisher

Izmir Institute of Technology

Open Access Color

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No

Research Projects

Journal Issue

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.

Description

Thesis (Master)--Izmir Institute of Technology, Energy Engineering, Izmir, 2013
Includes bibliographical references (leaves: 97-99)
Text in English; Abstract: Turkish and English
xii, 75 leaves
Full text release delayed at author's request until 2016.09.01

Keywords

Multiple regression analysis, Energy performance analysis, Energy, İstatistik, Mechanical Engineering, Multivariate statistic, Statistics, Makine Mühendisliği, Multiple linear regression analysis, Enerji

Fields of Science

Citation

WoS Q

Scopus Q

Source

Volume

Issue

Start Page

End Page

Collections

Google Scholar Logo
Google Scholar™

Sustainable Development Goals