Selection of Climatic Design Points for Gas Turbine Power Augmentation

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Mustapha Chaker ◽  
Cyrus B. Meher-Homji
Keyword(s):  
Gas Turbine ◽  
Optimal Solution ◽  
Climatic Conditions ◽  
Weather Data ◽  
Climatic Data ◽  
Data Set ◽  
Suggested Approach ◽  
Design Point ◽  
Impact Performance ◽  
Selection Of

There is a widespread interest in the application of gas turbine power augmentation technologies such as evaporative cooling and mechanical chilling in the mechanical drive and power generation markets. Very often, the selection of the design point is based on the use of American Society of Heating and Refrigeration Engineers (ASHRAE) data or a design point that is in the basis of design for the project. This approach can be detrimental and can result in a non optimal solution. In order to evaluate the benefits of power augmentation, users can use locally collected weather data, or recorded hourly bin data set from databases such as typical meteorological year (TMY), engineering weather data (EWD), and integrated weather surface (IWS). This paper will cover a suggested approach for the analysis of climatic data for power augmentation applications and show how the selection of the design point can impact performance. The final selection of the design point depends on the specific application, the revenues generated and installation costs. To the authors’ knowledge, this is the first attempt to treat this topic in a structured analytical manner by comparing available database information with actual climatic conditions.

Selection of Climatic Design Points for Gas Turbine Power Augmentation

2011 ◽  
Author(s):  
Mustapha Chaker ◽  
Cyrus B. Meher-Homji
Keyword(s):  
Gas Turbine ◽  
Optimal Solution ◽  
Climatic Conditions ◽  
Weather Data ◽  
Climatic Data ◽  
Data Set ◽  
Suggested Approach ◽  
Design Point ◽  
Impact Performance ◽  
Selection Of

There is a widespread interest in the application of gas turbine power augmentation technologies such as evaporative cooling or mechanical chilling in the mechanical drive and power generation markets. Very often, the selection of the design point is based on the use of ASHRAE data or a design point that is in the basis of design for the project. This approach can be detrimental and can result in a non optimal solution. In order to evaluate the benefits of power augmentation, users can use locally collected weather data, or recorded hourly bin data set from databases such as TMY, EWD, and IWS. This paper will cover a suggested approach for the analysis of climatic data for power augmentation applications and show how the selection of the design point can impact performance and economics of the installation. The final selection of the design point depends on the specific application, the revenues generated and installation costs. To the authors’ knowledge, this is the first attempt to treat this topic in a structured analytical manner by comparing available database information with actual climatic conditions.

An Effective AQI Estimation Using Sensor Data and Stacking Mechanism

2021 ◽  
Author(s):  
Dat Q. Duong ◽  
Quang M. Le ◽  
Tan-Loc Nguyen-Tai ◽  
Hien D. Nguyen ◽  
Minh-Son Dao ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Research Topic ◽  
Sensor Data ◽  
Weather Data ◽  
Quality Estimation ◽  
Data Set ◽  
Adverse Health Effects ◽  
Overall Performance ◽  
Selection Of

Accurately assessing the air quality index (AQI) values and levels has become an attractive research topic during the last decades. It is a crucial aspect when studying the possible adverse health effects associated with current air quality conditions. This paper aims to utilize machine learning and an appropriate selection of attributes for the air quality estimation problem using various features, including sensor data (humidity, temperature), timestamp features, location features, and public weather data. We evaluated the performance of different learning models and features to study the problem using the data set “MNR-HCM II”. The experimental results show that adopting TLPW features with Stacking generalization yields higher overall performance than other techniques and features in RMSE, accuracy, and F1-score.

Available and Future Gas Turbine Power Augmentation Technologies: Techno-Economic Analysis in Selected Climatic Conditions

2012 ◽  
Author(s):  
R. K. Bhargava ◽  
L. Branchini ◽  
F. Melino ◽  
A. Peretto
Keyword(s):  
Power Generation ◽  
Economic Analysis ◽  
Electric Power ◽  
Gas Turbine ◽  
Climatic Conditions ◽  
Proper Selection ◽  
Peak Demand ◽  
Economic Analyses ◽  
Widespread Interest ◽  
Selection Of

There exist a widespread interest in the application of gas turbine power augmentation technologies in both electric power generation and mechanical drive markets attributable to deregulation in the power generation sector, increased electric rates during peak demand period, and need for a proper selection of the gas turbine in a given application. In this study detailed thermo-economic analyses of various power augmentation technologies, implemented on a selected gas turbine, have been performed to identify the best techno-economic solution depending on the selected climatic conditions. The presented results show that various power augmentation technologies examined have different payback periods. Such a techno-economic analysis is necessary for proper selection of a power augmentation technology.

scholarly journals Historical and Future Typical Meteorological Years for 33 locations in Greece: a handy tool for various applications

2021 ◽  
Author(s):  
Basil Psiloglou ◽  
Harry D. Kambezidis ◽  
Konstantinos V. Varotsos ◽  
Dimitris G. Kaskaoutis ◽  
Dimiitris Karagiannis ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Design Tool ◽  
Weather Data ◽  
Climate Simulation ◽  
Total Solar Radiation ◽  
Climatic Data ◽  
Data Set ◽  
Specific Location ◽  
Daily Data

<p>It is generally accepted that a climatic data set of meteorological measurements with true sequences and real interdependencies between meteorological variables is needed for a representative climate simulation. In the late 1970s the Typical Meteorological Year (TMY) concept was introduced in USA as a design tool for approximating expected climate conditions at specific locations, at a time when computers were much slower and had less memory than today. A TMY is a collation of selected weather data for a specific location, listing usually hourly values of meteorological and solar radiation elements for one-year period. The values are generated from a data bank much longer than a year in duration, at least 10 years. It is specially selected so that it presents the range of weather phenomena for the location in question, while still giving annual averages that are consistent with the long-term averages for the specific location. Each TMY data file consists of 12 months chosen as most “typical“ among the years present in the long-term data set. Although TMYs do not provide information about extreme events and do not necessarily represent actual conditions at any given time, they still reflect all the climatic information of the location. TMY sets remain in popular use until today providing a relatively concise data set from which system performance estimates can be developed, without the need of incorporating large amounts of data into simulation models. </p><p>TMY sets for 33 locations in Greece distributed all over the country were developed, covering for the first time all climatic zones, for both historical and future periods. Historical TMY sets generation was based on meteorological data collected from the Hellenic National Meteorological Service (HNMS) network in Greece in the period 1985-2014, while the corresponding total solar radiation values have been derived through the Meteorological Radiation Model (MRM).</p><p>Moreover, the generation of future TMY sets for Greece was also performed, for all 33 locations. To this aim, bias adjusted daily data for the closest grid point to the HNMS station’s location were employed from the RCA4 Regional Climate Model of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Earth system model of the Max Planck Institute for Meteorology (MPI-M). Simulations were carried out in the framework of the EURO-CORDEX modeling experiment, with a horizontal RCA4 model resolution of 0.11<sup>o</sup> (~12 x 12 km). We used daily data for four periods: the 1985-2014 used as reference period and the 2021-2050, 2046-2070 and 2071-2100 future periods under RCP4.5 and RCP8.5 scenarios. </p><p>This work was carried out in the framework of the “Development of synergistic and integrated methods and tools for monitoring, management and forecasting of environmental parameters and pressures” (KRIPIS-THESPIA-II) Greek national funded project.</p>

scholarly journals Influence of cooling air selections on the efficiency of a gas turbine installation

2020 ◽  
Vol 22 (4) ◽  
pp. 16-23
Author(s):  
I. I. Mubarakov ◽  
A. B. Shigapov
Keyword(s):  
Gas Turbine ◽  
Climatic Conditions ◽  
Input Device ◽  
Operational Parameter ◽  
Extensive Information ◽  
Air Compression ◽  
Cooling Air ◽  
Determining Factor ◽  
Turbine Installation ◽  
Selection Of

A gas turbine installation (GTI) consists of 5 main parts: an input device, a compressor, a combustion chamber, a gas turbine, and an output device. In this work, due to the lack of sufficiently extensive information about stationary GTI, data from the characteristics of aviation GTI were partially used. The GTI operation efficiency is influenced by many factors, among which, apparently, the determining factor is the degree of air compression in the compressor π К . Of course, the compression ratio depends on the design scheme of the gas turbine, the type of fuel, the climatic conditions of operation, and others. The most important operational parameter of the GTI is the effective power NP and specific fuel consumption bud . The article provides a numerical analysis of the effect π К on NP and bud under variations in the temperature of gases at the turbine inlet T3 , as well as the influence of other factors, including the selection of part of the air for cooling high-temperature surfaces of the structure. The conclusions were made based on the calculations, the results of which are shown in the tables, and in the comparison graphs of obtained results.

Accuracy of Weather Data in Long-Term Pavement Performance Program Database

2000 ◽  
Vol 1699 (1) ◽  
pp. 151-159 ◽  
Author(s):  
Chung-Lung Wu ◽  
Gonzalo R. Rada ◽  
Aramis Lopez ◽  
Yingwu Fang
Keyword(s):  
Weather Conditions ◽  
Test Site ◽  
Climatic Conditions ◽  
Weighting Scheme ◽  
Pavement Performance ◽  
Weather Data ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Weather Stations

To provide accurate climatic data for pavements under the Long-Term Pavement Performance (LTPP) Program, a climatic database was developed in 1992 and subsequently revised and expanded in 1998. In the development of this database, up to five nearby weather stations were selected for each test site. Pertinent weather data for the selected weather stations were obtained from the U.S. National Climatic Data Center and the Canadian Climatic Center. With a 1/ R2 weighting scheme, site-specific climatic data were derived from the nearby weather station data. The derived data were referred to as “virtual”weather data. To evaluate the effect of environmental factors on pavement performance and design, automated weather stations (AWS) were installed at LTPP Specific Pavement Study Projects 1, 2, and 8 to collect on-site weather data. Since the virtual weather data were developed for all LTPP test sites and will be used for future pavement performance studies, it is essential that the derived virtual data be accurate and representative of the actual onsite climatic conditions. The availability of the AWS weather data has provided an opportunity to evaluate whether virtual weather data can be used to represent on-site weather conditions. Daily temperature data and monthly temperature and precipitation data were used in this experiment. On the basis of the comparisons made between the virtual and onsite measured (AWS) data, it appears that climatic data derived from nearby weather stations using the 1/R2 weighting scheme estimate the actual weather data reasonably well and thus can be used to represent on-site weather conditions in pavement research and design.

scholarly journals Bin Weather Data for HVAC Systems Energy Calculations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3501
Author(s):  
Konstantinos T. Papakostas ◽  
Dimitrios Kyrou ◽  
Kyrillos Kourous ◽  
Dimitra Founda ◽  
Georgios Martinopoulos
Keyword(s):  
Air Temperature ◽  
Air Conditioning ◽  
Energy Performance ◽  
Climatic Conditions ◽  
Weather Data ◽  
Climatic Data ◽  
Outdoor Air ◽  
Energy Demands ◽  
Hourly Temperature

The increase in global air temperature is well documented, as during the last several years each decade has been consecutively warmer than the preceding. As climatic conditions affect the energy performance of buildings, the changes in outdoor air temperature and humidity will inevitably lead to significant alterations in energy consumption and costs for the heating, ventilating and air conditioning (HVAC) of buildings. The availability and quality of climatic data play an important role in the accuracy of energy analysis results. In this study, the hourly temperature and relative humidity of outdoor air measurements, for a period of three decades (1983–2012), recorded at the climatic station of the National Observatory of Athens were processed, and an up-to-date set of specific data for the application of bin methods was produced and presented. The data were then used to calculate changes in the energy demands in a typical office building throughout the specified period. Results showed a progressive reduction in the low and increase in the high temperature intervals, leading to an increase in the building’s annual energy requirements for air conditioning of up to 14.5% from the first to the third decade, with decrease in the energy demands for heating and increase in the energy demands for cooling.

scholarly journals Evaluation of the transferability of hydrological model parameters for simulations under changed climatic conditions

2011 ◽  
Vol 8 (3) ◽  
pp. 5891-5915 ◽  
Author(s):  
S. Bastola ◽  
C. Murphy ◽  
J. Sweeney
Keyword(s):  
Climatic Conditions ◽  
Data Series ◽  
Model Parameters ◽  
Data Sets ◽  
Climatic Data ◽  
Implicit Assumption ◽  
Data Set ◽  
Dry Conditions ◽  
Change Impact ◽  
One Year

Abstract. Conceptual hydrological models are widely used for climate change impact assessment. The implicit assumption in most such work is that the parameters estimated from observations remain valid for future climatic conditions. This paper evaluates a simple threshold based approach for testing this assumption, where a set of behavioural simulators are identified for different climatic conditions for the future simulation i.e. wet, average and dry conditions. These simulators were derived using three different data sets that are generated by sampling a block of one year of data without replacement from the observations such that they define the different climatic conditions. The simulators estimated from the wet climatic data set showed the tendency to underestimate flow when applied to dry data set and vice versa. However, the performances of the three sets of basin simulators on chronologically coherent data are identical to the simulators identified from a sufficiently long data series that contains both wet and dry climatic conditions. The results presented suggest that the issue of time invariance in the value of parameters has a minimal effect on the simulation if the change in precipitation is less than 10 % of the data used for calibration.

scholarly journals PENERAPAN DATA MINING UNTUK PRAKIRAAN CUACA DI KOTA MALANG MENGGUNAKAN ALGORITMA ITERATIVE DICHOTOMISER TREE (ID3)

JOUTICA ◽  
2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Broto Poernomo T.P ◽  
Rina Dewi Indah Sari
Keyword(s):  
Data Mining ◽  
Forecast Model ◽  
Weather Data ◽  
Data Set ◽  
Weather Forecasts ◽  
Id3 Algorithm ◽  
Application Data ◽  
Many Sources ◽  
Selection Of

In the preparation of weather forecasts information there are several obstacles, involving many sources of data and weather forecasts relying on the ability of the forerunner, so that the interpretations produced may differ between forecasters because of their own experience. Differences in interpretation can confuse users and potentially reduce the quality of information submitted. Based on this problem the author intends to study the forecast model with data mining using ID3 algorithm to obtain the appropriate model so as to facilitate the process of weather analysis and forecast. In building the application, data obtained from BMKG website is addressed dataonline.bmkg.go.id and the data taken is datacuaca on January 1, 2012 through November 30, 2015 for a total of 2414 data and 9 attributes. After the selection of attributes (only weather related attributes) and removing damaged data (incomplete data and outliers), the data is reduced to 1790 and attributes reduced to 6 pieces. In the testing process performed with 179 data (10% of the data set) random, it is known that there are 112 databases corresponding to the actual weather data. So it can be concluded that the accuracy of 73.74%.

Available and Future Gas Turbine Power Augmentation Technologies: Techno-Economic Analysis in Selected Climatic Conditions

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Rakesh K. Bhargava ◽  
Lisa Branchini ◽  
Francesco Melino ◽  
Antonio Peretto
Keyword(s):  
Power Generation ◽  
Economic Analysis ◽  
Gas Turbine ◽  
Significant Loss ◽  
Climatic Conditions ◽  
Proper Selection ◽  
Generation Capacity ◽  
Economic Analyses ◽  
Widespread Interest ◽  
Selection Of

There exists a widespread interest in the application of gas turbine power augmentation technologies in both electric power generation and mechanical drive markets, attributable to deregulation in the power generation sector, significant loss in power generation capacity combined with increased electric rates during peak demand period, and need for a proper selection of the gas turbine in a given application. In this study, detailed thermo-economic analyses of various power augmentation technologies, implemented on a selected gas turbine, have been performed to identify the best techno-economic solution depending on the selected climatic conditions. The presented results show that various power augmentation technologies examined have different payback periods. Such a techno-economic analysis is necessary for proper selection of a power augmentation technology.

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