scholarly journals ANALISIS KINERJA TURBIN UAP BERDASARKAN PERFORMANCE TEST PLTU PT. INDOCEMENT P-12 TARJUN

2016 ◽  
Vol 1 (1) ◽  
pp. 37-46
Author(s):  
Riyki Apriandi ◽  
Aqli Mursadin
Keyword(s):  
Performance Test ◽  
Heat Rate ◽  
Steam Pressure ◽  
Plant Performance ◽  
Outlet Temperature ◽  
Steam Temperature ◽  
Control Room ◽  
Average Value ◽  
Turbine Efficiency ◽  
Main Steam

This study aims to determine the performance of steam turbine PT. Indocement Tarjun Plant 12 by comparing the results of data obtained during each performance test in 1999, 2016, 2017, and 2018. This research data is taken from the control room of PT. Indocement Tarjun, variable data obtained in the form of load, main inlet steam temperature, main inlet steam pressure, HP heater feed outlet temperature, HP heater feed outlet pressure, main steam flow, and turbine by pass flow. The data is processed to get the turbine heat rate and the efficiency per time of each performance test and then averaging the data results over time, then comparing the turbine heat rate and the average efficiency of each performance test. The calculation of turbine heat rate using heat & mass balance method, turbine efficiency is obtained by comparing the energy of 1 kW with turbine heat rate and multiplying 100%. The result of the average heat turbine calculation per performance test ie August 1999 is 2.546, April 2016 2,537, June 2017 2.56, and May 2018 2.67. The average value of turbine efficiency in August 1999 was 39.30%, April 2016 39.43%, June 2017 39.07%, May 2018 37.46%. Turbine power plant performance of PT Indocement Tarjun Plant 12 decreased from 1999 to 2018 by 1.84%.

scholarly journals ANALISIS EFISIENSI TURBIN UAP UNIT 1 DI PT. PJB UBJOM PLTU PULANG PISAU KALIMANTAN TENGAH

JTAM ROTARY ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 57
Author(s):  
Edi Saputro
Keyword(s):  
Performance Test ◽  
Heat Rate ◽  
Steam Pressure ◽  
Plant Performance ◽  
Outlet Temperature ◽  
Steam Temperature ◽  
Control Room ◽  
Average Value ◽  
Turbine Efficiency ◽  
Main Steam

This study aims to determine the performance of steam turbine PT. PJB UBJOM PLTU Pulang Pisau Kalimantan Tengah the results of data obtained during each performance test in commisioning 2016 and 2018. This research data is taken from the control room of PT. PJB UBJOM PLTU Pulang Pisau, variable data obtained in the form of load, main inlet steam temperature, main inlet steam pressure, HP heater feed outlet temperature, HP heater feed outlet pressure, main steam flow, and turbine by pass flow. The data is processed to get the turbine heat rate and the efficiency per time of each performance test and then averaging the data results over time, then comparing the turbine heat rate and the average efficiency of each performance test. The calculation of turbine heat rate using heat & mass balance method, turbine efficiency is obtained by comparing the energy of 1 kW with turbine heat rate and multiplying 100%. The result of the average heat turbine calculation per performance test highest ie September 2016 is 3,51and Juli 2018 is 3,27. The average value of turbine efficiency in September 2016 was 29,03% and Juli 2018 was 33,84. Turbine power plant performance of PT. PJB UBJOM PLTU Pulang Pisau increase from 2016 to 2018 by 4,81 %.Keywords:Turbin Heat Rate, Efisiensi Turbin

scholarly journals ANALISIS KINERJA TURBIN UAP UNIT 3 BERDASARKAN PERFORMANCE TEST DI UNIT PELAKSANA PT.PLN (PERSERO) PEMBANGKITAN ASAM-ASAM

JTAM ROTARY ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 95
Author(s):  
Kemas Ronand Mahaputra
Keyword(s):  
Performance Test ◽  
Heat Rate ◽  
Steam Pressure ◽  
Outlet Temperature ◽  
Steam Turbines ◽  
Turbine Efficiency ◽  
Rate Calculation ◽  
Temperature And Pressure ◽  
Main Steam ◽  
Unit Unit

This study purpose to determine the performance of steam turbines Unit 3 of PT.PLN (Persero) Pembangkitan Asam-asam by comparing the results of the data obtained by each performance test. This research was carried out by taking data performance tests in 2012, 2017, 2018 and 2019 and then processing the data and obtaining turbine heat rate values and average turbine efficiency then comparing the values obtained in each year. The data taken is obtained from the rendal operation of PT.PLN (Persero) Pembangkitan Asam-asam, data variables taken are load, main steam temperature inlet, main steam pressure inlet, HP heater feed outlet temperature, HP heater outlet pressure, main steam flow. Temperature and pressure obtained are then searched for enthalpy values. The data obtained to calculate the value of the turbine heat rate and turbine efficiency on average per time from each performance test then averages the value of the turbine heat rate and turbine efficiency each time the data collection performance test is then compared with the data each year.The calculation of the turbine heat rate uses the heat & mass balance method by measuring the value of the incoming and outgoing fluid differences and comparing the load obtained, the efficiency of the turbine is obtained by dividing the energy of 1 kW with a turbine heat rate then multiplying by 100%. The average turbine heat rate calculation result for each performance test which is on May 23, 2012 is 2,701, October 27, 2017 is 3,136, September 5, 2018 is 3,005, May 21, 2019 is 3,113. The average turbine efficiency value on May 23, 2012 is 37.02%, October 27 2017 is 31.39%, September 5 2018 is 33.28%, May 21, 2019 is 32.12%. The performance of PT PLN (Persero) Pembangkit Asam-asam Implementing Unit Unit 3 has decreased from 2012 to 2019 which is 4.9%

Analisis Efektivitas Kondensor Di PLTU PT. Semen Tonasa Btg Unit I 2×25 MW

PoliGrid ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 20
Author(s):  
Jamal Chandra Bhuana ◽  
Irfan Muh ◽  
Aqsha Maulana
Keyword(s):  
Flow Rate ◽  
Water Flow Rate ◽  
Cooling Water ◽  
Steam Pressure ◽  
Inlet Temperature ◽  
Outlet Temperature ◽  
Steam Temperature ◽  
Control Room ◽  
Steam Power ◽  
Cooling Water Flow Rate

Abstract: This research was conducted to determine the effect of fouling on the effectiveness of condensers in the Steam Power Plant (PLTU) PT. Semen Tonasa. The research method used is data collection in the central control room PLTU PT. Semen Tonasa. Steam temperature inlet condenser (Thin), temperature of condensate water  (Thout), steam pressure inlet condenser (Ps), pressure of cooling water (Pcw), inlet temperature (Tcin) and outlet temperature of cooling water (Tcout), steam flow rate ( and cooling water flow rate () is the data needed in this research. Data were analyzed to get the value of effectiveness, number transfer of units (NTU), capacity ratio (C), log mean temperature different (LMTD) of the condenser. The results of the analysis showed that the decrease in condenser performance was influenced by the effect of fouling. Overhaul is done every 2 years. There was a decrease in NTU's value of 31.69% and an effective value of 22.29% in the period April 2016 to March 2018.

Review of Control Strategies Employing Neural Network for Main Steam Temperature Control in Thermal Power Plant

2014 ◽  
Vol 66 (2) ◽  
Author(s):  
N. A. Mazalan ◽  
A. A. Malek ◽  
Mazlan A. Wahid ◽  
M. Mailah
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Temperature Control ◽  
Pid Control ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Heat Rate ◽  
Steam Temperature ◽  
Multiple Variables ◽  
Main Steam

Main steam temperature control in thermal power plant has been a popular research subject for the past 10 years. The complexity of main steam temperature behavior which depends on multiple variables makes it one of the most challenging variables to control in thermal power plant. Furthermore, the successful control of main steam temperature ensures stable plant operation. Several studies found that excessive main steam temperature resulted overheating of boiler tubes and low main steam temperature reduce the plant heat rate and causes disturbance in other parameters. Most of the studies agrees that main steam temperature should be controlled within ±5 Deg C. Major factors that influenced the main steam temperature are load demand, main steam flow and combustion air flow. Most of the proposed solution embedded to the existing cascade PID control in order not to disturb the plant control too much. Neural network controls remains to be one of the most popular algorithm used to control main steam temperature to replace ever reliable but not so intelligent conventional PID control. Self-learning nature of neural network mean the load on the control engineer re-tuning work will be reduced. However the challenges remain for the researchers to prove that the algorithm can be practically implemented in industrial boiler control.

Introducing ASME PTC 48

2014 ◽  
Author(s):  
Olivier Le Galudec ◽  
James Oszewski ◽  
John Preston ◽  
David Thimsen
Keyword(s):  
Co2 Capture ◽  
Carbon Capture ◽  
Power Plants ◽  
Performance Test ◽  
Heat Rate ◽  
Air Separation ◽  
Plant Performance ◽  
Small Scale ◽  
Separation Unit ◽  
Combined Cycles

In the field of Power Generation, Operators — Plant Owners, Utilities, IPPs … — have had to face severe constraints linked not only with price of electricity and cost of fuel, but also with more and more demanding environmental constraints. It appears that the next atmospheric emission coming under scrutiny is CO2. Some small scale laboratory size experiments and pilot scale tests demonstrating the ability to capture CO2 before it reaches the atmosphere have already been conducted, and some industrial scale demonstrators are already at the permitting stage and will soon reach construction. In order to anticipate the needs of Performance Tests within this coming market, ASME decided to form a new committee in order to prepare and deliver ASME Performance Test Code – PTC 48 “Overall Plant Performance with Carbon Capture” test code. This new code may be seen as an evolution of ASME PTC 46 “Performance Test Code on Overall Plant Performance” 1996 (currently under revision), which goes beyond the sole verification of components to provide guidelines for testing a full Plant. Capturing CO2 from fuel–fired power plants will have a significant impact on net capacity and net heat rate of the plant. Such plants will, in addition to the Power Block and Steam Generator, also include systems not commonly included in non-CO2 capture power plants. The addition of an ASU (Air Separation Unit, for oxy-combustion with CO2 capture) and/or CPU (CO2 Purification Unit, for oxy-combustion or post-combustion CO2 capture) has made necessary the preparation of a dedicated test code based upon same guiding principle than PTC 46, i.e. treating the plant globally as a “Black Box”. This approach allows correction of output and efficiency at the plant interfaces, but at the exclusion of internal parameters. It is anticipated that the code can inform development of regulations that define the rules and obligations of Operators. Currently, the proposed PTC 48 aims at fossil fuel fired Steam-electric power plants using either post-combustion CO2 capture or oxy-combustion with CO2 capture technologies. Combined cycles and Integrated Gasification Combined Cycles — IGCCs — are not addressed.

Economic Analysis of a 660MW Supercritical Turbine for Steam Initial Parameters

2014 ◽  
Vol 960-961 ◽  
pp. 1550-1553 ◽  
Author(s):  
Yu Lin Tang ◽  
Shan Tu ◽  
Yang Du ◽  
Chao Wang ◽  
Hong Juan Wang
Keyword(s):  
Power Plant ◽  
Thermal Power ◽  
Steam Pressure ◽  
Heat Consumption ◽  
Operating Parameters ◽  
Steam Temperature ◽  
Operating Modes ◽  
Endothermic Process ◽  
Steam Parameters ◽  
Main Steam

Economic diagnosis of thermal power units is to determine the economy of its operating parameters and operating modes by quantitative and qualitative analysis, which is significant to economic operation and energy saving of power plant. On the basis of equivalent enthalpy drop method and the theory of variable conditions, the economic diagnosis model of operating parameters was established. As main steam temperature and main steam pressure for example, economic diagnosis of a 660MW supercritical steam turbine unit was performed. The result demonstrates that improving the main steam temperature or main steam pressure can reduce heat consumption of the unit. The essence of improving the initial steam parameters is to improve the average temperature of the steam cycle endothermic process, thus improving the circulation efficiency and reducing heat consumption. The economic impact of main steam temperature is up to 0.61g/(kW·h), while which of main steam pressure is little. Therefore, by increasing the initial steam parameters, especially the main steam temperature, to improve the economy of the entire power plant is the main way to enhance the efficiency of power plant in the current.

The Exergy Optimization Analysis of 700°C HUSC Steam Turbine Using a Echelon Cycle System

2016 ◽  
Author(s):  
Xiaolan Yi ◽  
Shiwang Fan ◽  
Haitao Li ◽  
Jiandao Yang ◽  
Tao Chen ◽  
...  
Keyword(s):  
High Temperature ◽  
Optimal Solution ◽  
Heat Rate ◽  
Thermodynamic System ◽  
Economic Benefits ◽  
Steam Temperature ◽  
Cycle System ◽  
System Solution ◽  
Reheat Steam ◽  
Main Steam

700°C HUSC technology is considered as the next generation of more efficiently coal-fired power generation technology, the heat rate of which can be reduced by more than 8% on the basis of current ultra-supercritical units. That means there is a huge energy saving benefits. With the main steam / reheat steam temperature increasing from 600°C / 620 °C to 700°C/ 720°C, the temperature of extraction steam increases dramatically, especially the first extraction stage after reheater, the temperature of which will increase to 630 ∼ 650 °C. That means a substantial increase in the cost of the initial investment because of the nickel-based material being used in extraction pipe and heaters. With EC system, the extraction steam temperature is reduced sharply because the high temperature extraction steam is moved from the main turbine to a small parallel extraction turbine and the steam source of the small extraction turbine is from the cold reheater. So the highest extraction steam temperature will not exceed 500 °C, and the high temperature risk of heat recovery system will be eliminated completely. In this paper, exergy theory is introduced to analyze the cycle efficiency of the new thermodynamic system and the conventional one. In order to obtain a better 700 °C high ultra-supercritical thermodynamic system solution, GA method is used to optimize the regenerative system parameters to lower the overall heat consumption. The exergy theory is also used to analyze the reason why optimal solution can bring economic benefits. Finally, the feasibility of the entire system project will be analyzed.

A Study of Fixed Steam Pressure Control of Ultra-Supercritical Unit

2013 ◽  
Vol 291-294 ◽  
pp. 2178-2181
Author(s):  
Shi He Chen ◽  
Xi Zhang ◽  
Guo Liang Wang ◽  
Wei Wu Yan ◽  
Heng Feng Tian ◽  
...  
Keyword(s):  
Predictive Control ◽  
Tracking Control ◽  
Pressure Control ◽  
Steam Pressure ◽  
Steam Temperature ◽  
Load Demand ◽  
Valve Opening ◽  
Simulation Results ◽  
Coal Flow ◽  
Main Steam

Ultra-supercritical (USC) unit is more and more popular these years for its advantages. In this paper, a model predictive control (MPC) method is introduced for coordinated control of USC unit running in fixed pressure mode. Three inputs (i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs (i.e. load, main steam temperature and main steam pressure). Piecewise models of the USC unit are obtained using the three inputs and the three outputs. In simulation, the output power follows load demand quickly and main steam temperature can be controlled around the setpoint closely in load tracking control. The simulation results show the effeteness of the proposed methods.

Variation of Plant Electrical Output Due to Main Steam Temperature and Thermal Power

2010 ◽  
Author(s):  
D. W. Yoon ◽  
C. K. Park ◽  
B. H. Lee ◽  
K. C. Jeong
Keyword(s):  
Power Plant ◽  
Thermal Performance ◽  
Thermal Efficiency ◽  
Thermal Power ◽  
Heat Rate ◽  
Steam Temperature ◽  
Turbine Inlet ◽  
Thermodynamic Performance ◽  
Main Steam ◽  
Electrical Output

As a measure of power plant thermodynamic performance, heat rate (H.R.) is used. As heat rate is inversely proportional to thermal efficiency, the thermal efficiency of a power plant increases as the heat rate decreases. The major thermodynamic performance parameters in a plant thermal cycle affecting the electrical output include but are not limited to: the initial pressure of main steam at the turbine inlet, the initial moisture content or superheated condition of main steam at the turbine inlet, the effectiveness of the feedwater heating cycle, the effectiveness of the moisture separator, the effectiveness of the reheater, the condenser pressure, the level of cycle separation and the accuracy of electric output measurement. A review of thermodynamic principles involved in a thermal performance plan is needed to understand the changes in the parameters and recognize the thermal performance status and trends, which will lead us to propose corrective actions when appropriate. This paper focuses on the effects of main steam temperature and thermal power.

Neural Network Modeling For Main Steam Temperature System

2014 ◽  
Vol 69 (3) ◽  
Author(s):  
N. A. Mazalan ◽  
A. A. Malek ◽  
Mazlan A. Wahid ◽  
M. Mailah
Keyword(s):  
Neural Network ◽  
Dead Time ◽  
Steam Pressure ◽  
Neural Network Modeling ◽  
Steam Temperature ◽  
Power Plant Boiler ◽  
Plant Data ◽  
Main Steam ◽  
Generator Output ◽  
Plant Boiler

Main Steam Temperature (MST) is non-linear, large inertia, long dead time and load dependant parameters. The paper present MST modeling method using actual plant data by utilizing MATLAB's Neural Network toolbox. The result of the simulation showed the MST model based on actual plant data is possible but the raw data need to be pre-processed for better output. Generator output, total main steam flow, main steam pressure and total spray flow are four main parameters affected the behavior of MST in coal fired power plant boiler.

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