Main Steam Flow Research Articles

A study of co-firing palm kernel shell on the Nagan Raya coal-fired power plant

Co-firing biomass with coal in existing utility boilers is seen as one strategy for promoting renewable energy with low upfront costs and little to no impact on the boilers' high efficiency. The purpose of this research is to analyse the fuel characteristics and performance of palm kernel shell co-firing at Nagan Raya Coal-Fired Power Plant (CFPP) at various percentages of palm kernel shell combination. The analysis is conducted based on the operational data obtained from Nagan Raya Power Plant. In this study, the characteristics of fuel and the performance of a power plant are analysed based on percentages of fuel variations, namely 100% coal, 95% coal-5% palm kernel shell, and 90% coal-10% palm kernel shell. The results reveal that co-firing's biomass ratio boosted operation parameters, including main steam pressure, temperature, and flow rate. Subsequently, co-firing with 90% coal-10% palm kernel shell has enhanced the power plant output to 90,7 MW compared to those with 100% coal, 95% coal-5% palm kernel shell, namely 89,3 MW and 90,4 MW, respectively

Deep learning-assisted multi-objective optimization of coke dry quenching system efficiency

Coke dry quenching is a promising technology for energy saving and environmental protection in the industrial sectors. Prediction of system efficiency index (SEI) and dynamic adjustment of operating parameters are essential to ensure high system efficiency. In this study, a deep learning-assisted multi-objective optimization framework was proposed to improve coke quenching efficiency and steam production simultaneously. Firstly, numerous on-site process parameters were collected as the data basis for subsequent model construction, and a system-level heat balance model was established and validated for real-time calculation of coke burning loss rate. Then, an attention-based one-dimensional convolutional neural network was developed as a data-driven surrogate model to establish the mapping relationship between the operating parameters and SEI. Finally, the Non-dominated Sorting Genetic Algorithm II was combined with the Technique for Order of Preference by Similarity to Ideal Solution to rapidly identify the optimal operating parameters under different loads. The optimization results also provided a new insight into the system dynamic characteristics. The results show that the surrogate model can swiftly and precisely predict SEI, with R2 exceeding 0.9. Compared with initial operating conditions, the optimal decision scheme has improved SEI by 82 %, with the optimal coke burning loss rate and main steam flow rate of 0.56 % and 83.6 t/h, respectively. This work will provide valuable decision aids for technicians to reach the desired system efficiency.

Artificial intelligence driven smart operation of large industrial complexes supporting the net-zero goal: Coal power plants

The true potential of artificial intelligence (AI) is to contribute towards the performance enhancement and informed decision making for the operation of the large industrial complexes like coal power plants. In this paper, AI based modelling and optimization framework is developed and deployed for the smart and efficient operation of a 660 MW supercritical coal power plant. The industrial data under various power generation capacity of the plant is collected, visualized, processed and subsequently, utilized to train artificial neural network (ANN) model for predicting the power generation. The ANN model presents good predictability and generalization performance in external validation test with R2 = 0.99 and RMSE =2.69 MW. The partial derivative of the ANN model is taken with respect to the input variable to evaluate the variable’ sensitivity on the power generation. It is found that main steam flow rate is the most significant variable having percentage significance value of 75.3 %. Nonlinear programming (NLP) technique is applied to maximize the power generation. The NLP-simulated optimized values of the input variables are verified on the power generation operation. The plant-level performance indicators are improved under optimum operating mode of power generation: savings in fuel consumption (3 t/h), improvement in thermal efficiency (1.3 %) and reduction in emissions discharge (50.5 kt/y). It is also investigated that maximum power production capacity of the plant is reduced from 660 MW to 635 MW when the emissions discharge limit is changed from 510 t/h to 470 t/h. It is concluded that the improved plant-level performance indicators and informed decision making present the potential of AI based modelling and optimization analysis to reliably contribute to net-zero goal from the coal power plant.

Research on dehumidification optimization of steam turbine wet steam stage hollow stator cascade heating

The secondary water droplets in the steam turbine wet steam stage are easy to cause water erosion damage to the rotor cascade, and there is a large speed slip between the main steam flow and the secondary water droplets, which will seriously affect the safe and stable operation and reduce the efficiency of the steam turbine. Secondary water droplets are formed when the water film deposited on the stator blade surface falls off at the trailing edge. Therefore, controlling the formation of a water film on the stator blade surface plays an important role in improving the efficiency and safety of the steam turbine wet steam stage. Based on the current research situation at home and abroad, taking the Dykas cascade as the research object, it is found that the covering area of dry steam film on blade surface expands with the increase of temperature and flow of hot steam inlet. With the increase of hot steam back-pressure, the wetness of blade surface increases. When the average heat flux on the blade surface reaches 5000W/m2, there will be no water film falling off the blade surface. By orthogonal test, the expression between the average heat flux on the blade surface, the inlet temperature, the flow rate and the back-pressure was obtained. The research results can provide reference for the parameter design of steam turbine hollow stator heating dehumidification.

An Optimization Method of Steam Turbine Load Resilient Adjustment by Characterizing Dynamic Changes in Superheated Steam Energy

Improving the dynamic regulation ability of thermal power units is effective for realizing flexible scheduling in modern power systems. At present, the unit regulation capacity is usually reflected by the load adjustment of the main steam pressure and flow tracking ability, through the calculation of the given and real-time deviation to complete the load, and by pressure adjustment. However, although the calculation involved in this method is easy and the results are intuitive, overshoot and lag can easily occur. The main reason for this is that the process from boiler combustion to turbine works has strong hysteresis and inertia, and the feedback signal of the pressure and flow rate cannot dynamically reflect the change in boiler combustion and steam energy. According to the heat transfer process of the unit, the main steam temperature can directly reflect the energy transfer in the furnace combustion process and then reflect the changing trend of steam energy. Analyzing the changing characteristics of the temperature, pressure, and flow of superheated steam under rapid load regulations makes it possible to calculate the instantaneous energy storage value of the main steam before the regulating valve, and this value was inserted into the coordinate system as a new feedforward signal. Finally, a simulation model was established by using the actual running data of the unit. A simulation experiment under variable working conditions demonstrated that this method could improve the dynamic adjustment of the unit to load and pressure and help the power grid absorb renewable energy.

Multi-Domain Modeling and Analysis of Marine Steam Power System Based on Digital Twin

The marine steam power system includes a large amount of thermal equipment; meanwhile, the marine environment is harsh and the working conditions change frequently. Operation management involves many disciplines, such as heat, machinery, control, electricity, etc. It is a complex multi-discipline physical system with typical nonlinear, multi-parameter, strong coupling characteristics. In order to realize the health management of a marine steam power system, based on digital twin technology combined with the Modelica language, modular modeling, etc., this paper conducts in-depth research on the multi-domain modeling of the marine steam power system, characteristic analysis of variable working conditions, fault simulation, etc. The analysis results show that the dynamic response trend of the model is consistent with the actual operation, the error of the main steam flow at 1800 s is the largest and is −4.9%, and the error of the main steam flow, steam turbine output power, cooling water outlet temperature and other key parameters is within ±5%. Virtual reality mapping between the digital model and the physical equipment is realized, which lays a foundation for mastering the dynamic characteristics of the marine steam power system.

Numerical Study of Heat Transfer Characteristics in High Pressure Steam Turbine During Stop Unit Process with Sliding Pressure

During maintenance of the turbine and its auxiliary equipment, which requires a stop of the turbine oil system equipment and an open turbine casing, the first stage metal temperature requirement must be below 150°C. The normal stop unit method with natural cooling takes about 14 to 17 days. In order to speed up the cooling time to 5 days, a forced cooling turbine is needed using the stop unit method with sliding pressure. The heat transfer that occurs in the high-pressure turbine during the stop unit process with sliding pressure was investigated using the numerical method of CFD simulation. The 2D geometry design was made from high-pressure turbine cutouts images. Then meshing was made. The solver stage and the post-processing stage were set. The simulation was running in a steady state and followed by transients. The validation method was to compare the first stage metal temperature parameter between the actual process and the results of the CFD simulation at a load of 350 MW, then re-simulate it at 500 MW and 645 MW. The stop unit process with sliding pressure starting at 645MW resulted in the best final cooling compared to the stop unit at 500 MW and 350MW loads. By increasing the main steam flow, the resulting cooling increases. By increasing the value of the fluid flow velocity, the Reynolds number increases, so the convection heat coefficient also increases.

Design and evaluation of a new solar-biomass based energy system for a small sustainable residential community

In this paper, an integrated energy system is developed and analyzed, which generates power, heating and freshwater while being supplied with two distinct renewable energies: biomass and solar thermal. The system combines a multi-staged steam Rankine cycle with the steam generator energized via heat transfer from hot biomass combustion gases and hot solar thermal oil. It also includes a multi-effect desalination unit energized with thermal energy recovered from hot flue gases. The biomass combustion rate is controlled so that steam is generated steadily and at constant parameters regardless of the fluctuation and intermittence of solar radiation. At the same time, no thermal storage is required for solar energy. The steam Rankine cycle is optimized to steam extraction fraction so that the net power generation is maximized. The optimum steam extraction fraction of a low-pressure turbine is 5.5% of the main steam flow rate, which is the steam ahead of the high-pressure turbine. Due to solar radiation, biomass consumption is reduced to about half. Considering the solar radiation for a typical day in the Kingdom of Saudi Arabia, biomass consumption decreases three times during noontime (when solar radiation is the maximum) with respect to the nighttime. Nevertheless, the studied system generates more heating by-products and more freshwater when the biomass combustion rate is higher. During daytime, the current study achieves freshwater and heating production almost three times higher than the nightime requirement. The study results show that the need for typical solar thermal storage can be eliminated, and so the economic competitiveness of the solar thermal energy resource substantially increased. The maximum energy efficiency is slightly over 50% due to cogeneration, whereas the maximum exergy efficiency is 47%. The Rankine cycle destroys three times more exergy than the combustion chamber, whereas the other subsystems destroy significantly less exergy than the Rankine cycle.

Operation optimization analysis of 600 MW steam turbine under new situation

It is of great significance to study the operation optimization of thermal power units under the new situation and the economic operation under low load. The bearing vibration of a 600 MW thermal power unit has been too large since it was put into operation, and steam distribution optimization and sliding pressure optimization were not carried out since the unit was put into operation. In order to solve the vibration hidden trouble of the unit and explore the energy saving potential, the operation optimization test of the steam turbine is carried out. When the valve sequence is changed from GV1/2-GV4-GV3 to GV2/3-GV1-GV4, the maximum vibration of #2 bearing decreases from 150-170 μm to 50-60 μm, and the maximum vibration of #1 bearing decreases from 90-100 μm to 30-40 μm. After optimization of steam distribution, the regulating characteristics of the unit are improved obviously, and the gap between the equivalent main steam flow feedback and the ideal value of the overall flow characteristics of the sequential valve decreases from 15.20% to less than 1%, and the load and valve of the unit change steadily in the process of switching between single valve and sequential valve. Five load conditions were carried out in the sliding pressure optimization test, and the sliding pressure curves were obtained when the back pressure was 3.35kPa, 4.9kPa and 7.95kPa. After optimized operation, the coal consumption of thermal power unit is reduced by 1.47g/(kW⋅h) on average.

Modeling of boiler variable load combustion system based on gradient lifting decision tree and improved bidirectional threshold cycle unit

Boiler combustion system is a typical dynamic system with many variables, strong coupling, large-lag, and multiple input/output. It is very difficult to build a combustion system model that conforms to the actual working conditions. This paper presents a new modeling method of boiler combustion system based on bidirectional threshold cycle unit (Bi-GRU), and establishes the training model of combustion system under variable load (low, medium and high load)conditions. At the same time, gradient lifting decision tree (GBDT) is used to reduce the dimension of input characteristic matrix. GBDT model can evaluate the weight of input features under different loads and outputs, and can identify the feature with the largest weight proportion on the basis of retaining the original physical meaning of the feature. The feature selection model based on GBDT can not only reduce the original input dimension, but also provide theoretical guidance for the subsequent combustion control strategy. The calculation results of actual operation data show that the new combustion system model established by Bi-GRU and GBDT can accurately reflect the dynamic changes of main steam flow, main steam pressure and NOx emission under different loads. Compared with the traditional recurrent neural network (RNN) model, the accuracy and performance of the new model in this paper are significantly improved, and the structure is simple and the amount of calculation is small.

Analysis of economy, energy efficiency, environment: A case study of the CHP system with both civil and industrial heat users

Integrated energy supply via the high-capacity combined heat and power (CHP) system is an effective way to achieve “win-win cooperation” for regional carbon reduction. A case study of the CHP system with both civil and industrial heat users is conducted to analysis the mixed impact of integrated energy supply on CHP systems. The steam-water equations and the off-design calculation model are developed to analyze the heat-power coupling mechanism of the CHP system. The linear-calculating diagram is obtained, which provides operational guidance for CHP system with simultaneous power, civil heat and industrial loads. Further, the analysis of economy, energy efficiency and environment within the operation region is performed. The results show that for a constant main steam flow rate, the industrial heat load is more profitable than the civil heat load. Moreover, the energy efficiency of the CHP unit can be further improved by undertaking the industrial heat load, despite at the expense of part capacity to supply civil heat. The average value of CO2 emissions per unit profit is reduced by approximately 7.69% overall after the stable industrial heat load of 100 MW, which means about 1.64 tons of CO2 can be reduced per 1000 USD profit.

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

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

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

Operating characteristics and ultra-low NOx emission of 75 t/h coal slime circulating fluidized bed boiler with post-combustion technology

Coal slime was a kind of industrial solid waste and it was hard to utilize. To realize the resource utilization of coal slime, a 75 t/h circulating fluidized bed (CFB) boiler with post-combustion technology was built. The operating and emission characteristics during mono-combustion of coal slime were investigated in detail. The fuel characteristics of coal slime and feeding from the top of the furnace resulted in the temperatures at the top and the bottom were higher than the middle of the furnace. When the furnace differential pressure increased, the furnace temperature and the main steam temperature both decreased, but the main steam flow increased. The main steam temperature could significantly increase after the soot blowing. The post-combustion air (PCA) was an effective means to adjust the main steam parameters. The main steam temperature increased as PCA increasing. The average SO2 emissions were only 8.4 mg·m−3 benefited from the excellent desulfurization effect of the combination of dry and semi-dry desulfurization. Nevertheless, due to the fluctuations of coal slime characteristics, the standard deviation of SO2 emission reached 8.6 mg·m−3. Under the conditions without desulphurization and SNCR, the NOx emissions of coal slime could be decreased to 38 mg·m−3 and reach the ultra-low NOx emission when post-combustion technology was used.

Flexible control of nuclear cogeneration plants for balancing intermittent renewables

Both intermittent renewable energy (IRE) and nuclear fission energy can provide carbon-free electric power to the grid. The electric power generation from the intermittent renewable energy (IRE) sources such as the wind and solar are strongly dependent on the climatic conditions, geographical location and large land footprint. While, nuclear plants can provide consistent and clean power supply with small land footprint. Due to the strong complementarity between the IRE and nuclear, it is attractive to interconnect them to build nuclear-renewable hybrid energy systems (NRHESs) which are defined as the integrated facilities comprised of nuclear reactors, renewable energy generation and industrial processes. The flexibility of a NRHES for grid balance can be provided by actively adjusting the electric power output of nuclear cogeneration plants (NCPs), which leads to the frequent redistribution of main steam flow to the turbine and cogeneration process. For the main steam redistribution, it is necessary to guarantee the stability of grid frequency and main steam pressure, which heavily relies on the flexible control strategy of NCPs. In this paper, a new flexible control of NCPs with saturated main steam is proposed based on the idea of actively suppressing the total disturbance to the dynamics of grid frequency and main steam pressure. The stabilization problems of pressure and frequency are transferred to the disturbance attenuation Problem of a second-order disturbed dynamical system, and an active disturbance rejection control (ADRC) is then originally proposed for system stabilization. This ADRC is applied to the flexible control of a NCP composed of a nuclear heating reactor (NHR), a turbine-generator set and a multi-effect-desalination and thermal-vapor-compression (MED-TVC) process for seawater desalination. Numerical simulation results in the cases of load stepping and maneuvering show that the flexibility of this NCP is satisfactory in balancing the grid.

Research on Method of the Flow Passage Condition Monitoring and Diagnosis for Steam Turbine

Monitoring and diagnosis of the steam turbine flow passage is the most important premise to achieve the power plant condition maintenance. The existing characteristic flow area of steam turbine changes with main steam flow and can not accurately reflect the flow passage state of steam turbine. In order to reflect the state change in turbine passage accurately, the characteristic flow area of steam turbine stage should be investigated in the same main steam flow. Because main steam flow on-line measuring method accuracy is deficient, a new method based on the exhaust pressure of IP cylinder as character parameter of main steam flow is proposed, and a correction method which takes the impact of the heat regenerative system on main steam flow into consideration is presented. Meanwhile, in the diagnostic process, the measuring result is strongly influenced by the system inevitable measuring error which directly affects the deviation between the characteristic flow area and its standard. Thus confidence intervals of characteristic flow area is given to eliminate the system errors. Finally, the actual diagnostic example in the article indicates the practicability of the method. It can be used to diagnose the flow passage of steam turbine and provide reliable basis to find out the steam turbine potential.

ANALISIS EFISIENSI BOILER UNIT 2 DAN 4 DI PT. PLN (PERSERO) WIL. KALSELTENG SEKTOR PLTU ASAM-ASAM

Boiler is a tool used to produce steam / steam for various purposes. The water in the boiler is heated by heat from the fuel combustion (other heat source) resulting in heat transfer from the heat source to the water causing the water to become hot or transformed into steam. Direct Methods Also known as "input-output method" because this method requires only output / output (steam) and heat input / fuel (fuel) for efficiency evaluation. From the results of boiler efficiency study from August 8, 2017 to August 17, 2017 with a total average - unit 4 has a boiler efficiency 75.5012% higher than unit 2 which only amounted to 65.24% 84%. The high efficiency of boiler unit 2 is due to the average pressure on unit 4 of 86.9229 bar is greater than the pressure of unit 2 which is only about 82.9155 bar. Then Main steam flow on unit 4 is 66,6605 kg / s while unit 2 is only 63,61111 kg/s. For feed water flow unit 4 only able to flow 65,9 kg / s and unit 2 equal to 66,675 kg/s.

Change in Steam Generators Main and Auxiliary Energy Flow Streams During the Load Increase of LNG Carrier Steam Propulsion System

In this paper is presented an analysis of main and auxiliary steam energy flow streams from steam generators during the increase in steam system load at conventional LNG carrier. During the steam system load increase was presented differences in steam pressure and temperature between main and auxiliary steam flow streams. Energy power of the auxiliary flow stream is higher than energy power of the main flow stream only at the lowest steam system loads after which main flow stream takes over primacy at middle and high steam system loads. Cumulative auxiliary energy flow stream was divided on energy flow streams to each auxiliary device and energy power consumption of each auxiliary device was also investigated throughout number steam system loads. Analysis of steam production from marine steam generators presented in this paper provides insight into the operation dynamics of the entire steam propulsion system.

Sensitivity Analysis on Neural Network Algorithm for Primary Superheater Spray Modeling

ABSTRACTNonlinear, large inertia with long dead time is always associated with the main steam temperature parameter in coal fired power plant. Successful control of the main steam temperature within ±2°C of its setpoint is the ultimate target for coal-fired power plant operators. Two of the most common main steam temperature circuit are primary superheater spray and secondary superheater spray. Various methods were used to model the primary superheater spray control valve opening, and the neural network remains one of the most popular choices among researchers. It remains inconclusive which neural network algorithm types, setup, number of layers, and training algorithm will give the best result. As such, the paper shows the best setup for the neural network algorithm based on sensitivity analysis methodology for one hidden layer. The inputs selected for the neural network are generator output, main steam flow, total spray flow, and secondary superheater outlet steam temperature, while the output selected is primary spray flow control valve opening.

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

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%.