Optimization of Condenser Vacuum Based on Neural Network and SA-BBO

2013 ◽  
Vol 860-863 ◽  
pp. 676-679
Author(s):  
Lei Zhang ◽  
Ya Lan Ye ◽  
Feng Qi Si
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Hybrid Algorithm ◽  
Market Value ◽  
Operating Conditions ◽  
Steam Turbines ◽  
Water Pump ◽  
Characteristic Analysis ◽  
Circulating Water ◽  
Save Energy

The optimization of condenser vacuum is significant to improve efficiency and save energy in the power plant. Taking a 600MW unit as the research object, the condenser vacuum optimization model was established synthetically based on neural network, simulated annealing and biogeography optimization hybrid algorithm (SA-BBO). Circulating pumps power, slight increase of turbine power as well as the market value difference between coal and electric were included in the model. The objective function of the model is to maximize the profit of the power plant. The most effective combinations of the condenser vacuum and the circulating water pump were calculated eventually in different operating conditions by using characteristic analysis of variable condenser conditions. In a certain condition, running three circulating pumps for two steam turbines instead of two pumps can make the condenser vacuum reduce 0.49kPa, and increase revenue 110.2 yuan/h.

Study on 3-D Flow Field of Concrete Volute Conduit of Circulating Water Pump in Nuclear Power Plant

2011 ◽  
Vol 99-100 ◽  
pp. 350-353
Author(s):  
Xiao Bing Sun ◽  
Xu Bin Qiao
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Stokes Equations ◽  
Three Dimensional ◽  
Gradual Change ◽  
Water Pump ◽  
Pump System ◽  
Circulating Water ◽  
Operating Modes

As the largest unit capacity of nuclear power plant at present, the flow conduit of circulating water pump in EPR1750 nuclear power plant is a volute conduit, which is a cast-in-situ conceret structure with complexly gradual change cavity. Therefore, the hydraulic efficiency of circulating water pump is not only related with the design of pump leaves, but also closely related to the design of volute and the complicated spatial type of intake and outtake conduits. With the pump leaves and the intake and outtake conduits of conceret volute as the research model, based on computational fluid dynamics (CFD)and the three dimensional Reynolds averaged Navier-Stokes equations, an analytic model suitable for computation is established to simulate the three-dimensional steady flow in the whole pumping system under different operating modes. By use of the commercial fluid-computation softer ANSYS, the distribution of basic physic quantities in the fluid field inside the pump and the conduits is obtained. The analysis and prediction of the performance of pump system are made, and the spatial type design of intake and outtake conduits is evaluated. The calculation results can be referenced to improve the design of pump systems in the similar projects.

scholarly journals Failure Analysis of Shaft Circulating Water Pump (CWP) used in Power Plant

2018 ◽  
Vol 159 ◽  
pp. 02027 ◽  
Author(s):  
Abdul Hamid ◽  
Sri Nugroho ◽  
Gunawan Dwi Haryadi ◽  
Khaeroman
Keyword(s):  
Stainless Steel ◽  
Chemical Composition ◽  
Power Plant ◽  
Failure Analysis ◽  
Fatigue Cracking ◽  
Hardness Test ◽  
Water Pump ◽  
Circulating Water ◽  
Pump Shaft ◽  
Sem Test

Pump shafts are generally exposed to the liquid being pumped either on a continual basis or at certain locations along the length of the shaft. The shaft material is austenitic stainless steel, description ASTM AU 79 TY 316. The purpose of this study is to determine the failure of the water pump shaft used in the power plant. Metallography is the study of structure metal shaft can used as a means for CWP metal pelleting (Circulating Water Pump), for the purpose of damaged or deeply degraded areas. SEM test is used to know the beginning of the crack (crack initiation). EDS test is used to chemical composition and Vikers hardness test is also used to know the hardness material. These three tests to support in analyzing the failure of the pump shaft. The conclusion of this failure analysis is the shaft material has porosity. Fatigue cracking comes from the outer surface area.

scholarly journals The design of a circulating water pump for a power plant based on CFD

2020 ◽  
Vol 194 ◽  
pp. 03026
Author(s):  
Wanbo Chen
Keyword(s):  
Power Plant ◽  
Guide Vane ◽  
Flow State ◽  
Water Pump ◽  
Mixed Flow ◽  
High Discharge ◽  
Circulating Water ◽  
Cfd Method ◽  
Flow Pump

Because of the head and efficiency of the circulating water pump in a power plant could not satisfy application requirement, the guide vane and impeller were optimized according to the CFD method. The optimization of the mixed-flow pump effectively improves the flow state at the design and high discharge conditions. Finally, the CFD results show that the head is improved by 3.49m and the efficiency is improved by 3.16% after the optimization, which has met the use requirements.

Security Reliability Analysis of Circulating Water Pump House Pit Excavation of Chen Jiagang Power Plant

2013 ◽  
Vol 353-356 ◽  
pp. 229-234
Author(s):  
Jian Pan ◽  
Xiao Yong Ding
Keyword(s):  
Power Plant ◽  
Taylor Series ◽  
Feedback System ◽  
Successful Implementation ◽  
Series Method ◽  
Water Pump ◽  
Foundation Pit ◽  
Circulating Water ◽  
Taylor Series Method ◽  
Pump House

The circulating water pump house pit excavation of Chen Jiagang power plant is characterized with complex geological and hydrological condition, high water level, and weakly permeable silt layer within the scope of pit excavation. Based on design and construction principles of safety, feasibility, rationality and economy, different foundation pit dewatering and support programs were analyzed and compared, a excavation method featured with well dewatering and steel pipe soil nails hanging net and stakes was elaborately designed, and establish a monitoring feedback system. And in the base of mathematical statistics, Taylor series method is used to analyze the reliability probability problems of excavation slope stability analysis. The successful implementation of the project indicated that the design and parameters of Chen Jiagang power plant circulating water pump house pit excavation is feasible, and Taylor series method combined with conventional safety factor is able to analyze the influence of material parameters variation on the excavation of the slopes safety.

scholarly journals Economic Operation Analysis of Circulating Water Pump in a Power Plant

2019 ◽  
Vol 118 ◽  
pp. 02067
Author(s):  
Shuai Chen
Keyword(s):  
Power Plant ◽  
Flow Rate ◽  
Test Results ◽  
Water Pump ◽  
Circulating Water ◽  
Operation Analysis ◽  
Economic Operation ◽  
Shaft Power ◽  
Technical Specifications

This paper calculates the main indexes of circulating water pump in a power plant, such as flow rate, head, shaft power and efficiency, and shows the test results. The results reach the guaranteed value of design technical specifications.

scholarly journals ANALISA PENGOPERASIAN 1 CWP DAN 2 CWP PADA COOLING WATER SYSTEM PLTU ASAM ASAM UNIT 4

2019 ◽  
Vol 4 (2) ◽  
pp. 37-52
Author(s):  
Juni Eko Hartanto ◽  
Mastiadi Tamjidillah
Keyword(s):  
Power Plant ◽  
Electric Power ◽  
Daily Life ◽  
Water System ◽  
Cooling Water ◽  
Electrical Energy ◽  
Water Pump ◽  
Full Load ◽  
Circulating Water ◽  
Acid Acid

Electric power is used to support daily life, therefore electrical energy must be continually developed considering the increasing need for this energy. Therefore it is necessary to do preventive, corrective maintenance and efforts to optimize the generating unit such as savings in the production process, one of which is by analyzing the operation of a Circulating Water Pump CWP at the Unit 4 Acid-Acid Power Plant. The formulation of the problem in this study is that in the manufacturer's design for 65 MW full load 2 CWP pumps are needed, this can be seen from the pump specification data, but in fact with only a Circulating Water Pump CWP can produce a full load of 65 MW.

Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

2019 ◽  
Author(s):  
Ryther Anderson ◽  
Achay Biong ◽  
Diego Gómez-Gualdrón
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Molecular Simulation ◽  
Large Scale ◽  
Learning Model ◽  
Operating Conditions ◽  
Small Subset ◽  
Screening Methods ◽  
Large Set ◽  
Metal Organic

<div>Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation, such as grand canonical Monte Carlo (GCMC), has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our neural network only on alchemical species, represented only by their geometry and force field parameters, and used this neural network to predict the loadings of real adsorbates. We focused on predicting room temperature adsorption of small (one- and two-atom) molecules relevant to chemical separations. Namely, argon, krypton, xenon, methane, ethane, and nitrogen. However, we also observed surprisingly promising predictions for more complex molecules, whose properties are outside the range spanned by the alchemical adsorbates. Prediction accuracies suitable for large-scale screening were achieved using simple MOF (e.g. geometric properties and chemical moieties), and adsorbate (e.g. forcefield parameters and geometry) descriptors. Our results illustrate a new philosophy of training that opens the path towards development of machine learning models that can predict the adsorption loading of any new adsorbate at any new operating conditions in any new MOF.</div>

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