Early Warning Method for Power Station Auxiliary Failure Considering Large-Scale Operating Conditions

2019 ◽  
Author(s):  
Yang Tingting ◽  
Bai Yang ◽  
Ge Weichun ◽  
Luo Huanhuan ◽  
Zhou Guiping ◽  
...  
Keyword(s):  
Early Warning ◽  
Large Scale ◽  
Operating Conditions ◽  
Power Station

Architecture and Key Technologies of Intelligent Dispatching Based on Situational Awareness

2013 ◽  
Vol 448-453 ◽  
pp. 2259-2265
Author(s):  
Sheng Chun Yang ◽  
Bi Qiang Tang ◽  
Jian Guo Yao ◽  
Feng Li ◽  
Yi Jun Yu ◽  
...  
Keyword(s):  
Decision Making ◽  
Risk Analysis ◽  
Human Computer Interaction ◽  
Early Warning ◽  
Large Scale ◽  
Situational Awareness ◽  
Power Grid ◽  
Operating Conditions ◽  
Knowledge Mining ◽  
Grid Operation

With the construction of UHV power grid, integration of large-scale renewable clean energy, and large-scale energy base putting into operation, the power grid dispatching faced with more and more complex challenges. On the basis of existing research results, architecture of intelligent dispatching based on situation awareness is proposed, so as to accurately achieve prevention and control of the power system. The shortcomings of traditional dispatching mode are analyzed firstly, and the concepts and characterization approaches of grid situational awareness and operation state trajectory of power grid are then introduced. The overall objective of intelligent dispatching is presented, including data processing and integrated knowledge mining, predictive perception of grid operation, risk analysis and comprehensive early warning, so as to achieve "automatic cruise under normal operating conditions, automatic navigation under abnormal operating conditions ". The functional framework of intelligent dispatching is also proposed in details, including four major aspects of the perception and forecasts, risk analysis, decision-making support, and automatic control, as well as three supporting functions such as post-assessment of dispatching, trajectory index calculation, and human-computer interaction (HCI).Technical innovations to support automatic intelligent dispatching are discussed and organised in three levels, i.e. perception, comprehension and projection. The breakthroughs are: construction of index system, trajectory recognition based on massive information and knowledge mining, trajectory projection taking into accounts the uncertainties, online risk assessment and early warning, power grid intelligent decision-making support, automatic coordination of grid operation control, online assessment, natural human-computer interaction mode, and etc... These are the future research areas of automatic intelligent dispatching.

scholarly journals Wind – Hydro Coordination for Enhanced Worth of Wind Power and Potentials in Karnataka State of India

2019 ◽  
Vol 8 (9S2) ◽  
pp. 23-29
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Large Scale ◽  
Operating Conditions ◽  
Power Station ◽  
Hydro Power ◽  
Wind Power Station ◽  
Simulink Model ◽  
Wind Power Systems ◽  
Scale Grid

The augmented demand for the power across the globe has resulted in the growth of non-conventional sources of energy as an appendage to the conventional sources. The large scale grid connected wind power systems have become one of the better alternatives among renewable energy based power generation methods. However the intermittency of wind power is one of the major limitations in the effective harvesting of energy leading to its reduced worth. Several methods are proposed and implemented to overcome the issue of wind power intermittency. In this paper a coordinated approach between wind and dispatchable and geographically proximal hydro power station is proposed to enhance the value of wind power. A MATLAB SIMULINK model of a wind power station is developed. Three potential sites with the conducive operating conditions for the implementation of the proposed scheme have been considered for the analysis. The results obtained are correlated to the enhanced worth of wind power.

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>

scholarly journals Heat Transfer in Rotating Serpentine Passages With Trips Normal to the Flow

1992 ◽  
Vol 114 (4) ◽  
pp. 847-857 ◽  
Author(s):  
J. H. Wagner ◽  
B. V. Johnson ◽  
R. A. Graziani ◽  
F. C. Yeh
Keyword(s):  
Heat Transfer ◽  
Turbine Blade ◽  
Large Scale ◽  
Flow Direction ◽  
Operating Conditions ◽  
Transfer Model ◽  
Transfer Coefficients ◽  
Flow Equations ◽  
Turbine Blade Cooling ◽  
Heat Transfer Coefficients

Experiments were conducted to determine the effects of buoyancy and Coriolis forces on heat transfer in turbine blade internal coolant passages. The experiments were conducted with a large-scale, multipass, heat transfer model with both radially inward and outward flow. Trip strips on the leading and trailing surfaces of the radial coolant passages were used to produce the rough walls. An analysis of the governing flow equations showed that four parameters influence the heat transfer in rotating passages: coolant-to-wall temperature ratio, Rossby number, Reynolds number, and radius-to-passage hydraulic diameter ratio. The first three of these four parameters were varied over ranges that are typical of advanced gas turbine engine operating conditions. Results were correlated and compared to previous results from stationary and rotating similar models with trip strips. The heat transfer coefficients on surfaces, where the heat transfer increased with rotation and buoyancy, varied by as much as a factor of four. Maximum values of the heat transfer coefficients with high rotation were only slightly above the highest levels obtained with the smooth wall model. The heat transfer coefficients on surfaces where the heat transfer decreased with rotation, varied by as much as a factor of three due to rotation and buoyancy. It was concluded that both Coriolis and buoyancy effects must be considered in turbine blade cooling designs with trip strips and that the effects of rotation were markedly different depending upon the flow direction.

Comparison of the efficiency of large-scale ceramic and membrane aeration systems with the dynamic off-gas method

2002 ◽  
Vol 46 (4-5) ◽  
pp. 317-324 ◽  
Author(s):  
J.A. Libra ◽  
A. Schuchardt ◽  
C. Sahlmann ◽  
J. Handschag ◽  
U. Wiesmann ◽  
...  
Keyword(s):  
Large Scale ◽  
Operating Conditions ◽  
Air Distribution ◽  
Energy Costs ◽  
Dissolved Oxygen Concentration ◽  
Membrane Aeration ◽  
Aeration System ◽  
Oxygen Transfer Efficiency ◽  
Aeration Efficiency ◽  
Period Measurement

The aeration systems of two full-scale activated sludge basins were compared over 2.5 years under the same operating conditions using dynamic off-gas testing. Only the material of the diffuser was different, membrane vs. ceramic tube diffusers. The experimental design took the complexity and dynamics of the system into consideration. The investigation has shown that, although the membrane diffusers have higher initial standard oxygen transfer efficiency (SOTE) and standard aeration efficiency (SAE), these decreased over time, while the SAE of the ceramic diffusers started lower, but increased slightly over the whole period. Measurement of air distribution in the basins along with dissolved oxygen concentration profiles have provided important information on improving process control and reducing energy costs. The results show that dynamic off-gas testing can effectively be used for monitoring the aeration system and to check design assumptions under operating conditions. The information can be used to improve the design of new aeration systems or in retro-fitting existing basins.

scholarly journals Hardware-in-the-loop simulation of wave energy converters based on dielectric elastomer generators

Meccanica ◽  
2021 ◽  
Vol 56 (5) ◽  
pp. 1223-1237
Author(s):  
Giacomo Moretti ◽  
Andrea Scialò ◽  
Giovanni Malara ◽  
Giovanni Gerardo Muscolo ◽  
Felice Arena ◽  
...  
Keyword(s):  
Wave Energy ◽  
Large Scale ◽  
Low Cost ◽  
Test Site ◽  
Dielectric Elastomer ◽  
Operating Conditions ◽  
Polymer Materials ◽  
Hardware In The Loop ◽  
Wave Energy Converters ◽  
Energy Converters

AbstractDielectric elastomer generators (DEGs) are soft electrostatic generators based on low-cost electroactive polymer materials. These devices have attracted the attention of the marine energy community as a promising solution to implement economically viable wave energy converters (WECs). This paper introduces a hardware-in-the-loop (HIL) simulation framework for a class of WECs that combines the concept of the oscillating water columns (OWCs) with the DEGs. The proposed HIL system replicates in a laboratory environment the realistic operating conditions of an OWC/DEG plant, while drastically reducing the experimental burden compared to wave tank or sea tests. The HIL simulator is driven by a closed-loop real-time hydrodynamic model that is based on a novel coupling criterion which allows rendering a realistic dynamic response for a diversity of scenarios, including large scale DEG plants, whose dimensions and topologies are largely different from those available in the HIL setup. A case study is also introduced, which simulates the application of DEGs on an OWC plant installed in a mild real sea laboratory test-site. Comparisons with available real sea-test data demonstrated the ability of the HIL setup to effectively replicate a realistic operating scenario. The insights gathered on the promising performance of the analysed OWC/DEG systems pave the way to pursue further sea trials in the future.

Sign in / Sign up

Export Citation Format

Share Document