The application of charge balance transmission technology in real time data monitoring system of the power plant

Author(s):  
Jian Wang ◽  
Yuan Li ◽  
Jingli Kang ◽  
Chuanfu Liu
2014 ◽  
Vol 595 ◽  
pp. 175-179
Author(s):  
Chuan Wei Zhang ◽  
Ming Yu Wang

The monitoring information of the coal mine trackless rubber tyre electric vehicle is analyzed and researched. The hardware and software of real-time data monitoring system electric vehicle is designed based on the TMS320F2812 DSP chip and LCD module MS12864. The coal mine trackless rubber tyre electric vehicle real-time data monitoring is achieved.


2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Gao Li ◽  
Hongtao Li ◽  
Yingfeng Meng ◽  
Na Wei ◽  
Chaoyang Xu ◽  
...  

In this work, a methodology for characterizing reservoir pore pressure and permeability during underbalanced drilling of horizontal wells was presented. The methodology utilizes a transient multiphase wellbore flow model that is extended with a transient well influx analytical model during underbalanced drilling of horizontal wells. The effects of the density behavior of drilling fluid and wellbore heat transfer are considered in our wellbore flow model. Based on Kneissl’s methodology, an improved method with a different testing procedure was used to estimate the reservoir pore pressure by introducing fluctuations in the bottom hole pressure. To acquire timely basic data for reservoir characterization, a dedicated fully automated control real-time data monitoring system was established. The methodology is applied to a realistic case, and the results indicate that the estimated reservoir pore pressure and permeability fit well to the truth values from well test after drilling. The results also show that the real-time data monitoring system is operational and can provide accurate and complete data set in real time for reservoir characterization. The methodology can handle reservoir characterization during underbalanced drilling of horizontal wells.


2021 ◽  
Vol 9 (2) ◽  
pp. 27-36
Author(s):  
Sheikh Hasib Cheragee ◽  
Nazmul Hassan ◽  
Sakil Ahammed ◽  
Abu Zafor Md. Touhidul Islam

We have Developed an IoT-based real-time solar power monitoring system in this paper. It seeks an opensource IoT solution that can collect real-time data and continuously monitor the power output and environmental conditions of a photovoltaic panel.The Objective of this work is to continuously monitor the status of various parameters associated with solar systems through sensors without visiting manually, saving time and ensures efficient power output from PV panels while monitoring for faulty solar panels, weather conditionsand other such issues that affect solar effectiveness.Manually, the user must use a multimeter to determine what value of measurement of the system is appropriate for appliance consumers, which is difficult for the larger System. But the Solar Energy Monitoring system is designed to make it easier for users to use the solar system.This system is comprised of a microcontroller (Node MCU), a PV panel, sensors (INA219 Current Module, Digital Temperature Sensor, LDR), a Battery Charger Module, and a battery. The data from the PV panels and other appliances are sent to the cloud (Thingspeak) via the internet using IoT technology and a Wi-Fi module (NodeMCU). It also allows users in remote areas to monitor the parameters of the solar power plant using connected devices. The user can view the current, previous, and average parameters of the solar PV system, such as voltage, current, temperature, and light intensity using a Graphical User Interface. This will facilitate fault detection and maintenance of the solar power plant easier and saves time.


Author(s):  
G. Hariharan ◽  
B. Kosanovic

The ability of modern power plant data acquisition systems to provide a continuous real-time data feed can be exploited to carry out interesting research studies. In the first part of this study, real-time data from a power plant is used to carry out a comprehensive heat balance calculation. The calculation involves application of the first law of thermodynamics to each powerhouse component. Stoichiometric combustion principles are applied to calculate emissions from fossil fuel consuming components. Exergy analysis is carried out for all components by the combined application of the first and second laws of thermodynamics. In the second part of this study, techniques from the field of System Identification and Linear Programming are brought together in finding thermoeconomically optimum plant operating conditions one step ahead in time. This is done by first using autoregressive models to make short-term predictions of plant inputs and outputs. Then, parameter estimation using recursive least squares is used to determine the relations between the predicted inputs and outputs. The estimated parameters are used in setting up a linear programming problem which is solved using the simplex method. The end result is knowledge of thermoeconomically optimum plant inputs and outputs one step ahead in time.


2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.


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