scholarly journals An automatic energy-saving and thermal monitoring/controlling system for a pond

2017 ◽  
Vol 123 ◽  
pp. 00021
Author(s):  
Ching-Chien Cheng ◽  
Min-Chie Chiu ◽  
Che-Min Chiu ◽  
Huang-Kuang Kung ◽  
Chin-Yu Wang ◽  
...  
2014 ◽  
Vol 9 (3) ◽  
pp. 398-408
Author(s):  
Woonou Cha ◽  
Wan Myung Chun ◽  
Byoung Soo Kim ◽  
Miyoung Choi ◽  
Jinman Kim

To construct an energy saving airflow-controlling system for Doyang sewage treatment plant, the factors affecting airflow of the influent was analyzed in this study. This research analyzed the operation data of Doyang sewage treatment plant for 912 days. As a result, the key factors deciding the optimum airflow were found to be temperature, F/M ratio, the loading rate of BOD5 and T-N of the influent. Among the factors, the temperature of the influent had the most decisive effect on the aeration volume. The result showed that an increase of 1 °C of the influent requires 45.3 m3/h airflow. Since the factors affected by seasons like flow rate, F/M ratio and MLSS affect airflow required of blowers, and the change of temperature is considered to intensify the change of airflow even more. Therefore, it is preferable to consider flow rate, F/M ratio, MLSS and water temperature altogether than considering only one factor when deciding airflow of blowers. The results of this research can be utilized as indicators when designing energy saving system for sewage treatment plants.


2022 ◽  
Vol 12 (1) ◽  
pp. 420
Author(s):  
Chun-Te Lee ◽  
Liang-Bi Chen ◽  
Huan-Mei Chu ◽  
Che-Jen Hsieh ◽  
Wei-Chieh Liang

Reducing residential and industrial electricity consumption has been a goal of governments around the world. Lighting sources account for a large portion of the whole energy/power consumption. Unfortunately, most of the existing installed lighting systems are ancient and have poor energy efficiency. Today, many manufacturers have introduced light-controlling systems into the current market. However, existing light controlling systems may not be successfully applied to buildings, streets, and industrial buildings due to high costs and difficult installation and maintenance. To combat this issue, this article presents an easy-to-install, low-cost, Master-Slave intelligent LED light-controlling system based on Internet of Things (IoT) techniques. The benefit of using the proposed system is that the brightness of the LED lights in the same zone can be changed simultaneously to save in energy consumption. Furthermore, the parameters of the LED lights can be directly set. Moreover, the related data are collected and uploaded to a cloud platform. In this article, we use 15 W T8 LED tubes (non-induction lamps) as a case study. When the proposed system is installed in a zone with few people, the energy-saving rate is as high as 90%. Furthermore, when 12 people pass by a zone within one hour, its energy-saving rate can reach 81%. Therefore, the advantages of using the proposed system include: (1) the original lamp holder can be retained; (2) no wiring is required; and (3) no server is set up. Moreover, the goal of energy saving can also be achieved. As a result, the proposed system changes the full-dark mode of the available sensor lamp to the low power low-light mode for standby. Further, it makes the sensor lamps in the same zone brighten or low-light way simultaneously, which can quickly complete large-scale energy-saving and convenient control functions of intelligent LED lighting controlling system.


2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.


2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.


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