Fuzzy model representation of thermosyphon solar water heating system

Kishor, Nand; Das, Mihir Kr.; Narain, Anirudha; Ranjan, Vibhaw Prakash

doi:10.1016/j.solener.2010.03.002

Cited by 21 publications

(8 citation statements)

References 17 publications

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“…Finally, it tends to be concluded that the MFLPID structure controlling can be extensively decreased the energy consumption of system. A few results have affirmed the benefit of the fuzzy controller in reducing the power consumption [30,31,32].…”

Section: Performance Of the Actuatorsmentioning

confidence: 99%

Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house system

Lahlouh

Rerhrhaye

Elakkary

et al. 2020

Heliyon

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Broiler house systems are operated for the primary purpose of providing the appropriate conditions suitable to have a significant efficiency of animal production. The major environmental conditions in the poultry building are controlling the hygro-thermal parameters (temperature and relative humidity) and contaminant gases (NH 3 , CO 2). In this paper, a poultry house prototype is monitored and controlled using the Supervisory Control and Data Acquisition (SCADA) tool like LabVIEW. A full prototype is designed and an efficient hybrid control strategy is implemented to control in real-time the poultry house climate. In the suggested approach, a Multi-Input Multi-Output (MIMO) fuzzy logic controller (FLC) is combined with a proportional, integral, derivative (PID) controller tuned by fuzzy rules. The proposed method, fuzzy logic, and On/Off controllers were tested by experimental measures and studies in a prototype model over 30 days during hot climates. The comparison results showed that the root mean square error of temperature and relative humidity response with the MFLPID controller (0.8 C, 1.34%) were lower than that of FLC (1.16 C, 1.86%) and On/Off controller (2.09 C, 3.08%). The mean value of CO 2 concentration with MFLPID (2461 ppm) was lower than that of FLC (3294 ppm) and On/Off controller (3624 ppm). However, the mean value of NH 3 concentration was limited in small value (<5 ppm) for all controllers. The performance of the daily weight gained by the chickens for the MFLPID system was found to be 97%, which is higher than that of FLC (88%) and On/Off (80%). The energy consumption of the actuators can be saved at 43% and 14% with MFLPID compared to the On/Off and fuzzy controllers. These results indicate that the proposed control strategy is more efficient in the application of the poultry farming sector.

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Section: Performance Of the Actuatorsmentioning

confidence: 99%

Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house system

Lahlouh

Rerhrhaye

Elakkary

et al. 2020

Heliyon

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“…They reported that total energy saving in buildings (including heating, cooling and lighting) with fuzzy system was 36.8% lower than that of on/off system. Also, reducing energy consumption by fuzzy controller was reported by Javadikiya (2010), Kolokotsa (2003), Wang et al (2008), Kishor et al (2010), and Dounis and Caraiscos (2008). Also, for example, the control signals for ventilation fan (in one random hour) for on/off and fuzzy controllers are shown in Fig.…”

Section: Performance Of Actuatorsmentioning

confidence: 88%

Comparison of fuzzy and on/off controllers for winter season indoor climate management in a model poultry house

Mirzaee‐Ghaleh

Omid

Keyhani

et al. 2015

Computers and Electronics in Agriculture

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“…The population of the world is increasing day by day. Accordingly, the demand for electricity and fuel is rising [20]. As energy, diesel, petrol, and coal from crude oil are used.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Smart Hybrid Solar Water Heater Erection Model to Extract Maximum Energy

Bharathi

Sripriya

Muthuraj³

et al. 2022

International Journal of Photoenergy

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Currently, we are trying to get electricity in alternative ways. Many solar powered water heaters have come up to use water heaters. However, these tools are not 100 percent fully effective. The device we have manufactured is an automatic device that runs in the direction of sunlight. The device runs automatically in the morning facing east and in the evening facing west. In this instrument, the defective one-inch tube lamp and the three-quarter-inch tube lamp are put together and connected in series. In this paper, a smart deep learning model was proposed to improve the performance of the solar water heater. The gap between the tube lights is filled with methane gas, and the tube inside is filled with water. The water thus filled is heated by sunlight. Methane gas acts as a fast conductor of solar heat. An electronic control device is placed to determine the temperature of the hot water and to expel the hot water. This device can heat at least 10 liters of water in 15 minutes. Increasing the number of incandescent tube lights can heat up a large amount of water when this device is set up, or it can be designed by replacing tube lights with a series of large glass tubes using the same technology. This tool can be manufactured at low cost so that people from all walks of life can use it.

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Fuzzy model representation of thermosyphon solar water heating system

Cited by 21 publications

References 17 publications

Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house system

Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house system

Comparison of fuzzy and on/off controllers for winter season indoor climate management in a model poultry house

Deep Learning-Based Smart Hybrid Solar Water Heater Erection Model to Extract Maximum Energy

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