Laboratory-scale reactor Research Papers

A laboratory scale IoT-based measuring of the solar photovoltaic parameters

2024, International Journal of Reconfigurable and Embedded Systems (IJRES)

Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment,... more

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Undershot Waterwheel Analysis Comparing Three Variations of the Laboratory Scale

by Agustina Kasa'

2024, Proceedings of the 4th Annual Conference of Engineering and Implementation on Vocational Education, ACEIVE 2022, 20 October 2022, Medan, North Sumatra, Indonesia

A waterwheel is a technology that has been used by people in rural areas to lift and distribute water to a higher base than water sources. The waterwheel has a relatively simple design, large diameter, high speed and high torque. However,... more

Figure 2. Laboratory scale undershot waterwheel model The design of the water channel on the undershot waterwheel can be seen in the imagt below:

After conducting experiments and data co ‘rom the research data of the water wheel und rariety of b ised was 8 and each measurement was taken 7 02 ms/d 0 d)=1m;1 ades (flat, curved and bent). In the .14 and to support data collection, 1 lection, the data obtained are then processed. ershot, data collection was carried out with a data collection process, the number of buckets times. The water height is varied starting from is known that the diameter of the waterwheel The radius of the waterwheel(r)= 0.5 m; The width of the blade of the waterwheel 1) = 0.07 m; Waterwheel blade height(t) = 0.04 m;length Bucket (p) = 0.11 m;diameter 3ucket(d) = 0.007 m; distance between blades n; accelera ion due to gravity (g) = 9.81 m/s’; t) = 0.21 m; the width of the wheel (1) = 0.07 Time (t)= 2 s; Bucket volume (Vb) = 0.00128 n?; Volume (V) = 0.0189 m?; wheel rotational speed (n) = 1.467 put/s; Channel width (1) = 15m; Wh eel radius (r) = 0.5 m Figure 3. Graph of the relationship between (a) the flow of water to the rotation of the waterwheel; (b) the flow rate of water to the ratio between efficiency and flow of water to the power of the waterwheel; (c) the flow rate of the water to the water discharge in the bucket; (d) water flow rate on water wheel efficiency

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A Data Acquisition System for Solar PV Module with Variable Load

by Gour Mazumder

2023, The Dhaka University Journal of Science

This paper describes the design, development and performance of a locally developed data acquisition system for solar PV module with variable load. The system can automatically change the operating point of a PV module and acquire the... more

Fig. 2. Signal Conditioning Circuit for Vpy f the active load would have been directly connected across the PV output, the short circuit current couldn’t be achieved, because the active load has some resistance even at hard saturation. Hence, a high ampere PS (power supply) has been used in series with the PV Module. As the active load increases the output current of the PV module, the current from the PS also increases. When the load current equals the sc of the PV module, Vpy, becomes zero. This Vpy is a differential voltage (difference of voltage between points A and B of Fig. 1), but the ADC needs a common mode voltage (with respect to ground). To do this, a differential voltage amplifier has been designed which is given below. The function of this circuit is two-fold. One is to convert the differential voltage Vpy into common mode voltage and to attenuate the high module voltage into a suitable value for

Fig. 1. Block diagram of the developed system Uno is the main controlling unit, the Current Sensing unit converts the current into voltage, the Variable Load (Active Load) changes the output current of the PV module and the Signal Conditioning unit provides all necessary preprocessing of all signals. In fact, the signal conditioning unit has many subunits. The design method of every section of the system is described in the following subheadings.

To measure the output current of the module, a current sensor, ACS712, has been used. This device uses Hall sensor and produces bipolar output voltage depending on the current direction. The output of this sensor has been processed by a conditioning circuit shown in Fig. 3. This circuit shifts the operating range of the current sensor from bipolar (-2.5V to +2.5V) to unipolar (OV — 5V). The gain of this circuit can be adjusted from 9 (nine) to 18 (eighteen) using S; and S, switches. This arrangement can increase o1 decrease the number of acquired data even for the same value of the current input. The output of this circuit is fed to channel-1 of A/D converter’. Fig. 3. Signal Conditioning Circuit for the Current Sensor Active Load

Fig. 5. Staircase voltage generator As a digital-to-analog converter, DAC0808IC has been used. It is a current summing DAC; hence a current to voltage converter (CVC) has been used at the output. The gain of the CVC can be varied by changing the value of the feedback resistor. Here, two 270Q resistors (Rg & R7) have been used as the feedback resistor (Fig. 5). R7 can be connected or disconnect by $3. Thus when S$; is open, a staircase with large step size and when 8; is closed, a staircase with smaller step size will be produced. An 8-bit ripple counter has been developed by connecting two 74L8293 ICs. The MSB output of the first counter works as the CLK input to the second counter and the CLK of the first counter comes from the controlling unit. The MR (Master Reset) inputs of the ICs are connected in parallel and used by the controlling unit as the RESET input. The 8- bit output of the counter has been applied to the DAC.

and the bit-size of the counter. To get precise data from the PV module the step-size should be as small as possible (Here 5mV). With an 8-bit counter, the maximum voltage will be 1.275V(5mV 255). Since the V; of the MOSFET is 4.5V; the staircase voltage cannot start the conduction of PV load current. This problem has been overcome by adding 4.5V at the output of the staircase as shown in the Fig. 7. The amount of threshold voltage at zero count can be changed by the potentiometer Rg. Fig. 7. Threshold voltage producing circuit

Fig. 8. Staircase voltage before and after using the Circuit of Fig. 7 The driver program of the whole system has been developed using Arduino IDE and uploaded into the Arduino board. The flowchart of the program is shown in Fig. 9. At the beginning of the data acquisition process of the PV module, the program sends a RESET pulse to the counter of the staircase generator, so that the active load turns OFF. This will give the open circuit condition of the PV module. Then it will read the module output current (Ipy) and the terminal voltage (Vpy). Ten samples of each variable are taken and averaged. The average values of Ipy and Vpy are assigned to the variables Ip, and Vp, and sent to the computer. Then, the program sends a clock pulse to the counter of the staircase generator so that the load current of the PV module increases by one step. Again, the value of Ip, and Vp, are determined and sent to the computer. This process is

All of the subsections described above have been interconnected in a PCB and a 10A 12V power supply has been made and incorporated into the system. The photograph of the complete system is shown in Fig.10. IV. Performance Study of the System

continued until the Counter recycles (Count=255) or Vpa becomes zero. Then the process stops sending another RESET pulse to the staircase generator. Fig. 9. Flowchart of the program

Fig. 12. Graph for calibration of current sensor Fig. 11. Graph for calibration of current sensor

The same test has been done for another 50 Wp module. The obtained graph is shown in Fig. 14 and the results are shown in Table II. Each of the graphs has been plotted by averaging every 10 raw data into a single data. From Table 1 and Table 2 it is found that the measured data are very close to the actual data.

appropriate positions of different resolution setting switches of the system have been set. Then the final test of the module has been done. The radiation level has been measured by a pyranometer and the area of the module has been measured manually. The acquired data have been converted using the conversion factor and plotted into a graph which is shown in Fig. 13. After calculating the data the following (Table I) results have been found.

Table 1. Parameters found for 30W p module

Table 2. Parameters found for the 50Wp module V. Conclusion

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A laboratory scale IoT-based measuring of the solar photovoltaic parameters

by Ahmad Raditya Cahya Baswara

2023, International Journal of Reconfigurable and Embedded Systems (IJRES)

Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment,... more

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Undershot Waterwheel Analysis Comparing Three Variations of the Laboratory Scale

by Atus Buku

2023, Proceedings of the 4th Annual Conference of Engineering and Implementation on Vocational Education, ACEIVE 2022, 20 October 2022, Medan, North Sumatra, Indonesia

A waterwheel is a technology that has been used by people in rural areas to lift and distribute water to a higher base than water sources. The waterwheel has a relatively simple design, large diameter, high speed and high torque. However,... more

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Undershot Waterwheel Analysis Comparing Three Variations of the Laboratory Scale

by BENYAMIN TANGARAN

2023, Proceedings of the 4th Annual Conference of Engineering and Implementation on Vocational Education, ACEIVE 2022, 20 October 2022, Medan, North Sumatra, Indonesia

A waterwheel is a technology that has been used by people in rural areas to lift and distribute water to a higher base than water sources. The waterwheel has a relatively simple design, large diameter, high speed and high torque. However,... more

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Smart building trend, role, and position: a systematic literature review

by Prasetya Saputra

2023, International Journal of Reconfigurable and Embedded Systems (IJRES)

Property growth, especially in high-rise buildings in developed and developing countries, has experienced a significant increase. The increasingly expensive resources and the development of information technology encourage the growth of... more

Figure 1. Features of smart building [5]

Figure 2. KPMG creating the building of the future through internet of things (loT) technology [6]

The next stage is to filter documents that have been cited by other authors with the number of citations per document above 3 citations. This is to provide confidence that the article has been proven to be known and cited by other authors. From this filter, 122 documents were found. Furthermore, from 122 documents, an abstract filter was carried out according to the writing theme regarding components, roles, and trends, obtained 78. The last filter sorted out the suitability of 78 documents from full-text and obtained 56 documents to be reviewed. The number of selected papers as many as 56 are papers published in the Scopus database according to the filter carried out with the criteria previously mentioned and based on the year of publication between 2018 and 2021. The graph of published papers per year can be seen in Figure 5. In 2018 there were 14 articles, in 2019 there were 21 articles which was the highest number in 4 years, in 2020 there were 16 articles and in 2021 there were only 5 articles that met the screening criteria according to Figure 4. The number of articles in 2021 the number decreased drastically possibly. This is due to the COVID-19 pandemic conditions around the world, so that a lot of research on smart buildings is expected because they cannot freely collect data, are limited to conducting interviews with respondents and there are lots of buildings or properties for their activities during the COVID-19 pandemic.

Figure 5. Number of articles from 2018-2021

Smart building trend, role and position: a systematic literature review (Prasetya Cahya Saputra) ne EE IIE lg EES sls aaeial diesen aaa aaa ee To see what components are contained in in smart building, the relationship between keywords is used and the keyword used is the author keyword contained in the 56 full-text documents reviewed. As a tool for mapping the keywords used in 56 full-text documents, the VOSviewer application [20] is used. This VOSviewer application can provide a view of the relationship between keywords from export files such as RIS and CSV. In this study, the file used is an imported file from the Scopus database in CSV format. Before the author keyword mapping process, improvements were made to combine several of the same keywords. In one article the author keyword wrote "internet of things" some wrote "IoT", the author combined if there were conditions such as to obtain keywords that were not duplicated.

Figure 7. The country where the smart building research is conducted 31 papers specifically mention the country where the research was carried out and 25 papers do not mention it, Figure 7. Of the 31 papers spread across 17 countries where smart building research was conducted, there are only 3 regions. Regions Europe and Central Asia, East Asia and Pacific and North America as ranked by the World Bank [76] most of them are countries with income levels at the “high income” and “upper middle income” levels and in Figure 8 it can be seen that there are 71% of countries that occupy the “high income” position and 23% of countries with “upper middle income” category and only 6% occupy the position as a country with the income category of "lower middle income". It means that the country where smart building is currently being researched is dominated by countries with a good economy and in terms of income, the country with a minimum level is "lower middle income".

‘igure 8. Category based on the income of the country where the smart building research is conducted

Figure 9. Category based on property type where the smart building research is conducted From the number of articles per property type, a graph is made to be able to see the percentage of the smart building research location grouping. The results of the percentage per property type can be seen in Figure 9. Research with the location of commercial building as much as 65%, namely there are 11 articles from 17 articles and residential property as much as 35% or 6 articles from 17 articles which inform the location of the smart building research.

Figure 10. Research discussion trends in smart building

Table 1. Keyword clustering using VOSviewer application The clustering of keywords above is based on the proximity between keywords. Keywords in the same color are closer together than keywords in different color clusters. Smart building is placed in cluster 5 with purple color, one cluster with building information management, demand response, and sensors. This provides information that smart buildings have various roles in the discussion on building information management, demand response, and sensors. In cluster 1 in red, there are the keywords heating, renewal energy and smart grid, meaning that there is a close relationship between the keywords in the discussion of heating, renewal energy and smart grid, which are closely related to artificial neural network (ANN), big data and machine learning. The green color represents cluster 2 in which some keywords play a role and are close together, namely building management system, deep learning, energy harvesting, fault-tolerant control, smart city.

Table 4. Smart building research locations by property type The grouping of research location data based on the type of property in Figure 9 displays information with 2 types of large groups, namely residential and commercial shown in Figure 8. Research using non- commercial properties as much as 41% and commercial properties as much as 59%. Residential properties consist of residential/apartment/family house has 6 papers and government building has 1 paper. As for commercial property, there are 3 types, namely hotels with | paper, campus/school building with 6 papers, and office building with 4 papers.

Table 5. Grouping of keywords in smart building articles

Smart building trend, role and position: a systematic literature review (Prasetya Cahya Saputra)

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A laboratory scale IoT-based measuring of the solar photovoltaic parameters

by Anggit Pamungkas

2022, International Journal of Reconfigurable and Embedded Systems (IJRES)

Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment,... more

Figure 2. Single diode model PV module equivalent circuit where STC-Ip;, is the photocurrent generated under standard test conditions, STC-J) is the saturation current of the diode, R, is the series resistance, Rg is the shunt resistance, and ideally diode factor-n which can be estimated by the Bisection and Lambert-W methods [31]. In this system, the PV panel has a voltage of 18 V with an output power of 50 W. The PV panel is connected to the input of a buck-boost DC-DC converter-type power conversion device. The converter is embedded in a solar charge control (SCC) device, which is then connected to the load. If the PV panel generates sufficient power, the SCC will regulate the power supplied to the load and supply power to charge the battery while it is not fully charged. However, if the PV panel does not have enough power, then the SCC will arrange for the battery to provide power to the load.

A PV. system generally consists of a PV module, a power conversion device, and a load, as shown in Figure 1. The configuration of the PV system varies depending on the requirements of the application. For applications with high voltage requirements, a multilevel power conversion (DC-AC-DC) is usually required or used in conjunction with a power converter with a high voltage ratio [30]. But when there is a DC load or a need to charge a battery, the configuration is usually simpler. The PV module consists of a combination of PV cells made of pn junction semiconductor material. Accurate modeling is needed to anticipate the nonlinear structure of the PV module output due to the input variable temperature and solar irradiation. Figure 2 shows the equivalent circuit of the widely used single- diode PV model. The cell output current (/¢¢;;) can be calculated by (2) via Kirchhoff's law.

SCC regulates four stages of battery charging, and the charging process diagram is shown in Figure 3. When the battery is not fully charged, in this case, the battery is in the bulk charge stage, and the power will be fully sent to the battery. The charging process operates at the absorption stage until the battery is almost at the absorption voltage setpoint. At this stage, a constant voltage is applied for 150-180 minutes (depending on the type of battery) so that the battery voltage is at the setpoint [32]. Finally, once the battery is fully charged, the voltage is reduced to a float voltage setpoint so that it can be used to supply the load. If the load exceeds the SCC current, the battery cannot be maintained at the float setpoint. Also, if the battery voltage is lower than the setpoint of the float stage for a certain period, then charge back to the bulk stage.

Figure 4. PV system parameter measurement configuration The IoT system in this system is used as a monitoring output of parameter values generated from sensors to identify data in real-time. Then, the collected data is displayed on the LCD output and stored on the web server. After that, the parameter value data can be processed for further processing. Figure 4 shows a system diagram, while Figure 5 shows the process of the system.

Figure 5. The process of the PV parameter monitoring system

Figure 6. PV system parameter data collection Figure 6 shows the process of taking parameter data in a PV system. The PV system consists of a PV module controlled by the SCC as the primary source of power generation used for battery charging. The ThingSpeak platform as a graphics viewer is accessed via a laptop. The sensors, microcontrollers, and other parts are put in a box, which is then attached to the PV module holder.

Int J Reconfigurable & Embedded Syst Figure 7. Measurement results of (a) temperature and (b) irradiance displayed graphically on ThingSpeak

Figure 8. Measurement results (a) voltage, (b) current, and (c) power due to variations in temperature and irradiance Changes in temperature and irradiance variables will cause the PV output power value to change. As shown in Figures 8(a) and 8(b), the PV output is in the form of fluctuating voltage and current. This is because temperature and irradiance affect the PV output voltage and current. As a result, the PV output power depicted in Figure 8(c) varies.

Figure 9. Irradiation value measured from morning to evening Furthermore, the test was carried out for 18 hours with a full internet connection. It aimed to determine the correlation between essential parameters in the PV system and the surrounding environment. The parameter values are stored on the microSD and recorded in real-time via the RTC module. Figures 9 and 10 show the effect of daily time on the irradiation and stress parameters, respectively. The irradiation value shown in Figure 9 was recorded and started to increase after 04.00 to 06.00, then began to decrease after 16.00 to 18.00. In daylight, irradiation was recorded to be relatively stable due to bright lighting. But between 14:00 and 16:00, there was shading, which made the irradiation value temporarily drop.

Figure 10. Voltage values measured from morning to evening On the side of the voltage parameters shown in Figure 10, the characteristics are not much different from the irradiation parameters when tested from morning to evening. The shading phenomenon that causes the irradiation value to decrease also affects the measured voltage value. It can be seen that the voltage value decreases similarly to irradiation. On the other hand, the voltage values measured during daylight show uneven fluctuations. This is influenced by the ambient temperature value, which also varies. This clearly shows that the parameters of irradiation and the temperature of the environment affect the PV output voltage.

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A laboratory scale IoT-based measuring of the solar photovoltaic parameters

by IJRES Team and

2022, International Journal of Reconfigurable and Embedded Systems

Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment,... more

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