scholarly journals Optimal Solar Power System for Remote Telecommunication Base Stations: A Case Study Based on the Characteristics of South Korea’s Solar Radiation Exposure

2016 ◽  
Vol 8 (9) ◽  
pp. 942 ◽  
Author(s):  
Mohammed Alsharif ◽  
Jeong Kim
Author(s):  
Sunimerjit Kaur ◽  
Yadwinder Singh Brar ◽  
Jaspreet Singh Dhillon

In this paper, a multi-objective hydro-thermal-wind-solar power scheduling problem is established and optimized for the Kanyakumari (Tamil Nadu, India) for the 18th of September of 2020. Four contrary constraints are contemplated for this case study (i) fuel cost and employing cost of wind and solar power system, (ii) NOx emission, (iii) SO2 emission, and (iv) CO2 emission. An advanced hybrid simplex method named as-the -constrained simplex method (ACSM) is deployed to solve the offered problem. To formulate this technique three amendments in the usual simplex method (SM) are adopted (i) -level differentiation, (ii) mutations of the worst point, and (iii) the incorporation of multi-simplexes. The fidelity of the projected practice is trailed upon two test systems. The first test system is hinged upon twenty-four-hour power scheduling of a pure thermal power system. The values of total fuel cost and emissions (NOx, SO2, CO2) are attained as 346117.20 Rs, 59325.23 kg, 207672.70 kg, and 561369.20 kg, respectively. In the second test system, two thermal generators are reintegrated with renewable energy resources (RER) based power systems (hydro, wind, and solar system) for the same power demands. The hydro, wind, and solar data are probed with the Glimn-Kirchmayer model, Weibull Distribution Density Factor, and Normal Distribution model, respectively. For this real-time hydro-thermal-wind-solar power scheduling problem the values of fuel cost and emissions (Nox, SO2, CO2) are shortened to 119589.00 Rs, 24262.24 kg, 71753.80 kg, and 196748.20 kg, respectively for the specified interval. The outturns using ACSM are contrasted with the SM and evolutionary method (EM). The values of the operating cost of solar system, wind system, total system transmission losses, and computational time of test system-2 with ACSM, SM, and EM are evaluated as 620497.40 Rs, 1398340.00 Rs, 476.6948 MW & 15.6 seconds; 620559.45 Rs, 1398479.80 Rs, 476.7425 MW & 16.8 seconds; and 621117.68 Rs, 1399737.80 Rs, 477.1715 MW and 17.3 seconds, respectively. The solutions portray the sovereignty of ACSM over the other two methods in the entire process.


Solar Energy ◽  
2014 ◽  
Vol 109 ◽  
pp. 45-53 ◽  
Author(s):  
Adriana Ipiña ◽  
Carolina Castaño ◽  
M. Laura Dántola ◽  
Andrés H. Thomas

2019 ◽  
Vol 51 (Supplement) ◽  
pp. 14
Author(s):  
Hidenori Otani ◽  
Mitsuharu Kaya ◽  
Akira Tamaki ◽  
Heita Goto ◽  
Ronald J. Maughan

Author(s):  
Yoerdy Agusmal Saputra ◽  
Dewi Susanna

To date, coronavirus disease 2019 (COVID-19) is still a threat to public health systems around the world. As of July 25, 2021, the numbers were still increasing in most countries, and the total confirmed cases reached 194,582,750 with 4,171,672 deaths (CFR 2.1%). In Indonesia, 3,166,505 cases were reported with 83,279 deaths (CFR 2.7%) in all provinces and dominated by cases from Jakarta. Therefore, this study aimed to find a correlation and the duration of solar radiation exposure spatially on the pattern of COVID-19 cases. An ecological design was used based on time and place with the integration of geographic information systems and statistical techniques. The correlation test results between solar radiation exposure and COVID-19 cases in Jakarta showed a significant relationship (p = 0.000) with a strong closeness and positive pattern (r = 0.666). Furthermore, the spatial map overlaying solar radiation exposure and COVID-19 cases showed urban villages with high radiation tend to increase in cases earlier than areas with moderate and low. The differences in geographical and temporal conditions are a concern for the Provincial Health Office. This can be a consideration in strengthening more specific prevention and control programs according to the risk level and characteristics of each region.


2016 ◽  
Vol 67 (5) ◽  
pp. 577-587 ◽  
Author(s):  
Alberto Modenese ◽  
Fabio Bisegna ◽  
Massimo Borra ◽  
Carlo Grandi ◽  
Franco Gugliermetti ◽  
...  

2019 ◽  
Vol 70 (6) ◽  
pp. 763-768 ◽  
Author(s):  
Magdalena Salińska ◽  
Hanna Kowalska ◽  
Jolanta Torzecka ◽  
Elżbieta Waszczykowska ◽  
Anna Woźniacka

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