USING FUZZY LOGIC IN SOLAR POND AND PARABOLIC TROUGH COLLECTOR TECHNOLOGIES FOR POWER GENERATION PREDICTION: A CASE STUDY OF KHUZDAR REGION.

Abstract

World is facing difficulties dealing with energy crisis due to the depletion of fossil fuels and other constraints like cost. In the current scenario, globally power generation is necessary for industrial and economic development, so efforts are required to be made to find out the ways to replace fossil fuels with more environmental-friendly alternatives. In today’s era, renewable energy is considered 
a viable option as an alternative energy source. Solar Energy use for power generation is an area of research which has gained more popularity in recent times. Out of many options, Solar Pond and Parabolic Trough have been selected for this work. Researchers have argued that variations in the solar data cause ambiguities in the data. A review has been presented on the recent works on application of solar pond and parabolic trough technology in this area. Besides that, potential use of these technologies in Khuzdar region, a remote area of Pakistan has been described. Review shows that remote areas of Balochistan province especially Khuzdar region is very much feasible to use solar energy as replacement of conventional power generation resources with a focus on solar pond and parabolic trough collector technologies of renewable energy. To deal with this, fuzzy logic field of Artificial Intelligence has been selected to represent the ambiguities found in the solar data in terms of prediction of power generation ultimately beneficial in efficient solar pond and Parabolic Trough Collector Design suited to areas like Khuzdar where solar irradiance is very high. Three parameters namely Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI) and Diffused Horizontal Irradiance (DHI) have been selected. The data set used for the investigation has been taken from BUET Khuzdar weather station for the Khuzdar region 
for the years 2022 and 2023. This region has very high solar irradiance. A fuzzy Inferencing system has been generated with the help of these input variables. Each variable has been divided into three membership functions namely low, medium, and high. A rule set has been created which after Inferencing provides the output as power prediction with fuzzy values. Mamdani-type fuzzy Inferencing has been used. The output of the system is power prediction. Analysis has been done of the three data sets. The analysis shows that a developed fuzzy system can capture the complexities and variabilities of the data sets. It has also been discussed that the findings can be used for efficient power generation design by integrating fuzzy systems with solar ponds and parabolic trough collector technologies. Future work also mentions the potential use of Artificial Intelligence-based techniques to be used for solving problems related to power generation through solar energy.