Improve the Electric Power Generation Issue by Cognitive Thinking

Abstract

The enormous increase in power demand due to the prevalent heat wave, the worst power shortage in the last decades, and lack of sufficient fossil fuels like natural gas, coal, oil, etc. has attracted the attention of researchers worldwide. One of the main reasons behind the problem is the mismanagement of proper regulation of the electrical power generation unit. This paper looks at cognitive thinking to address and improve this issue by noting that it is the process of gaining knowledge and understanding through thought, experience, and the senses that have enabled researchers to infer cognitive processes. Highly controlled and rigorous methods of study have always been employed to enable the work. Thermal energy power plants have been taken as the source of power generation and genetic algorithm (GA), fuzzy, and PID (Proportional, Integral, Derivative) controllers are used. All these controllers handle and control sudden changes in load frequency and power. For better and more effective results of the system, combined feedback has been obtained with the help of MATLAB Simulink software. The results obtained from the combined feedback are tabulated, which shows that all the controllers improve the electrical power generation issue by modulating the changes in load frequency and power, but the GA controller produces effective, efficient, and better results by adjusting to the changes in less time. The use of this cognitive thinking of the controller helps in the proper management of power demand which automatically improves and controls the power generation.