Prediksi Kebutuhan Cadangan Daya Pembangkit Sel Surya Menggunakan Jaringan Syaraf Tiruan

Abstract

Electrical energy is needed for the continuity of human life which is the most significant and crucial that cannot be separated from daily needs. Currently the need for electrical energy is increasing along with population growth and technological advances. To offset the demand for electrical energy that is triggered by population growth, you can utilize alternative energy which is very abundant in Indonesia. Potential for New Renewable Energy (RE) in Indonesia. The need for the availability of continuous electricity supply services is absolutely necessary for modern society. But in reality, PLN as a provider of electricity resources has not been able to maintain the continuity of the availability of electric power, development planning is a very important instrument in selecting EBT which is cleaner, has minimal emissions, is environmentally friendly, and has a fairly good volume in the future. The solution to the problem of meeting the supply of electrical energy needs in the future is to take advantage of the potential demand for renewable energy from solar power in the city of Medan. In this study, the authors will make predictions about the need for backup power for solar power plants in the city of Medan by using artificial neural network technology and utilizing the multiple linear regression method so that they can produce power plants that are cleaner, have less emissions, are environmentally friendly and have good enough volume in the future.