Abstract
Traditional energy sources have become one of the most serious causes of environmental pollution because of the growing demand for energy. Because of the carbon emissions that have recently increased greatly, we had to search for a safe, cheap, and environmentally friendly energy source. Many photovoltaic (PV) solar panels are used as an energy source because of free and environmental friendliness. However, this technology has become a source of inspiration for many researchers. The proposed method suggests to extract useful features from PV and wind generators and then train the system to control them and update the inputs according to prediction results. Solar energy produces energy that varies according to the external influences and the immediate changes in weather conditions. Solar panels are connected through an inverter with the grid, through which the work of the solar panels is monitored using the Internet. It is worth using neural networks (NN) to control variables and adopt system output of previous iteration in processing operations. Use of deep learning (DL) in the control of solar energy panels helps reduce the direct surveillance of the system online. Solar power generation systems mainly depend on reducing the pollution resulting from carbon emissions. Saving CO2 emission is the main purpose of PV panel cells, so smart monitoring can achieve better result in that case.
Highlights
IntroductionWith regard to the increasing population density, which has become uncontrollable, the requirements of life have increased according to technological development
With regard to the increasing population density, which has become uncontrollable, the requirements of life have increased according to technological development.e electric power network is one of the largest and most complex networks that supply electrical energy to citizens, so there must be economic feasibility in transmitting and generating this energy [1]
Generation comes on the main level in terms of importance. e second issue that controls the supply of electrical energy is the transmission which is responsible for transmit the power from source generating to the destination demands [4]. e third issue that affects the electrical system is the uniform distribution between local networks
Summary
With regard to the increasing population density, which has become uncontrollable, the requirements of life have increased according to technological development. It is imperative to provide the increasing demand for electric power with the lowest acceptable cost in order to reach the level of environmental safety [2]. E second issue that controls the supply of electrical energy is the transmission which is responsible for transmit the power from source generating to the destination demands [4]. Since our study includes controlling the solar energy generation system, we must take into consideration the three issues that determine electrical energy [5]. Due to the proposed system which is managed remotely, we have to train the remote-sensing system to be able to adapt with the deep learning system It is worth using electric grid of the energy when neural network (NN) system is used and run .
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