Quantum Neural Networks (QNN) Application in Weather Prediction of Smart Grids

In this paper, a practical field of quantum technology known as “quantum technology, and weather prediction of smart grids”, and their future have been analyzed. Smart grids are among the significant fundamentals of a smart city and its supplying sources. So, factors such as weather prediction, or demand response are among important factors and have a crucial role. Also, experts should use highly accurate models to predict these factors such as weather prediction Therefore, when they are combined with Artificial Intelligence (AI), and Neural Networks (NN), they will be more efficient. However, in the smart grids of future Smart Sustainable Cities (SSCs) that the gathered big data has enormous amount, the classical AI, and ANN models will inefficient. Accordingly, using a higher technology known as “Quantum technology”, and its practical features, and potentials, has noticeable applications in smart grids, also, weather prediction. This paper presents weather prediction of smart grids, their regular methods, and quantum technology with its usage in the ladders. Respectively, it compares Quantum Neural Networks (QNN) method with other regular techniques that are ANN-based in the area of weather prediction. Finally, it is concluded that quantum technology and Quantum Neural Networks (QNN) have the potential to be combined with other techniques which leads to accurate models with ultrafast processing, and execution speed. Accordingly, they can be used in every field, and smart grids or weather predictions are not an exception.