Emerging Smart Grid Technology for Optimal Renewable Energy Sources Integration: A Bibliometric and Review Analyses on Techniques and Algorithms

The growing demand for sustainable energy sources, the urgent need to mitigate global warming, and the pursuit of more cost-effective solutions have motivated the development of modern smart grids (SGs) by integrating renewable energy (RE) systems into grids and forming microgrids (MGs). The intermittent nature of RE systems demands optimization strategies. Past surveys have focused on specific parameters of an SG without considering the impact of the design on each parameter of the network. Nevertheless, this paper aims to provide a bibliometric and review analysis of past work, highlighting the integration of SG technology and RE sources. One of the key challenges is implementing SGs with RE usage and control. This review provides insights into the most effective methods and technologies for maximizing the use of RE sources in SGs. In addition, a comprehensive review of the state-of-the-art algorithms and methodologies for using RE systems in SGs is provided. Due to the issue that existing SGs depend on instant management techniques, which shows a lack of AI role in forecasting and control in this field, this work explores various methods of energy forecasting, load balancing, demand response (DR), and optimization techniques for RE sources, with a particular emphasis on artificial intelligence (AI), machine learning (ML), and advanced computational algorithms. A smart grid can be optimized by using algorithms as software controllers and communication systems as hardware optimizers. Furthermore, the results obtained from this work provide insight into cleaner, more resilient, and sustainable energy systems.

کلیدواژه ها:

smart grid ، Renewable Energy ، hybrid energy systems ، optimization ، Smart Technology