Artificial Intelligent based Cost Optimized Smart Energy Distribution and Management

The ever-increasing need for energy, along with the requirement to cut emissions of greenhouse gases and maximize efficiency in energy use, has been a driving force behind the development of cutting-edge technology in the field of intelligent energy distribution and management. This research article proposes an Artificial Intelligence (AI)-based cost-optimized smart energy distribution and management system. The purpose of this research is to present a new solution to addressing these difficulties. In order to intelligently manage the distribution and consumption of energy resources in a manner that is both cost-effective and efficient, the system that has been developed makes use of several artificial intelligence approaches, such as machine learning, optimization algorithms, and data analytics. The system's goal is to maximize energy utilization while keeping costs to a minimum and achieve the best possible optimization of energy distribution. In order to forecast energy demand and supply, the AI algorithms analyses data from the past as well as data that is being collected in real time. They also take into account aspects such as the current weather, the current time of day, and the preferences of individual users. The system makes real-time adjustments to the distribution of energy based on these projections, taking into account issues such as load balancing, the integration of renewable energy sources, and grid stability. Additionally, the system supports demand response capabilities, which enables users to actively participate in the management of energy by modifying their patterns of consumption based on real-time pricing signals. This allows users to actively participate in the management of energy. This demand-side management function not only promotes energy efficiency but also gives customers more agency in terms of the decisions they make regarding their energy consumption.