Design And Analysis On Operation Of Hybrid Micro Grid Using Artificial Intelligence

Abstract

Artificial intelligence approaches may be used to make engineering problems in a manner comparable to that of the human brain. Smart grid aims include greater integration of dispersed generation, grid stability, dependable power supply, and generation and supply stability. Using Artificial Intelligence methods, the objectives are realized. For microgrid energy management, there are several issues that contribute to its difficulties, including a dearth of inertia required for system stability, unpredictability in DER production, as well as complexity in MG network architecture (AC/DC and hybrid AC/DC MGs). Those issues can be solved with AI techniques, such as DRL, which have proven excellent recently for the resolution of decision-making issues. There is a special focus on DL and DRL in this paper. DL and DRL technologies are discussed, along with the power grid applications. We also examine MG-specific concerns, such as their layered architecture for control, single vs networked structure, and optimisation of topologies. MG operating and control issues are discussed, as well as possible AI solutions.