In power system studies, load flow (LF) analysis is one of the most crucial tools. It is the most important and required method of looking at issues with power system design and operation. A series of nonlinear algebraic equations make up the LF issue, which needs to be mathematically solved by iterative numerical methods. In the current modern distribution systems (DSs) field, the most significant criterion that is heavily influenced by the DS’s size—which keeps growing—is the convergence of the solution. This paper gives readers an overview of recent research that has used both classical and artificial intelligence-based methods to handle LF-related issues with particular attention to DSs. The impacts of high R/X ratio of DSs along with various load models are discussed. Various standard and non-standard test feeders used for investigating LF algorithms are addressed. It also offers suggestions for future paths for this field of study. The types of examined LF problems are used to categorize the surveyed literature.