IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 5 Ver. II (Sep – Oct. 2015), PP 01-12 www.iosrjournals.org DOI: 10.9790/1676-10520112 www.iosrjournals.org 1 | Page A Comprehensive Literature Survey on Recent Methods of Optimal Power Flow A.Immanuel 1 , Dr.Ch.Chengaiah 2 1 Research Scholar, 2 Associate ProfessorDepartment of Electrical and ElectronicsEngineering, Sri Venkateswara University College of Engineering, Sri Venkateswara University, Tirupati-517502- India. Abstract:Over the historyof five decades, Optimal Power Flow (OPF) has become one of the most important and extensivelyconsidered nonlinear optimization problems. In general, OPF needs to optimize the operation of electric power generation, transmission and distribution networks subjectedto varioussystem constraints and control limits. However, there is an extremely wide and variety of OPF formulations and solution techniques. Moreover, the character of OPF continues to evolve due to recent electricity markets and renewable resource integration. In this survey, both the conventional, intelligent OPF methods and both in the presence of Flexible Alternating Current Transmission Systems (FACTS) are surveyed in order to present a sound context for the state of the art in OPF formulation and solution methods. The survey contributes a comprehensive conversation of specific optimization techniques that have been applied to OPF, with an emphasis on the merits, drawbacks of each method of both conventional and intelligent methods of OPF. Keywords: Optimal Power Flow, Power System, System Constraints, Intelligent Methods and FACTS. I. Introduction: The Optimal Power Flow (OPF) problem has been one of the most extensively studied subjects in the power system since Carpentier first published a paper in 1962 [1]. The objective of an Optimal Power Flow (OPF) algorithm is to get a steady state solution which minimizes generation cost, system loss etc. or maximizes social welfare or system utilization etc. while maintaining an acceptable system performance in terms of limits on generator’s active and reactive powers, line flow limits and maximum output of different compensating devices etc. The general OPF problem is a non-convex, nonlinear, large-scale optimization problem which may contain both continuous and discrete control variables [2]. Several OPF formulations have been developed to address specific instances of the problem, using varying assumptions and selecting different objective functions, system constraints and controls. The consequential optimization problems go by many names depending on the particular objective function being addressed and the constraints under consideration. Regardless of the name, any power systems network optimization problem that includes a set of power flow expressions in the constraints may be classified as a form of OPF. Many OPF solution methods have also been developed, each with distinct mathematical characteristics and computational necessities. Almost each mathematical programming approach that can be applied to OPF has been attempted and it has taken developers many decades to develop software capable of solving OPF problems reliably [3].Today, OPF studies and methods present flexible and powerful tools which are widely used in industry applications, such as constrained economic dispatch and voltage control problems [4]. However, real-time OPF problems are frequently more significant and challenging than the classically considered problems and OPF methods vary considerably in their adaptability to the modeling and solution needs of different engineering applications. Therefore, there has been no single formulation and solution approach suitable for all the various types of OPF problems. In this survey,The OPF methods are broadly classified as Conventional and Intelligent methods. The conventional methodologies comprises of well-known techniques like Newton method, Gradient method, Quadratic Programming method, Linear Programming method and Interior point method. Intelligent methodologies include the popular methods developed recently such as artificial neural networks, Fuzzy, Genetic Algorithm, Particle swarm optimization and some of the latest OPF formulations with FACTS devices are presented below. II. Optimal Power Flow Problem In an OPF solution methodology, the values of some or all of the control variables arerequire to found so as to optimize (minimize or maximize) a specific objective. It is also important that, the proper problem formulations with clearly declared objectives are to be needed to find the best solution. The superiority of the solution depends on the accuracy of the model considered. Objectives ought to be modeled and its practicality with possible solutions. The OPF problem solution aims to optimize a chosen objective function via optimal