The key of reactive power planning (RPP), or Var planning, is the optimal allocation of reactive power sources considering location and size. Traditionally, the locations for placing new Var sources were either simply estimated or directly assumed. Recent research works have presented some rigorous optimization- based methods in RPP. Thus, the aim of this project is reviwing different kind of formulations appeared in recent papers and presenting an appropriate formulation for reactive power planning. Therefore, this thesis will first review various objectives of R The objective function of RPP may be cost-based, which means to minimize the possible cost associated with RPP such as variable and fixed Var installation cost, real power loss cost, and/or fuel cost. Other possible objectives may be to minimize the deviation from a given schedule of a control variable (such as voltage) or to maximize voltage stability margin. It is also reasonable to use a multi-objective (MO) model as the goal of the RPP formulation. Secondly, different constraints in RPP will be discussed. The constraints in RPP are even much more complicated than the objective functions. Conventional constraints may include the normal state (base case) power-flow limits and the contingency state power flow limits. However, more recent works proposed to include the voltage stability limits, under both normal state and contingency state, due to the increased pressure of voltage stability and stressed transmission systems. These different constraints are the key of the justify; LINE-HEIGHT: normal; MARGIN: 0in 0in 0pt; mso-layout-grid-align: none" Therefore, thirdly, the optimization-based models will be categorized as conventional algorithms, intelligent searches, and fuzzy set applications. The conventional algorithms include linear programming, nonlinear programming, mixed-integer nonlinear programming, etc. Recently, heuristic methods based on intelligent search have been used in RPP to deal with local minimum problems and uncertainties. Increasingly, these heuristic methods are being combined with conventional optimization methods to solve the RPP problem. The intelligent searches include simulated annealing, evolutionary algorithms, and tabu search. The fuzzy set applications in RPP address the uncertainties in objectives and constraints.Specifying candidate buses for reactive sources in a power system has been a challangable problem in power system planning, therefore in this thesis at first previous works on Specifying candidate buses will be reviewed, then a new method based on optimization will be presented and campared with previous methods. At the last, various formulation presented in this thesis will be tested on IEEE 30 bus test system. Keywords: 1- Ractive Power Planning, 2- Optimisation, 3- Candid Bus, 4- Voltage Stability, 5- Contingency