This thesis develops iterative algorithms for solving joint Chance Constrained Programming (CCP) based stochastic problems in power system planning. A generation expansion problem with load uncertainty is formulated as joint CCP and solved by incorporating sensitivity in the iterative algorithms. These algorithms exploit the characteristics and the response of the system with respect to the variations in the load. The buses in the system are classified according to its stress level and depending on contribution of each bus to the system reliability, it is treated uniquely in the iterative algorithm. By employing sensitivity, a few mathematical challenges in solving joint CCP problem is addressed and also optimal expansion solutions are obtained due to the correct estimation of the uncertain load. The IEEE 30- and 118- bus test systems are used to demonstrate the algorithms and results from the proposed algorithms are compared with the other existing algorithms for solving the joint CCP problem.