In view of deregulation and privatization processes, electricity pricing becomes one of the most important issues. The increases in power flows and environmental constraints are forcing electricity utilities to install new VAR equipment to enhance network operation. In this thesis a nonlinear multi-objective optimization problem has been formulated to maximize both social welfare and the maximum distance to collapse point in an open power market using reactive support like Static Var Compensator (SVC). The production and consumption costs of reactive power are intended to provide proper market signals to the electricity market agents. They are included in the multi-objective Optimal Power Flow (OPF) coupled with an (N-1) contingency criterion which is based on power flow sensitivity analysis. Considering the cost associated with the investment of VAR support, placing them at the optimal location in the network is an important issue. An index to find the optimal site for VAR support considering various technical and economical parameters based on Cost Benefit Analysis (CBA) is proposed. The weights for these parameters are computed through an Analytic Hierarchy Process (AHP). A new approach of transmission pricing calculation taking VSC-OPF based multi-objective maximization as the objective and studied the impact of SVC on it. The integrated approach is illustrated on a 6-bus and a standard IEEE 14-bus test systems and shows promising results Acknowledgement First of all, I would like to thank the Transcendental Lord Sri Krsna who is beyond mundane sense perception, for giving me strength and intelligence to complete this work. I would like to express my profound gratitude to my advisor Dr. Ali Feliachi for his invaluable advice and continuous encouragement throughout this work. I would also like to thank Dr. Muhammad Choudhry for his suggestions and providing the opportunity to instruct Electromechanics lab. I am also thankful to my committee member Dr. Powsiri Klinkhachorn for his support throughout my graduate education. I would also like to thank Dr. Federico Milano, from University of Castilla-La Mancha, Spain, for providing the PSAT software and suggestions. Thanks to Dr. Karl Schoder for his valuable suggestions and discussions. A special thank to the students of lab 1001: Talpasai, Silpa, Ram Praveen, Pradeep, Anisha, Ali at APERC. I enjoyed every moment working togather in the lab. Many thanks to my Morgantown and Vijayawada friends for their encouragement. It is impossible to find the right words to thank my beloved parents, uncle and sister for their love and encouragement. Without it, this thesis would not be completed.