The purpose of this dissertation is to introduce and demonstrate a new approach to Optimization.  This new methodologyis the hybridmulti-objective optimization algorithm for optimal allocation of distributed generation and economic power dispatch. Installation of Distributed Generation (DG) at the distribution site promotes many technical and other considerable benefits like reduction in active and reactive power losses, decrease in cost of power loss, enhancement of voltage profile, improvement of voltage stability index, environment friendliness, reliability, security, and postponement of up gradation of existing system etc. The allocation of DG must be optimal because benefit for user should be maximum. To describe the economic and technical benefits of DGs performance several methodologies were proposed for optimal allocation of DGs which includes location and capacity of DGs. Some deterministic, meta-heuristic and hybrid approaches are considering for optimal allocation of DGs. Some of the algorithms are used to perform the function of optimal DG allocation problem not only based on reduction in power loss and considering augmentation of voltage and minimization in cost of power loss.  In this dissertation, four effective hybridization algorithms were proposed to analyze the power flow issue and the allocation issue of DGs.

In this dissertation, the optimal allocation of DGs is investigated using multi-objective and multi-DG approach. In these approaches the power factor of the system would be considered as unity, 0.85 lagging, 0.9 lagging and 0.95 lagging. The type-1 i.e., Photo Voltaic (PV) modules and/or type-2 i.e., Wind Turbine (WT) modules and/or type-3 i.e., capacitors were considered as DGs. Firstly, objective function for optimization issue through various DGs allocation is considered as an optimization issue. In this optimization issue the objective function consists of, reduction in system’s active power losses, reactive power losses along with augmentation of voltage and voltage stability index.

This dissertation should be of interest to high-level decision makers, but also in other large private and public organizations.  It should also be of interest to scholars of decision analysis and operations research, and practitioners of policy analysis, defense planning, and business strategy.