Analysis of Artificial Intelligence Based Hybridization for Optimal Allocation of Distributed Generations and Economic Power Dispatch in Radial and Mesh Configuration Systems

Abstract

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 economical 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 also considering augmentation of voltage and minimization in cost of power loss. In this dissertation, four effective hybridization algorithms were proposed to analyse the power flow issue and the allocation issue of DGs. newlineThis dissertation presents hybridized techniques intend with to reduce active power and reactive power losses while improving voltage, minimization of cost of power loss and improving Voltage Stability Index (VSI) in radial and mesh configuration systems and also finding the Economic Power Dispatch (EPD) intend with reduction in final fuel cost of operation and scheduling of committed units generating output in such a way to meet the current load demand. Hybridizing solutions are the combination of 1. Gravitational Search Algorithm (GSA) and the Firefly Algorithm (FFA) 2. Bat Algorithm (BA) and the Firefly Approach (FFA) 3. Particle Swarm Optimization Algorithm (PSOA) based Ant-Lion Optimization Algorithm (ALOA) and 4. Fuzzy Logic Controller (FLC) based Ant-Lion Optimization Algorithm (ALOA) was used for optimal integration of DGs and to find newline newlinethe EPD.