Quorum Sensing Driven Bacterial Swarm Optimization to Solve Practical Dynamic Power Ecological Emission Economic Dispatch

Abstract

This paper presents a Quorum Sensing Driven Bacterial Swarm Optimization (QBSO) to solve Dynamic Power Economic Ecological Emission Dispatch (DPEEED) problem with valve point loading effects. The exploration capability of the bacterial swarm is improved in this paper using quorum sensing and the anti-predatory activity. The performance of the proposed QBSO method is verified for optimality, practicability, convergence and robustness on a 5, 10-unit system. Furthermore, a practical south Indian 20-thermal generating units with recorded load demand profiles of three different weather situations. The numerical dispatch result indicates that the presented technique finds the minimized generating cost and consistently progresses the computational time. The presented technique outperforms the Bacterial Swarm Optimization (BSO) and the previous presented methods.