Improved Jaya Algorithm for Economic Dispatch Considering Valve-Point Effect and Multi-Fuel Options
Chuanhu Chen, Dexuan Zou, Chunliang Li
Abstract
In this work, an improved Jaya (IJaya) algorithm is proposed and used to solve the economic load dispatch (ELD) problem considering valve-point effect and multi-fuel options. Compared with original Jaya, the convergence rate of IJaya is accelerated by distance-varying acceleration coefficient (DVAC), and the population diversity is enlarged by a self-adaptive population mechanism (SAPM). Meanwhile, to avoid premature problem, Gaussian and Cauchy mutation (GCM) is used to help IJaya jump out of local optima. The superiorities of IJaya have been validated by solving ELD cases with 6, 10, 13, 15, 40 generators, and the results are analysed in aspects of convergence rate, solution quality and robustness. The conclusion is that, in the tested ELD cases, IJaya behaves much more competitive than Jaya under the same testing conditions.