Economic power dispatch with cubic cost models using teaching learning algorithm

Economic dispatch (ED) solution accuracy can be improved with cubic cost models and optimisation algorithms. This article proposes a new methodology for solving ED problem with cubic cost models using teaching learning-based optimisation (TLBO) algorithm. The key aspects of ED scenario such as valve point effects, environmental factors, transmission losses, spinning reserve, ramp rate, prohibited operating zones and fuel limitations are considered in this study. The proposed methodology is applied to test systems involving cubic cost equations in 3, 5, 6, 13, 26 and a large-scale system containing 156 units, in order to evaluate its efficiency and feasibility. Convergence characteristics of the TLBO has been assessed and investigated through comparison with results reported in the literature. Many trials with different initial values have been carried out for all the test systems in order to justify the robustness of the proposed methodology. Considering the quality of the solution and convergence speed obtained, this method seems to be a promising alternative approach for solving the ED problems with cubic functions.