A solution to the ramp rate and prohibited operating zone constrained unit commitment by GHS-JGT evolutionary algorithm

• A new efficient hybrid approach of Gaussian harmony search with jumping gene transposition (GHS-JGT) algorithm is implemented and applied to the Unit commitment problem with and without ramp rate constraints.
• Moreover, prohibited operating zone constraints (POZ) constraints are also used in Unit commitment (UC) problem, with and without ramp rate constraints.
• This proposed method has been implemented for 10, 40 and 100 units systems and obtained results are compared with all recent and best existing results.
• These results have shown that proposed method can solve both small and large scale UC problems effectively.
• Based on the performance, the GHS-JGT algorithm has been found an effective method to solve the complex, nonlinear problem with large number of constraints.

Unit commitment (UC) problem on a large scale with the ramp rate and prohibited zone constraints is a very complicated nonlinear optimization problem with huge number of constraints. This paper presents a new hybrid approach of ’Gaussian Harmony Search’ (GHS) and ’Jumping Gene Transposition’ (JGT) algorithm (GHS-JGT) for UC problem. In this proposed hybrid GHS-JGT for UC problem, scheduling variables are handled in binary form and other constants directly through optimum conditions in decimal form. The efficiency of this method is tested on ten units, forty units and hundred units test system. Simulation results obtained by GHS-JGT algorithm for each case show a better generation cost in less time interval, in comparison to the other existing results.