Alternative method for economic dispatch utilizing grey wolf optimizer - Wong, Lo Ing (2015)
Power system is one of the largest and most complex engineering systems created by human. The systems are created in order to ensure the longevity and sustainability of the energy for civilization development. As been known, the nonstorage characteristics of electricity and constantly rising prices for labour, supplies and maintenance cost worldwide call for the need of economically power system operation. Economic Dispatch (ED) has the objective of dividing the power demand among the online generators economically while satisfying various constraints. Small Alternative method for economic dispatch utilizing grey wolf optimizer improvements in optimal output scheduling can contribute significantly in term of cost savings. Although several optimization methodologies have been developed for solving ED problems, the complexity of the task reveals the necessity for development of efficient algorithms to accurately locate the optimum solution. Thus, the objective of this research is to demonstrate an alternative approach for solving ED problems, aiming to provide a practical alternative for conventional methods. In this research, Grey Wolf Optimizer (GWO) is chosen because it has not been implemented in solving ED problem. Besides, the performance of the algorithm had been benchmarked on 29 well-known test functions and is able to give very competitive results compared to others well-known metaheuristic. In addition, the flexibility of this algorithm is a merit to solve different problems by only setting few parameters such as number of population and number of iteration without any special changes in the structure of the algorithm. Thus, in this research, GWO has been successful to solve higher-order nonlinearities and discontinuities characteristic of ED due to valve-point loading effects, ramp rate limits and prohibited zones. To show the feasibility and applicability of the proposed method, seven different test cases which consist of all types of practical constraints were applied and analyzed and the results were compared with recent research studies. From the simulation results, it shows that GWO is able to find the combination of scheduling generators in order to minimize the fuel cost. It has been observed that the GWO also has the ability to converge to a quality solution and possesses an alternative method for solving ED problems.