Solving economic dispatch problem using particle swarm optimization - Syed Jamalil, Syed Akhmal (2013)
This project presents a new approach to solve Economic Dispatch (ED) using Particle Swarm Optimization (PSO) technique with consideration of several generators constraints to search the optimal solution and the minimum of total generation operating cost. Conventional optimization methods assume generator cost curves to be continuous and monotonically increasing, but modern generators have a variety of nonlinearities in their cost curves making this assumption inaccurate, and the resulting approximate dispatches cause a lot of revenue loss. In PSO technique, the movement of a particle is governed by three behaviors namely, inertial, cognitive, and social. The cognitive behavior helps the particle to remember its previously visited best position. This technique helps to explore the search space very effectively. The proposed method considers the nonlinear characteristics of a generator such as ramp rate limits, power balance constraints with maximum and minimum operating limits and prohibited operating zone for actual power system operation. The practicality of the proposed method was demonstrated for different cases on 6-unit generation system and 15-unit generation system based on IEEE standard operation. The PSO algorithms with the proposed objective function are being considered efficient in solving this kind of models. Also, PSO has been successfully applied in many complex optimization problems in power systems. The proposed function approach was first tested on some less complex systems and then the effectiveness of the PSO was compared with the research studies from several references of studied papers.